Evaluating the Influence of Organic Waste Compost Amendments on Microbiome Richness and Diversity in Pre-Plantation and Post-Harvest Soils: Insights from 16S rRNA Metagenomic Profiling

Evaluating the Influence of Organic Waste Compost Amendments on Microbiome Richness and Diversity in Pre-Plantation and Post-Harvest Soils: Insights from 16S rRNA Metagenomic Profiling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluating the Influence of Organic Waste Compost Amendments on Microbiome Richness and Diversity in Pre-Plantation and Post-Harvest Soils: Insights from 16S rRNA Metagenomic Profiling Sophayo Mahongnao, Pooja Sharma, Arif Ahamad, Sarita Nanda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3247820/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Understanding the dynamics of soil microbiomes is crucial for sustainable agriculture and developing effective soil management strategies. This study investigates the impact of leaf-based compost and other organic waste bio-compost amendments on the microbial richness and diversity in soils using 16S rRNA metagenomic profiling. Our results revealed significant variation of the microbiome richness and diversity on soil due to the bio-composts amendment. Interestingly, the bio-composts amendment resulted in a pronounced enrichment of beneficial microorganisms such as Achromobacter, Agromyces, Bacillus, Clostridium, Nitrospira, Planctomyces, Pseudomonas, Steroidobacter , Streptomyces, Alicyclobacillus , and Bdellovibrio , known for their roles in nutrient recycling, plant growth promotion, and disease suppression. The presence of pathogenic bacteria such as Flavobacterium, Leptolyngbya, Balneimonas, Geobacter, Nocardia , and Mycobacterium , were higher in the chemical fertilizer-amended soil sample than the bio-composts amended soils, which indicated the bioremediation of pathogens due to bio-compost amendment. Moreover, it was also observed that the microbiome population of the cultivars were affected by the bio-compost amendments. Generally, the organic cultivars produced using bio-compost amendments had higher beneficial microorganisms and lower pathogens than the conventional produce with chemical fertiliser amendment. Thus, leaf-based compost and other organic-waste compost could be used as bio-organic fertilizer for healthy sustainable productivity. 16S RNA metagenomic profiling Bio-organic fertilizer Microbiome diversity Beneficial microorganisms and Pathogenic microorganisms Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Highlights Compost amendments impacted the microbiome richness and diversity in the soil Compost amended soil had higher beneficial bacteria than fertilizer amendment The pathogens levels were lower in the soil amended with compost The organic cultivars had higher beneficial microbes and lower pathogens 1. Introduction The study of soil microbiomes and their dynamics has gained significant attention recently due to their crucial roles in soil health, nutrient recycling, and plant productivity. The composition and diversity of microbial communities in soil play a vital role in maintaining ecosystem functions and influencing plant growth and development (Liu et al. 2022; Luo et al. 2016 ). One approach to enhancing soil microbiome activity and function is applying bio-composts, which are organic amendments derived from various organic wastes such as leaf waste, animal manures, and food waste. Bio-composts contribute to soil fertility and plant growth by enriching the soil with organic matter and essential nutrients (Jahangir et al. 2021 ; Ho et al. 2022 ). Additionally, they can also alter the structure and composition of soil microbial communities, leading to changes in microbial diversity, functions, and activity (Farrell et al. 2010 ; Azeem et al. 2020 ). Understanding the impact of bio-composts on the soil microbiome dynamics is essential for optimising their application in agriculture and sustainable land management practices. Some previous studies have reported bio-composts’ benefits to soil health and plant growth by increasing nutrients solubilisation, promoting plant growth, and suppressing plant pathogens (Tao et al. 2020 ; Viti et al. 2010 ). Reports also highlighted the potential of bio-compost formulations in shaping the soil microbiome for agricultural systems (Heisey et al. 2022 ). It was found that the compost altered the structure of the microbial community and introduced new microorganisms into the soil system. In addition to the aforementioned studies, other investigations have contributed to our understanding of the microbiome dynamics in soils amended with bio-composts. For example, researchers had studied the effects of bio-compost application on soil microbial diversity and enzyme activities in a vegetable field. It was observed that there were significant changes in the microbial community structure and an increase in the enzymatic activities in the agricultural soil amended with bio-composts (Zhen et al. 2014 ; Jiang et al. 2021 ). Furthermore, a study by Samaddar examined the impact of bio-compost amendments derived from different animal manures on soil microbial community composition and found distinct responses in microbial diversity and functional profiles (Samaddar et al. 2019 ). The interconnectedness of the soil microbiome with that of the cultivars, food safety, and human health has been explored, which reported that the beneficial microorganisms in the soil could significantly improve the environmental sustainability, food quality, and human health (Bertola, Ferrarini, and Visioli 2021 ). Enhancement of soil health has become paramount important for sustainable productivity with improved food quality that can promote human health. While previous studies have examined the effects of bio-compost amendments on soil microbiomes, there is a need for further research to explore the specific dynamics and mechanisms involved. To investigate the microbiome dynamics in pre-plantation and post-harvest soils amended with different bio-composts, 16S rRNA metagenomic profiling was adopted in this study. The 16S rRNA gene is a widely used molecular marker for identifying and characterising microbial communities based on their phylogenetic relationships. Metagenomic profiling using the 16S rRNA gene allows for a comprehensive analysis of the microbial composition and diversity of bacteria in a given soil sample, which could help us identify the beneficial and pathogenic microorganisms in the soil. By comparing pre-plantation soils, before the application of bio-composts, to post-harvest soils, after the crop cycle, we could assess the impact of bio-compost amendments on the soil microbiome. This analysis could provide insights into the changes in microbial community structure, diversity, and potential shifts in functional profiles. Moreover, it could help identify specific microbial taxa that are influenced by applying bio-composts and potentially associated with improved soil fertility and plant productivity. In this study, the novelty has been introduced by focusing on specific types of bio-composts which were derived from novel sources such as leaf waste and other organic waste bio-composts, viz. cow dung manure, kitchen waste compost, municipal organic waste compost, and vermicompost. The impact of these bio-composts on the soil microbiome richness and diversity has been investigated. Additionally, an examination of the temporal dynamics of the microbiome from pre-plantation to post-harvest stages has also been analysed, which could provide us with an understanding of the long-term effects of bio-compost amendments on soil microbial communities. The examination of microbiome dynamics in pre-plantation and post-harvest soils amended with bio-composts through 16S rRNA metagenomic profiling offers a powerful tool to understand the effects of bio-compost application on soil bacterial communities. This knowledge can contribute to the development of sustainable agricultural practices aimed at improving soil health, nutrient recycling, and overall sustainable agricultural productivity. We also analysed the relationship of the microbiome of the cultivars with that of the soil microbiome by comparing the OTUs of beneficial and pathogenic microorganisms in the cultivars of chemical fertiliser and bio-composts amended soils. Such analysis could give insights into the relatedness of the microbiome in the bio-composts, soils, and cultivars, which could help the cultivators to choose the most appropriate bio-composts and soil types to produce the best quality cultivars. 2. Materials and methods 2.1. Experimental setup, sample collection and preparation Two types of soils were collected from different locations; the floodplain soil from the Yamuna riverbank, Burari area, North Delhi, India, and residential soil from the institution campus, University of Delhi, North Campus, North Delhi, India. They were mixed with the leaf-based compost and other different composts, viz. cow dung manure, kitchen waste compost, municipal organic waste compost, and vermicompost, in a ratio of 5: 1 (w/w) before potting. A control was also set up using soil and DAP chemical fertilisers, without composts. The plantation was done by potting red amaranth ( Amaranthus cruentus ) using these soils in different pots. Seedling and potting were done in the month of April in the ambient environment and harvested in the month of July. The pre-plantation and post-harvest soil samples were collected in a sterilised zip-lock polybag. The collected samples were maintained at 0ºC to -18 ºC for further processing (Table 1 ). Table 1 Soil samples code along with its descriptions and the International Nucleotide Sequence Database Collaboration (INSDC) accession number Sample code Description The International Nucleotide Sequence Database Collaboration (INSDC) accession number YC Pre-plantation floodplain soil amended with cow dung manure ERS15529941 YD Pre-plantation floodplain soil amended with leaf litter compost ERS15529942 YK Pre-plantation floodplain soil amended with Kitchen waste compost ERS15529947 YM Pre-plantation floodplain soil amended with municipal organic waste composts ERS15530011 YV Pre-plantation floodplain soil amended with vermicompost ERS15530204 YF Pre-plantation floodplain soil amended with chemical fertilizers (DAP) ERS15532765 YCRAH Post-harvest floodplain soil amended with cow dung manure, planted with red amaranth ERS15532766 YDRAH Post-harvest floodplain soil amended with leaf waste compost, planted with red amaranth ERS15532767 YKRAH Post-harvest floodplain soil amended with kitchen waste compost, planted with red amaranth ERS15532768 YMRAH Post-harvest floodplain soil amended with municipal organic waste compost, planted with red amaranth ERS15532770 YVRAH Post-harvest floodplain soil amended with vermicompost, planted with red amaranth ERS15532769 YFRAH Post-harvest floodplain soil amended with chemical fertilizers, planted with red amaranth ERS15532771 NCRAH Post-harvest residential soil amended with cow dung manure, planted with red amaranth ERS16204221 NDRAH Post-harvest residential soil amended with leaf waste compost, planted with red amaranth ERS16204222 NKRAH Post-harvest residential soil amended with kitchen waste compost, planted with red amaranth ERS16204644 NFRAH Post-harvest residential soil amended with chemical fertilizers (DAP), planted with red amaranth ERS16204249 2.2. The physico-chemical parameters of soils The pH and EC of the soils were measured using a pH meter and an EC meter. For the analysis, the samples were dissolved in distilled water at a ratio of 1: 2 (w/v soil: distilled water), and then measurements were carried out using pH and EC meter. The total organic carbon and nitrogen content of the soil was analysed using CHNS analyser (varioEL cube, Ser.no: 19171021). 2.3. DNA Extraction and PCR Amplification of V3-V4 Region of 16s Gene: DNA extraction was done using the suitable method for the sample type from commercially available kits such as QIAGEN, ZYMO RESEARCH, and Thermo-Fisher. DNA extraction was done as per the manufacturer's recommendation. Extracted DNA from the samples was subjected to NanoDrop and GEL Check before being taken for PCR amplification: The NanoDrop readings of 260/280 at a value of 1.8 to 2 were used to determine the DNA’s quality. For the metagenomic analysis, the extracted DNA was amplified and sequenced to obtain the DNA sequence of the V3-V4 region of the 16S rRNA bacterial gene. The amplification was performed using a PCR mix containing: High-Fidelity DNA Polymerase, 0.5mM dNTPs, 3.2mM MgCl₂, and PCR Enzyme Buffer. The primers used were: 16sF 5’ AGAGTTTGATGMTGGCTCAG 3’and 16sR 5’ TTACCGCGGCMGCSGGCAC 3’. The conditions for the polymerase chain reaction (PCR) amplification were; 40ng of Extracted DNA and 10 pM of each primer used for amplification. The initial denaturation was set at 95ºC. The 25 Cycles were set with the following condition: Denaturation at 95ºC for 15 seconds, annealing at 60ºC for 15 seconds, Elongation at 72ºC for 2 minutes, and final extension at 72ºC for 10 minutes, and hold at 4ºC. The amplified 16s PCR Product is purified and subjected to GEL check and Nanodrop Quality Control. The NanoDrop readings of 260/280 at 1.8 to 2 were used to determine the DNA’s quality. 2.4. Overview of sequencing and bioinformatics protocol The amplicons from each sample were purified with Ampure beads to remove unused primers. An additional eight cycles of PCR were performed using Illumina barcoded adapters to prepare the sequencing libraries. Libraries were purified using Ampure beads and quantitated using a Qubit dsDNA High Sensitivity assay kit. Sequencing was performed using Illumina Miseq with 2x300PE v3 sequencing kit. Raw data quality control (QC) was done using FASTQC and MULTIQC, followed by trimming adapters and low-quality reads by TRIMGALORE. The trimmed reads are further taken for processing, including merging of paired-end reads, chimera removal, and OTU abundance calculation and estimation correction. This was achieved using QIIME 2 / MOTHUR / KRAKEN / BRACKEN workflows. This workflow enables highly accurate investigations at the genus level. The microbial diversity of different bio-composts was analysed through Alpha and Beta diversity indices. The databases used were SILVA / GREENGENES / NCBI. Each read was classified based on % coverage and identity. The 16S workflow is useful in identifying pathogens in a mixed sample or understanding microbial community composition. 2.5. Data processing, filtering, and normalisation To process the metagenomics data for advanced analysis like alpha and beta diversity, the input file must contain at least two groups, and each group must have a minimum of three samples for the analysis. We have grouped the samples into three group; Group 1 includes pre-plantation Yamuna floodplain soil samples, Group 4 includes post-harvest Yamuna floodplain soil samples, and Group 6 includes post-harvest residential soil samples. In the analysis, features with identical values (i.e., zeros) across all samples were excluded, and the features appearing in only one sample were excluded (considered artifacts). Data filtering was done to remove low-quality informative features to improve downstream statistical analysis. The low-count filter features with very small counts in very few samples are likely due to sequencing errors or low-level contaminations. We specified a default minimum count (default 4). A 20% prevalence filter means at least 20% of its values should contain at least four counts. The low variance filters are the features that are close to constant throughout the experiment and are unlikely to be associated with the conditions under study. Their variances can be measured using inter-quantile range (IQR), standard deviation or the coefficient of variation (CV). This project followed the default low count filter at a 20% prevalence with a minimum count of four. The low variance was filtered based on the inter-quantile range with 10% to remove. Normalisation was done to address the variability in sampling depth and the sparsity of the data to enable more biologically meaningful comparisons. The data were rarefied to minimum library size. The data was scaled by the total sum scaling (TSS) factor to bring all the samples to the same scale. 2.6. Diversity and significance testing The data input was filtered, and the alpha diversity was measured and resulted with four methods, like Chao1, Shannon, Simpson and Fisher, with the statistical method of T-test /ANOVA. The beta diversity was constructed at the taxonomic level of Genus with Bray-Curtis index distance method based on Permutational MANOVA (PERMANOVA) statistical method. 2.7. Sequencing raw data deposition The raw data of the Illumina Miseq sequencing was deposited at the Indian Nucleotide Data Archive (INDA) of the Indian Biological Data Centre with the referenced INDA (Study/Bioproject) Accession No. INRP000065. The International Nucleotide Sequence Database Collaboration (INSDC) Bioproject Accession no. of this study is PRJEB62447 ( Table 1 ). 3. Results 3.1. The physico-chemical parameters of the soil All the soil samples before plantation and post0harvest were moderately alkaline, with pH ranging from 7.66 to 8.56. The soil sample amended with fertilizer (YF), had the lowest pH at 7.66, whereas the sample amended with cow dung manure (YC) had the highest pH at 8.56. The soil samples' electrical conductivity (EC) ranged from non-saline to moderately saline categories across all the samples. The soil sample amended with municipal organic waste compost (YMRAH) had the lowest EC of 0.363 dS/m, which is non-saline. Whereas, the vermicompost amended soil (YV) had the highest EC of 0.938 dS/m, which is moderately saline. The other soil samples had the EC ranging from 0.44 dS/m to 0.775 dS/m, which were in a slightly saline category. The total organic carbon (TOC) content in the pre-plantation floodplain soil ranged from 2.3–6.7%. The chemical fertilizer amended soil (YF) had the lowest level of total carbon, whereas the leaf compost amended soil (YD) had the highest total carbon content. The pre-plantation soil amended with kitchen waste compost (YK), cow dung manure (YC), and municipal organic waste compost (YM) also had high levels of total carbon content at 6.6%, 6.6%, and 6.4%, respectively. The post-harvest soil samples had higher levels of total carbon than the pre-plantation soils, ranging from 6.01–7.87%. In the post-harvest floodplain soils, the sample amended with chemical fertilizer (YFRAH) had the lowest level of TOC. While, the soil sample amended with cow dung manure (YCRAH) and leaf waste compost (YDRAH) had the highest levels of TOC at 7.87% and 7.72%, respectively. Among the residential post-harvest soil sample, leaf (NDRAH) and kitchen waste compost (NKRAH) amendments had higher levels of TOC at 45 and 3.84%, respectively. The total nitrogen levels in the pre-plantation floodplain soil ranged from 0.10–1.41%. The fertilizer amended soil (YF) had the lowest level of total nitrogen whereas, the vermicompost amended soil (YV) had the highest level of total nitrogen. The post-harvest floodplain soils had the total nitrogen ranging from 0.11–0.2%. The soil samples amended with vermicompost (YVRAH) and cow dung manure (YCRAH) had higher levels of total nitrogen at .02% and 0.19%, respectively. Among the residential post-harvest soil samples, the cow dung manure (NCRAH)and kitchen waste compost (NKRAH) amendments had the higher levels of total nitrogen at 1.35% and 0.82%, respectively (Table 2 ). Table 2 The pH and Electrical Conductivity (EC) of the soils Samples of different soil types pH Electrical Conductivity (EC) (dS/m) Total Carbon Total Nitrogen YC 8.56 0.607 6.6 ± 0.3 0.12 ± 0.0 YD 8.18 0.605 6.7 ± 0.3 0.17 ± 0.01 YK 7.8 0.755 6.6 ± 0.3 0.70 ± 0.01 YM 8.03 0.775 6.4 ± 0.3 0.22 ± 0.01 YV 7.7 0.938 3.7 ± 0.2 1.41 ± 0.1 YF 7.66 0.64 2.3 ± 0.1 0.10 ± 0.0 YCRAH 8.16 0.44 7.87 ± 0.4 0.19 ± 0.01 YDRAH 8.12 0.467 7.72 ± 0.4 0.17 ± 0.01 YKRAH 8.03 0.51 6.36 ± .03 0.16 ± 0.01 YMRAH 8.46 0.363 7.33 ± 0.4 0.11 ± 0.1 YVRAH 8.19 0.463 7.42 ± 0.4 0.2 ± 0.01 YFRAH 8.01 0.442 6.01 ± 0.3 0.15 ± 0.01 NCRAH 8.23 0.539 2.16 ± 0.11 1.35 ± 0.07 NDRAH 8.37 0.593 4 ± 0.2 0.52 ± 0.03 NKRAH 8.23 0.535 3.84 ± 0.19 0.82 ± 0.04 NFRAH 8.24 0.617 2.52 ± 0.13 0.74 ± 0.04 This table shows different soil samples' pH and electrical conductivity (EC). All the soil samples had a pH of moderately alkaline level, ranging from 7.66 to 8.56. The EC of the soil samples ranged from 0.64 to 0.938 mS/cm before plantation, while after harvest, the salinity of the soil samples was reduced slightly and ranged from 0.363 to 0.617 mS/cm. 3.2. Microbiome richness and diversity of soils 3.2.1. The total number of reads and OTUs The number of reads ranged from 0.2 million to 1.2 million in different soils. The residential soil amended with leaf compost (NDRAH) had the lowest number of reads, while the floodplain soil amended with chemical fertilizer (YF) had the highest number of reads among all the soil samples. Among the floodplain soil samples, the soil amended with chemical fertilizer (YF) and municipal organic waste compost (YM) had the largest library size before plantation. While in the post-harvest floodplain soil samples, the chemical fertilizer (YFRAH) and leaf compost (YDRAH) amended soil had the largest library size. On the other hand, the kitchen waste composted amended soil sample (NKRAH) had the largest library size among the post-harvest residential soil samples ( Fig. 1 ). All the samples had GC contents ranging from 54.50–56.50%. The total number of OTUs generated varied significantly from sample to sample, extending from 38305 to 335868. The soil sample YF had the highest total OTU, whereas sample YCRAH had the lowest total OTU. There was a reduction of OTUs in the post-harvest soil samples compared to the pre-plantation soil samples, except in the soil sample amended with leaf waste compost (YD and YDRAH), in which there was an increase in the total number of OTUs from 86390 to 149472. All samples were rarefied to even sequencing depth based on the sample having the lowest sequencing depth, and the analysis was visualised with the filtered data source. The result revealed a rarefaction curve indicating that all the sequencing reads were completely sampled. It also revealed that the pre-plantation soils had higher species richness than the post-harvest soil samples (Fig. 2 ). 3.2.2. Alpha and beta diversity analysis The alpha diversity was measured and resulted with four methods viz. Chao1, Shannon, Simpson, and Fisher with the statistical method of T-test /ANOVA. It was observed that pre-plantation soil samples had higher alpha diversity indices compared to the post-harvest soil samples ( Table 3 ). The Chao1 index provides an estimate of the true species richness in a sample, considering the potential presence of unseen species. In this study, the Chao1 index ranged from 176.35 to 219.00, with the YF sample having the highest Chao1 index, indicating a potentially higher species richness compared to the other samples. The Fisher index gives equal weight to all species, meaning that if a sample has an even distribution of individuals across all species, the Fisher index will be higher, indicating higher diversity. The Fisher index ranged from 0.929 to 0.969, with the YD sample having the lowest Fisher index and the YC sample having the highest Fisher index. Nevertheless, the differences in the Fisher index between most samples were relatively small, suggesting that the samples had similar levels of diversity ( Fig. 3 A ). Table 3 Alpha diversity indices Samples Chao1 index Fisher Index Shannon Index Simpson Index YC 189.86 34.60 3.77 0.94 YD 192.50 35.31 4.15 0.97 YK 195.00 35.79 4.05 0.97 YM 203.55 37.23 3.92 0.95 YV 200.71 38.20 4.19 0.97 YF 219.00 36.03 4.05 0.97 YCRAH 179.40 33.41 3.90 0.95 YDRAH 176.35 30.84 3.66 0.94 YKRAH 191.06 33.88 3.98 0.96 YMRAH 186.55 33.18 3.71 0.95 YVRAH 182.71 33.88 3.67 0.93 YFRAH 177.06 31.54 3.83 0.95 NCRAH 162.95 29.01 3.60 0.95 NDRAH 166.18 28.78 3.77 0.96 NKRAH 199.80 33.41 3.75 0.95 NFRAH 171.40 28.32 3.71 0.96 This table shows the alpha diversity indices of different soil samples. The microbial diversity was relatively higher in the pre-plantation soils than in post-harvest soils. The chemical fertiliser, municipal organic waste compost, and vermicompost-amended soils had higher levels of microbial diversity before plantation. In comparison, kitchen waste compost amended-higher levels of microbial diversity in the post-harvest soils. The Shannon index gives more weight to rare species, meaning that if a sample has a high number of rare species, the Shannon index will be higher, indicating higher diversity. The Shannon index ranged from 3.605 to 4.192, with the YV sample having the highest Shannon index, indicating higher diversity and evenness compared to the other samples. However, the differences in the Shannon index between most samples are relatively small, suggesting that the samples had similar levels of diversity. The Simpson index gives more weight to dominant species, meaning that if a sample has a high number of dominant species, the Simpson index will be higher, indicating lower diversity. In this study, the Simpson index ranged from 0.943 to 0.969, with the YD sample having the highest Simpson index, indicating lower diversity compared to the other samples. The differences in the Simpson index between most samples were relatively small, suggesting that the samples had similar levels of diversity ( Fig. 3 B ). In general, the microbial diversity among the soil samples was found to be statistically significant. The p-value in Chao1, Fisher, Shannon, and Simpson alpha diversity were measured to be 0.0079, 0.00014, 0.0057, and 0.11 with the ANOVA F-value of 7.17, 18.95, 7.90, and 2.66, respectively. The beta diversity was constructed at the Genus taxonomic level with the Bray-Curtis index distance method based on the Permutational MANOVA (PERMANOVA) statistical method. The p-value was < 0.001 with the PERMANOVA f-value of 9.2961. It revealed that sample groups were significantly different regarding their microbiome diversity ( Fig. 4 ). 3.2.3. Clustering analysis The dendrogram was constructed based on the distance measure of the Bray-Curtis Index with the Ward clustering algorithm. The result revealed that pre-plantation soils were clustered together, and post-harvest soil samples were clustered together, but pre-plantation soils and post-harvest soils were clustered distantly. Among the pre-plantation soil, the samples YC, YM, and YK are clustered more relatedly, whereas the samples YD, YF, and YK are clustered together more closely. In the post-harvest soil samples, YFRAH and YDRAH are closely related to each other, while YCRAH and YKRAH are closely related to each other. The sample YMRAH was more closely clustered towards YFRAH and YDRAH, but YVRAH was uniquely distanced from all the other samples. In the residential soil types samples, NFRAH and NDRAH are clustered together, while NCRAH and NKRAH were clustered together more relatedly ( Fig. 5 ). 3.3. Taxonomic classification and identification of beneficial and pathogenic microbes The OTU table gives an overall microbial community present in the given samples. From the generated OTU, the stacked bar charts are pivoted based on taxonomic levels from Phylum to Species. More than 30 phyla, 70 classes, 170 orders, 190 families, 240 genera of bacteria were identified across all the samples. 3.3.1. At the phylum level About Twenty-one phyla were identified across all the samples ( Supplementary Fig. S1 ). The most abundant ten phyla cover about 97 to 98% of all the phyla identified ( Supplementary Fig. S2 and S3 ). These phyla were further classified into more than Classes, Orders, Families, Genera, and Species ( Supplementary Fig. S4, S5, S6, S7, and S8 ). The most abundant bacterial phyla identified across all the soil samples were Proteobacteria, Planctomycetes, Actinobacteria, Firmicutes, Chloroflexi, Acidobacteria, Bacteroidetes, Verrucomicrobia, Gemmatimonadetes, Armatimonadetes, Cyanobacteria, Euryarchaeota, Nitrospirae , and Chlamydiae (Table 4 ). ). The counts of Proteobacteria showed a reduction in the post-harvest soils compared to pre-plantation soils, except in the leaf waste compost amended soil, where there was an increase of 98.30% (YD = 23532; YDRAH = 46664). The maximum reduction was seen in the vermicompost amended soil, about 66.87% (YV = 30021; YVRAH = 9946), followed by fertiliser-amended soil in which there was a reduction of approximately 49.34% (YF = 81283; YFRAH = 47197). Proteobacteria counts were seen highest in the fertilizer amended soils sample in both pre-plantation and post-harvest of the river bank soil. While its count was highest in the kitchen waste compost amended post-harvest soil among the residential soil samples. Table 4 Bacterial Phyla identified in different soil samples. Phylum Pre-plantation soils with OTUs Post-harvest soils with OTUs YC YD YK YM YV YF YCR AH YDR AH YKR AH YMR AH YVR AH YFR AH NCR AH NDR AH NKR AH NFR AH Proteobacteria 17403 23532 45575 57753 30021 81283 13684 46664 41494 30138 9946 47197 32289 30254 53374 44137 Planctomycetes 6594 10578 6847 22498 14486 40131 8924 29308 21839 19215 8423 27764 11065 7779 11093 12821 Actinobacteria 2611 3335 6736 10980 4899 18452 3343 10878 10580 7538 2881 12448 9355 8916 12758 13700 Firmicutes 9680 5363 12733 13258 6278 37115 4644 6546 18054 6025 3239 7337 1086 1178 3344 939 Chloroflexi 23657 11493 15112 36788 17529 55091 10729 16782 13700 14137 4361 18677 10665 6764 13415 9568 Acidobacteria 2611 3335 6736 10980 4899 18452 3343 10878 10580 7538 2881 12448 9355 8916 12758 13700 Bacteroidetes 8044 5106 16476 21780 10242 20104 3013 7846 7375 5141 1288 9725 15190 15305 21034 20170 Verrucomicrobia 638 1189 1224 2364 1800 5121 1293 4074 3912 2651 737 5303 3892 4316 7368 6008 Gemmatimonadetes 83 188 254 365 266 952 277 1069 509 587 149 1358 424 171 972 332 Armatimonadetes 63 84 249 326 206 585 85 337 327 202 56 541 278 525 638 854 Cyanobacteria 576 892 508 1117 1755 9142 101 288 433 259 87 480 365 411 641 514 Euryarchaeota 931 473 442 1771 1353 2755 184 133 127 101 36 184 369 337 369 429 [Thermi] 341 439 649 4310 296 1198 107 71 273 269 30 112 243 119 207 121 Nitrospirae 212 273 398 980 491 2627 235 810 642 442 283 1114 338 217 361 412 Chlamydiae 200 296 342 546 416 1613 377 1186 989 862 161 1672 64 88 89 154 Total OTU 73644 66576 114281 185816 94937 294621 50339 136870 130834 95105 34558 146360 94978 85296 138421 123859 This table shows the bacterial Phyla identified in the pre-plantation and post-harvest soil samples amended with different bio-compost. The level of bacterial phyla varied depending on the types of bio-compost used for soil amendment. There was a reduction of the bacterial phyla in the post-harvest soil samples, except in the leaf waste compost amended soil, where there was a significant increase in the bacterial phyla. Planctomycetes increased in the post-harvest soils amended with cow dung manure, leaf waste compost, and kitchen waste compost. At the same time, there was a decrease in its counts in the municipal organic waste compost, vermicompost, and fertilisers amended post-harvest soils as compared to pre-plantation soils. The highest increase of about 218% was observed in the kitchen waste compost amended soil, followed by the leaf waste compost amended soil, with a 177% increase in the post-harvest soil. The fertiliser-amended soil (YF) had the highest counts of Planctomycetes among the pre-plantation soil samples. At the same time, the leaf waste compost amended soil sample (YDRAH) had the highest counts of this phylum in the post-harvest soil samples. Actinobacteria counts were increased in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compost. In contrast, there was a decrease in its counts in the soils amended with municipal organic waste compost, vermicompost, and fertilisers. The highest increase of Actinobacteria was seen in the leaf waste compost amended post-harvest soil with an increase of about 226% and in kitchen waste compost amended soil of about 57%. In comparison, the maximum decrease of about 41% was seen in the vermicompost amended soil, followed by the fertiliser-amended soil with a reduction of about 32%. Generally, the fertiliser-amended soil samples had the highest counts of Actinobacteria among all the soil samples. The fertiliser-amended soil (YF) had the highest count of Firmicutes in the pre-plantation soil samples, but its count was drastically reduced in the post-harvest soil sample, with a decrease of about 80%. The decline was also seen in the soil amended with vermicompost, municipal organic waste compost, and cow dung manure. But there was an increase in the Firmicutes counts in the post-harvest soil samples amended with leaf and kitchen waste compost. The kitchen waste compost-amended soil sample had the highest count of Firmicutes amongst all the post-harvest soil samples. Chloroflexi and Bacteroidetes counts were increased in the post-harvest soil sample amended with leaf waste compost. Whereas there was a decrease in the fertiliser and other bio-composts amended post-harvest soil samples. The bacterial Phyla, such as Acidobacteria, Armatimonadetes , and Nitrospirae , were observed with increased counts in the post-harvest soil samples. These Phyla were reduced in the post-harvest soils amended with chemical fertilisers, municipal organic waste compost, and vermicompost. Gemmatimonadetes were relatively increased in all the post-harvest soil samples compared to pre-plantation soil samples. The other bacterial phyla, such as Cyanobacteria, Euryarchaeota , and Thermi , were also reduced in all the post-harvest soils. Generally, the beneficial phyla increased in the post-harvest soils, which were amended with leaf waste compost and kitchen waste compos. In contrast, there was a reduction in these phyla in the soils amended with chemical fertilisers, cow dung manure, municipal organic waste compost, and vermicompost. The most significant decrease was in the soil amended with vermicompost and chemical fertilisers, about 63% and 50%, respectively. Chlamydiae , which is a pathogenic bacterial phylum, was seen to increase in all the post-harvest soil samples. The highest counts were seen in the chemical fertiliser-amended soil, both in the pre-plantation and post-harvest soil samples. 3.3.2. At the genus and species level The bacterial genera identified varied across the samples of pre-plantation and post-harvest soils, amended with chemical fertiliser and different types of bio-composts. About 30 bacterial genera constitute the core microbiome, detected above a threshold level across the samples. The levels of these core microbiome varied in different soil samples depending on the types of composts used as soil amendment ( Fig. 6 ). In general, the significant beneficial genera seen across the soils samples with different proportions were Achromobacter, Agromyces, Bacillus, Clostridium, Nitrospira, Planctomyces, Pseudomonas, Steroidobacter , Streptomyces, Alicyclobacillus, Bdellovibrio , and others (Table 5 ; Fig. 7 ; and Supplementary Fig. S9 ). Achromobacter counts were found to be highest in the leaf waste compost amended soils, both in the pre-plantation and post-harvest samples. However, the counts were reduced in all the post-harvest soil samples except in the fertiliser-amended soil, where the count was slightly increased. Table 5 Beneficial bacterial genera identified in different soil samples. Bacterial Genera Pre-plantation soil samples with OTUs Post-harvest soil samples with OTUs YC YD YK YM YV YF YCR AH YDR AH YKR AH YMR AH YVR AH YFR AH NCR AH NDR AH NKR AH NFR AH Achromobacter 69 238 19 25 46 38 36 140 7 17 13 48 55 13 27 70 Actinomadura 34 1 670 426 9 3 27 9 259 73 27 2 11 16 740 6 Agromyces 203 441 358 470 267 1056 74 348 208 148 90 331 21 23 4 10 Alcanivorax 7 8 740 229 36 10 1 3 18 1 1 0 0 1 0 0 Brevibacterium 566 18 3330 339 8 75 0 0 3 1 1 1 0 0 1 1 Bacillus 261 69 554 514 80 658 417 137 1052 430 58 78 40 34 276 38 Clostridium 20 22 19 59 25 63 128 53 114 43 32 40 1 2 25 2 Myxococcus 114 300 510 1196 226 692 74 573 353 428 75 384 53 65 42 254 Halomonas 2223 2 2038 63 13 2 0 0 1 0 1 0 1 2 6 2 Kaistobacter 134 151 516 367 102 921 68 168 208 140 163 414 693 1026 1225 1479 Methanobacterium 43 186 98 354 51 890 4 23 29 16 1 29 2 0 0 0 Methanosarcina 632 1 12 90 67 35 90 1 4 3 5 0 14 0 9 2 Microbulbifer 73 1 678 9 2 14 9 0 1008 4 2 1 10 7 33 2 Nitrospira 156 254 346 831 349 1976 214 770 618 412 226 970 286 197 336 363 Planctomyces 1144 1395 1221 4689 2407 5981 1208 3609 2779 2631 1323 3325 1492 856 1338 1356 Pseudomonas 120 116 524 234 259 541 73 33 57 27 29 290 24 21 41 62 Rhodoplanes 136 202 333 553 186 675 123 510 485 322 125 485 203 153 263 275 Sphingobacterium 31 44 1162 83 56 183 0 0 4 1 1 8 11 6 7 11 Streptomyces 2005 292 467 5423 245 2236 15 39 114 37 8 24 42 43 36 36 Steroidobacter 276 292 416 883 327 670 343 1894 1559 1090 263 1000 1927 1025 2802 1275 Lactobacillus 20 16 94 16 132 59 20 21 70 27 11 26 37 82 67 76 Xiphinematobacter 46 220 21 107 42 231 72 242 427 133 29 347 18 126 187 88 Alicyclobacillus 100 416 611 867 528 1811 161 824 532 356 130 1095 2 3 1 7 Truepera 116 227 43 123 30 354 10 50 27 34 14 69 2 5 3 4 Gemmata 206 438 347 1107 543 2334 790 2680 1498 2175 781 2687 334 287 471 506 Beneficial OTU 9301 5368 18457 19396 6044 21583 3957 12127 11437 8550 3410 11655 5279 3993 7941 5926 Total OTU 15220 12272 31931 42295 18333 49024 7928 23066 24704 19800 6352 24131 15722 14134 23460 21711 Percentage 61% 44% 58% 46% 33% 34% 50% 53% 46% 43% 54% 48% 34% 28% 34% 27% This table shows the beneficial genera identified in the soil samples amended with different bio-compost. The level of each bacterial genera varied depending on the types of bio-composts used as soil amendments. Generally, there was a reduction in the level of the beneficial bacteria in the post-harvest soil samples, except in the leaf waste compost amended soil, where there was an increase in the beneficial genera. Agromyces level was highest in the fertiliser-amended soil among the pre-plantation soil sample. Still, leaf waste compost amended soil became highest in its count in the post-harvest soil samples. There was a reduction in Agromyces counts in the post-harvest soil samples. The most significant decrease was seen in the fertiliser-amended soil at about 68%. While the leaf waste compost-amended soil saw the least reduction in Agromyces , about 21%. Bacillus count was highest in the fertiliser-amended soil (YF = 658) among the pre-plantation soil samples, but its count was reduced drastically, about 88%, in the post-harvest sample (YFRAH = 80). The Bacillus levels were increased in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compost. The greatest increment of about 98% was seen in the leaf waste compost amended soil sample in the post-harvest soil samples. Among the post-harvest soil samples, the kitchen waste compost amended soil sample had the highest level of Bacillus in both the river bank soil and residential soil. Clostridium was detected with relatively lower counts in the pre-plantation soil samples, but its level was increased in the post-harvest soil samples. The Clostridium level was highest in the cow dung manure and kitchen waste compost-amended post-harvest soils. Nitrospira was identified with the highest count in fertiliser-amended soil, followed by municipal organic waste compost-amended soil among the pre-plantation soil samples. Though, its count was reduced to half in the post-harvest soil samples. While there was an increase in the Nitrospira counts in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compost. The count of Nitrospira was relatively higher in the fertiliser, cow dung manure and leaf waste compost-amended soil samples compared to municipal organic waste compost and vermicompost-amended soil samples amongst the post-harvest soil. Planctomyces counts were relatively high in all the soil samples. The highest counts were seen in the fertiliser and municipal organic waste compost-amended soil in the pre-plantation soil samples. Nonetheless, its count was reduced to almost half in the post-harvest soil samples. At the same time, there was an increase in the counts of Planctomyces in the post-harvest soils amended with cow dung manure, leaf waste compost, and kitchen waste compost. The leaf waste compost-amended soil sample had the highest level of Planctomycetes among the post-harvest soil samples. Steroidobacter was identified with relatively higher counts in the post-harvest soil samples than in the pre-plantation soils. The municipal organic waste compost-amended soil had the highest level in the pre-plantation soil samples. While, the Steroidobacter counts became highest in the leaf waste compost and kitchen waste compost-amended soil samples among the post-harvest soil samples. Pseudomonas was higher in the pre-plantation soil samples than the post-harvest soil samples. In the pre-plantation soil samples, the kitchen waste compost and chemical fertiliser-amended soils had relatively higher counts of Bacillus , but the post-harvest soils had relatively similar levels of this genus, though slightly higher in the chemical fertiliser-amended sample. Streptomyces was observed with a relatively high count in the pre-plantation soils, but its count was reduced drastically in the post-harvest soil samples. The pre-plantation soil samples amended with municipal organic waste compost, chemical fertiliser, and cow dung manure were seen with relatively higher Streptomyces among the pre-plantation soil samples. Alicyclobacillus was seen with relatively higher levels in the pre-plantation soil samples amended with chemical fertiliser, municipal organic waste compost, kitchen waste compost, and vermicompost. But the count of Alicyclobacillus was reduced in the post-harvest soil samples. On the other hand, the soil samples amended with leaf waste compost and cow dung manure showed an increase in Alicyclobacillus in the post-harvest soil samples. Kaistobacter was also observed at a relatively higher level in the pre-plantation soil samples in all the amendments, but its counts were reduced in the post-harvest samples. This genus is the only bacterial genus that was observed to be higher in the residential soil than in the Yamuna floodplain soil samples. Kaistobacter was seen with relatively higher level in the fertilizer-amended soil sample in both the pre-plantation and post-harvest soils. The other bacterial genera such as Brevibacterium, Halomonas, Methanobacterium , and Sphingobacterium , were observed to be relatively higher in the pre-plantation soil samples of all amendments, but their counts were reduced drastically in the post-harvest soil samples. The counts of such genera were highest in the kitchen waste compost-amended soil samples, except for the Methanobacterium , where the count was higher in the chemical fertiliser-amended soil sample. Microbulbifer was also observed to be relatively high only in the kitchen waste compost-amended soil samples, both in the pre-plantation and post-harvest. There was a reduction in the overall OTUs of the beneficial genera in all the post-harvest soil samples compared to the pre-plantation soils, except in the leaf waste compost-amended soil. The leaf waste compost amended soil had the lowest beneficial OTU amongst the pre-plantation soils but the highest beneficial OTU among the post-harvest soil samples. There was an increase of about 125% in the OTU of the beneficial genera in the post-harvest soil amended with leaf waste compost. While, a reduction of about 46% was observed in the fertiliser-amended soil. The most significant reduction of the beneficial OTU was seen in the soil sample amended with cow dung manure, which was about a 57% reduction. The vermicompost and cow dung manure amended-soil samples had the lowest counts of beneficial OTUs among the post-harvest soil samples. The pathogenic genera identified across the samples were Agrobacterium, Flavobacterium, Leptolyngbya, Geobacter, Nocardia, Mycobacterium , and others (Table 6 ). The pre-plantation soil samples had negligible levels of Agrobacterium , except in the leaf waste compost amended soil. While the counts of Agrobacterium were increased in all the post-harvest soil samples. Flavobacterium counts were higher in the pre-plantation soils than the post-harvest soils in all the samples. The fertiliser-amended soil samples had the highest counts of the Flavobacterium in both the pre-plantation and post-harvest soil samples. Whereas the cow dung-amended soils had the lowest counts of the genus in all the samples. Leptolyngbya was also detected across the samples, but its counts were relatively higher in the pre-plantation soil. The highest count of Leptolyngbya was seen in the fertiliser-amended soil samples, whereas the vermicompost-amended soil samples had the lowest counts in the pre-plantation as well as the post-harvest soil samples. Table 6 Pathogenic bacterial genera identified in different soil samples. Bacterial Genera Pre-plantation soils with OTUs Post-harvest soils with OTUs YC YD YK YM YV YF YCR AH YDR AH YKR AH YMR AH YVR AH YFR AH NCR AH NDR AH NKR AH NFR AH Agrobacterium 1 131 5 0 9 3 18 376 6 142 16 24 40 68 31 43 Flavobacterium 110 224 409 482 683 1442 35 48 95 37 63 103 78 67 88 195 Cupriavidus 0 3 1 1 4 4 4 4 1 3 4 18 65 122 43 220 Prevotella 6 4 17 10 21 20 0 1 6 6 3 5 9 18 27 20 Leptolyngbya 159 157 166 204 127 1222 7 27 30 19 7 77 1 0 21 0 Balneimonas 26 33 100 113 23 121 25 53 52 69 47 107 125 54 81 113 Protochlamydia 2 7 24 20 5 57 10 38 52 59 5 75 0 12 3 12 Saccharothrix 0 0 0 0 0 0 0 0 0 0 3 0 7 0 21 405 Rhabdochlamydia 3 14 18 29 10 42 2 26 10 14 7 30 2 26 7 52 Phaeospirillum 20 48 57 136 38 202 55 110 106 80 24 132 83 137 174 266 Saprospira 4 1 0 0 6 8 1 18 33 3 3 23 0 0 1 0 Aeromicrobium 3 15 20 23 10 21 6 34 31 42 8 85 2 1 1 6 Legionella 5 7 9 18 6 25 12 20 54 39 8 53 1 2 1 7 Geobacter 11 4 29 40 13 146 20 159 99 93 22 248 38 45 225 17 Nocardia 28 198 80 191 9 18 7 82 34 25 23 129 9 28 15 5 Mycobacterium 409 579 1436 928 286 800 174 634 573 500 137 483 90 158 166 74 C.Solibacter 63 82 129 295 105 467 88 182 167 149 41 258 217 150 366 213 Pathogenic OTU 850 1507 2500 2490 1355 4598 464 1812 1349 1280 421 1850 767 888 1271 1648 Total OTU 15220 12272 31931 42295 18333 49024 7928 23066 24704 19800 6352 24131 15722 14134 23460 21711 Percentage 6% 12% 8% 6% 7% 9% 6% 8% 5% 6% 7% 8% 5% 6% 5% 8% This table shows the pathogenic genera identified in the soil samples amended with different bio-compost. The level of each pathogenic bacterial genera varied depending on the types of bio-composts used as soil amendments. Generally, there was a reduction in the level of the beneficial bacteria in the post-harvest soil samples. The other bacterial genera such as Balneimonas, Protochlamydia, Rhabdochlamydia , and Phaeospirillum , were also found to be present across all the samples, but the number of counts varied across the samples. The fertiliser-amended soil samples had the highest level of all these pathogenic genera amongst the pre-plantation as well as the post-harvest soil samples. The level of Balneimonas, Protochlamydia , and Rhabdochlamydia remain almost the same in the post-harvest soils corresponding to the pre-plantation soils. While there was a slight increase in the counts of Phaeospirillum in the post-harvest soils concerning the pre-plantation soils. The vermicompost and cow dung manure-amended soil samples had the lowest counts of these pathogenic genera. Mycobacterium was detected with a relatively high concentration in all the samples. The kitchen waste and municipal organic waste compost-amended soils had the highest counts of Mycobacterium amongst the pre-plantation soils, while the leaf waste compost-amended soil had the highest count in the post-harvest soil samples. Geobacter was also detected with a relatively higher level in the post-harvest soil samples compared to the pre-plantation soils. The fertilizer-amended soil had the highest count of the genus amongst all the samples. The leaf waste compost-amended soil had the lowest count of the genus amongst the pre-plantation soils, whereas the cow dung manure and vermicompost-amended soils had the lowest counts in the post-harvest soil samples. The overall sum of OTUs of pathogenic genera was observed to be highest in the fertiliser-amended soil samples in the pre-plantation soil as well as in the post-harvest soil. The cow dung manure and vermicompost amended soil samples had the lowest counts of pathogenic OTUs. In general, there was a reduction in the total pathogenic OTUs in the post-harvest soil samples at the genus level. The resolution of the 16S rRNA metagenomic profiling of the bacterial microbiome became vaguer at the species level. But there was detection of some beneficial and pathogenic bacterial species in the soil samples. The type of bacterial species and its proportion present in the pre-plantation soil samples were different from the post-harvest soils and also varied amongst the soil samples amended with different types of bio-composts ( Supplementary Fig. S10 and S11 ). The major beneficial species identified across the samples were bacteriovorus, cellulosum, clausii, copri, debontii, diminuta, endophyticus, hirsuta, multivorum, ochraceum, vinacea , and others (Supplementary Table S1 ). The fertiliser-amended soil had the highest count of bacteriovorus amongst all the pre-plantation soil samples. In contrast, the leaf waste compost-amended soil sample had the highest level of the species in the post-harvest soil samples. The residential soil samples had a relatively higher bacteriovorus level than the riverbank soil samples. Cellulosum was found to be highest in the fertiliser and municipal organic waste compost-amended soil samples in the pre-plantation soils, while the leaf waste compost-amended soil had the highest counts of the species after the harvest. The abundance of copri was reduced in the post-harvest soil samples compared to the pre-plantation soils. The fertiliser and municipal organic waste compost-amended soils had the highest counts of copri before plantation, but the kitchen and leaf waste compost-amended soils had the higher counts of the species in the post-harvest samples. The counts of debontii were relatively higher in the post-harvest soil samples than the pre-plantation soils. Also, the residential soil samples had higher species counts than the Yamuna floodplain soil samples. The counts of diminuta and hirsuta were lower in the post-harvest soil samples compared to the pre-plantation soils samples. The fertiliser and municipal organic waste compost-amended soil samples had relatively higher diminuta . While the leaf waste compost and cow dung manure amended soils had the higher counts of hirsuta in both pre-plantation and post-harvest soil samples. The level of bacterial species, endophyticus , were also reduced in all the post-harvest soil samples, except in the soil sample amended with leaf waste compost in which there was an increase in its count. The level of ochraceum was observed to be higher in the post-harvest soil samples than the pre-plantation soil samples. The leaf waste compost and kitchen waste compost-amended soil samples had a relatively higher level of ochraceum in the post-harvest soil samples. The total counts of vinacea were observed to be lower in the post-harvest soils. The kitchen waste compost and municipal organic waste compost-amended soil samples were seen with a relatively higher level of the vinacea species , among all the soil samples, both in pre-plantation as well as post-harvest soils. Generally, the pre-plantation soils had a relatively higher counts of the beneficial species as compared to the post-harvest soils, except in the leaf waste compost-amended soil in which there was a slight increase in the count of the beneficial species. The presence of some pathogenic species was also detected across the soil samples. The major pathogenic bacterial species identified were campisalis, fulvum, intestinale, parahaemolyticus, parainfluenza stationis , and stercorea (Supplementary Table S2). Campisalis was detected only in the pre-plantation soil which was amended with the kitchen waste compost. while, there was a complete absence of this bacterial species in all the post-harvest soil samples. The relative level of fulvum tend to increase in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compos. The counts of fulvum were highest in the fertilizer-amended soil in both pre-plantation and post-harvest soil samples. The count of parahaemolyticus was relatively high only in the pre-plantation soil which was amended with municipal organic waste compost, while the other soil samples had negligible level of this bacterial species. The level of stercorea was observed to be relatively higher in the pre-plantation soils compared to the post-harvest soils. The fertiliser-amended soil had the higher level of this bacterial species in all the soil samples. In general, the counts of pathogenic bacterial OTU at the species level were relatively higher in the fertiliser-amended soil samples in both the pre-plantation and post-harvest soil samples. 3.4. Relative abundance of beneficial and pathogenic microorganisms in the cultivars vis-à-vis soils. The microbiome in the cultivars, Amaranthus cruentus , varied significantly depending on the types of soil and bio-compost used to grow them (Sharma et al., 2023). The cultivars which were cultivated using bio-composts had relatively higher beneficial bacteria with lower pathogens than the cultivar of the chemical fertiliser, except in the municipal organic waste compost-amended soil produce (Supplementary Table S3 and S4). It was also observed that the vegetable produce of the Yamuna floodplain soil had higher beneficial microorganisms than the produce of the residential soil. The cultivar of the leaf waste compost and kitchen waste compost-amended soil had the highest level of the beneficial microorganisms with the observed total OTUs of 16678 and 16573, respectively. While, the municipal organic waste compost and chemical fertiliser-amended soil cultivar had the lowest level of beneficial microorganisms with the observed total OTUs of 6202 and 8463, respectively. On the other hand, the cultivar of the chemical fertiliser (total OTU = 2984) had highest pathogenic bacteria and the cultivars of the municipal organic waste compost and leaf waste compost-amended soil had the lowest pathogens with the observed total OTUs of 347 and 588, respectively (Fig. 8 ). 4. Discussion 4.1. The effect of bio-composts on the microbial richness and diversity in the soils The variation in the number of reads and GC contents across the samples suggest differences in microbial richness and diversity. Studies have shown that microbial richness and diversity was influenced by various factors, including soil type, management practices, soil amendments, and environmental conditions (Fierer, Bradford, and Jackson 2007 ; Delgado-Baquerizo et al. 2016 ). Higher microbial diversity is generally considered beneficial for ecosystem functioning and resilience. The significant variation in the total number of OTUs across the samples indicated differences in microbial community composition. The soil sample amended with chemical fertiliser of Yamuna floodplain soil had the highest number of OTUs, while the post-harvest Yamuna floodplain soil amended with cow dung manure had the lowest OTU. This variation could be attributed to variations in soil characteristics, land use, bio-compost use, and plant-microbe interactions in this cropping system. Different microbial taxa may respond differently to environmental changes, addition of the soil amendments like bio-composts, and management practices, leading to varying OTU counts (Berg and Smalla 2009 ; Philippot et al. 2013 ). There was a reduction in the total OTUs in the post-harvest soil samples compared to the pre-plantation soils, except in the leaf waste compost amended soil sample, where there was an increase in the total OTU in the post-harvest soil. This general reduction in OTUs in post-harvest soil samples was consistent with previous studies that have reported a decrease in microbial diversity following disturbance events such as harvesting or land-use changes. Disturbances can disrupt microbial communities and reduce overall diversity. However, the increase in OTUs observed in the soil samples amended with leaf waste compost was intriguing. This could be due to the favourable condition for the microbial growth and activity promoted by the leaf waste bio-compost. Compost amendments have been reported to enhance soil fertility, organic matter content, and microbial activity, which promotes microbial diversity (Kibblewhite, Ritz, and Swift 2008 ). The addition of bio-compost may introduce new microbial taxa or create favourable conditions for the growth of certain microbial populations, leading to an increase in OTU counts. The bio-composts generated from the various types of organic wastes had different qualities depending on the nutrients and potentially toxic elements content (Mahongnao et al. 2023 ). The impact of the bio-compost amendment on the microbial community composition of the soil needs to be understood. Nevertheless, some studies have investigated the changes in microbial community composition following bio-compost amendment. For example, a recent study examined the microbial communities in compost-amended soils using high-throughput sequencing techniques. They found that the long-term application of bio-compost amendment significantly altered the microbial community structure, leading to an increase in beneficial microbial groups such as Sphingomonas , Acidibacter , and Nocardioides , and reduced the relative abundance of the pathogenic microorganisms such as Stachybotrys and Aspergillus (Liu et al. 2022). Such results are consistent with our results in which we have shown that adding bio-composts in the soil increases beneficial microorganisms such as Achromobacter, Agromyces, Bacillus , and others. Also, there was a reduction of the pathogenic microbial group such as Leptolyngbya , Balneimonas, Protochlamydia, Rhabdochlamydia , and Phaeospirillum in the bio-compost-amended soils compared to the fertiliser-amended soil. The addition of bio-compost also enhanced the microbial diversity in the soil. In this study, we have shown that bio-compost amendments such as leaf waste compost, kitchen waste compost, vermicompost, municipal organic waste compost, and cow dung manure enhanced the microbial diversity and evenness of the microbial distribution in the soil. Other studies have also shown that compost amendment significantly increased microbial diversity, and enhanced functionality which is essential for soil health and ecosystem functioning. Recent research has also focused on understanding the functional potential of microbial communities in compost-amended soils. A study by Delmont used metagenomic approaches to investigate the functional genes present in compost-amended soils. They found an enrichment of genes associated with organic matter decomposition, nutrient recycling, and plant-microbe interactions, suggesting the positive influence of compost on soil microbial functions (Delmont et al. 2018 ). Beneficial microorganisms in the bio-compost could benefit plant health when used as a soil amendment. Applying bio-compost as soil amendments has been shown to promote plant growth and improve plant health. These effects are often attributed to the interactions between compost-influenced microbial communities and plants. For example, a study demonstrated that compost amendment increased the abundance of beneficial microbes, such as plant growth-promoting bacteria and mycorrhizal fungi, leading to improved nutrient availability and plant growth (Hu et al. 2018 ). Recent studies have also investigated the long-term effects and sustainability of bio-compost amendments on soil microbial dynamics by evaluating the persistence of compost-induced changes in microbial communities over several years. They found that the impact of compost on microbial community composition and diversity was still evident even several years after initial application, highlighting the potential long-term benefits of bio-compost amendments (Heisey et al. 2022 ). 4.2. Augmentation of beneficial microorganisms in the soil Bio-composts, also known as organic composts, are valuable soil amendments that enhance soil fertility and promote the growth of beneficial microorganisms. Adding compost to the soil is an effective way to augment beneficial microorganisms and improve soil health. Compost is rich in organic matter and nutrients, making it an ideal substrate for microbial growth. The soil amendment with compost enhances microbial diversity, activity, and biomass, leading to numerous benefits for soil fertility, nutrient recycling, and plant growth. In our study, we observed that the addition of bio-compost, such as leaf waste compost, cow dung manure, kitchen waste compost, and municipal organic waste compost, in the soil enhanced the beneficial bacteria such as Clostridium, Nitrospira, Planctomyces, Pseudomonas, Steroidobacter , and Streptomyces and others. It was observed that the soil sample amended with leaf waste compost was seen with the highest augmentation of the beneficial microorganisms in the post-harvest soil. On the other hand, the soil sample amended with chemical fertiliser was seen with the most significant reduction in the beneficial microorganisms in the post-harvest soils. These microorganisms can potentially impart beneficial effects on soil and plant health through nutrient solubilisation, nitrogen fixation, bio-control, and plant growth-promoting activities (Wang et al. 2020 ). Compost contains diverse microorganisms, including bacteria, fungi, protozoa, and beneficial nematodes. These microorganisms play crucial roles in nutrient transformation, organic matter decomposition and soil structure formation. The addition of compost could promote the colonisation of soil with diverse microbial communities, leading to increased functional diversity and resilience of the soil ecosystem (Fierer et al. 2013 ). The beneficial microorganisms present in bio-compost actively participate in nutrient recycling processes. They decompose organic matter, releasing nutrients such as nitrogen, phosphorus, and micronutrients in plant-available forms. Compost-amended soils show improved nutrient availability and cycling, which enhances plant nutrient uptake and reduces the risk of nutrient leaching (Wani et al. 2015 ). Microorganisms in compost also contribute to forming and stabilising soil aggregates, improving soil structure. This enhances soil porosity, water infiltration, and water-holding capacity, leading to better moisture retention in the root zone. The presence of compost-derived microorganisms could improve soil physical properties and mitigate the negative impacts of soil compaction (Grundmann 2004 ). 4.3. Biocontrol of pathogenic microorganisms in the soils Bioremediation of pathogenic microorganisms aims to mitigate their presence and potential harm through natural processes. Bio-composts have been increasingly recognised for their potential in bioremediation due to their diverse microbial communities and ability to enhance soil health. Composts can contribute to the bioremediation of pathogenic microorganisms in the soil through several mechanisms like microbial competition, antibiosis, predation, production of antimicrobial compounds, and alteration of environmental conditions (e.g., pH or moisture) unfavourable for pathogens survival (Tóthné et al. 2021; Pugliese et al. 2011 ). The diverse microbial community in bio-composts contributes to the effectiveness of these mechanisms. It is worth noting that bio-composts’ efficacy in bioremediation can vary depending on factors such as compost composition, application rates, and environmental conditions. Therefore, it is essential to consider site-specific factors when implementing bioremediation strategies using bio-composts. In this study, we analysed the effectiveness of different bio-composts, such as leaf waste compost, kitchen waste compost, cow dung manure, vermicompost, and municipal organic waste compost, in comparison with the chemical fertilizer, on the bioremediation of pathogens. We observed that the number of pathogenic OTU was higher in the pre-plantation soils than post-harvest soils. Also, the chemical fertiliser-amended soil samples had a higher level of pathogenic OTUs, in both the pre-plantation and post-harvest soils than the bio-composts-amended soil samples. The addition of bio-composts was seen with a higher level of bioremediation of the pathogenic microorganisms in the post-harvest soils, such as Flavobacterium, Prevotella, Leptolyngbya , and Nocardia. Bio-composts' effectiveness in bioremediation has also been demonstrated in some recent studies. For instance, studies have reported the potential of thermophilic compost and vermicompost in the bioremediation of soil contaminated phytopathogenic. The researchers reported the disease suppressive properties of thermophilic compost on a wide range of phytopathogens viz., Rhizoctonia Phytopthora, Plasmidiophora brassicae, Gaeumannomyces graminis , and Fusarium sp. Bio-composts were also reported to be effective in controlling the arthropods and nematodes and improved overall soil health (Pathma and Sakthivel 2015 ; Tóthné Bogdányi et al. 2021 ). Similarly, researchers have also examined the antagonistic activity of microorganisms isolated from bio-composts on the soil-borne plant pathogens and found to be effective in suppressing the pathogens such as Fusarium sp. (Suárez-Estrella et al. 2007 ; Pugliese et al. 2008 ). The green waste compost and the compost products like compost tea, compost extract, and the solid phase after extraction, were also reported to be having a strong inhibitory action on the growth of plant pathogens such as Fusarium oxysporum, Rhizoctonia sp. and Pythium debaryanum (Milinković et al. 2019 ). Bio-composts from different sources could be fortified with biocontrol agents, which can suppress soil-borne plant pathogens. Applying such bio-composts could bring about environmental-friendly control of pathogens, improve soil fertility, and achieve environmental sustainability. 4.4. Relationship of soil microbiome vis-à-vis the cultivars The beneficial and pathogenic microbiome of the cultivars had been observed to be significantly impacted by the soil types and amendments used to grow them (Sharma et al. 2023). The cultivars produced using bio-composts generally exhibited higher levels of beneficial bacteria than those produced using chemical fertilisers, except when municipal organic waste compost was used. This implies that bio-composts could contribute to a more favourable microbial community in the cultivars, potentially enhancing their growth and overall health. The higher abundance of beneficial microorganisms in the leaf waste compost and kitchen waste compost-amended cultivars, as evidenced by higher total operational taxonomic units (OTUs), which indicates the positive impact of these composts on the microbial diversity and richness. On the other hand, the cultivars grown with chemical fertiliser alone showed a higher abundance of pathogenic bacteria, as indicated by the total pathogenic OTUs. This finding suggests that chemical fertilisers may not support the beneficial microbiome and potentially favour the growth of harmful microorganisms. This is supported by study that reported that prolonged chemical fertiliser application limits ecosystem functioning (Bai et al. 2020 ). Moreover, this study revealed variations in the abundance of beneficial microorganisms in the cultivars depending on the soil type. Specifically, the cultivar grown in the Yamuna floodplain soil exhibited higher levels of beneficial microorganisms than those grown in residential soil. This observation highlights the importance of soil quality and composition in shaping the microbial community associated with plant cultivars. Recent studies have reported the interconnectedness of the beneficial soil microbiome with that of food safety and human health, that beneficial microorganisms in the soil could significantly promote food safety and human health (Bertola, Ferrarini, and Visioli 2021 ). So, the present study showed that applying bio-composts as soil amendments enhances soil quality and promotes beneficial microorganisms in the soil that can improve food safety and human health. Though there are some limitations in this study that certain OTUs generated could not be assigned to a particular bacterial taxonomy and also, some bacterial taxa identified are novel and their functions are not known to the current literature whether they are beneficial or pathogenic. 5. Conclusion This study revealed that applying bio-composts enhances the soil’s microbial richness and diversity. The types of microorganisms and their proportion in the soils varied depending on the nature of the bio-composts added to the soil. Adding bio-composts also helps enrich the beneficial microorganisms and the bioremediation of the pathogenic microorganisms in the soils. Declarations Acknowledgement The Authors acknowledged the University Grants Commission, Govt. of India, for providing a research fellowship to the first author, bearing the award letter no. 598/CSIR-UGC NET JUNE 2018. We thank Prof. Savita Roy, Principal of the Daulat Ram College, University of Delhi, and the Department of Biochemistry, Daulat Ram College, University of Delhi, for providing the logistics, working space, and equipment for this research. Author’s contributions Sophayo Mahongnao – Data compilation, analysis, data curation, and original manuscript drafting Pooja Sharma - Data compilation, analysis, and data curation Arif Ahamad – Conceptualization and methodology Sarita Nanda – Conceptualization, experimental design and supervision Funding Source This research study received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors. Consent to Participate: Not applicable. Consent to Publish: Not applicable. References Azeem M, Hale L, Montgomery J, Crowley D, McGiffen ME (2020) Biochar and compost effects on soil microbial communities and nitrogen induced respiration in turfgrass soils. PLoS One 15(11 November):1–20. https://doi.org/10.1371/journal.pone.0242209 Bai YC, Chang YY, Hussain M, Lu B, Zhang JP, Song XB, Lei XS, Pei D (2020) Soil chemical and microbiological properties are changed by long-term chemical fertilizers that limit ecosystem functioning. Microorganisms 8(5). https://doi.org/10.3390/microorganisms8050694 Berg G, Smalla K (2009) Plant species and soil type cooperatively shape the structure and function of microbial communities in the rhizosphere. FEMS Microbiol Ecol 68(1):1–13. https://doi.org/10.1111/j.1574-6941.2009.00654.x Bertola M, Ferrarini A, Visioli G (2021) Improvement of soil microbial diversity through sustainable agricultural practices and its evaluation by -omics approaches: A perspective for the environment, food quality and human safety. Microorganisms 9(7). https://doi.org/10.3390/microorganisms9071400 Delgado-Baquerizo M, Maestre FT, Reich PB, Jeffries TC, Gaitan JJ, Encinar D, Berdugo M, Campbell CD, Singh BK (2016) Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat Commun 7:1–8. https://doi.org/10.1038/ncomms10541 Delmont TO, Quince C, Shaiber A, Esen ÖC, Lee ST, Rappé MS, MacLellan SL, Lücker S, Eren AM (2018) Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes. Nat Microbiol 3(7):804–813. https://doi.org/10.1038/s41564-018-0176-9 Farrell M, Griffith GW, Hobbs PJ, Perkins WT, Jones DL (2010) Microbial diversity and activity are increased by compost amendment of metal-contaminated soil. FEMS Microbiol Ecol 71(1):94–105. https://doi.org/10.1111/j.1574-6941.2009.00793.x Fierer N, Bradford MA, Jackson RB (2007) Toward an ecological classification of soil bacteria. Ecology 88(6):1354–1364. https://doi.org/10.1890/05-1839 Fierer N, Ladau J, Clemente JC, Leff JW, Owens SM, Pollard KS, Knight R, Gilbert JA, McCulley RL (2013) Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science (80- ) 342(6158):621–624. https://doi.org/10.1126/science.1243768 Grundmann GL (2004) Spatial scales of soil bacterial diversity - The size of a clone. FEMS Microbiol Ecol 48(2):119–127. https://doi.org/10.1016/j.femsec.2004.01.010 Heisey S, Ryals R, Maaz TM, Nguyen NH (2022) A Single Application of Compost Can Leave Lasting Impacts on Soil Microbial Community Structure and Alter Cross-Domain Interaction Networks. Front Soil Sci 2(April):1–16. https://doi.org/10.3389/fsoil.2022.749212 Hirt H (2020) Healthy soils for healthy plants for healthy humans. :1–5. https://doi.org/10.15252/embr.202051069 Ho TTK, Tra VT, Le TH, Nguyen NKQ, Tran CS, Nguyen PT, Vo TDH, Thai VN, Bui XT (2022) Compost to improve sustainable soil cultivation and crop productivity. Case Stud Chem Environ Eng 6(April):100211. https://doi.org/10.1016/j.cscee.2022.100211 Hu L, Robert CAM, Cadot S, Zhang X, Ye M, Li B, Manzo D, Chervet N, Steinger T, Van Der Heijden MGA, Schlaeppi K, Erb M (2018) Root exudate metabolites drive plant-soil feedbacks on growth and defense by shaping the rhizosphere microbiota. Nat Commun 9(1):1–13. https://doi.org/10.1038/s41467-018-05122-7 Jahangir MMR, Islam S, Nitu TT, Uddin S, Kabir AKMA, Meah MB, Islam R (2021) Bio-compost-based integrated soil fertility management improves post-harvest soil structural and elemental quality in a two-year conservation agriculture practice. Agronomy 11(11). https://doi.org/10.3390/agronomy11112101 Jiang Y, Wang X, Zhao Y, Zhang C, Jin Z, Shan S, Ping L (2021) Effects of Biochar Application on Enzyme Activities in Tea Garden Soil. Front Bioeng Biotechnol 9(September):1–8. https://doi.org/10.3389/fbioe.2021.728530 Kibblewhite MG, Ritz K, Swift MJ (2008) Soil health in agricultural systems. Philos Trans R Soc B Biol Sci 363(1492):685–701. https://doi.org/10.1098/rstb.2007.2178 Kumar M, Ahmad S, Singh RP (2022) Plant growth promoting microbes : Diverse roles for sustainable and ecofriendly agriculture. 7(May). https://doi.org/10.1016/j.nexus.2022.100133 Liu S, Sun Y, Shi F, Liu Y, Wang F, Dong S, Li M (2022a) Composition and Diversity of Soil Microbial Community Associated With Land Use Types in the Agro–Pastoral Area in the Upper Yellow River Basin. Front Plant Sci 13(April):1–14. https://doi.org/10.3389/fpls.2022.819661 Liu X, Shi Y, Kong L, Tong L, Cao H, Zhou H, Lv Y (2022b) Long-Term Application of Bio-Compost Increased Soil Microbial Community Diversity and Altered Its Composition and Network. Microorganisms 10(2). https://doi.org/10.3390/microorganisms10020462 Luo X, Fu X, Yang Y, Cai P, Peng S, Chen W, Huang Q (2016) Microbial communities play important roles in modulating paddy soil fertility. Sci Rep 6(February):1–12. https://doi.org/10.1038/srep20326 Mahongnao S, Sharma P, Singh D, Ahamad A, Kumar P V, Kumar P (2023) Formation and characterization of leaf waste into organic compost. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-023-27768-7 Milinković M, Lalević B, Jovičić-Petrović J, Golubović-Ćurguz V, Kljujev I, Raičević V (2019) Biopotential of compost and compost products derived from horticultural waste—Effect on plant growth and plant pathogens’ suppression. Process Saf Environ Prot 121:299–306. https://doi.org/10.1016/j.psep.2018.09.024 Pathma J, Sakthivel N (2015) Microbial Diversity of Vermicompost Bacteria that Exhibit Useful Agricultural Traits and Waste Management Potential. Biol Treat Solid Waste Enhancing Sustain i:169–216. https://doi.org/10.1201/b18872-15 Philippot L, Raaijmakers JM, Lemanceau P, Van Der Putten WH (2013) Going back to the roots: The microbial ecology of the rhizosphere. Nat Rev Microbiol 11(11):789–799. https://doi.org/10.1038/nrmicro3109 Pooja Sharma, Sophayo Mahongnao, Arif Ahamad, Radhika Gupta, Anita Goela NK and S, Nanda (2023) 16S rRNA metagenomic profiling of red amaranth grown organically with different composts and soil. The Lancent Pschch 11(August):133–143 Pugliese M, Liu BP, Gullino ML, Garibaldi A (2008) Selection of antagonists from compost to control soil-borne pathogens. J Plant Dis Prot 115(5):220–228. https://doi.org/10.1007/BF03356267 Pugliese M, Liu BP, Gullino ML, Garibaldi A (2011) Microbial enrichment of compost with biological control agents to enhance suppressiveness to four soil-borne diseases in greenhouse. J Plant Dis Prot 118(2):45–50. https://doi.org/10.1007/BF03356380 Samaddar S, Han GH, Chauhan PS, Chatterjee P, Jeon S, Sa T (2019) Changes in structural and functional responses of bacterial communities under different levels of long-term compost application in paddy soils. J Microbiol Biotechnol 29(2):292–296. https://doi.org/10.4014/jmb.1811.11018 Suárez-Estrella F, Vargas-García C, López MJ, Capel C, Moreno J (2007) Antagonistic activity of bacteria and fungi from horticultural compost against Fusarium oxysporum f. sp. melonis. Crop Prot 26(1):46–53. https://doi.org/10.1016/j.cropro.2006.04.003 Tao C, Li R, Xiong W, Shen Z, Liu S, Wang B, Ruan Y, Geisen S, Shen Q, Kowalchuk GA (2020) Bio-organic fertilizers stimulate indigenous soil Pseudomonas populations to enhance plant disease suppression. Microbiome 8(1):1–14. https://doi.org/10.1186/s40168-020-00892-z Tóthné Bogdányi F, Boziné Pullai K, Doshi P, Erdős E, Gilián LD, Lajos K, Leonetti P, Nagy PI, Pantaleo V, Petrikovszki R, Sera B, Seres A, Simon B, Tóth F (2021) Composted municipal green waste infused with biocontrol agents to control plant parasitic nematodes—a review. Microorganisms 9:1–39 Viti C, Tatti E, Decorosi F, Lista E, Giovannetti L, Rea E, Tullio M, Sparvoli E (2010) Compost Effect on Plant Growth-Promoting Rhizobacteria and Mycorrhizal Fungi Population in Maize Cultivations. Compost Sci Util 18(4):273–281. https://doi.org/10.1080/1065657X.2010.10736966 Wang J, Li R, Zhang H, Wei G, Li Z (2020) Beneficial bacteria activate nutrients and promote wheat growth under conditions of reduced fertilizer application. :1–12 Wani FS, Ahmad L, Ali T, Mushtaq A (2015) Role of microorganisms in nutrient mobilization and soil health - A review. J Pure Appl Microbiol 9(2):1401–1410 Zhen Z, Liu H, Wang N, Guo L, Meng J, Ding N, Wu G, Jiang G (2014) Effects of manure compost application on soil microbial community diversity and soil microenvironments in a temperate cropland in China. PLoS One 9(10). https://doi.org/10.1371/journal.pone.0108555 Supplementary Files GraphicalAbstract.tiff SupplementaryMaterials.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3247820","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":229782910,"identity":"d9bf48e5-ad2a-4c4a-8119-3212861aa69d","order_by":0,"name":"Sophayo Mahongnao","email":"","orcid":"","institution":"Department of Biochemistry, Daulat Ram College, University of Delhi","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sophayo","middleName":"","lastName":"Mahongnao","suffix":""},{"id":229782911,"identity":"000b3c66-cf8b-41ee-be67-264324cd7229","order_by":1,"name":"Pooja Sharma","email":"","orcid":"","institution":"Department of Biochemistry, Daulat Ram College, University of Delhi","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pooja","middleName":"","lastName":"Sharma","suffix":""},{"id":229782912,"identity":"e1c79432-c8a7-420f-9967-57aed0086538","order_by":2,"name":"Arif Ahamad","email":"","orcid":"","institution":"Jamia Millia Islamia","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Arif","middleName":"","lastName":"Ahamad","suffix":""},{"id":229782913,"identity":"fa0d541f-504f-4b41-a332-becf13810438","order_by":3,"name":"Sarita Nanda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYJCCAxAqgeHAhx82QAZj4wGCWiAqEhgPzuxJA2lpIKgFak0C82EetsPI9mIH8u1nHx7+UHNH3pw9+cEBHp7zdmvbDwNtqbGJxqXF4Ey6wYEDx54Z7ux5ZnBAwuJ28rYziUAtx9JyG3BpYUgD+oXtMOOGGwkGBwx4biebHQBqYWw4jFOLfP8zoJZ/h+033Ej/cCCB7Vyy2fmH+LUw3ADacrDtcOKGGzlAF7IdsDO7QcAWgxtAW872HU7ecOZNwcHGnuQEsxtAWxLw+EW+P435Q8W3w7Ybjqdv/vznh5292fn0hw8+1Njgdhg6SASrTCBWOQjYk6J4FIyCUTAKRgYAAEDedauSOG6GAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-3684-606X","institution":"Department of Biochemistry, Daulat Ram College, University of Delhi, Delhi","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Sarita","middleName":"","lastName":"Nanda","suffix":""}],"badges":[],"createdAt":"2023-08-09 07:34:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3247820/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3247820/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":42513771,"identity":"c4291176-d5dc-4c4a-bf5d-d7f64e271695","added_by":"auto","created_at":"2023-09-01 18:30:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157341,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe library size overview of the soils with different amendments.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/2b69a2f4eb40719b82998d07.png"},{"id":42513193,"identity":"abbe2748-1876-439b-be76-9094987f403d","added_by":"auto","created_at":"2023-09-01 18:14:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72888,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRarefaction curve. \u003c/strong\u003eThe rarefaction curve indicates the sequencing dept of the samples, which also correlates with the species richness of the microbiome present in each sample. The pre-plantation soils had a relatively higher species richness than the post-harvest soils.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/5a80bce96cf4d2c2d028c269.png"},{"id":42513772,"identity":"27121afb-2259-41e8-8ab6-a1383b9f1d02","added_by":"auto","created_at":"2023-09-01 18:30:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":218711,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. Alpha diversity of soil amended with different bio-composts using Chao 1 and Fisher indices. \u003c/strong\u003eGroup 1 is the pre-plantation soil samples of the Yamuna floodplain. Group 4 is the post-harvest soil samples of the Yamuna floodplain. Group 6 is the post-harvest residential soil samples.\u003cstrong\u003e \u003c/strong\u003eThe pre-plantation soil samples had a higher microbial diversity level than the post-harvest soils. The alpha diversity indices were significantly different among all the soil samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB. Alpha diversity of soil amended with different bio-composts using Shannon and Simpson indices.\u003c/strong\u003e The pre-plantation soil samples had a higher microbial diversity level than the post-harvest soils. The alpha diversity indices were significantly different among all the soil samples.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/3c49eb196d951ca2373e3e19.png"},{"id":42513560,"identity":"fcae9b8f-70b8-4110-891c-25df495f8246","added_by":"auto","created_at":"2023-09-01 18:22:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":155862,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe beta diversity of soils amended with different organic waste composts before plantation and post-harvest.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/f9fefde2e41ff9a8a2a1b94e.png"},{"id":42513557,"identity":"4972fa0d-7094-49a1-b387-d98ee3f22556","added_by":"auto","created_at":"2023-09-01 18:22:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":17039,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDendogram analysis of the soil samples amended with various composts and chemical fertilizer before plantation and after harvest.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/481e25ae7e898531cc097206.png"},{"id":42513559,"identity":"eec22899-a681-4bbb-ba9c-398bab454f27","added_by":"auto","created_at":"2023-09-01 18:22:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":46903,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCore microbiome identified in the soil samples amended with composts and chemical fertilizer.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/4e9d06670c0ffca9f2a4e3e9.png"},{"id":42513196,"identity":"f4092e70-8a02-470f-b3a2-1a42e4c24b50","added_by":"auto","created_at":"2023-09-01 18:14:25","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1145144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBacterial genera identified in the soil amended with different bio-composts. \u003c/strong\u003eThe types of bacterial genera identified and their levels across the sample varied depending on the nature of the bio-compost used. They were also diverse in the pre-plantation and post-harvest soils. The most abundant twenty genera covered more than 50% of the overall genera detected.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/4fd1e2100f425d489b167f44.png"},{"id":42513561,"identity":"615ccb3d-43ea-4613-bdc1-b33fcd7d9411","added_by":"auto","created_at":"2023-09-01 18:22:25","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":238530,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelative abundance of beneficial and pathogenic genera in the cultivars vis-à-vis the soils amended with different compost and chemical fertilizer. \u003c/strong\u003eRed amaranth A and B are the cultivars of Yamuna floodplain and residential soil, respectively. The cultivars of the bio-composts amended soils had a higher OTU of beneficial microorganisms. At the same time, the cultivar of the chemical fertiliser-amended soil had the highest OTU of the pathogenic microbiome.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/16001aa66cf895b690d82622.png"},{"id":43337391,"identity":"6f2cf113-29ec-4f25-97b1-aa56b1172766","added_by":"auto","created_at":"2023-09-19 05:25:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1739044,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/e69e5e21-141a-446e-a3d0-a17a476c4fd7.pdf"},{"id":42513199,"identity":"bfc1f846-f09b-4a22-9383-a60ee842d3c0","added_by":"auto","created_at":"2023-09-01 18:14:25","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2033948,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.tiff","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/1dbc5e4230c45d83fbb61243.tiff"},{"id":42513202,"identity":"d0e759ae-8938-4ec1-9483-f78aed1d08f0","added_by":"auto","created_at":"2023-09-01 18:14:25","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3450466,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3247820/v1/46d0e7790e28ccfbc2c5e6cd.pdf"}],"financialInterests":"","formattedTitle":"Evaluating the Influence of Organic Waste Compost Amendments on Microbiome Richness and Diversity in Pre-Plantation and Post-Harvest Soils: Insights from 16S rRNA Metagenomic Profiling","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eCompost amendments impacted the microbiome richness and diversity in the soil\u003c/li\u003e\n \u003cli\u003eCompost amended soil had higher beneficial bacteria than fertilizer amendment\u003c/li\u003e\n \u003cli\u003eThe pathogens levels were lower in the soil amended with compost\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe organic cultivars had higher beneficial microbes and lower pathogens\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eThe study of soil microbiomes and their dynamics has gained significant attention recently due to their crucial roles in soil health, nutrient recycling, and plant productivity. The composition and diversity of microbial communities in soil play a vital role in maintaining ecosystem functions and influencing plant growth and development (Liu et al. 2022; Luo et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). One approach to enhancing soil microbiome activity and function is applying bio-composts, which are organic amendments derived from various organic wastes such as leaf waste, animal manures, and food waste. Bio-composts contribute to soil fertility and plant growth by enriching the soil with organic matter and essential nutrients (Jahangir et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ho et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, they can also alter the structure and composition of soil microbial communities, leading to changes in microbial diversity, functions, and activity (Farrell et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Azeem et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Understanding the impact of bio-composts on the soil microbiome dynamics is essential for optimising their application in agriculture and sustainable land management practices.\u003c/p\u003e \u003cp\u003eSome previous studies have reported bio-composts\u0026rsquo; benefits to soil health and plant growth by increasing nutrients solubilisation, promoting plant growth, and suppressing plant pathogens (Tao et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Viti et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Reports also highlighted the potential of bio-compost formulations in shaping the soil microbiome for agricultural systems (Heisey et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It was found that the compost altered the structure of the microbial community and introduced new microorganisms into the soil system. In addition to the aforementioned studies, other investigations have contributed to our understanding of the microbiome dynamics in soils amended with bio-composts. For example, researchers had studied the effects of bio-compost application on soil microbial diversity and enzyme activities in a vegetable field. It was observed that there were significant changes in the microbial community structure and an increase in the enzymatic activities in the agricultural soil amended with bio-composts (Zhen et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Jiang et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, a study by Samaddar examined the impact of bio-compost amendments derived from different animal manures on soil microbial community composition and found distinct responses in microbial diversity and functional profiles (Samaddar et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The interconnectedness of the soil microbiome with that of the cultivars, food safety, and human health has been explored, which reported that the beneficial microorganisms in the soil could significantly improve the environmental sustainability, food quality, and human health (Bertola, Ferrarini, and Visioli \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Enhancement of soil health has become paramount important for sustainable productivity with improved food quality that can promote human health.\u003c/p\u003e \u003cp\u003eWhile previous studies have examined the effects of bio-compost amendments on soil microbiomes, there is a need for further research to explore the specific dynamics and mechanisms involved. To investigate the microbiome dynamics in pre-plantation and post-harvest soils amended with different bio-composts, 16S rRNA metagenomic profiling was adopted in this study. The 16S rRNA gene is a widely used molecular marker for identifying and characterising microbial communities based on their phylogenetic relationships. Metagenomic profiling using the 16S rRNA gene allows for a comprehensive analysis of the microbial composition and diversity of bacteria in a given soil sample, which could help us identify the beneficial and pathogenic microorganisms in the soil. By comparing pre-plantation soils, before the application of bio-composts, to post-harvest soils, after the crop cycle, we could assess the impact of bio-compost amendments on the soil microbiome. This analysis could provide insights into the changes in microbial community structure, diversity, and potential shifts in functional profiles. Moreover, it could help identify specific microbial taxa that are influenced by applying bio-composts and potentially associated with improved soil fertility and plant productivity.\u003c/p\u003e \u003cp\u003eIn this study, the novelty has been introduced by focusing on specific types of bio-composts which were derived from novel sources such as leaf waste and other organic waste bio-composts, viz. cow dung manure, kitchen waste compost, municipal organic waste compost, and vermicompost. The impact of these bio-composts on the soil microbiome richness and diversity has been investigated. Additionally, an examination of the temporal dynamics of the microbiome from pre-plantation to post-harvest stages has also been analysed, which could provide us with an understanding of the long-term effects of bio-compost amendments on soil microbial communities. The examination of microbiome dynamics in pre-plantation and post-harvest soils amended with bio-composts through 16S rRNA metagenomic profiling offers a powerful tool to understand the effects of bio-compost application on soil bacterial communities. This knowledge can contribute to the development of sustainable agricultural practices aimed at improving soil health, nutrient recycling, and overall sustainable agricultural productivity. We also analysed the relationship of the microbiome of the cultivars with that of the soil microbiome by comparing the OTUs of beneficial and pathogenic microorganisms in the cultivars of chemical fertiliser and bio-composts amended soils. Such analysis could give insights into the relatedness of the microbiome in the bio-composts, soils, and cultivars, which could help the cultivators to choose the most appropriate bio-composts and soil types to produce the best quality cultivars.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Experimental setup, sample collection and preparation\u003c/h2\u003e \u003cp\u003eTwo types of soils were collected from different locations; the floodplain soil from the Yamuna riverbank, Burari area, North Delhi, India, and residential soil from the institution campus, University of Delhi, North Campus, North Delhi, India. They were mixed with the leaf-based compost and other different composts, viz. cow dung manure, kitchen waste compost, municipal organic waste compost, and vermicompost, in a ratio of 5: 1 (w/w) before potting. A control was also set up using soil and DAP chemical fertilisers, without composts. The plantation was done by potting red amaranth (\u003cem\u003eAmaranthus cruentus\u003c/em\u003e) using these soils in different pots. Seedling and potting were done in the month of April in the ambient environment and harvested in the month of July. The pre-plantation and post-harvest soil samples were collected in a sterilised zip-lock polybag. The collected samples were maintained at 0\u0026ordm;C to -18 \u0026ordm;C for further processing (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSoil samples code along with its descriptions and the International Nucleotide Sequence Database Collaboration (INSDC) accession number\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample code\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe\u0026nbsp;International Nucleotide Sequence Database Collaboration (INSDC) accession number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-plantation floodplain soil amended with cow dung manure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15529941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-plantation floodplain soil amended with leaf litter compost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15529942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-plantation floodplain soil amended with Kitchen waste compost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15529947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-plantation floodplain soil amended with municipal organic waste composts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15530011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-plantation floodplain soil amended with vermicompost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15530204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-plantation floodplain soil amended with chemical fertilizers (DAP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYCRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest floodplain soil amended with cow dung manure, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532766\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYDRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest floodplain soil amended with leaf waste compost, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532767\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYKRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest floodplain soil amended with kitchen waste compost, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532768\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYMRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest floodplain soil amended with municipal organic waste compost, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532770\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYVRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest floodplain soil amended with vermicompost, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532769\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYFRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest floodplain soil amended with chemical fertilizers, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS15532771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNCRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest residential soil amended with cow dung manure, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS16204221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest residential soil amended with leaf waste compost, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS16204222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNKRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest residential soil amended with kitchen waste compost, planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS16204644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-harvest residential soil amended with chemical fertilizers (DAP), planted with red amaranth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERS16204249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. The physico-chemical parameters of soils\u003c/h2\u003e \u003cp\u003eThe pH and EC of the soils were measured using a pH meter and an EC meter. For the analysis, the samples were dissolved in distilled water at a ratio of 1: 2 (w/v soil: distilled water), and then measurements were carried out using pH and EC meter. The total organic carbon and nitrogen content of the soil was analysed using CHNS analyser (varioEL cube, Ser.no: 19171021).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. DNA Extraction and PCR Amplification of V3-V4 Region of 16s Gene:\u003c/h2\u003e \u003cp\u003eDNA extraction was done using the suitable method for the sample type from commercially available kits such as QIAGEN, ZYMO RESEARCH, and Thermo-Fisher. DNA extraction was done as per the manufacturer's recommendation. Extracted DNA from the samples was subjected to NanoDrop and GEL Check before being taken for PCR amplification: The NanoDrop readings of 260/280 at a value of 1.8 to 2 were used to determine the DNA\u0026rsquo;s quality.\u003c/p\u003e \u003cp\u003eFor the metagenomic analysis, the extracted DNA was amplified and sequenced to obtain the DNA sequence of the V3-V4 region of the 16S rRNA bacterial gene. The amplification was performed using a PCR mix containing: High-Fidelity DNA Polymerase, 0.5mM dNTPs, 3.2mM MgCl₂, and PCR Enzyme Buffer. The primers used were: 16sF 5\u0026rsquo; AGAGTTTGATGMTGGCTCAG 3\u0026rsquo;and 16sR 5\u0026rsquo; TTACCGCGGCMGCSGGCAC 3\u0026rsquo;. The conditions for the polymerase chain reaction (PCR) amplification were; 40ng of Extracted DNA and 10 pM of each primer used for amplification. The initial denaturation was set at 95\u0026ordm;C. The 25 Cycles were set with the following condition: Denaturation at 95\u0026ordm;C for 15 seconds, annealing at 60\u0026ordm;C for 15 seconds, Elongation at 72\u0026ordm;C for 2 minutes, and final extension at 72\u0026ordm;C for 10 minutes, and hold at 4\u0026ordm;C. The amplified 16s PCR Product is purified and subjected to GEL check and Nanodrop Quality Control. The NanoDrop readings of 260/280 at 1.8 to 2 were used to determine the DNA\u0026rsquo;s quality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Overview of sequencing and bioinformatics protocol\u003c/h2\u003e \u003cp\u003eThe amplicons from each sample were purified with Ampure beads to remove unused primers. An additional eight cycles of PCR were performed using Illumina barcoded adapters to prepare the sequencing libraries. Libraries were purified using Ampure beads and quantitated using a Qubit dsDNA High Sensitivity assay kit. Sequencing was performed using Illumina Miseq with 2x300PE v3 sequencing kit. Raw data quality control (QC) was done using FASTQC and MULTIQC, followed by trimming adapters and low-quality reads by TRIMGALORE. The trimmed reads are further taken for processing, including merging of paired-end reads, chimera removal, and OTU abundance calculation and estimation correction. This was achieved using QIIME 2 / MOTHUR / KRAKEN / BRACKEN workflows. This workflow enables highly accurate investigations at the genus level. The microbial diversity of different bio-composts was analysed through Alpha and Beta diversity indices. The databases used were SILVA / GREENGENES / NCBI. Each read was classified based on % coverage and identity. The 16S workflow is useful in identifying pathogens in a mixed sample or understanding microbial community composition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data processing, filtering, and normalisation\u003c/h2\u003e \u003cp\u003eTo process the metagenomics data for advanced analysis like alpha and beta diversity, the input file must contain at least two groups, and each group must have a minimum of three samples for the analysis. We have grouped the samples into three group; Group 1 includes pre-plantation Yamuna floodplain soil samples, Group 4 includes post-harvest Yamuna floodplain soil samples, and Group 6 includes post-harvest residential soil samples. In the analysis, features with identical values (i.e., zeros) across all samples were excluded, and the features appearing in only one sample were excluded (considered artifacts).\u003c/p\u003e \u003cp\u003eData filtering was done to remove low-quality informative features to improve downstream statistical analysis. The low-count filter features with very small counts in very few samples are likely due to sequencing errors or low-level contaminations. We specified a default minimum count (default 4). A 20% prevalence filter means at least 20% of its values should contain at least four counts. The low variance filters are the features that are close to constant throughout the experiment and are unlikely to be associated with the conditions under study. Their variances can be measured using inter-quantile range (IQR), standard deviation or the coefficient of variation (CV). This project followed the default low count filter at a 20% prevalence with a minimum count of four. The low variance was filtered based on the inter-quantile range with 10% to remove.\u003c/p\u003e \u003cp\u003eNormalisation was done to address the variability in sampling depth and the sparsity of the data to enable more biologically meaningful comparisons. The data were rarefied to minimum library size. The data was scaled by the total sum scaling (TSS) factor to bring all the samples to the same scale.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Diversity and significance testing\u003c/h2\u003e \u003cp\u003eThe data input was filtered, and the alpha diversity was measured and resulted with four methods, like Chao1, Shannon, Simpson and Fisher, with the statistical method of T-test /ANOVA. The beta diversity was constructed at the taxonomic level of Genus with Bray-Curtis index distance method based on Permutational MANOVA (PERMANOVA) statistical method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Sequencing raw data deposition\u003c/h2\u003e \u003cp\u003eThe raw data of the Illumina Miseq sequencing was deposited at the Indian Nucleotide Data Archive (INDA) of the Indian Biological Data Centre with the referenced INDA (Study/Bioproject) Accession No. INRP000065. The International Nucleotide Sequence Database Collaboration (INSDC) Bioproject Accession no. of this study is PRJEB62447 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. The physico-chemical parameters of the soil\u003c/h2\u003e \u003cp\u003eAll the soil samples before plantation and post0harvest were moderately alkaline, with pH ranging from 7.66 to 8.56. The soil sample amended with fertilizer (YF), had the lowest pH at 7.66, whereas the sample amended with cow dung manure (YC) had the highest pH at 8.56. The soil samples' electrical conductivity (EC) ranged from non-saline to moderately saline categories across all the samples. The soil sample amended with municipal organic waste compost (YMRAH) had the lowest EC of 0.363 dS/m, which is non-saline. Whereas, the vermicompost amended soil (YV) had the highest EC of 0.938 dS/m, which is moderately saline. The other soil samples had the EC ranging from 0.44 dS/m to 0.775 dS/m, which were in a slightly saline category. The total organic carbon (TOC) content in the pre-plantation floodplain soil ranged from 2.3\u0026ndash;6.7%. The chemical fertilizer amended soil (YF) had the lowest level of total carbon, whereas the leaf compost amended soil (YD) had the highest total carbon content. The pre-plantation soil amended with kitchen waste compost (YK), cow dung manure (YC), and municipal organic waste compost (YM) also had high levels of total carbon content at 6.6%, 6.6%, and 6.4%, respectively. The post-harvest soil samples had higher levels of total carbon than the pre-plantation soils, ranging from 6.01\u0026ndash;7.87%. In the post-harvest floodplain soils, the sample amended with chemical fertilizer (YFRAH) had the lowest level of TOC. While, the soil sample amended with cow dung manure (YCRAH) and leaf waste compost (YDRAH) had the highest levels of TOC at 7.87% and 7.72%, respectively. Among the residential post-harvest soil sample, leaf (NDRAH) and kitchen waste compost (NKRAH) amendments had higher levels of TOC at 45 and 3.84%, respectively. The total nitrogen levels in the pre-plantation floodplain soil ranged from 0.10\u0026ndash;1.41%. The fertilizer amended soil (YF) had the lowest level of total nitrogen whereas, the vermicompost amended soil (YV) had the highest level of total nitrogen. The post-harvest floodplain soils had the total nitrogen ranging from 0.11\u0026ndash;0.2%. The soil samples amended with vermicompost (YVRAH) and cow dung manure (YCRAH) had higher levels of total nitrogen at .02% and 0.19%, respectively. Among the residential post-harvest soil samples, the cow dung manure (NCRAH)and kitchen waste compost (NKRAH) amendments had the higher levels of total nitrogen at 1.35% and 0.82%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe pH and Electrical Conductivity (EC) of the soils\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamples of different soil types\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElectrical Conductivity (EC) (dS/m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal Carbon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal Nitrogen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYK\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYCRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYDRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYKRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.36\u0026thinsp;\u0026plusmn;\u0026thinsp;.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYMRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYVRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e7.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYFRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNCRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNDRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNKRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNFRAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThis table shows different soil samples' pH and electrical conductivity (EC). All the soil samples had a pH of moderately alkaline level, ranging from 7.66 to 8.56. The EC of the soil samples ranged from 0.64 to 0.938 mS/cm before plantation, while after harvest, the salinity of the soil samples was reduced slightly and ranged from 0.363 to 0.617 mS/cm.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Microbiome richness and diversity of soils\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. The total number of reads and OTUs\u003c/h2\u003e \u003cp\u003eThe number of reads ranged from 0.2\u0026nbsp;million to 1.2\u0026nbsp;million in different soils. The residential soil amended with leaf compost (NDRAH) had the lowest number of reads, while the floodplain soil amended with chemical fertilizer (YF) had the highest number of reads among all the soil samples. Among the floodplain soil samples, the soil amended with chemical fertilizer (YF) and municipal organic waste compost (YM) had the largest library size before plantation. While in the post-harvest floodplain soil samples, the chemical fertilizer (YFRAH) and leaf compost (YDRAH) amended soil had the largest library size. On the other hand, the kitchen waste composted amended soil sample (NKRAH) had the largest library size among the post-harvest residential soil samples \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAll the samples had GC contents ranging from 54.50\u0026ndash;56.50%. The total number of OTUs generated varied significantly from sample to sample, extending from 38305 to 335868. The soil sample YF had the highest total OTU, whereas sample YCRAH had the lowest total OTU. There was a reduction of OTUs in the post-harvest soil samples compared to the pre-plantation soil samples, except in the soil sample amended with leaf waste compost (YD and YDRAH), in which there was an increase in the total number of OTUs from 86390 to 149472.\u003c/p\u003e \u003cp\u003eAll samples were rarefied to even sequencing depth based on the sample having the lowest sequencing depth, and the analysis was visualised with the filtered data source. The result revealed a rarefaction curve indicating that all the sequencing reads were completely sampled. It also revealed that the pre-plantation soils had higher species richness than the post-harvest soil samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Alpha and beta diversity analysis\u003c/h2\u003e \u003cp\u003eThe alpha diversity was measured and resulted with four methods viz. Chao1, Shannon, Simpson, and Fisher with the statistical method of T-test /ANOVA. It was observed that pre-plantation soil samples had higher alpha diversity indices compared to the post-harvest soil samples \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The Chao1 index provides an estimate of the true species richness in a sample, considering the potential presence of unseen species. In this study, the Chao1 index ranged from 176.35 to 219.00, with the YF sample having the highest Chao1 index, indicating a potentially higher species richness compared to the other samples. The Fisher index gives equal weight to all species, meaning that if a sample has an even distribution of individuals across all species, the Fisher index will be higher, indicating higher diversity. The Fisher index ranged from 0.929 to 0.969, with the YD sample having the lowest Fisher index and the YC sample having the highest Fisher index. Nevertheless, the differences in the Fisher index between most samples were relatively small, suggesting that the samples had similar levels of diversity \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAlpha diversity indices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChao1 index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFisher Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShannon Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSimpson Index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e192.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e203.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYCRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e179.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYDRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYKRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e191.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYMRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e186.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYVRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e182.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYFRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e177.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNCRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e166.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNKRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e199.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFRAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e171.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThis table shows the alpha diversity indices of different soil samples. The microbial diversity was relatively higher in the pre-plantation soils than in post-harvest soils. The chemical fertiliser, municipal organic waste compost, and vermicompost-amended soils had higher levels of microbial diversity before plantation. In comparison, kitchen waste compost amended-higher levels of microbial diversity in the post-harvest soils.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Shannon index gives more weight to rare species, meaning that if a sample has a high number of rare species, the Shannon index will be higher, indicating higher diversity. The Shannon index ranged from 3.605 to 4.192, with the YV sample having the highest Shannon index, indicating higher diversity and evenness compared to the other samples. However, the differences in the Shannon index between most samples are relatively small, suggesting that the samples had similar levels of diversity. The Simpson index gives more weight to dominant species, meaning that if a sample has a high number of dominant species, the Simpson index will be higher, indicating lower diversity. In this study, the Simpson index ranged from 0.943 to 0.969, with the YD sample having the highest Simpson index, indicating lower diversity compared to the other samples. The differences in the Simpson index between most samples were relatively small, suggesting that the samples had similar levels of diversity \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn general, the microbial diversity among the soil samples was found to be statistically significant. The p-value in Chao1, Fisher, Shannon, and Simpson alpha diversity were measured to be 0.0079, 0.00014, 0.0057, and 0.11 with the ANOVA F-value of 7.17, 18.95, 7.90, and 2.66, respectively.\u003c/p\u003e \u003cp\u003eThe beta diversity was constructed at the Genus taxonomic level with the Bray-Curtis index distance method based on the Permutational MANOVA (PERMANOVA) statistical method. The p-value was \u0026lt;\u0026thinsp;0.001 with the PERMANOVA f-value of 9.2961. It revealed that sample groups were significantly different regarding their microbiome diversity \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3. Clustering analysis\u003c/h2\u003e \u003cp\u003eThe dendrogram was constructed based on the distance measure of the Bray-Curtis Index with the Ward clustering algorithm. The result revealed that pre-plantation soils were clustered together, and post-harvest soil samples were clustered together, but pre-plantation soils and post-harvest soils were clustered distantly. Among the pre-plantation soil, the samples YC, YM, and YK are clustered more relatedly, whereas the samples YD, YF, and YK are clustered together more closely. In the post-harvest soil samples, YFRAH and YDRAH are closely related to each other, while YCRAH and YKRAH are closely related to each other. The sample YMRAH was more closely clustered towards YFRAH and YDRAH, but YVRAH was uniquely distanced from all the other samples. In the residential soil types samples, NFRAH and NDRAH are clustered together, while NCRAH and NKRAH were clustered together more relatedly \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Taxonomic classification and identification of beneficial and pathogenic microbes\u003c/h2\u003e \u003cp\u003eThe OTU table gives an overall microbial community present in the given samples. From the generated OTU, the stacked bar charts are pivoted based on taxonomic levels from Phylum to Species. More than 30 phyla, 70 classes, 170 orders, 190 families, 240 genera of bacteria were identified across all the samples.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. At the phylum level\u003c/h2\u003e \u003cp\u003eAbout Twenty-one phyla were identified across all the samples (\u003cb\u003eSupplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). The most abundant ten phyla cover about 97 to 98% of all the phyla identified (\u003cb\u003eSupplementary Fig. S2 and S3\u003c/b\u003e). These phyla were further classified into more than Classes, Orders, Families, Genera, and Species (\u003cb\u003eSupplementary Fig. S4, S5, S6, S7, and S8\u003c/b\u003e). The most abundant bacterial phyla identified across all the soil samples were \u003cem\u003eProteobacteria, Planctomycetes, Actinobacteria, Firmicutes, Chloroflexi, Acidobacteria, Bacteroidetes, Verrucomicrobia, Gemmatimonadetes, Armatimonadetes, Cyanobacteria, Euryarchaeota, Nitrospirae\u003c/em\u003e, and \u003cem\u003eChlamydiae\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e). The counts of \u003cem\u003eProteobacteria\u003c/em\u003e showed a reduction in the post-harvest soils compared to pre-plantation soils, except in the leaf waste compost amended soil, where there was an increase of 98.30% (YD\u0026thinsp;=\u0026thinsp;23532; YDRAH\u0026thinsp;=\u0026thinsp;46664). The maximum reduction was seen in the vermicompost amended soil, about 66.87% (YV\u0026thinsp;=\u0026thinsp;30021; YVRAH\u0026thinsp;=\u0026thinsp;9946), followed by fertiliser-amended soil in which there was a reduction of approximately 49.34% (YF\u0026thinsp;=\u0026thinsp;81283; YFRAH\u0026thinsp;=\u0026thinsp;47197). \u003cem\u003eProteobacteria\u003c/em\u003e counts were seen highest in the fertilizer amended soils sample in both pre-plantation and post-harvest of the river bank soil. While its count was highest in the kitchen waste compost amended post-harvest soil among the residential soil samples.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBacterial Phyla identified in different soil samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhylum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"16\" nameend=\"c17\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePre-plantation soils with OTUs\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePost-harvest soils with OTUs\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYCR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYDR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYKR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eYMR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eYVR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eYFR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNCR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNDR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNKR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eNFR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e81283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e46664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e41494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e30138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e9946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e47197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e32289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e30254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e53374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e44137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePlanctomycetes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e29308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e21839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e19215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e8423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e27764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e11065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e7779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e11093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e12821\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eActinobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e12448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e9355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e8916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e12758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e13700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFirmicutes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e37115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e18054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e1178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e3344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e939\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChloroflexi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e55091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e16782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e13700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e14137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e18677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e10665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e6764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e13415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e9568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcidobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e12448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e9355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e8916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e12758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e13700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacteroidetes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e9725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e15190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e15305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e21034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e20170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVerrucomicrobia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e5303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e3892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e4316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e7368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e6008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGemmatimonadetes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eArmatimonadetes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCyanobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e514\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEuryarchaeota\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e[Thermi]\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNitrospirae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e412\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlamydiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal OTU\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e73644\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e66576\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e114281\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e185816\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e94937\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e294621\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e50339\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e136870\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e130834\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e95105\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e34558\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e146360\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e94978\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e85296\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e138421\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e123859\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"17\"\u003eThis table shows the bacterial Phyla identified in the pre-plantation and post-harvest soil samples amended with different bio-compost. The level of bacterial phyla varied depending on the types of bio-compost used for soil amendment. There was a reduction of the bacterial phyla in the post-harvest soil samples, except in the leaf waste compost amended soil, where there was a significant increase in the bacterial phyla.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ePlanctomycetes\u003c/em\u003e increased in the post-harvest soils amended with cow dung manure, leaf waste compost, and kitchen waste compost. At the same time, there was a decrease in its counts in the municipal organic waste compost, vermicompost, and fertilisers amended post-harvest soils as compared to pre-plantation soils. The highest increase of about 218% was observed in the kitchen waste compost amended soil, followed by the leaf waste compost amended soil, with a 177% increase in the post-harvest soil. The fertiliser-amended soil (YF) had the highest counts of \u003cem\u003ePlanctomycetes\u003c/em\u003e among the pre-plantation soil samples. At the same time, the leaf waste compost amended soil sample (YDRAH) had the highest counts of this phylum in the post-harvest soil samples.\u003c/p\u003e \u003cp\u003e \u003cem\u003eActinobacteria\u003c/em\u003e counts were increased in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compost. In contrast, there was a decrease in its counts in the soils amended with municipal organic waste compost, vermicompost, and fertilisers. The highest increase of \u003cem\u003eActinobacteria\u003c/em\u003e was seen in the leaf waste compost amended post-harvest soil with an increase of about 226% and in kitchen waste compost amended soil of about 57%. In comparison, the maximum decrease of about 41% was seen in the vermicompost amended soil, followed by the fertiliser-amended soil with a reduction of about 32%. Generally, the fertiliser-amended soil samples had the highest counts of \u003cem\u003eActinobacteria\u003c/em\u003e among all the soil samples. The fertiliser-amended soil (YF) had the highest count of \u003cem\u003eFirmicutes\u003c/em\u003e in the pre-plantation soil samples, but its count was drastically reduced in the post-harvest soil sample, with a decrease of about 80%. The decline was also seen in the soil amended with vermicompost, municipal organic waste compost, and cow dung manure. But there was an increase in the \u003cem\u003eFirmicutes\u003c/em\u003e counts in the post-harvest soil samples amended with leaf and kitchen waste compost. The kitchen waste compost-amended soil sample had the highest count of \u003cem\u003eFirmicutes\u003c/em\u003e amongst all the post-harvest soil samples.\u003c/p\u003e \u003cp\u003e \u003cem\u003eChloroflexi\u003c/em\u003e and \u003cem\u003eBacteroidetes\u003c/em\u003e counts were increased in the post-harvest soil sample amended with leaf waste compost. Whereas there was a decrease in the fertiliser and other bio-composts amended post-harvest soil samples. The bacterial Phyla, such as \u003cem\u003eAcidobacteria, Armatimonadetes\u003c/em\u003e, and \u003cem\u003eNitrospirae\u003c/em\u003e, were observed with increased counts in the post-harvest soil samples. These Phyla were reduced in the post-harvest soils amended with chemical fertilisers, municipal organic waste compost, and vermicompost. \u003cem\u003eGemmatimonadetes\u003c/em\u003e were relatively increased in all the post-harvest soil samples compared to pre-plantation soil samples. The other bacterial phyla, such as \u003cem\u003eCyanobacteria, Euryarchaeota\u003c/em\u003e, and \u003cem\u003eThermi\u003c/em\u003e, were also reduced in all the post-harvest soils. Generally, the beneficial phyla increased in the post-harvest soils, which were amended with leaf waste compost and kitchen waste compos. In contrast, there was a reduction in these phyla in the soils amended with chemical fertilisers, cow dung manure, municipal organic waste compost, and vermicompost. The most significant decrease was in the soil amended with vermicompost and chemical fertilisers, about 63% and 50%, respectively. \u003cem\u003eChlamydiae\u003c/em\u003e, which is a pathogenic bacterial phylum, was seen to increase in all the post-harvest soil samples. The highest counts were seen in the chemical fertiliser-amended soil, both in the pre-plantation and post-harvest soil samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. At the genus and species level\u003c/h2\u003e \u003cp\u003eThe bacterial genera identified varied across the samples of pre-plantation and post-harvest soils, amended with chemical fertiliser and different types of bio-composts. About 30 bacterial genera constitute the core microbiome, detected above a threshold level across the samples. The levels of these core microbiome varied in different soil samples depending on the types of composts used as soil amendment \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e In general, the significant beneficial genera seen across the soils samples with different proportions were \u003cem\u003eAchromobacter, Agromyces, Bacillus, Clostridium, Nitrospira, Planctomyces, Pseudomonas, Steroidobacter\u003c/em\u003e, \u003cem\u003eStreptomyces, Alicyclobacillus, Bdellovibrio\u003c/em\u003e, and others (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003e; \u003cb\u003eand Supplementary Fig. S9\u003c/b\u003e). \u003cem\u003eAchromobacter\u003c/em\u003e counts were found to be highest in the leaf waste compost amended soils, both in the pre-plantation and post-harvest samples. However, the counts were reduced in all the post-harvest soil samples except in the fertiliser-amended soil, where the count was slightly increased.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBeneficial bacterial genera identified in different soil samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacterial Genera\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePre-plantation soil samples with OTUs\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c17\" namest=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePost-harvest soil samples with OTUs\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eYD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eYK\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eYM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eYV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eYF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eYCR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eYDR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eYKR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eYMR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eYVR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003eYFR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003eNCR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003eNDR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003eNKR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003eNFR\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAchromobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eActinomadura\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAgromyces\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlcanivorax\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBrevibacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eClostridium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMyxococcus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHalomonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKaistobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMethanobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMethanosarcina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMicrobulbifer\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNitrospira\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePlanctomyces\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRhodoplanes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSphingobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptomyces\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSteroidobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLactobacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eXiphinematobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlicyclobacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTruepera\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGemmata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e506\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeneficial OTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e11655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5926\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal OTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e24131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e14134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e23460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e21711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e46%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e54%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e27%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"17\"\u003eThis table shows the beneficial genera identified in the soil samples amended with different bio-compost. The level of each bacterial genera varied depending on the types of bio-composts used as soil amendments. Generally, there was a reduction in the level of the beneficial bacteria in the post-harvest soil samples, except in the leaf waste compost amended soil, where there was an increase in the beneficial genera.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAgromyces\u003c/em\u003e level was highest in the fertiliser-amended soil among the pre-plantation soil sample. Still, leaf waste compost amended soil became highest in its count in the post-harvest soil samples. There was a reduction in \u003cem\u003eAgromyces\u003c/em\u003e counts in the post-harvest soil samples. The most significant decrease was seen in the fertiliser-amended soil at about 68%. While the leaf waste compost-amended soil saw the least reduction in \u003cem\u003eAgromyces\u003c/em\u003e, about 21%. \u003cem\u003eBacillus\u003c/em\u003e count was highest in the fertiliser-amended soil (YF\u0026thinsp;=\u0026thinsp;658) among the pre-plantation soil samples, but its count was reduced drastically, about 88%, in the post-harvest sample (YFRAH\u0026thinsp;=\u0026thinsp;80).\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eBacillus\u003c/em\u003e levels were increased in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compost. The greatest increment of about 98% was seen in the leaf waste compost amended soil sample in the post-harvest soil samples. Among the post-harvest soil samples, the kitchen waste compost amended soil sample had the highest level of \u003cem\u003eBacillus\u003c/em\u003e in both the river bank soil and residential soil. \u003cem\u003eClostridium\u003c/em\u003e was detected with relatively lower counts in the pre-plantation soil samples, but its level was increased in the post-harvest soil samples. The \u003cem\u003eClostridium\u003c/em\u003e level was highest in the cow dung manure and kitchen waste compost-amended post-harvest soils. \u003cem\u003eNitrospira\u003c/em\u003e was identified with the highest count in fertiliser-amended soil, followed by municipal organic waste compost-amended soil among the pre-plantation soil samples. Though, its count was reduced to half in the post-harvest soil samples. While there was an increase in the \u003cem\u003eNitrospira\u003c/em\u003e counts in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compost. The count of \u003cem\u003eNitrospira\u003c/em\u003e was relatively higher in the fertiliser, cow dung manure and leaf waste compost-amended soil samples compared to municipal organic waste compost and vermicompost-amended soil samples amongst the post-harvest soil. \u003cem\u003ePlanctomyces\u003c/em\u003e counts were relatively high in all the soil samples. The highest counts were seen in the fertiliser and municipal organic waste compost-amended soil in the pre-plantation soil samples. Nonetheless, its count was reduced to almost half in the post-harvest soil samples. At the same time, there was an increase in the counts of \u003cem\u003ePlanctomyces\u003c/em\u003e in the post-harvest soils amended with cow dung manure, leaf waste compost, and kitchen waste compost. The leaf waste compost-amended soil sample had the highest level of \u003cem\u003ePlanctomycetes\u003c/em\u003e among the post-harvest soil samples. \u003cem\u003eSteroidobacter\u003c/em\u003e was identified with relatively higher counts in the post-harvest soil samples than in the pre-plantation soils. The municipal organic waste compost-amended soil had the highest level in the pre-plantation soil samples. While, the \u003cem\u003eSteroidobacter\u003c/em\u003e counts became highest in the leaf waste compost and kitchen waste compost-amended soil samples among the post-harvest soil samples.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePseudomonas\u003c/em\u003e was higher in the pre-plantation soil samples than the post-harvest soil samples. In the pre-plantation soil samples, the kitchen waste compost and chemical fertiliser-amended soils had relatively higher counts of \u003cem\u003eBacillus\u003c/em\u003e, but the post-harvest soils had relatively similar levels of this genus, though slightly higher in the chemical fertiliser-amended sample. \u003cem\u003eStreptomyces\u003c/em\u003e was observed with a relatively high count in the pre-plantation soils, but its count was reduced drastically in the post-harvest soil samples. The pre-plantation soil samples amended with municipal organic waste compost, chemical fertiliser, and cow dung manure were seen with relatively higher \u003cem\u003eStreptomyces\u003c/em\u003e among the pre-plantation soil samples. \u003cem\u003eAlicyclobacillus\u003c/em\u003e was seen with relatively higher levels in the pre-plantation soil samples amended with chemical fertiliser, municipal organic waste compost, kitchen waste compost, and vermicompost. But the count of \u003cem\u003eAlicyclobacillus\u003c/em\u003e was reduced in the post-harvest soil samples. On the other hand, the soil samples amended with leaf waste compost and cow dung manure showed an increase in \u003cem\u003eAlicyclobacillus\u003c/em\u003e in the post-harvest soil samples. \u003cem\u003eKaistobacter\u003c/em\u003e was also observed at a relatively higher level in the pre-plantation soil samples in all the amendments, but its counts were reduced in the post-harvest samples. This genus is the only bacterial genus that was observed to be higher in the residential soil than in the Yamuna floodplain soil samples. \u003cem\u003eKaistobacter\u003c/em\u003e was seen with relatively higher level in the fertilizer-amended soil sample in both the pre-plantation and post-harvest soils.\u003c/p\u003e \u003cp\u003eThe other bacterial genera such as \u003cem\u003eBrevibacterium, Halomonas, Methanobacterium\u003c/em\u003e, and \u003cem\u003eSphingobacterium\u003c/em\u003e, were observed to be relatively higher in the pre-plantation soil samples of all amendments, but their counts were reduced drastically in the post-harvest soil samples. The counts of such genera were highest in the kitchen waste compost-amended soil samples, except for the \u003cem\u003eMethanobacterium\u003c/em\u003e, where the count was higher in the chemical fertiliser-amended soil sample. \u003cem\u003eMicrobulbifer\u003c/em\u003e was also observed to be relatively high only in the kitchen waste compost-amended soil samples, both in the pre-plantation and post-harvest.\u003c/p\u003e \u003cp\u003eThere was a reduction in the overall OTUs of the beneficial genera in all the post-harvest soil samples compared to the pre-plantation soils, except in the leaf waste compost-amended soil. The leaf waste compost amended soil had the lowest beneficial OTU amongst the pre-plantation soils but the highest beneficial OTU among the post-harvest soil samples. There was an increase of about 125% in the OTU of the beneficial genera in the post-harvest soil amended with leaf waste compost. While, a reduction of about 46% was observed in the fertiliser-amended soil. The most significant reduction of the beneficial OTU was seen in the soil sample amended with cow dung manure, which was about a 57% reduction. The vermicompost and cow dung manure amended-soil samples had the lowest counts of beneficial OTUs among the post-harvest soil samples.\u003c/p\u003e \u003cp\u003eThe pathogenic genera identified across the samples were \u003cem\u003eAgrobacterium, Flavobacterium, Leptolyngbya, Geobacter, Nocardia, Mycobacterium\u003c/em\u003e, and others (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The pre-plantation soil samples had negligible levels of \u003cem\u003eAgrobacterium\u003c/em\u003e, except in the leaf waste compost amended soil. While the counts of \u003cem\u003eAgrobacterium\u003c/em\u003e were increased in all the post-harvest soil samples. \u003cem\u003eFlavobacterium\u003c/em\u003e counts were higher in the pre-plantation soils than the post-harvest soils in all the samples. The fertiliser-amended soil samples had the highest counts of the \u003cem\u003eFlavobacterium\u003c/em\u003e in both the pre-plantation and post-harvest soil samples. Whereas the cow dung-amended soils had the lowest counts of the genus in all the samples. \u003cem\u003eLeptolyngbya\u003c/em\u003e was also detected across the samples, but its counts were relatively higher in the pre-plantation soil. The highest count of \u003cem\u003eLeptolyngbya\u003c/em\u003e was seen in the fertiliser-amended soil samples, whereas the vermicompost-amended soil samples had the lowest counts in the pre-plantation as well as the post-harvest soil samples.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePathogenic bacterial genera identified in different soil samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacterial Genera\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePre-plantation soils with OTUs\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c17\" namest=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePost-harvest soils with OTUs\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYCR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYDR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYKR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eYMR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eYVR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eYFR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNCR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNDR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNKR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eNFR\u003c/p\u003e \u003cp\u003eAH\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAgrobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFlavobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCupriavidus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePrevotella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLeptolyngbya\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBalneimonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProtochlamydia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSaccharothrix\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRhabdochlamydia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePhaeospirillum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSaprospira\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAeromicrobium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLegionella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGeobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNocardia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC.Solibacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogenic OTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1648\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal OTU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e24131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e14134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e23460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e21711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"17\"\u003eThis table shows the pathogenic genera identified in the soil samples amended with different bio-compost. The level of each pathogenic bacterial genera varied depending on the types of bio-composts used as soil amendments. Generally, there was a reduction in the level of the beneficial bacteria in the post-harvest soil samples.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe other bacterial genera such as \u003cem\u003eBalneimonas, Protochlamydia, Rhabdochlamydia\u003c/em\u003e, and \u003cem\u003ePhaeospirillum\u003c/em\u003e, were also found to be present across all the samples, but the number of counts varied across the samples. The fertiliser-amended soil samples had the highest level of all these pathogenic genera amongst the pre-plantation as well as the post-harvest soil samples. The level of \u003cem\u003eBalneimonas, Protochlamydia\u003c/em\u003e, and \u003cem\u003eRhabdochlamydia\u003c/em\u003e remain almost the same in the post-harvest soils corresponding to the pre-plantation soils. While there was a slight increase in the counts of \u003cem\u003ePhaeospirillum\u003c/em\u003e in the post-harvest soils concerning the pre-plantation soils. The vermicompost and cow dung manure-amended soil samples had the lowest counts of these pathogenic genera. \u003cem\u003eMycobacterium\u003c/em\u003e was detected with a relatively high concentration in all the samples. The kitchen waste and municipal organic waste compost-amended soils had the highest counts of \u003cem\u003eMycobacterium\u003c/em\u003e amongst the pre-plantation soils, while the leaf waste compost-amended soil had the highest count in the post-harvest soil samples. \u003cem\u003eGeobacter\u003c/em\u003e was also detected with a relatively higher level in the post-harvest soil samples compared to the pre-plantation soils. The fertilizer-amended soil had the highest count of the genus amongst all the samples. The leaf waste compost-amended soil had the lowest count of the genus amongst the pre-plantation soils, whereas the cow dung manure and vermicompost-amended soils had the lowest counts in the post-harvest soil samples.\u003c/p\u003e \u003cp\u003eThe overall sum of OTUs of pathogenic genera was observed to be highest in the fertiliser-amended soil samples in the pre-plantation soil as well as in the post-harvest soil. The cow dung manure and vermicompost amended soil samples had the lowest counts of pathogenic OTUs. In general, there was a reduction in the total pathogenic OTUs in the post-harvest soil samples at the genus level.\u003c/p\u003e \u003cp\u003eThe resolution of the 16S rRNA metagenomic profiling of the bacterial microbiome became vaguer at the species level. But there was detection of some beneficial and pathogenic bacterial species in the soil samples. The type of bacterial species and its proportion present in the pre-plantation soil samples were different from the post-harvest soils and also varied amongst the soil samples amended with different types of bio-composts (\u003cb\u003eSupplementary Fig. S10 and S11\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eThe major beneficial species identified across the samples were \u003cem\u003ebacteriovorus, cellulosum, clausii, copri, debontii, diminuta, endophyticus, hirsuta, multivorum, ochraceum, vinacea\u003c/em\u003e, and others \u003cb\u003e(Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/b\u003e The fertiliser-amended soil had the highest count of \u003cem\u003ebacteriovorus\u003c/em\u003e amongst all the pre-plantation soil samples. In contrast, the leaf waste compost-amended soil sample had the highest level of the species in the post-harvest soil samples. The residential soil samples had a relatively higher \u003cem\u003ebacteriovorus\u003c/em\u003e level than the riverbank soil samples. \u003cem\u003eCellulosum\u003c/em\u003e was found to be highest in the fertiliser and municipal organic waste compost-amended soil samples in the pre-plantation soils, while the leaf waste compost-amended soil had the highest counts of the species after the harvest. The abundance of \u003cem\u003ecopri\u003c/em\u003e was reduced in the post-harvest soil samples compared to the pre-plantation soils. The fertiliser and municipal organic waste compost-amended soils had the highest counts of \u003cem\u003ecopri\u003c/em\u003e before plantation, but the kitchen and leaf waste compost-amended soils had the higher counts of the species in the post-harvest samples. The counts of \u003cem\u003edebontii\u003c/em\u003e were relatively higher in the post-harvest soil samples than the pre-plantation soils. Also, the residential soil samples had higher species counts than the Yamuna floodplain soil samples. The counts of \u003cem\u003ediminuta\u003c/em\u003e and \u003cem\u003ehirsuta\u003c/em\u003e were lower in the post-harvest soil samples compared to the pre-plantation soils samples. The fertiliser and municipal organic waste compost-amended soil samples had relatively higher \u003cem\u003ediminuta\u003c/em\u003e. While the leaf waste compost and cow dung manure amended soils had the higher counts of \u003cem\u003ehirsuta\u003c/em\u003e in both pre-plantation and post-harvest soil samples. The level of bacterial species, \u003cem\u003eendophyticus\u003c/em\u003e, were also reduced in all the post-harvest soil samples, except in the soil sample amended with leaf waste compost in which there was an increase in its count. The level of \u003cem\u003eochraceum\u003c/em\u003e was observed to be higher in the post-harvest soil samples than the pre-plantation soil samples. The leaf waste compost and kitchen waste compost-amended soil samples had a relatively higher level of \u003cem\u003eochraceum\u003c/em\u003e in the post-harvest soil samples. The total counts of \u003cem\u003evinacea\u003c/em\u003e were observed to be lower in the post-harvest soils. The kitchen waste compost and municipal organic waste compost-amended soil samples were seen with a relatively higher level of the \u003cem\u003evinacea species\u003c/em\u003e, among all the soil samples, both in pre-plantation as well as post-harvest soils. Generally, the pre-plantation soils had a relatively higher counts of the beneficial species as compared to the post-harvest soils, except in the leaf waste compost-amended soil in which there was a slight increase in the count of the beneficial species.\u003c/p\u003e \u003cp\u003eThe presence of some pathogenic species was also detected across the soil samples. The major pathogenic bacterial species identified were \u003cem\u003ecampisalis, fulvum, intestinale, parahaemolyticus, parainfluenza stationis\u003c/em\u003e, and \u003cem\u003estercorea\u003c/em\u003e\u003cb\u003e(Supplementary Table S2).\u003c/b\u003e\u003cem\u003eCampisalis\u003c/em\u003e was detected only in the pre-plantation soil which was amended with the kitchen waste compost. while, there was a complete absence of this bacterial species in all the post-harvest soil samples. The relative level of \u003cem\u003efulvum\u003c/em\u003e tend to increase in the post-harvest soil samples amended with cow dung manure, leaf waste compost, and kitchen waste compos. The counts of \u003cem\u003efulvum\u003c/em\u003e were highest in the fertilizer-amended soil in both pre-plantation and post-harvest soil samples. The count of \u003cem\u003eparahaemolyticus\u003c/em\u003e was relatively high only in the pre-plantation soil which was amended with municipal organic waste compost, while the other soil samples had negligible level of this bacterial species. The level of \u003cem\u003estercorea\u003c/em\u003e was observed to be relatively higher in the pre-plantation soils compared to the post-harvest soils. The fertiliser-amended soil had the higher level of this bacterial species in all the soil samples. In general, the counts of pathogenic bacterial OTU at the species level were relatively higher in the fertiliser-amended soil samples in both the pre-plantation and post-harvest soil samples.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Relative abundance of beneficial and pathogenic microorganisms in the cultivars vis-\u0026agrave;-vis soils.\u003c/h2\u003e \u003cp\u003eThe microbiome in the cultivars, \u003cem\u003eAmaranthus cruentus\u003c/em\u003e, varied significantly depending on the types of soil and bio-compost used to grow them (Sharma et al., 2023). The cultivars which were cultivated using bio-composts had relatively higher beneficial bacteria with lower pathogens than the cultivar of the chemical fertiliser, except in the municipal organic waste compost-amended soil produce \u003cb\u003e(Supplementary Table S3 and S4).\u003c/b\u003e It was also observed that the vegetable produce of the Yamuna floodplain soil had higher beneficial microorganisms than the produce of the residential soil. The cultivar of the leaf waste compost and kitchen waste compost-amended soil had the highest level of the beneficial microorganisms with the observed total OTUs of 16678 and 16573, respectively. While, the municipal organic waste compost and chemical fertiliser-amended soil cultivar had the lowest level of beneficial microorganisms with the observed total OTUs of 6202 and 8463, respectively. On the other hand, the cultivar of the chemical fertiliser (total OTU\u0026thinsp;=\u0026thinsp;2984) had highest pathogenic bacteria and the cultivars of the municipal organic waste compost and leaf waste compost-amended soil had the lowest pathogens with the observed total OTUs of 347 and 588, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.1. The effect of bio-composts on the microbial richness and diversity in the soils\u003c/h2\u003e \u003cp\u003eThe variation in the number of reads and GC contents across the samples suggest differences in microbial richness and diversity. Studies have shown that microbial richness and diversity was influenced by various factors, including soil type, management practices, soil amendments, and environmental conditions (Fierer, Bradford, and Jackson \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Delgado-Baquerizo et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Higher microbial diversity is generally considered beneficial for ecosystem functioning and resilience. The significant variation in the total number of OTUs across the samples indicated differences in microbial community composition. The soil sample amended with chemical fertiliser of Yamuna floodplain soil had the highest number of OTUs, while the post-harvest Yamuna floodplain soil amended with cow dung manure had the lowest OTU. This variation could be attributed to variations in soil characteristics, land use, bio-compost use, and plant-microbe interactions in this cropping system. Different microbial taxa may respond differently to environmental changes, addition of the soil amendments like bio-composts, and management practices, leading to varying OTU counts (Berg and Smalla \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Philippot et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). There was a reduction in the total OTUs in the post-harvest soil samples compared to the pre-plantation soils, except in the leaf waste compost amended soil sample, where there was an increase in the total OTU in the post-harvest soil. This general reduction in OTUs in post-harvest soil samples was consistent with previous studies that have reported a decrease in microbial diversity following disturbance events such as harvesting or land-use changes. Disturbances can disrupt microbial communities and reduce overall diversity. However, the increase in OTUs observed in the soil samples amended with leaf waste compost was intriguing. This could be due to the favourable condition for the microbial growth and activity promoted by the leaf waste bio-compost. Compost amendments have been reported to enhance soil fertility, organic matter content, and microbial activity, which promotes microbial diversity (Kibblewhite, Ritz, and Swift \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The addition of bio-compost may introduce new microbial taxa or create favourable conditions for the growth of certain microbial populations, leading to an increase in OTU counts.\u003c/p\u003e \u003cp\u003eThe bio-composts generated from the various types of organic wastes had different qualities depending on the nutrients and potentially toxic elements content (Mahongnao et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The impact of the bio-compost amendment on the microbial community composition of the soil needs to be understood. Nevertheless, some studies have investigated the changes in microbial community composition following bio-compost amendment. For example, a recent study examined the microbial communities in compost-amended soils using high-throughput sequencing techniques. They found that the long-term application of bio-compost amendment significantly altered the microbial community structure, leading to an increase in beneficial microbial groups such as \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eAcidibacter\u003c/em\u003e, and \u003cem\u003eNocardioides\u003c/em\u003e, and reduced the relative abundance of the pathogenic microorganisms such as \u003cem\u003eStachybotrys\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e (Liu et al. 2022). Such results are consistent with our results in which we have shown that adding bio-composts in the soil increases beneficial microorganisms such as \u003cem\u003eAchromobacter, Agromyces, Bacillus\u003c/em\u003e, and others. Also, there was a reduction of the pathogenic microbial group such as \u003cem\u003eLeptolyngbya\u003c/em\u003e, \u003cem\u003eBalneimonas, Protochlamydia, Rhabdochlamydia\u003c/em\u003e, and \u003cem\u003ePhaeospirillum\u003c/em\u003e in the bio-compost-amended soils compared to the fertiliser-amended soil.\u003c/p\u003e \u003cp\u003eThe addition of bio-compost also enhanced the microbial diversity in the soil. In this study, we have shown that bio-compost amendments such as leaf waste compost, kitchen waste compost, vermicompost, municipal organic waste compost, and cow dung manure enhanced the microbial diversity and evenness of the microbial distribution in the soil. Other studies have also shown that compost amendment significantly increased microbial diversity, and enhanced functionality which is essential for soil health and ecosystem functioning. Recent research has also focused on understanding the functional potential of microbial communities in compost-amended soils. A study by Delmont used metagenomic approaches to investigate the functional genes present in compost-amended soils. They found an enrichment of genes associated with organic matter decomposition, nutrient recycling, and plant-microbe interactions, suggesting the positive influence of compost on soil microbial functions (Delmont et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Beneficial microorganisms in the bio-compost could benefit plant health when used as a soil amendment. Applying bio-compost as soil amendments has been shown to promote plant growth and improve plant health. These effects are often attributed to the interactions between compost-influenced microbial communities and plants. For example, a study demonstrated that compost amendment increased the abundance of beneficial microbes, such as plant growth-promoting bacteria and mycorrhizal fungi, leading to improved nutrient availability and plant growth (Hu et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Recent studies have also investigated the long-term effects and sustainability of bio-compost amendments on soil microbial dynamics by evaluating the persistence of compost-induced changes in microbial communities over several years. They found that the impact of compost on microbial community composition and diversity was still evident even several years after initial application, highlighting the potential long-term benefits of bio-compost amendments (Heisey et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Augmentation of beneficial microorganisms in the soil\u003c/h2\u003e \u003cp\u003eBio-composts, also known as organic composts, are valuable soil amendments that enhance soil fertility and promote the growth of beneficial microorganisms. Adding compost to the soil is an effective way to augment beneficial microorganisms and improve soil health. Compost is rich in organic matter and nutrients, making it an ideal substrate for microbial growth. The soil amendment with compost enhances microbial diversity, activity, and biomass, leading to numerous benefits for soil fertility, nutrient recycling, and plant growth. In our study, we observed that the addition of bio-compost, such as leaf waste compost, cow dung manure, kitchen waste compost, and municipal organic waste compost, in the soil enhanced the beneficial bacteria such as \u003cem\u003eClostridium, Nitrospira, Planctomyces, Pseudomonas, Steroidobacter\u003c/em\u003e, and \u003cem\u003eStreptomyces\u003c/em\u003e and others. It was observed that the soil sample amended with leaf waste compost was seen with the highest augmentation of the beneficial microorganisms in the post-harvest soil. On the other hand, the soil sample amended with chemical fertiliser was seen with the most significant reduction in the beneficial microorganisms in the post-harvest soils. These microorganisms can potentially impart beneficial effects on soil and plant health through nutrient solubilisation, nitrogen fixation, bio-control, and plant growth-promoting activities (Wang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compost contains diverse microorganisms, including bacteria, fungi, protozoa, and beneficial nematodes. These microorganisms play crucial roles in nutrient transformation, organic matter decomposition and soil structure formation. The addition of compost could promote the colonisation of soil with diverse microbial communities, leading to increased functional diversity and resilience of the soil ecosystem (Fierer et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The beneficial microorganisms present in bio-compost actively participate in nutrient recycling processes. They decompose organic matter, releasing nutrients such as nitrogen, phosphorus, and micronutrients in plant-available forms. Compost-amended soils show improved nutrient availability and cycling, which enhances plant nutrient uptake and reduces the risk of nutrient leaching (Wani et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Microorganisms in compost also contribute to forming and stabilising soil aggregates, improving soil structure. This enhances soil porosity, water infiltration, and water-holding capacity, leading to better moisture retention in the root zone. The presence of compost-derived microorganisms could improve soil physical properties and mitigate the negative impacts of soil compaction (Grundmann \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Biocontrol of pathogenic microorganisms in the soils\u003c/h2\u003e \u003cp\u003eBioremediation of pathogenic microorganisms aims to mitigate their presence and potential harm through natural processes. Bio-composts have been increasingly recognised for their potential in bioremediation due to their diverse microbial communities and ability to enhance soil health. Composts can contribute to the bioremediation of pathogenic microorganisms in the soil through several mechanisms like microbial competition, antibiosis, predation, production of antimicrobial compounds, and alteration of environmental conditions (e.g., pH or moisture) unfavourable for pathogens survival (T\u0026oacute;thn\u0026eacute; et al. 2021; Pugliese et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The diverse microbial community in bio-composts contributes to the effectiveness of these mechanisms. It is worth noting that bio-composts\u0026rsquo; efficacy in bioremediation can vary depending on factors such as compost composition, application rates, and environmental conditions. Therefore, it is essential to consider site-specific factors when implementing bioremediation strategies using bio-composts.\u003c/p\u003e \u003cp\u003eIn this study, we analysed the effectiveness of different bio-composts, such as leaf waste compost, kitchen waste compost, cow dung manure, vermicompost, and municipal organic waste compost, in comparison with the chemical fertilizer, on the bioremediation of pathogens. We observed that the number of pathogenic OTU was higher in the pre-plantation soils than post-harvest soils. Also, the chemical fertiliser-amended soil samples had a higher level of pathogenic OTUs, in both the pre-plantation and post-harvest soils than the bio-composts-amended soil samples. The addition of bio-composts was seen with a higher level of bioremediation of the pathogenic microorganisms in the post-harvest soils, such as \u003cem\u003eFlavobacterium, Prevotella, Leptolyngbya\u003c/em\u003e, and \u003cem\u003eNocardia.\u003c/em\u003e Bio-composts' effectiveness in bioremediation has also been demonstrated in some recent studies. For instance, studies have reported the potential of thermophilic compost and vermicompost in the bioremediation of soil contaminated phytopathogenic. The researchers reported the disease suppressive properties of thermophilic compost on a wide range of phytopathogens viz., \u003cem\u003eRhizoctonia Phytopthora, Plasmidiophora brassicae, Gaeumannomyces graminis\u003c/em\u003e, and \u003cem\u003eFusarium sp.\u003c/em\u003e Bio-composts were also reported to be effective in controlling the arthropods and nematodes and improved overall soil health (Pathma and Sakthivel \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; T\u0026oacute;thn\u0026eacute; Bogd\u0026aacute;nyi et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, researchers have also examined the antagonistic activity of microorganisms isolated from bio-composts on the soil-borne plant pathogens and found to be effective in suppressing the pathogens such as \u003cem\u003eFusarium sp.\u003c/em\u003e (Su\u0026aacute;rez-Estrella et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pugliese et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The green waste compost and the compost products like compost tea, compost extract, and the solid phase after extraction, were also reported to be having a strong inhibitory action on the growth of plant pathogens such as \u003cem\u003eFusarium oxysporum, Rhizoctonia sp.\u003c/em\u003e and \u003cem\u003ePythium debaryanum\u003c/em\u003e (Milinković et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Bio-composts from different sources could be fortified with biocontrol agents, which can suppress soil-borne plant pathogens. Applying such bio-composts could bring about environmental-friendly control of pathogens, improve soil fertility, and achieve environmental sustainability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Relationship of soil microbiome vis-\u0026agrave;-vis the cultivars\u003c/h2\u003e \u003cp\u003eThe beneficial and pathogenic microbiome of the cultivars had been observed to be significantly impacted by the soil types and amendments used to grow them (Sharma et al. 2023). The cultivars produced using bio-composts generally exhibited higher levels of beneficial bacteria than those produced using chemical fertilisers, except when municipal organic waste compost was used. This implies that bio-composts could contribute to a more favourable microbial community in the cultivars, potentially enhancing their growth and overall health. The higher abundance of beneficial microorganisms in the leaf waste compost and kitchen waste compost-amended cultivars, as evidenced by higher total operational taxonomic units (OTUs), which indicates the positive impact of these composts on the microbial diversity and richness. On the other hand, the cultivars grown with chemical fertiliser alone showed a higher abundance of pathogenic bacteria, as indicated by the total pathogenic OTUs. This finding suggests that chemical fertilisers may not support the beneficial microbiome and potentially favour the growth of harmful microorganisms. This is supported by study that reported that prolonged chemical fertiliser application limits ecosystem functioning (Bai et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, this study revealed variations in the abundance of beneficial microorganisms in the cultivars depending on the soil type. Specifically, the cultivar grown in the Yamuna floodplain soil exhibited higher levels of beneficial microorganisms than those grown in residential soil. This observation highlights the importance of soil quality and composition in shaping the microbial community associated with plant cultivars. Recent studies have reported the interconnectedness of the beneficial soil microbiome with that of food safety and human health, that beneficial microorganisms in the soil could significantly promote food safety and human health (Bertola, Ferrarini, and Visioli \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). So, the present study showed that applying bio-composts as soil amendments enhances soil quality and promotes beneficial microorganisms in the soil that can improve food safety and human health. Though there are some limitations in this study that certain OTUs generated could not be assigned to a particular bacterial taxonomy and also, some bacterial taxa identified are novel and their functions are not known to the current literature whether they are beneficial or pathogenic.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study revealed that applying bio-composts enhances the soil\u0026rsquo;s microbial richness and diversity. The types of microorganisms and their proportion in the soils varied depending on the nature of the bio-composts added to the soil. Adding bio-composts also helps enrich the beneficial microorganisms and the bioremediation of the pathogenic microorganisms in the soils.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Authors acknowledged the University Grants Commission, Govt. of India, for providing a research fellowship to the first author, bearing the award letter no. 598/CSIR-UGC NET JUNE 2018. We thank Prof. Savita Roy, Principal of the Daulat Ram College, University of Delhi, and the Department of Biochemistry, Daulat Ram College, University of Delhi, for providing the logistics, working space, and equipment for this research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSophayo Mahongnao\u003c/strong\u003e \u0026ndash; Data compilation, analysis, data curation, and original manuscript drafting\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePooja Sharma\u003c/strong\u003e - Data compilation, analysis, and data curation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArif Ahamad\u003c/strong\u003e \u0026ndash; Conceptualization and methodology\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSarita Nanda\u003c/strong\u003e\u0026ndash; Conceptualization, experimental design and supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research study received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human participants or animals performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAzeem M, Hale L, Montgomery J, Crowley D, McGiffen ME (2020) Biochar and compost effects on soil microbial communities and nitrogen induced respiration in turfgrass soils. PLoS One 15(11 November):1\u0026ndash;20. https://doi.org/10.1371/journal.pone.0242209\u003c/li\u003e\n\u003cli\u003eBai YC, Chang YY, Hussain M, Lu B, Zhang JP, Song XB, Lei XS, Pei D (2020) Soil chemical and microbiological properties are changed by long-term chemical fertilizers that limit ecosystem functioning. Microorganisms 8(5). https://doi.org/10.3390/microorganisms8050694\u003c/li\u003e\n\u003cli\u003eBerg G, Smalla K (2009) Plant species and soil type cooperatively shape the structure and function of microbial communities in the rhizosphere. FEMS Microbiol Ecol 68(1):1\u0026ndash;13. https://doi.org/10.1111/j.1574-6941.2009.00654.x\u003c/li\u003e\n\u003cli\u003eBertola M, Ferrarini A, Visioli G (2021) Improvement of soil microbial diversity through sustainable agricultural practices and its evaluation by -omics approaches: A perspective for the environment, food quality and human safety. Microorganisms 9(7). https://doi.org/10.3390/microorganisms9071400\u003c/li\u003e\n\u003cli\u003eDelgado-Baquerizo M, Maestre FT, Reich PB, Jeffries TC, Gaitan JJ, Encinar D, Berdugo M, Campbell CD, Singh BK (2016) Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat Commun 7:1\u0026ndash;8. https://doi.org/10.1038/ncomms10541\u003c/li\u003e\n\u003cli\u003eDelmont TO, Quince C, Shaiber A, Esen \u0026Ouml;C, Lee ST, Rapp\u0026eacute; MS, MacLellan SL, L\u0026uuml;cker S, Eren AM (2018) Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes. Nat Microbiol 3(7):804\u0026ndash;813. https://doi.org/10.1038/s41564-018-0176-9\u003c/li\u003e\n\u003cli\u003eFarrell M, Griffith GW, Hobbs PJ, Perkins WT, Jones DL (2010) Microbial diversity and activity are increased by compost amendment of metal-contaminated soil. FEMS Microbiol Ecol 71(1):94\u0026ndash;105. https://doi.org/10.1111/j.1574-6941.2009.00793.x\u003c/li\u003e\n\u003cli\u003eFierer N, Bradford MA, Jackson RB (2007) Toward an ecological classification of soil bacteria. Ecology 88(6):1354\u0026ndash;1364. https://doi.org/10.1890/05-1839\u003c/li\u003e\n\u003cli\u003eFierer N, Ladau J, Clemente JC, Leff JW, Owens SM, Pollard KS, Knight R, Gilbert JA, McCulley RL (2013) Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science (80- ) 342(6158):621\u0026ndash;624. https://doi.org/10.1126/science.1243768\u003c/li\u003e\n\u003cli\u003eGrundmann GL (2004) Spatial scales of soil bacterial diversity - The size of a clone. FEMS Microbiol Ecol 48(2):119\u0026ndash;127. https://doi.org/10.1016/j.femsec.2004.01.010\u003c/li\u003e\n\u003cli\u003eHeisey S, Ryals R, Maaz TM, Nguyen NH (2022) A Single Application of Compost Can Leave Lasting Impacts on Soil Microbial Community Structure and Alter Cross-Domain Interaction Networks. Front Soil Sci 2(April):1\u0026ndash;16. https://doi.org/10.3389/fsoil.2022.749212\u003c/li\u003e\n\u003cli\u003eHirt H (2020) Healthy soils for healthy plants for healthy humans. :1\u0026ndash;5. https://doi.org/10.15252/embr.202051069\u003c/li\u003e\n\u003cli\u003eHo TTK, Tra VT, Le TH, Nguyen NKQ, Tran CS, Nguyen PT, Vo TDH, Thai VN, Bui XT (2022) Compost to improve sustainable soil cultivation and crop productivity. Case Stud Chem Environ Eng 6(April):100211. https://doi.org/10.1016/j.cscee.2022.100211\u003c/li\u003e\n\u003cli\u003eHu L, Robert CAM, Cadot S, Zhang X, Ye M, Li B, Manzo D, Chervet N, Steinger T, Van Der Heijden MGA, Schlaeppi K, Erb M (2018) Root exudate metabolites drive plant-soil feedbacks on growth and defense by shaping the rhizosphere microbiota. Nat Commun 9(1):1\u0026ndash;13. https://doi.org/10.1038/s41467-018-05122-7\u003c/li\u003e\n\u003cli\u003eJahangir MMR, Islam S, Nitu TT, Uddin S, Kabir AKMA, Meah MB, Islam R (2021) Bio-compost-based integrated soil fertility management improves post-harvest soil structural and elemental quality in a two-year conservation agriculture practice. Agronomy 11(11). https://doi.org/10.3390/agronomy11112101\u003c/li\u003e\n\u003cli\u003eJiang Y, Wang X, Zhao Y, Zhang C, Jin Z, Shan S, Ping L (2021) Effects of Biochar Application on Enzyme Activities in Tea Garden Soil. Front Bioeng Biotechnol 9(September):1\u0026ndash;8. https://doi.org/10.3389/fbioe.2021.728530\u003c/li\u003e\n\u003cli\u003eKibblewhite MG, Ritz K, Swift MJ (2008) Soil health in agricultural systems. Philos Trans R Soc B Biol Sci 363(1492):685\u0026ndash;701. https://doi.org/10.1098/rstb.2007.2178\u003c/li\u003e\n\u003cli\u003eKumar M, Ahmad S, Singh RP (2022) Plant growth promoting microbes : Diverse roles for sustainable and ecofriendly agriculture. 7(May). https://doi.org/10.1016/j.nexus.2022.100133\u003c/li\u003e\n\u003cli\u003eLiu S, Sun Y, Shi F, Liu Y, Wang F, Dong S, Li M (2022a) Composition and Diversity of Soil Microbial Community Associated With Land Use Types in the Agro\u0026ndash;Pastoral Area in the Upper Yellow River Basin. Front Plant Sci 13(April):1\u0026ndash;14. https://doi.org/10.3389/fpls.2022.819661\u003c/li\u003e\n\u003cli\u003eLiu X, Shi Y, Kong L, Tong L, Cao H, Zhou H, Lv Y (2022b) Long-Term Application of Bio-Compost Increased Soil Microbial Community Diversity and Altered Its Composition and Network. Microorganisms 10(2). https://doi.org/10.3390/microorganisms10020462\u003c/li\u003e\n\u003cli\u003eLuo X, Fu X, Yang Y, Cai P, Peng S, Chen W, Huang Q (2016) Microbial communities play important roles in modulating paddy soil fertility. Sci Rep 6(February):1\u0026ndash;12. https://doi.org/10.1038/srep20326\u003c/li\u003e\n\u003cli\u003eMahongnao S, Sharma P, Singh D, Ahamad A, Kumar P V, Kumar P (2023) Formation and characterization of leaf waste into organic compost. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-023-27768-7\u003c/li\u003e\n\u003cli\u003eMilinković M, Lalević B, Jovičić-Petrović J, Golubović-Ćurguz V, Kljujev I, Raičević V (2019) Biopotential of compost and compost products derived from horticultural waste\u0026mdash;Effect on plant growth and plant pathogens\u0026rsquo; suppression. Process Saf Environ Prot 121:299\u0026ndash;306. https://doi.org/10.1016/j.psep.2018.09.024\u003c/li\u003e\n\u003cli\u003ePathma J, Sakthivel N (2015) Microbial Diversity of Vermicompost Bacteria that Exhibit Useful Agricultural Traits and Waste Management Potential. Biol Treat Solid Waste Enhancing Sustain i:169\u0026ndash;216. https://doi.org/10.1201/b18872-15\u003c/li\u003e\n\u003cli\u003ePhilippot L, Raaijmakers JM, Lemanceau P, Van Der Putten WH (2013) Going back to the roots: The microbial ecology of the rhizosphere. Nat Rev Microbiol 11(11):789\u0026ndash;799. https://doi.org/10.1038/nrmicro3109\u003c/li\u003e\n\u003cli\u003ePooja Sharma, Sophayo Mahongnao, Arif Ahamad, Radhika Gupta, Anita Goela NK and S, Nanda (2023) 16S rRNA metagenomic profiling of red amaranth grown organically with different composts and soil. The Lancent Pschch 11(August):133\u0026ndash;143\u003c/li\u003e\n\u003cli\u003ePugliese M, Liu BP, Gullino ML, Garibaldi A (2008) Selection of antagonists from compost to control soil-borne pathogens. J Plant Dis Prot 115(5):220\u0026ndash;228. https://doi.org/10.1007/BF03356267\u003c/li\u003e\n\u003cli\u003ePugliese M, Liu BP, Gullino ML, Garibaldi A (2011) Microbial enrichment of compost with biological control agents to enhance suppressiveness to four soil-borne diseases in greenhouse. J Plant Dis Prot 118(2):45\u0026ndash;50. https://doi.org/10.1007/BF03356380\u003c/li\u003e\n\u003cli\u003eSamaddar S, Han GH, Chauhan PS, Chatterjee P, Jeon S, Sa T (2019) Changes in structural and functional responses of bacterial communities under different levels of long-term compost application in paddy soils. J Microbiol Biotechnol 29(2):292\u0026ndash;296. https://doi.org/10.4014/jmb.1811.11018\u003c/li\u003e\n\u003cli\u003eSu\u0026aacute;rez-Estrella F, Vargas-Garc\u0026iacute;a C, L\u0026oacute;pez MJ, Capel C, Moreno J (2007) Antagonistic activity of bacteria and fungi from horticultural compost against Fusarium oxysporum f. sp. melonis. Crop Prot 26(1):46\u0026ndash;53. https://doi.org/10.1016/j.cropro.2006.04.003\u003c/li\u003e\n\u003cli\u003eTao C, Li R, Xiong W, Shen Z, Liu S, Wang B, Ruan Y, Geisen S, Shen Q, Kowalchuk GA (2020) Bio-organic fertilizers stimulate indigenous soil Pseudomonas populations to enhance plant disease suppression. Microbiome 8(1):1\u0026ndash;14. https://doi.org/10.1186/s40168-020-00892-z\u003c/li\u003e\n\u003cli\u003eT\u0026oacute;thn\u0026eacute; Bogd\u0026aacute;nyi F, Bozin\u0026eacute; Pullai K, Doshi P, Erdős E, Gili\u0026aacute;n LD, Lajos K, Leonetti P, Nagy PI, Pantaleo V, Petrikovszki R, Sera B, Seres A, Simon B, T\u0026oacute;th F (2021) Composted municipal green waste infused with biocontrol agents to control plant parasitic nematodes\u0026mdash;a review. Microorganisms 9:1\u0026ndash;39\u003c/li\u003e\n\u003cli\u003eViti C, Tatti E, Decorosi F, Lista E, Giovannetti L, Rea E, Tullio M, Sparvoli E (2010) Compost Effect on Plant Growth-Promoting Rhizobacteria and Mycorrhizal Fungi Population in Maize Cultivations. Compost Sci Util 18(4):273\u0026ndash;281. https://doi.org/10.1080/1065657X.2010.10736966\u003c/li\u003e\n\u003cli\u003eWang J, Li R, Zhang H, Wei G, Li Z (2020) Beneficial bacteria activate nutrients and promote wheat growth under conditions of reduced fertilizer application. :1\u0026ndash;12\u003c/li\u003e\n\u003cli\u003eWani FS, Ahmad L, Ali T, Mushtaq A (2015) Role of microorganisms in nutrient mobilization and soil health - A review. J Pure Appl Microbiol 9(2):1401\u0026ndash;1410\u003c/li\u003e\n\u003cli\u003eZhen Z, Liu H, Wang N, Guo L, Meng J, Ding N, Wu G, Jiang G (2014) Effects of manure compost application on soil microbial community diversity and soil microenvironments in a temperate cropland in China. PLoS One 9(10). https://doi.org/10.1371/journal.pone.0108555\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"16S RNA metagenomic profiling, Bio-organic fertilizer, Microbiome diversity, Beneficial microorganisms, and Pathogenic microorganisms","lastPublishedDoi":"10.21203/rs.3.rs-3247820/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3247820/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding the dynamics of soil microbiomes is crucial for sustainable agriculture and developing effective soil management strategies. This study investigates the impact of leaf-based compost and other organic waste bio-compost amendments on the microbial richness and diversity in soils using 16S rRNA metagenomic profiling. Our results revealed significant variation of the microbiome richness and diversity on soil due to the bio-composts amendment. Interestingly, the bio-composts amendment resulted in a pronounced enrichment of beneficial microorganisms such as \u003cem\u003eAchromobacter, Agromyces, Bacillus, Clostridium, Nitrospira, Planctomyces, Pseudomonas, Steroidobacter\u003c/em\u003e, \u003cem\u003eStreptomyces, Alicyclobacillus\u003c/em\u003e, and \u003cem\u003eBdellovibrio\u003c/em\u003e, known for their roles in nutrient recycling, plant growth promotion, and disease suppression. The presence of pathogenic bacteria such as \u003cem\u003eFlavobacterium, Leptolyngbya, Balneimonas, Geobacter, Nocardia\u003c/em\u003e, and \u003cem\u003eMycobacterium\u003c/em\u003e, were higher in the chemical fertilizer-amended soil sample than the bio-composts amended soils, which indicated the bioremediation of pathogens due to bio-compost amendment. Moreover, it was also observed that the microbiome population of the cultivars were affected by the bio-compost amendments. Generally, the organic cultivars produced using bio-compost amendments had higher beneficial microorganisms and lower pathogens than the conventional produce with chemical fertiliser amendment. Thus, leaf-based compost and other organic-waste compost could be used as bio-organic fertilizer for healthy sustainable productivity.\u003c/p\u003e","manuscriptTitle":"Evaluating the Influence of Organic Waste Compost Amendments on Microbiome Richness and Diversity in Pre-Plantation and Post-Harvest Soils: Insights from 16S rRNA Metagenomic Profiling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-09-01 18:14:20","doi":"10.21203/rs.3.rs-3247820/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a61c93f-7a43-41bb-b34c-b59913cdbcae","owner":[],"postedDate":"September 1st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-09-19T05:17:04+00:00","versionOfRecord":[],"versionCreatedAt":"2023-09-01 18:14:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3247820","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3247820","identity":"rs-3247820","version":["v1"]},"buildId":"iFTdqyg4nuje_uAy1AHro","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}