Effect of intercropping of paulownia and buckwheat on soil microbial biodiversity and enzymatic activity

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The soil samples were characterized by measuring abundance of microorganisms determining the microbial and fungal community structure using Illumina MiSeq sequencing, the activity of dehydrogenase (DHA) and total glomalin-related soil proteins (T-GRSP). In addition, we assessed the buckwheat roots' colonisation by fungi, as well as yield and biometric traits of the plant. The calculated alpha indicators of the bacterial microbiome diversity and abundance show higher bacterial diversity in the intercropping samples, when compared to the control site. NGS (Next-Generation Sequencing) analysis showed that Actionobacteria, Proteobacteria and Acidobacteria were dominant in the microbiome in every variant of the experiment, regardless of the crop. By contrast, the mycobiome was dominated by fungi classified as the Ascomycota and Mortierellomycota. At the first sampling date (T1), intercropping sample analysis showed significant increase in DHA activity, but not in glomalin concentration. As a rule, the biometric traits’ values were higher when buckwheat was intercropped with paulownia compared to the control culture, both in terms of buckwheat yield and the total kernels of weight per plant. agroforestry biodiversity buckwheat intercropping paulownia soil microbial activity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Intercropping of trees and cultivated annuals, i.e. the integration of trees into the agricultural landscape in the form of tree-based intercropping systems (TBI), is part of a system called agroforestry, which involves cultivation of forest trees and shrubs alongside agro- and zootechnical activities within the same land area. Agroforestry constitutes a system that ensures continuous supply of organic material to the soil. 1 The development of agroforestry systems seems particularly relevant in the context of the following: counteracting negative effects of climate change, water and wind erosion of the soil, leaching of nutrients and plant protection products from the soil, loss of biodiversity, large areas of marginal agricultural land, increasing demand for bioenergy and organic products. 2 Buckwheat ( Fagopyrum esculentum Moench) is a crop that is in high demand around the world for its nutritional, economic and pharmaceutical qualities. To ensure food and nutrition security in a global climate change scenario, this pseudo-cereal is a competent alternative to staple crops (rice, wheat, rice and maize). Buckwheat also has favorable agroecological traits, such as: enabling weed control due to inhibitory effect of root secretions on the development of couch grass (allelopathy), effective protection of the soil against water erosion, high capacity to assimilate nitrogen and phosphorus from the soil, phytosanitary effect on the soil through effective control of nematodes (reduction of potato cyst nematode populations), and benefitting insects during flowering. 3 Paulownia ssp. is a type of fast-growing deciduous tree with high tolerance to variable soil and climatic conditions and low water requirements. 4 Paulownia Clon in Vitro 112 is a tree developed under laboratory conditions by crossing and cloning two species of Paulownia elongata and P. fortunei . The hybrid is considered suitable for biomass production and revegetation. 5 Furthermore, Valdivia et al. (2012) 6 found that trees of the genus Paulownia ssp. have an advantage over most other tree species in that they have a sparse canopy with late foliage and leaf drop, thus not blocking sun rays reaching the fields during the periods where many commonly grown crops, including cereals require sunlight most. Intercropping of trees and annuals expands the agroecosystem's biodiversity, promoting biological life in the soil. 2 According to research, the diversity of soil microorganisms is higher within agroforestry systems. 7 Knowledge about both activity and diversity of soil microorganisms enables researchers to assess the state of the soil, which is beneficial for agriculture and ecology. 8 , 9 A diverse soil microbial community is crucial to the productivity of any agroecosystem. They are thus a high-sensitivity indicator of changes to soil organic matter. Even modest decreases in microbial abundance can be detrimental to the soil ecosystem 10 , as soil microorganisms are responsible for various biogeochemical processes, are involved in the mineralisation of organic matter and responsible for nutrient cycling in the environment. Moreover, microorganisms one of the principal sources of soil enzymes, which act as mediators and biological catalysts for various soil functions, such as organic matter breakdown, release of inorganic nutrients (C, N, P, S) for plant growth, nitrogen fixation, nitrification, denitrification, detoxification of xenobiotics, stabilisation of soil structure and others. 11 Enzyme-related activity in the soil is one of the biological properties used as an indicator of soil quality, due to its interrelationship with soil biology. In addition, it is a highly sensitive and easily measured indicator of soil biological management, microbial activity, soil fertilisation, degree of pollution and anthropopressure. Dehydrogenases (DHGs) are one of the key components of the soil enzyme testing as they determine the correct sequence of all biochemical pathways occurring in the soil. 11 Determining the relationship between the soil humus layer and the microbiome has been possible through advances in sequencing technologies. 12 Metagenomics is a particularly useful tool for understanding microbe-soil-plant relationships and visualising patterns of microbial co-occurrence. 13 Furthermore, it simultaneously examines all microorganisms present in a soil sample, combining methods of traditional microbiology with molecular biology and bioinformatics. The diversity of bacteria and fungi is a major driver of fundamental metabolic processes in a dynamic environment such as soil. It is thus important to explore the biodiversity of the soil environment in order to develop management strategies for terrestrial ecosystems to maintain their integrity, function and long-term stability. Metagenomics results can also be used to identify key microbial taxa 13 having significant impact on the soil community. 14 Our study aimed to establish the feasibility of growing paulownia and buckwheat in the same field (buckwheat grown in inter-rows between the trees) and to capture changes in the soil environment in terms of its microbiology. Our findings stem from research spanning a two-year cycle and should be considered a contribution towards follow-up long-term field studies. This research is particularly vital in the context of efforts to maintain biological balance and protect soil biodiversity. It can also serve as a basis for the development of innovative crop management strategies for energy biomass production and annual crops, contributing towards strategies that are best adapted to the existing species in terms of mitigating negative effects of climate change. The present study can thus provide insights into the key processes of microbial diversity enhancement in ecosystems for sustainable agriculture. Materials and Methods Study Sites and Soil Sampling In 2019, a rigorous field experiment using the randomised block method with buckwheat ( Fagopyrum esculentum Moench) and paulownia (Clon in Vitro 112; P. elongata × P. fortunei ) was set up at the Research and Teaching Station of the Wrocław University of Environmental and Life Sciences (51°07′00″N; 17°10E, 121 meters above sea level). The factor tested was the intercropping of buckwheat between paulownia (AP) trees. The experiment also included control sites (AK), i.e. buckwheat plots grown without paulownia, and consisted of 5 replications. Paulownia seedlings were planted on 30.05.2019. In spring 19.05.2020, we carried our technical pruning, where we established the main shoot (future trunk). Buckwheat (Kora cultivar) was sown on 11.05.2021, 04.05.2022 at a density of 250 seeds per square meter. The area of the buckwheat plot was 30 square metres. The trees were planted in rows of 5. In the plot, the row spacing was 5 meters and tree-to-tree spacing was 4 meters. The tree density was typical for growing paulownia for round wood. For microbiological and enzyme analyses, we sampled soil from the rhizosphere of buckwheat grown without paulownia (AK) and from buckwheat grown in inter row with paulownia (AP). Soil was sampled twice before buckwheat sowing (T1) and at the buckwheat flowering stage (T2) in the first (2021) and second (2022) years of the study. Soil samples for analysis of each cultivation variant were taken from 5 replicates. Chemical-physical soil analysis The rigorous field experiment was based on soil class fied as humic ordinary alluvial soils Polish Soil Classification (SGP6) or Eutric Fluvisols ( Humic), IUSS Working Group WRB, 2022). According to agricultural evaluation, the soil was identified in F – IV b-a class (moderately poor). 15 , 16 Soil samples for bioavailable forms of macronutrients (P, K, Mg) and mineral nitrogen content analysis were sourced before sowing buckwheat and after the end of vegetation from several randomly selected locations in the field, separately for each site to obtain an average sample. Soil samples were sources from the 0–30 cm layer using soil sampler tool, air-dried, ground using a porcelain pestle and mortar, and sieved to < 2 mm. A portion of each sample was then finely ground for analysis. Soil testing included: determination of basic soil characteristics and properties, such as soil morphology, soil classification, land use value, pH, macronutrient content, including mineral nitrogen. We carried out characterisation of the following soil properties: content of bioavailable forms of P, K - assessed using the Egner-Riehm (DL) method; soil Ca content - using Sheibler method; available magnesium content - using Schachtschabel method; pH in distilled water and in 1M KCl - using potentiometric pH metres; nitrogen content using the modified Kjehdal method (total nitrogen determination); The soil pH and microelement content of the soil is presented in Table 1 . The soil pH in both the intercropped site and the control site was slightly acidic in both years of the study. Phosphorus and potassium contents on both sites were very high in the year the experiment started. At the end of the 2022 season, the potassium content was found to be reduced to ‘medium’ for the intercropping variant and for phosphorus to ‘high’ for this site. In terms of magnesium content - it was very high in the soil in both sites in the year the experiment started, while by the end of 2022 it had decreased to medium on both sites (Table 1 ). Over time, the mineral nitrogen content in the soil, decreased under intercropping of paulownia and buckwheat, while the monoculture cultivation of buckwheat contributed to an increase in mineral nitrogen content in the 30 cm-deep soil layer. Table 1 Soil pH and macroelement content of the soil profile (0–30 cm) in 2019 and 2022. Detailed determination 2019 2022 AK AP AK AP pH in KCl (soil pH) 6.2 (slightly acidic) 5.8 (slightly acidic) 5.7 (slightly acidic) 5.7 (slightly acidic) Phosphorus P 2 O 5 (mg 100 g − 1 of soil) 48.5 (very high) 27.6 (very high) 22.6 (very high) 18.8 (high) Potassium K 2 O (mg 100 g − 1 of soil) 33.5 (very high) 33.5 (very high) 28.9 (very high) 24.1 (medium) Magnesium Mg (mg 100 g − 1 of soil) 7.6 (very high) 7.6 (very high) 6.7 (medium) 5.4 (medium) N min. (kg ha − 1 ) 43.8 (very low) 48.0 (very low) 56.8 (low) 21.4 (very low) AP - intercropping, AK – control, N min. – mineral nitrogen Table 1 . Soil pH and macroelement content of the soil profile (0–30 cm) in 2019 and 2022. Agrotechnology of the experiment Prior to starting the experiment, following the 2018 winter triticale harvest, the field was ploughed with a subsoiler plough and then the soil was kept in a weed-free state using a cultivating unit (rotary harrow with crushing roller). In autumn, deep pre-winter ploughing was carried out to a depth of 25 cm. In the year we started our experiment, i.e. spring 2019, the soil was ploughed again using a subsoiler plough and further amended using a cultivating unit. After planting the paulownia seedlings, the soil in the interrows was loosened with a rotary harrow. The following year, in the spring of 2020, the soil was ploughed shallow and then was amended using a cultivator before sowing buckwheat. Following technical tree pruning in May 2020, the paths in the experiment were mechanically tended. After harvesting the buckwheat with a plot harvester, the soil was kept weed-free by harrowing (rotary harrow). In 2021, a cultivating unit equipped with a string roller was used to cultivate the soil after winter. By May 2021, harrowing had been carried out twice as a weed control measure. After sowing the buckwheat, the paths were mechanically cultivated several times until harvesting using combine harvester. Before winter, the soil was kept weed-free by harrowing with a rotary harrow. Tillage in 2022 included harrowing the field after winter with a cultivator, followed by ploughing with a subsoiler plough to a depth of 12 cm. Before sowing buckwheat, the soil was treated with a cultivating unit consisting of a rotary harrow and a crushing roller. The sowing of buckwheat was done with a plot seeder. Paths between the plots were tended during the growing season. No mineral or organic fertilisers or any pesticides were used in the experiment. Weather conditions As part of the experimental design, we took into account meteorological data on the weather during the experimental period (Table 2 ). Meteorological conditions were analysed using data provided by the meteorological station (AsterMet) in Swojczyce (Wrocław). We used Selyaninov's hydrothermal coefficient (HTC) to describe the impact of weather conditions on the plant development, using the following formula: Table 2 Weather conditions and HTC in 2019–2022 provided by the meteorological station (AsterMet) in Swojczyce (Wrocław). Month Temperature (°C) Rainfall (mm) HTC (K) 2019 2020 2021 2022 Mean 1990 − 2020 2019 2020 2021 2022 Mean 1990 − 2020 2019 2020 2021 2022 IV 10.8 9.50 7.5 6.4 9.6 24.2 6.4 32.5 32.7 32.8 0.75 0.23 1.45 1.46 V 12.1 11.6 12.4 12.7 14.3 76.8 77.2 59.0 20.9 58.9 2.06 2.14 1.54 0.44 VI 22.1 18.5 19.8 20.1 17.8 27.0 94.5 38.4 39.7 74.6 0.41 1.22 0.65 0.58 VII 19.3 19.5 20.5 20.7 19.7 44.5 53.2 41.1 132.5 86.6 0.74 1.29 0.64 2.12 VIII 20.3 22.5 17.3 17.7 19.2 59.8 6.2 11.0 92.5 63.6 0.95 0.09 0.21 1.45 IX 14.4 14.7 15.0 14.8 14.2 42.0 92.9 14.5 82.0 50.6 0.97 2.11 0.32 2.12 X 10.4 10.7 9.5 9.1 9.3 32.1 100.5 10.2 8.6 40.8 3.21 3.03 0.35 0.25 Mean / sum (IV-X) 15.6 15.3 14.6 14.5 14.5 306.4 430.9 206.7 408.9 377.0 - - - - K = P / (0.1×T) where: K – Selyaninov's hydrothermal coefficient, P – total rainfall per month, T – sum of daily average temperatures per month 17 Table 2 . Weather conditions and HTC in 2019–2022 provided by the meteorological station (AsterMet) in Swojczyce (Wrocław). Characterization of soil microbiological properties DNA extraction, PCR and Illumina amplicon sequencing Total DNA for metagenomic analysis was extracted from the soil samples using the PowerSoil® DNA Isolation Kit (MO BIO) according to the manufacturer’s instructions. The extracted genomic DNA was quantified and checked for quality at A 260/280nm (1.7–2.0) and diluted in sterile water to 10 ng µL − 1 . Meta-barcoding analysis of the microbial community was performed based on the variable regions: V3 - V4 of the 16S rRNA gene for bacteria and hypervariable region of ITS1 for fungi. Specific primer sequences 341F and 785R (16S analysis); ITS1FI2 and 5.8S (ITS1 analysis) were used to amplify the selected region and prepare the library. PCR was performed using Q5 Hot Start High-Fidelity 2X Master Mix, reaction conditions according to manufacturer’s recommendations. Next – generation sequencing was performed by Genomed S.A. (Warsaw, Poland) on a MiSeq sequencers (Illumina, San Diego, CA, USA) in paired-end (PE) technology, 2 × 300 nt, using the Illumina v 3 kit (San Diego, CA, USA). Bioinformatic analysis Bioinformatics analysis ensuring the classification of reads was carried out with the QIIME 2 software package based on the reference sequence database Silva 138 (for bacteria) and UNITE v8.2 (for fungi). The DADA2 package was also used, which allowed for the specification of sequences of biological origin from those newly created in the sequencing process. This package was also used to isolate unique sequences of biological origin, i.e. ASV (amplicon sequence variant). The analysis consisted of the following stages: reading quality control, initial data processing using the Cutadapt tool, selecting unique ASV and OTU (operational taxonomic units) sequences and assigning taxonomies to the generated sequences based on reference databases. In addition, α-diversity indices (Shannon diversity H′, Simpson index D and observed AVS/OTU) were assessed from the Illumina MiSeq results. Quantification of Cultivable Bacteria and Fungi In order to determine the colony-forming units of bacteria and fungi in the test soils (AK, AP, T1 and T2), we did surface culture combined with the technique of successive dilutions on medium developed by Bunt and Rovira 18 and Martin 19 , respectively. Analyses were performed in 3 average samples taken from each test plot. Results are presented in units forming colonies in 1 g of soil (CFU × g -1 ). Actual results were subject to three-way analysis of variance (ANOVA) with post-hoc Tukey HSD test. Soil dehydrogenase activity (DHA) and T-GRSP concentration Dehydrogenase activity (DHA) was analysed according to PN-ISO 23753-1 (2008) using 2,3,5-triphenyltetrazolium chloride (TTC), reduced via enzymatic activity to triphenylformazan (TPF). We added 5 mL of a 3% solution of TTC (Merck, Germany) to the soil using 1:1 ratio (g:mL), mixed them thoroughly and incubated at 25°C for 16 h. The released triphenylformazane (TPF, Merck, Germany) was extracted using methanol and spectrophotometrically analysed (Ray Leight, VIS 723G) at 485 nm. The control sample was soil without added TTC. The amount of TPF released was expressed as microgram per gram of dry soil per hour. Total glomalin-related soil proteins (T-GRSP) were also determined and extracted from soil samples using the method developed by Wright and Upadhyay (1999) 20 including our alterations. Soil samples (10 g) were flooded with 0.05M citrate buffer, pH 8.0, and autoclaved at 121°C for 60 min. The extraction was repeated several times until the organic fraction was completely eluted from the soil. Following each autoclaving, the supernatant containing T-GRSP was poured off and centrifuged at 10 000 rpm for 10 min. Soil samples were covered with sterile buffer and autoclaved again. The extracts, collected after each heating and centrifugation, were combined, and stored at 4°C until analysis. T-GRSP content in the supernatants was quantified via the Bradford method using bovine serum albumin (Sigma-Aldrich, Inc., Saint Louis, USA) as a standard. Principal component analysis of soil microbial properties We performed PCA multivariate statistical analysis of the tested soil samples’ variability to determine the relation among the measured activities. Mean values from three replicates were used for PCA analysis. Data were standardized prior to the analysis. All statistical analyses were performed using Statistica 13.1 software (StatSoft, Inc., Tulsa, OK, USA). Colonisation of buckwheat roots by filamentous fungi We assessed the degree of colonisation of buckwheat roots by potential pathogenic fungi. Filamentous fungi were isolated from buckwheat roots collected at flowering (T2) and their genus and/or species were established based on their morphological characteristics. 21 , 22 For this purpose, root sections that had been previously disinfected with 0.5% NaOCl (for 15 min, rinsed 4 times with sterile distilled water) were plated on PDA medium (BTL, Łódź) supplemented with streptomycin (30 µg mL − 1 ). The plates were incubated at 28°C for 72 h. The fungi were then reisolated onto PDA medium. Ten replicates (60 inoculations each) were performed from each sample. Results are presented as percentage of root colonisation by fungi. Analysis of buckwheat biometric traits and the yield Before harvesting the buckwheat, we randomly sampled 10 plants from each plot. The samples were sourced from the middle rows to mitigate the border effect. The biometric analysis included: plant height, number of branches, number of twigs, number of inflorescences, number of kernels and weight of full kernels per plant. The yield per plot was adjusted to 15% moisture content and converted to tonnes per hectare. To assess the effect of cultivation method and time by years of study, we performed a two-factor ANOVA analysis using Statistica 13.1. When differences between means were found to be significant, they were compared using the HSD-Tukey test, with a significance level of α = 0.05. Actual DHA and T-GRSP results were subject to a three-way analysis of variance (ANOVA) with post-hoc Tukey HSD test. Homogenous groups has been established from largest to the smallest. Results Characterization of soil microbiological properties Diversity and structure of microbiome and mycobiome The results obtained using the NGS analysis (Table 3 ) showed variability in the bacterial population in the plant root zone between the test plots and the reference plots, as shown by the Shannon (H') and Simpson (D) indices. The highest Shannon index value was obtained in soil samples sourced on the first sampling date (T1) for the AP combination in 2021. A similar relationship was established for soil samples collected in 2022, when the highest Shannon index value was obtained for T1 sampling and for the AP combination. Simpson's index was less differentiated, though once again the highest index value was observed in 2021 for the samples sourced on the first date (T1) for the AP combination. The lowest diversity indices values (both Simpson's and Shannon's) were found in samples collected in 2022 for the AK combination on the second date, or during the second soil sampling campaign (T2). The index valued calculated for fungi based on NGS analysis also showed variability in fungal populations between cropping systems. The AP variant resulted in the highest Shannon index value in samples collected in 2022 on the first date (T1), but the index also showed seasonal dynamics. Furthermore, the Shannon index values were lower in the AP plots when compared to the AK plots on all other sampling dates. The richness of the observed AVS for bacterial populations was higher in soil samples collected from paulownia and buckwheat intercropping variant compared to the control samples, on all sampling dates. However, a different relationship was observed for fungal populations. Table 3 Estimation of alpha diversity index and richness (number of AVSs and OTUs of bacterial and fungal microbiomes. Year Period Samples BACTERIA FUNGI Shannon Diversity Index (H’) Simpson’s Index (D) Observed AVSs Shannon Diversity Index (H’) Simpson’s Index (D) Observed OTUs 2021 T1 AK 5.055 0.988 511 2.981 0.817 294 AP 5.219 0.990 581 2.876 0.820 278 T2 AK 5.022 0.987 496 2.824 0.833 293 AP 5.044 0.988 524 2.750 0.836 272 2022 T1 AK 5.154 0.989 551 2.872 0.804 262 AP 5.158 0.989 551 3.086 0.848 273 T2 AK 4.855 0.984 452 2.688 0.814 288 AP 5.024 0.987 513 2.606 0.789 282 AP – intercropping; AK – control; T1, T2 – the first and second soil sampling date; AVS – Amplicon Sequencing Variants; OUT - Operational Taxonomic Units Table 3 . Estimation of alpha diversity index and richness (number of AVSs and OTUs of bacterial and fungal microbiomes. Nine bacterial phyla proved to be most prevalent in the rhizosphere soil samples: Actinobacteriota, Proteobacteria, Chloroflexi, Gemmatimonadota, Bacteroidota, Firmicutes, Myxococcota, Verrucomicrobiota and Planctomycetota. Other phyla usually did not exceed 5% relative abundance (Fig. 1). In all combinations under study, the largest group was the Actinomycetes, up to 45% (2022/T2/AK). Proteobacteria were also a significant group in all combinations (about 20–30%, depending on the combination). Samples collected in 2021 had lower relative abundance of Actinobacteria based on 16S rRNA gene fragment sequencing analysis for bacteria compared to samples from the 2022 collection in all combinations. 16S rRNA sequencing also showed that the intercropping variant in the 2022 collection samples had no effect on Proteobacteria, regardless of sampling date. In contrast, for the 2021 samples, we noted an increase in this population for the intercropping (AP) samples collected at the first sampling time compared to the AK combination. We observed no such difference at the second sampling date (T2). Figure 1 . The relative abundance of bacteria at the phylum level The dominant fungi included four phyla: Ascomycota, Basidiomycota, Mortierellomycota, Mucoromycota. Unclassified fungi also formed a significant part of the population (Fig. 2). In all combinations studied, Ascomycota were the largest group, accounting for up to about 65% (2022/T2/AK). Relative abundance of Ascomycota was lowest in 2021 samples collected from AP at T2. In 2022, Ascomycota were slightly lower in AP than in AK on both sampling dates. Analysing different variants in the plot experiment, we noted that in 2021 the Basidiomycota phylum was the least abundant in AP in the first sampling (T1) compared to the other variants and sampling dates. In contrast, the Mortierellomycota phylum was most abundant in the 2022 samples collected on the first sampling date (T1) for the AK combination. The Mucoromycota phylum was much less abundant than the other three main fungal phyla, but its proportion increased significantly in the AP variant in the second sampling of 2022 (T2). The largest group of unclassified fungi was observed in the soil samples collected in 2021 on the second sampling date (T2) in AP (approximately 30% of the total population of the sample). Figure 2. The relative abundance of fungi at the phylum level Figure 3. Microbial community heatmap of top 15 bacteria on the general level. Different colors represent relative abundance of bacteria (%). Red means higher relative abundance, whereas green means lower relative abundance The top 15 genera in bacteria communities under study are presented in Fig. 3. Sequences assigned to Nocardioides were most abundant in all communities throughout the experiment, accounting for 2.10% − 6.23% of the total high-quality sequences. Candidatus_Solibacter was one of the dominant genus (2,43% relative abundance) in control sample sourced on T1 2022. Pseudarthrobacter was abundant in AP T2 2021 and AP T2 2022 samples, as well as in both T2 2022 samples, whereas Streptomyces was characteristic for the rhizosphere microbiomes in T2 2022 samples. Figure 4. Microbial community heatmap of top 15 fungi on the genera level. Different colors represent the relative abundance of fungi (%). Red means higher relative abundance, whereas green means lower relative abundance. Heatmap analysis of relative abundances of the most abundant genera showed clear differences in the fungal community structures between all samples (Fig. 4). Genera whose abundance were above 2% in all samples were: Exophiala , Fusarium and Mortierella . We wish to highlight that Mortierella was the dominant genus, accounting for 9.69% − 23.56% of the total high-quality sequences. Botryotinia was abundant in AK T1 2021 sample, whereas genus Penicillium in AK T2 2022 sample. Quantification of Cultivable Bacteria and Fungi Bacterial counts ranged from 2.4 ×10 4 to 2.1 ×10 6 CFU in 1 g of soil, and fungal counts ranged from 1.0 to 5.0 ×10 4 CFU in 1 g of soil (Table 4 ). Compared to the control, intercropping (AP) did not significantly affect the number of bacteria and fungi, both in the first and second year of the study. However, the number of CFUs was influenced by the sampling date and the year of the study. It is noteworthy that at both T1 and T2 for both cultivation methods, a significant increase in bacterial counts was observed in the second year of the study compared to 2021. In 2021, fungal CFU counts presented no statistically significant differences between the control sample and the soil sample where buckwheat was grown with paulownia on both sampling dates. In contrast, there was a statistically significant increase in the number of fungal CFUs on T2 in 2022 compared to the previous year (Table 4 ). Table 4 Total abundances of bacteria and fungi in the field experiment. Year Period Samples Total bacterial count (CFU g − 1 ) Total fungal count (CFU g − 1 ) 2021 T1 AK 2.4×10 4 c 3.8×10 4 abc AP 4.3×10 4 c 3.3×10 4 abc T2 AK 2.1×10 6 ab 1.6×10 4 cd AP 1.6×10 6 b 1.0×10 4 d 2022 T1 AK 2.9×10 6 ab 1.8×10 4 bcd AP 2.4×10 6 ab 1.7×10 4 cd T2 AK 3.1×10 6 ab 5.0×10 4 a AP 4.6×10 6 a 3.8×10 4 ab AK – control site; AP – intercropping; T1, T2 – the first and second soil sampling date; Values are the mean of four replicates of each sample. Values followed by different letters in columns indicate significant differences according to three-way ANOVA with post-hoc Tukey HSD test Table 4 . Total abundances of bacteria and fungi in the field experiment. Soil biological activity Soil biological activity was determined in the soil samples based on dehydrogenase activity (DHA) and total glomalin concentration (T-GRSP). The results are shown in Table 5 , Table S1 . Table 5 Dehydrogenase activity (DHA) and total glomalin concentration (T-GRSP) in the air-dried soil. Year Period Samples DHA (µg TPF g − 1 h − 1 ) Total GRSP (µg g − 1 ) 2021 T1 AK 3.8 c 1699.0 a AP 7.9 b 1522.9 a T2 AK 2.9 c 1492.1 a AP 3.0 c 1533.2 a 2022 T1 AK 7.7 b 1460.2 ab AP 12.8 a 1471.6 ab T2 AK 2.0 c 1088.0 c AP 2.5 c 1233.2 bc AK – control site; AP – intercropping; T1, T2 – the first and second soil sampling dates; DHA – dehydrogenase activity expressed as the amount of released µg triphenylformazan (TPF) per hour per gram of soil; GRSP – glomalin-related soil protein content per gram of air-dried soil. Values followed by different letters in columns indicate significant differences according to three-way ANOVA with post-hoc Tukey HSD test Table 5 . Dehydrogenase activity (DHA) and total glomalin concentration (T-GRSP) in the air-dried soil. Table 1 S. Summary of three-way analysis of variance (ANOVA) results testing the effects of cultivation (monoculture and intercropping), year (2021 and 2022), and sampling periods (T1 and T2) on total bacterial count, total fungal count, dehydrogenase activity and T-GRSP. Data shown represent F-value and significance levels for each factor and interaction. Dehydrogenase activity in the intercropping (AP) and control (AK) samples ranged from 2.0 to 12.8 µg TPF g − 1 h − 1 . Dehydrogenase activity was higher in the intercropping samples compared to the control, but statistically significant differences were observed for the first sampling date (T1). The highest DHA activity was observed in the intercropping samples in 2022 from the first sampling date (AP, T1). At the flowering stage of buckwheat (T2), enzyme activity decreased regardless of the cultivation method. The T-GRSP concentration ranged from 1039.2 to 1699.0 µg g − 1 . The concentration of glomalin depended on the sampling date and not on the cultivation method. The highest concentration of T-GRSP was found in 2021 in the control sample (AK) from the first sampling date (T1). The following year, T-GRSP concentrations decreased compared to those in samples sourced on the first sampling date (T1). Principal component analysis (PCA) The relationships in all soil samples and their properties were assessed using principal components analysis (PCA) (Fig. 5). The first two principal components (PCs) accounted for 44.27% and 25.04% of the total variance of the tested samples. The analysis showed that the 2021 samples clustered based on the sampling year, while sampling date proved to be differentiating factor for the 2022 samples. Figure 5 . Biplot diagram of principal components analysis (PCA), describing the microbial properties of soil samples collected from different cultivation sites (monoculture AK and intercropping AP), year (2021 and 2022) and sampling period (T1 and T2) Buckwheat root colonization by fungi We assessed the degree of colonisation of buckwheat roots by potentially pathogenic fungi. Table 6 shows the percentage of fungi on buckwheat roots at flowering (T2). Buckwheat roots in both the first and the second year of the study were most abundantly colonised by fungi of the genus Fusarium . The most abundant species we isolated were F. oxysporum , accounting for 54 to 67% of the total number of fungi. We also isolated the potentially pathogenic species F. culmorum and F. avenaceum (between 4 and 10%). In both the first and second year of the study, buckwheat roots were colonised by saprotrophs of the genus Trichoderma ranging from 3 to 20%. However, their number decreased in the second year of the study to 8% in the intercropping sample and to 3% compared to the control crop. In the first year of the study, Penicillium notatum fungi were recorded in the intercropping sample (13%). An increased percentage of Exserohilum pedicellatum (from 2 to 10%) was also found on buckwheat roots in the 2022 crop year. Other potentially pathogenic fungi such as F. solani , Rhizoctonia solani , Phoma spp. or Pythium spp. colonised buckwheat roots sporadically (< 1%) in both AK and AP crops. Table 6 Percentage of filamentous fungi isolated from buckwheat roots by culture method. Fungi 2021 2022 AK AP AK AP Colletotrichum sp. < 1 – – – Cylindrocarpon sp. 1 – – – Exserohilum pedicellatum – 2 6 < 10 Fusarium avenaceum – – 6 < 9 Fusarium culmorum 10 7 5 4 Fusarium oxysporum 66 54 66 67 Fusarium solani – – < 1 – Fusarium sporotrichoides – < 1 2 – Mucor mucedo 1 – < 1 – Penicillium notatum – 13 – – Penicillium purpurogeum < 1 < 1 < 1 < 1 Penicillium vermiculatum – < 1 – – Penicillium sp. 6 – 7 < 1 Phoma sp. – – < 1 – Pythium sp. – – – < 1 Rhizoctonia solani – – < 1 < 1 Rhizopus nigricans < 1 – < 2 3 Trichoderma hamatum 2 7 – 2 Trichoderma harzianum 7 12 < 1 4 Trichoderma viride < 1 < 1 2 < 2 Other fungi 4 4 – – AP – intercropping; AK – control; T1 and T2 – the first and second buckwheat roots sampling date; symbol „– ” indicates that no fungi were isolated from the sample Table 6 . Percentage of filamentous fungi isolated from buckwheat roots by culture method. Biometric traits and yield of buckwheat The cultivation variant, i.e. intercropping of buckwheat with paulownia and no intercropping, did not significantly affect any of the studied buckwheat traits, i.e. plant height, number of branches on the main shoot, number of branches, inflorescences, number of kernels, total kernels weight per plant. Despite lack of significant statistical differences, in many cases the values of biometric traits were higher when buckwheat was grown with paulownia, compared to the control site, i.e. the number of full kernels per plant and the total kernels weight per plant. Over the years of the study, time has significantly affected the kernels yield and the values for some of the traits studied, such as the number of branches per plant, the number of kernels and the total kernels weight per plant (Table 7 ). In 2022, we registered a nearly 100% higher yield of kernels per hectare. Table 7 Select morphological and flowering biology-related traits of buckwheat and buckwheat yield (averages for specific combinations and years). Specification Plant height (cm) Number of branches on main shoot Number of branches Number of inflorescences Number of full seeds Total seed mass per plant (g) Buckwheat yield (t ha − 1 ) Cultivation AP 46.7 1.22 2.99 5.95 22.5 0.260 0.650 AK 47.2 1.57 3.59 6.44 21.8 0.205 0.513 NIR , LSD ns ns ns ns ns ns ns Years 2021 47.3 1.41 2.36 6.84 15.5 0.156 0.390 2022 47.1 1.38 4.22 5.55 28.8 0.309 0.773 NIR, LSD ns ns 0.69 ns 9.1 0.100 0.252 AP - intercropping, AK – control, ns – statistically insignificant, NIR- the least statistical difference, LSD - least significant difference Table 7 . Select morphological and flowering biology-related traits of buckwheat and buckwheat yield (averages for specific combinations and years). The average height of the trees at the beginning of the growing season in 2021 was 145 cm, while at the end of the 2022 season it was 311 cm. Tree crown sizes in October 2021 had an average of: 108 cm (height) × 157 (width) cm, and in 2022: 156 cm × 209 cm. Trunk girths at breast height (at 130 cm from the ground level) at the end of the 2021 and 2022 seasons were respectively: 16.4 cm and 17.9 cm. Discussion In the present multidisciplinary study, we determined the effects of Tree Based Intercropping (TBI) of paulownia trees on soil physicochemical and microbial properties and the biometric traits of buckwheat. To the best of our knowledge, our study is the first to consider the microbiological aspect of soils in the intercropping of buckwheat and paulownia in European conditions. In northern China, Paulownia elongata trees are intercropped with wheat or beans. Typically, scientists investigate intercropping with hybrid poplar clones, black walnut, white ash, red alder. 23 , 24 Intercropping is an important element of modern agricultural systems, having an impact on yields, soil quality, and soil microbial community's activity and structure. 25 Soil pH is considered to be the main soil variable. It interacts with microorganisms, thus determining plant growth and biomass yield. 26 In the present study, we observed that both buckwheat monoculture and intercropping resulted in lower soil pH. However, the soil pH in both crops oscillated at the same level in the last year of the study. These results are consistent with previous studies on cassava and soybean intercropping and pepper and garlic intercropping 27 , 28 , which showed the intercropping system to lower soil pH. These findings are also supported by Bughio et al. (2013) 29 , who indicated that soil pH decreases with an increase in leaf litter from Eucalyptus camaldulensis . Furthermore, Khan et al. (2010) 30 found that several soil physicochemical properties in Robinia pseudoacacia plantations, such as pH, were modified by leaf decomposition. Hinsinger et al. (2006) 31 and Hagen-Thorn et al. (2004) 32 showed that tree roots acidify the soil through the release of acidic compounds and through microbial respiration. In general, all plants produce and release secondary compounds that may show the potential to alter the chemical properties of the substrate on which they grow. Furthermore, a major mechanism ensuring the efficiency of phosphorus uptake by buckwheat may be the plant's ability to acidify the rhizosphere. 33 Lower soil pH may be associated with greater nutrient availability and their consequent direct uptake through plant roots. 34 Soil microbial diversity and activity is a significant aspect of soil quality affected by TBI. So far, the relationship between soil microbial properties and the diversification of intercropping has remained understudied. Over the past two decades, soil microbial communities in temperate zone agroforestry systems have been researched, mostly via traditional methods. 35 More recently, Banerjee et al. (2016) 36 studied bacterial communities in Canadian agroforestry systems using both quantitative PCR and 454 pyrosequencing of bacterial 16S rRNA. Still, we lack comprehensive, involving both high-throughput metagenomic sequencing techniques of bacterial and fungal populations and traditional techniques to measure microbial abundance and enzymatic activity, as well as plant biometry in temperate zone agroforestry systems. Land use patterns have a significant impact on the composition and diversity of soil microorganisms, which are extremely sensitive to changes in the soil environment. 25 , 37 Our metagenomic sequence analysis of 16S rRNA gene fragments and ITS regions has provided unique data on bacterial and fungal population diversity and structure. Intercropping increased the diversity of rhizosphere bacterial populations, while the opposite trend was observed for fungal populations, evidenced by the values of the Shannon and Simpson indices. Bigger bacterial diversity may be due to increased carbon and nutrient supply from litter, dead root cells and tree root secretions. 38 In addition, although the crop plant biomass is negligible compared to trees, the decomposition of litter from crop plants with a high diversity of secondary metabolites can impact soil microbial communities. 39 Tree rows exert strong influence over soil microbial communities and provide habitat for a microbiome that differs in composition from the microbiome of neighbouring crops. Consequently, the introduction of the soil microbiome associated with tree rows onto arable land through agroforestry increases the overall diversity of the system. Our findings related to the diversity and number of OTUs of the mycobiome are in line with previous studies, which have shown that fungal communities under trees gradually diversified. Young tree cultivation within an agroforestry system do not affect the rhizosphere fungal community, and no increase in fungal populations was detected in young agroforestry systems. Clivot et al., (2020) 40 with Beule and Karlovsky (2021) 24 only detecting strong promotion of soil fungi after 10 years of poplar cultivation. This may be due to the adaptation to the heterogeneous understorey space of tree biomass and understorey vegetation or stochastic phenomena as a result of limited exchange between fungal populations. Analysing the microbiome structure of our soil samples, we noted that the microbiome of the rhizosphere soil from intercropping and buckwheat monoculture was dominated by bacteria classified as Actinobabateria, Proteobacteria, Acidobacteria, and the mycobiome by Ascomycota, Basidiomycota and Mortiellomycota. In our own study (Woźniak et al., 2019) 41 , we reported that the rhizosphere of Paulownia trees was dominated by the above-mentioned types of bacteria and fungi. Wang et al. (2022) 42 found that in the rhizosphere of buckwheat the dominant phylum were Actinobacteria, Proteobacteria and Acidobacteria and fungi classified as Ascomycota, Basidiomycota and Mortierellomycota. The dominance of Actinobacteria and Proteobacteria is probably related to the nutrient-rich conditions of the rhizosphere. 43 , 44 However, Ascomycota and Basidiomycota fungi play an important role in maintaining soil stability, in plant biomass decomposition and plant interactions. 45 Mortierellomycota, on the other hand, are fungi other than saprotrophs, living in the soil on decaying leaves and other organic materials. In addition, Basidiomycota these fungi promote plant growth in different types of crops, so they can be considered as a potential bioindicator for crop production and soil health assessment. 46 It has already been noted that high relative abundance of Mortierellomycota can be evidence of good soil health. 47 In our study, we recorded increased relative abundance of i.e. Candidatus Solibacter , Nocardioides , Pseudarthrobacter and Sphingomonas . These microorganisms, considered to be PGPR (plant growth-promoting rhizobacteria), are widely recognised to exhibit plant growth-promoting activities by e.g. mobilising nutrients, mediating phytostimulation and plant biocontrol. 48 , 49 , 50 , 51 The accumulation of these microorganisms in rhizosphere soil may be a factor that can positively affect buckwheat biometrics. The study by Peng et al. (2022) 50 also showed that intercropping promotes the enrichment of PGPR. In addition, in our metagenomic study we observed a decrease in the relative abundance of i.e., Fusarium genus - common soilborne plant pathogens - in intercropping. 52 It is likely that intercropping can effectively reduce disease incidence in crop fields. Mechanisms supporting this effect include: modification of the crop microclimate; secretion of allopathic compounds; positive effects on antagonistic microbial communities; and diversification of soil microbial communities. 53 Undoubtedly, the intercropping of trees and plants influences quantitative and qualitative changes in soil microbial life. Most studies show a significant increase in the number of microorganisms in the soil in two-plant intercropping. In our study, we noted that growing buckwheat with paulownia had a positive effect on the increase in the number of bacteria CFU. In addition, there was an increase in the number of fungi CFU in the intercropping during the flowering period of buckwheat in the second year of the study, compared to 2021. It is likely that the higher abundance of bacteria and fungi could be the result of direct contact between plant roots in the intercropping system, which stimulates plant roots to release more nutrients. 54 Similar results were obtained by Beule et al. 2020 55 , who observed an increase in bacterial abundance in poplar-based agroforestry systems compared to neighbouring monocultures in arable fields. Furthermore, the results of Lee and Jose (2003) 56 indicate that the age of the agroforestry system influences the increase in microbial biomass. In a study by Li et al. (2013) 57 , the number of soil fungi, bacteria and actinomycetes in intercropping of two species, i.e. soybean and sugarcane, increased by 115.5%, 43.6% and 57.3%, respectively, compared with monoculture. Our study showed that the CFU counts of bacteria and fungi were dependent on the sampling date, being generally higher at the flowering stage of buckwheat (T2), which is consistent with the study of Wang et al. (2019) 58 . Increasing soil microbial abundance is extremely important as it can influence plant health and soil quality, thus ensuring the stability and productivity of natural ecosystems. 59 Soil enzyme activity, including dehydrogenases, is an important indicator of organic matter decomposition and nutrient dynamics. Dehydrogenase activity (DHA) is often used as a high-sensitivity indicator of soil fertility. 8 In our study, we noted that intercropping increases DHA activity, which is particularly evident on T1, in spring, when the optimum temperature under conditions of sufficient moisture may be a factor favouring higher enzymatic activity. 60 In our own study (Woźniak et al., 2022) 8 , we reported that young plantations of paulownia trees have a positive effect on some soil microbial parameters, i.e. dehydrogenase activity. Similarly, Wan and Chen (2004) 61 observed higher enzymatic activity in tree-based intercropping including Paulownia spp. probably due to increased carbon content, nutrients, leaf residues and root secretions in the soil. The high organic content of the soil contributes to a significant increase in the number of microorganisms and changes in their community structure, thereby improving the microbial activity of the soil. 62 It appears that intercropping can provide sufficient energy to soil microorganisms that play a key role in the accumulation, decomposition and transformation of organic carbon in the soil. 63 Glomalin related soil protein (GRSP) is a glycoprotein produced by arbuscular mycorrhizal fungi (AMF), which are widespread in various terrestrial ecosystems and can form symbiotic associations with the roots of more than 80% of land plants 38 . Many authors point to GRSP as a good indicator of soil stability and fungal activity. 64 , 65 Our study showed that higher amounts of GRSP were recorded in the intercropping at T2 compared to the control objects. This may be due to the plant roots secreting more C and energetic substances that promote AMF growth and reproduction, which may increase mycelial density and length and thus GRSP amounts. 66 Furthermore, the results of our study confirm previous findings that GRSP shows sensitivity to seasonal variation and land use change. 64 Our results are also consistent with those of Zhao et al. (2020) 67 on the impact of maize and soybean intercropping on GRSP. It is also notable that AMF can expand the uptake area of plant roots to improve water and mineral absorption, promoting plant growth. 68 Yengwe et al. (2018) 69 assessed the potential of Faidherbia albida in intercropping with maize in Zambia and found that the presence of F. albida litter can provide more than 18 kg N ha − 1 year − 1 and increase microbial diversity and abundance. In contrast, according to Lucas-Borja et al. (2011) 70 , paulownia plantations worsened soil health (characterised by soil enzyme activity) compared to Aleppo pine plantations or undisturbed soil area. However, paulownia plantations contribute to better soil health than do maize cultivation (intensive soil use). In a study by Woźniak et al. (2022) 8 , following one year of observation, we concluded that some soil microbial parameters (activity of dehydrogenases and acid phosphatases, catabolic activity according to Biolog EcoPlates) decreased along with increasing distance from the nearest tree, which is related to the decreasing content of nutrients contributed by root secretions and leaf residues. Intercropping affects crop yields depending on a number of factors, i.e. plant growing conditions, species, soil and climatic conditions. Research shows that the results vary. The yield and the biometric traits of intercropped plants depend largely on the species composition and the coexistence mechanisms developed by the plants. In a study by Dang et al. (2020) 71 , intercropping led to significant improvements in biometric and compositional traits of millet grain yield, number of ears per plant and their length, grain mass per plant and 1000 grain weight, with increases in grain yield of 5.6–20.7% in 2017, 7.9–53.9% in 2018 and 28.3–75.4% in 2019. Mung bean seed yield was lower in this cropping system due to the spatial structure of the millet crown. 72 Almond trees intercropped with mung bean had the highest vegetative growth performance, compared to growing almond trees alone. Intercropping of beans with almond trees had a significant effect on the yield and quality of snap beans contributing to enhanced pod parameters, i.e. length, diameter, fresh weight, dry weight, total yield, protein, fibre in both seasons. In a study by Yin and He (1997) 73 , 9-year-old paulownia trees led to a 23% reduction in wheat yields in a paulownia-wheat intercropping system in China. Similar results were obtained by Chirko et al. (1996) 74 , who proved that shading provided by 11-year-old paulownia trees in a paulownia-wheat intercropping system reduced yields by only 7%. However, the system had no effect on reducing the number of grains per square metre and of dry matter per 1000 grains. A study by Li et al. (2008) 75 showed that wheat yield was reduced by up to 50% in the paulownia-wheat intercropping system, and a similar reduction in wheat yield was also found in the walnut-wheat system with an 8 m spacing between tree rows. 76 Liu et al. (2013) 57 found that sugarcane yields in intercropping were significantly higher than in monoculture. Different results have been reported in the studies by Zhu et al. (2012) 33 and Shukla et al. (2019) 77 . A study by Zhu et al. (2012) 33 showed that 2-year-old mulberry trees did not have a significant effect on millet yield, but mulberry tree leaf production increased by 30%. Shukla et al. (2019) 77 found that yields of all crops tested in the agroforestry system were lower in shaded sites compared with sites with full light exposure. In our study, we found no statistically significant effect of intercropping on biometric traits of buckwheat or its yield. The buckwheat yield was decisively influenced by conditions that occurred in specific years of our research, with significantly better conditions for yield and development of this plant occurring in the 2022 season. The close dependence of buckwheat yield on weather conditions has been confirmed by other studies. 78 Pseudo-cereal plants, as well as buckwheat, can be infected by various species of pathogenic fungi, which affect the yield and deteriorate its quality. One of the most serious diseases of cereal plants is Fusarium wilt , which is dangerous as it generates mycotoxins. 79 , 80 The present study showed that fungi of the genus Fusarium colonised buckwheat roots most abundantly, regardless of the crop used. However, the study did not show symptoms characteristic of infestation by these fungi, such as wilting and withering of leaves or browning and rotting of roots. The predominant species were F. oxysporum considered to be part of a natural microflora colonising plant roots. 81 , 82 , 83 Some species may be potentially pathogenic, as are the few isolated species of F. culmorum and F. avenaceum . We should stress that in the second year of our study, we recorded a nearly 5-fold increase in Exserohilum pedicellatum on buckwheat roots in intercropping sample (AP) - an organism which can cause Exserohilum root rot. 84 , 85 Conclusions Our research indicates that, in general, the paulownia and buckwheat intercropping system had a positive effect on soil microbial properties, which provide a high-sensitivity indicator of soil quality. However, our results are inconclusive, necessitating more studies that would take into account long-term and lasting effects of intercropping. Nevertheless, our study, including both high-throughput metagenomic sequencing techniques of bacterial and fungal populations combined with traditional techniques for measuring microbial abundance and enzymatic activity, showed that the TBI system tested in temperate climates had a positive effect on the abundance, diversity and function of soil bacteria when compared to monocultures in arable fields, potentially contributing to the biological fertility of soil in these systems. Our study also indicated that there were greater changes in the abundance and diversity of bacterial than in fungal populations, depending on the cultivation method. This may suggest that the mycobiome is less sensitive to land use change and that it diversifies gradually. Our results also suggest that both the mycobiome and the TBI microbiome were abundant in terms of plant growth promoting microbes positively influencing plant growth and yields. Given the seasonal and annual trend of each parameter we analysed, temporal fluctuation is a key factor influencing soil biological properties. We have thus demonstrated that microorganisms have the ability to modulate their activity in response to changing nutrient conditions. Growing buckwheat in-between Paulownia tree rows did not result in a deterioration of the biometric and yield characteristics of this annual crop. Growing trees and crops in close spatial proximity allows for different interspecies interactions that can result in complementary resource use. Our study can provide a foundation for the development of innovative management strategies for the cultivation of trees for biomass energy production. Our aim has also been to provide scientific evidence in support of TBI systems implementation based on paulownia trees in temperate climates. Declarations Credit authorship contribution statement Woźniak Małgorzata: Data curation, Formal analysis, Investigation, Resources, Validation, Visualization, Software, Writing - original draft, Writing - review & editing, Supervision; Jama-Rodzeńska Anna: Data curation, Formal analysis, Investigation, Resources; Funding acquisition, Project administration, Writing - original draft, Writing - review & editing; Supervision; Gębarowska Elżbieta: Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Writing - original draft, Writing - review & editing; Liszewski Marek : Conceptualization, Data curation, Investigation, Resources, Methodology, Project administration, Resources, Supervision; Siebielec Sylwia: Resources, Writing - original draft; Kaczmarek-Pinczewska Agata : Data curation; Kucińska Jolanta: Data curation; Gałka Bernard: Formal analysis; Zalewski Dariusz: Formal analysis, Software; Bąbelewski Przemysław: Funding acquisition, Project administration, Investigation. Funding This work was supported by the Wrocław University of Environmental and Life Sciences (Poland) as part of the research project no N090/0008/2024 The APC/BPC is financed/co-financed by Wroclaw University of Environmental and Life Sciences and by the National Centrum of Science DEC-2022/06/X/ST10/00047. Declaration of competing interest The authors declare no competing interests. Data availability All data generated or analysed during this study are included in this published article. References Nair, P.K.R, Gordone, A.M, Mosquera-Losadac, M.R Agroforestry. Elsevier, Netherland, 101–110 (2008). Borek, R. Agroforestry Systems in Poland a preliminary identification. Papers on global change IGBP , 22 , 37–51. https://doi.org/10.1515/igbp-2015-0014 (2015). Liszewski M., Chorbiński P. The influence of foliar buckwheat fertilization with copper, manganese and iron on selected parameters of its nectar production and seed yield. Polish J. Agron . 46 , 23-30 (2021). 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The spatial and temporal effects of paulownia intercropping: The case of northern China, Agrofor. Sys. https://doi.org/ 10.1023/A:1005837729528 (1997). Chirko, C.P, Gold, M.A, Nguyen PV, Jiang, J.P. Influence of direction and distance from trees on wheat yield and photosynthetic photon density ( Q p ) in a Paulownia and wheat intercropping system. Agric Forest Meteorol . 83 , 171–180 (1996). Li, F., Meng, P., Fu, D., Wang, B.. Light distribution, photosynthetic rate and yield in a Paulownia-wheat intercropping system in China. Agrofor. Sys. 74 , 2, 163-172. https://doi.org/ 10.1007/s10457-008-9122-9 (2008). Qiao, X., Sai, L., Chen, X., Xue, L., Lei, J. Impact of fruit-tree shade intensity on the growth, yield, and quality of intercropped wheat. PLOS ONE 14(4), e0203238. https://doi.org/10.1371/journal.pone.0203238 (2019). Shukla, P. R., Skeg, J., Buendia, E. C., Masson-Delmotte, V., Pörtner, H. O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., van Diemen, R., Ferrat, M., Haughey, E., Luz, S., Neogi, S., Pathak, M., Petzold, J., Portugal Pereira, J., Vyas, P., Huntley, E., Kissick, K., Belkacemi, M. and Malley, J. Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. [Online] Available at: https://www.ipcc.ch/srccl/cite-report/.(2019). [Accessed 15th March 2022]. Liszewski M., Response of buckwheat to sowing dates and rates depending on soil and weather conditions. Zesz. Nauk AR Wrocław , 316 , 199-207 (1997). Munkvold, G. P.. Epidemiology of Fusarium diseases and their mycotoxins in maize ears. Eur. J. Plant Pathol. 109 , 705-713 (2003). Ma, L. J., Geiser, D. M., Proctor, R. H., Rooney, A. P., O'Donnell, K., Trail, F., Gardiner, D.M., Manners, J.M., Kazan, K. Fusarium pathogenomics. Annu. Rev. Microbiol . 67 , 399-416. https://doi.org 10.1146/annurev-micro-092412-155650 (2013). Rana, A., Sahgal, M., Johri, B. N.. Fusarium oxysporum: genomics, diversity and plant–host interaction. Develop. Fungal Biol. Applied Mycology , 159-199. https://doi.org/10.1007/978-981-10-4768-8_10 (2017). Edel-Hermann, V., Lecomte, C. Current status of Fusarium oxysporum formae speciales and races. Phytopathol. 109(4) , 512-530. https://doi.org/10.1094/PHYTO-08-18-0320-RVW (2019). Sajeena, A., Nair, D. S., Sreepavan, K. Non-pathogenic Fusrium oxysporum as a biocontrol agent. Indian Phytopathol . 73 , 2, 1-7. https://doi.org/10.1007/s42360-020-00226-x (2020). Özer, G., Göre, M. E., Alkan, M., Yaman, T., Dababat, A. A. First report of Exserohilum pedicellatum causing root rot of wheat in Azerbaijan. Plant Disease , 103 ,6, 1416-1416. https://doi.org/10.1094/PDIS-09-18-1678-PDN (2019). Özer, G., Paulitz, T. C., Imren, M., Alkan, M., Muminjanov, H., Dababat, A. A. Identity and pathogenicity of fungi associated with crown and root rot of dryland winter wheat in Azerbaijan. Plant Disease , 104, 8, 2149-2157. https://doi.org/10.1094/PDIS-08-19-1799-RE (2020). Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.doc 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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12:06:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4611632/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4611632/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60422060,"identity":"76544a21-b342-4655-a621-6454c1df43ba","added_by":"auto","created_at":"2024-07-16 14:56:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118752,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative abundance of bacteria at the phylum level\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/5ea512a44e99d324b1ccc724.png"},{"id":60422058,"identity":"1e4b929e-2a45-4a51-87b3-c12603629d52","added_by":"auto","created_at":"2024-07-16 14:56:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86556,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative abundance of fungi at the phylum level\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/12881b82cea5f1d893d9aef3.png"},{"id":60422609,"identity":"5c2b5629-3590-43bc-bb41-c1ed824ae35f","added_by":"auto","created_at":"2024-07-16 15:04:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":207278,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial community heatmap of top 15 bacteria on the general level. Different colors represent relative abundance of bacteria (%). Red means higher relative abundance, whereas green means lower relative abundance\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/de8b8effa6008c51b2566b1b.png"},{"id":60422063,"identity":"df248f25-8fb4-49c6-b31a-22dfc6fda2c0","added_by":"auto","created_at":"2024-07-16 14:56:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":192978,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial community heatmap of top 15 fungi on the genera level. Different colors represent the relative abundance of fungi (%). Red means higher relative abundance, whereas green means lower relative abundance.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/23660810c4dafc5ca369f106.png"},{"id":60422062,"identity":"37f72f76-7011-4460-8678-64a4835096bf","added_by":"auto","created_at":"2024-07-16 14:56:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":51131,"visible":true,"origin":"","legend":"\u003cp\u003eBiplot diagram of principal components analysis (PCA), describing the microbial properties of soil samples collected from different cultivation sites (monoculture AK and intercropping AP), year (2021 and 2022) and sampling period (T1 and T2)\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/8b6193eadd0be2f109d4b7d8.png"},{"id":70201858,"identity":"2e0d52ca-d57b-4e6c-b0ac-fd599b29a8e3","added_by":"auto","created_at":"2024-11-29 12:39:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2140385,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/7f3f68aa-ce09-44b2-b0a2-e8be55e9db61.pdf"},{"id":60422061,"identity":"e650072e-155e-4477-9a16-033d62da3749","added_by":"auto","created_at":"2024-07-16 14:56:53","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36864,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.doc","url":"https://assets-eu.researchsquare.com/files/rs-4611632/v1/b507a2a27f9bea34a8a01016.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of intercropping of paulownia and buckwheat on soil microbial biodiversity and enzymatic activity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIntercropping of trees and cultivated annuals, i.e. the integration of trees into the agricultural landscape in the form of tree-based intercropping systems (TBI), is part of a system called agroforestry, which involves cultivation of forest trees and shrubs alongside agro- and zootechnical activities within the same land area. Agroforestry constitutes a system that ensures continuous supply of organic material to the soil. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe development of agroforestry systems seems particularly relevant in the context of the following: counteracting negative effects of climate change, water and wind erosion of the soil, leaching of nutrients and plant protection products from the soil, loss of biodiversity, large areas of marginal agricultural land, increasing demand for bioenergy and organic products.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBuckwheat (\u003cem\u003eFagopyrum esculentum\u003c/em\u003e Moench) is a crop that is in high demand around the world for its nutritional, economic and pharmaceutical qualities. To ensure food and nutrition security in a global climate change scenario, this pseudo-cereal is a competent alternative to staple crops (rice, wheat, rice and maize). Buckwheat also has favorable agroecological traits, such as: enabling weed control due to inhibitory effect of root secretions on the development of couch grass (allelopathy), effective protection of the soil against water erosion, high capacity to assimilate nitrogen and phosphorus from the soil, phytosanitary effect on the soil through effective control of nematodes (reduction of potato cyst nematode populations), and benefitting insects during flowering.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003ePaulownia\u003c/em\u003e ssp. is a type of fast-growing deciduous tree with high tolerance to variable soil and climatic conditions and low water requirements.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e \u003cem\u003ePaulownia\u003c/em\u003e Clon in Vitro 112 is a tree developed under laboratory conditions by crossing and cloning two species of \u003cem\u003ePaulownia elongata\u003c/em\u003e and \u003cem\u003eP. fortunei\u003c/em\u003e. The hybrid is considered suitable for biomass production and revegetation. \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Furthermore, Valdivia et al. (2012)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e found that trees of the genus \u003cem\u003ePaulownia\u003c/em\u003e ssp. have an advantage over most other tree species in that they have a sparse canopy with late foliage and leaf drop, thus not blocking sun rays reaching the fields during the periods where many commonly grown crops, including cereals require sunlight most. Intercropping of trees and annuals expands the agroecosystem's biodiversity, promoting biological life in the soil.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e According to research, the diversity of soil microorganisms is higher within agroforestry systems.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Knowledge about both activity and diversity of soil microorganisms enables researchers to assess the state of the soil, which is beneficial for agriculture and ecology. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e A diverse soil microbial community is crucial to the productivity of any agroecosystem. They are thus a high-sensitivity indicator of changes to soil organic matter. Even modest decreases in microbial abundance can be detrimental to the soil ecosystem\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, as soil microorganisms are responsible for various biogeochemical processes, are involved in the mineralisation of organic matter and responsible for nutrient cycling in the environment. Moreover, microorganisms one of the principal sources of soil enzymes, which act as mediators and biological catalysts for various soil functions, such as organic matter breakdown, release of inorganic nutrients (C, N, P, S) for plant growth, nitrogen fixation, nitrification, denitrification, detoxification of xenobiotics, stabilisation of soil structure and others.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eEnzyme-related activity in the soil is one of the biological properties used as an indicator of soil quality, due to its interrelationship with soil biology. In addition, it is a highly sensitive and easily measured indicator of soil biological management, microbial activity, soil fertilisation, degree of pollution and anthropopressure. Dehydrogenases (DHGs) are one of the key components of the soil enzyme testing as they determine the correct sequence of all biochemical pathways occurring in the soil.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDetermining the relationship between the soil humus layer and the microbiome has been possible through advances in sequencing technologies. \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Metagenomics is a particularly useful tool for understanding microbe-soil-plant relationships and visualising patterns of microbial co-occurrence. \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Furthermore, it simultaneously examines all microorganisms present in a soil sample, combining methods of traditional microbiology with molecular biology and bioinformatics. The diversity of bacteria and fungi is a major driver of fundamental metabolic processes in a dynamic environment such as soil. It is thus important to explore the biodiversity of the soil environment in order to develop management strategies for terrestrial ecosystems to maintain their integrity, function and long-term stability. Metagenomics results can also be used to identify key microbial taxa \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e having significant impact on the soil community. \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur study aimed to establish the feasibility of growing paulownia and buckwheat in the same field (buckwheat grown in inter-rows between the trees) and to capture changes in the soil environment in terms of its microbiology. Our findings stem from research spanning a two-year cycle and should be considered a contribution towards follow-up long-term field studies. This research is particularly vital in the context of efforts to maintain biological balance and protect soil biodiversity. It can also serve as a basis for the development of innovative crop management strategies for energy biomass production and annual crops, contributing towards strategies that are best adapted to the existing species in terms of mitigating negative effects of climate change. The present study can thus provide insights into the key processes of microbial diversity enhancement in ecosystems for sustainable agriculture.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eStudy Sites and Soil Sampling\u003c/p\u003e \u003cp\u003eIn 2019, a rigorous field experiment using the randomised block method with buckwheat (\u003cem\u003eFagopyrum esculentum\u003c/em\u003e Moench) and paulownia (Clon in Vitro 112; \u003cem\u003eP. elongata\u003c/em\u003e \u0026times; \u003cem\u003eP. fortunei\u003c/em\u003e) was set up at the Research and Teaching Station of the Wrocław University of Environmental and Life Sciences (51\u0026deg;07\u0026prime;00\u0026Prime;N; 17\u0026deg;10E, 121 meters above sea level). The factor tested was the intercropping of buckwheat between paulownia (AP) trees. The experiment also included control sites (AK), i.e. buckwheat plots grown without paulownia, and consisted of 5 replications. Paulownia seedlings were planted on 30.05.2019. In spring 19.05.2020, we carried our technical pruning, where we established the main shoot (future trunk). Buckwheat (Kora cultivar) was sown on 11.05.2021, 04.05.2022 at a density of 250 seeds per square meter. The area of the buckwheat plot was 30 square metres. The trees were planted in rows of 5. In the plot, the row spacing was 5 meters and tree-to-tree spacing was 4 meters. The tree density was typical for growing paulownia for round wood. For microbiological and enzyme analyses, we sampled soil from the rhizosphere of buckwheat grown without paulownia (AK) and from buckwheat grown in inter row with paulownia (AP). Soil was sampled twice before buckwheat sowing (T1) and at the buckwheat flowering stage (T2) in the first (2021) and second (2022) years of the study. Soil samples for analysis of each cultivation variant were taken from 5 replicates.\u003c/p\u003e \u003cp\u003eChemical-physical soil analysis\u003c/p\u003e \u003cp\u003eThe rigorous field experiment was based on soil class fied as humic ordinary alluvial soils Polish Soil Classification (SGP6) or Eutric Fluvisols ( Humic), IUSS Working Group WRB, 2022). According to agricultural evaluation, the soil was identified in F \u0026ndash; IV b-a class (moderately poor). \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Soil samples for bioavailable forms of macronutrients (P, K, Mg) and mineral nitrogen content analysis were sourced before sowing buckwheat and after the end of vegetation from several randomly selected locations in the field, separately for each site to obtain an average sample. Soil samples were sources from the 0\u0026ndash;30 cm layer using soil sampler tool, air-dried, ground using a porcelain pestle and mortar, and sieved to \u0026lt;\u0026thinsp;2 mm. A portion of each sample was then finely ground for analysis. Soil testing included: determination of basic soil characteristics and properties, such as soil morphology, soil classification, land use value, pH, macronutrient content, including mineral nitrogen.\u003c/p\u003e \u003cp\u003eWe carried out characterisation of the following soil properties:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003econtent of bioavailable forms of P, K - assessed using the Egner-Riehm (DL) method;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003esoil Ca content - using Sheibler method;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eavailable magnesium content - using Schachtschabel method;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003epH in distilled water and in 1M KCl - using potentiometric pH metres;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003enitrogen content using the modified Kjehdal method (total nitrogen determination);\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe soil pH and microelement content of the soil is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The soil pH in both the intercropped site and the control site was slightly acidic in both years of the study. Phosphorus and potassium contents on both sites were very high in the year the experiment started. At the end of the 2022 season, the potassium content was found to be reduced to \u0026lsquo;medium\u0026rsquo; for the intercropping variant and for phosphorus to \u0026lsquo;high\u0026rsquo; for this site. In terms of magnesium content - it was very high in the soil in both sites in the year the experiment started, while by the end of 2022 it had decreased to medium on both sites (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Over time, the mineral nitrogen content in the soil, decreased under intercropping of paulownia and buckwheat, while the monoculture cultivation of buckwheat contributed to an increase in mineral nitrogen content in the 30 cm-deep soil layer.\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 pH and macroelement content of the soil profile (0\u0026ndash;30 cm) in 2019 and 2022.\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDetailed determination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAP\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\u003epH in KCl (soil pH)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003cp\u003e(slightly acidic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003cp\u003e(slightly acidic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003cp\u003e(slightly acidic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003cp\u003e(slightly acidic)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhosphorus P\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO\u003c/b\u003e\u003csub\u003e\u003cb\u003e5 \u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg 100 g\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eof soil)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.5\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003cp\u003e(high)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePotassium K\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO \u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg 100 g\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eof soil)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003cp\u003e(medium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMagnesium Mg \u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg 100 g\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eof soil)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003cp\u003e(very high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003cp\u003e(medium)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003cp\u003e(medium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN min. (kg ha\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003cp\u003e(very low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003cp\u003e(very low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.8\u003c/p\u003e \u003cp\u003e(low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003cp\u003e(very low)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAP - intercropping, AK \u0026ndash; control, N min. \u0026ndash; mineral nitrogen\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Soil pH and macroelement content of the soil profile (0\u0026ndash;30 cm) in 2019 and 2022.\u003c/p\u003e \u003cp\u003eAgrotechnology of the experiment\u003c/p\u003e \u003cp\u003ePrior to starting the experiment, following the 2018 winter triticale harvest, the field was ploughed with a subsoiler plough and then the soil was kept in a weed-free state using a cultivating unit (rotary harrow with crushing roller). In autumn, deep pre-winter ploughing was carried out to a depth of 25 cm. In the year we started our experiment, i.e. spring 2019, the soil was ploughed again using a subsoiler plough and further amended using a cultivating unit. After planting the paulownia seedlings, the soil in the interrows was loosened with a rotary harrow. The following year, in the spring of 2020, the soil was ploughed shallow and then was amended using a cultivator before sowing buckwheat. Following technical tree pruning in May 2020, the paths in the experiment were mechanically tended. After harvesting the buckwheat with a plot harvester, the soil was kept weed-free by harrowing (rotary harrow). In 2021, a cultivating unit equipped with a string roller was used to cultivate the soil after winter. By May 2021, harrowing had been carried out twice as a weed control measure. After sowing the buckwheat, the paths were mechanically cultivated several times until harvesting using combine harvester. Before winter, the soil was kept weed-free by harrowing with a rotary harrow. Tillage in 2022 included harrowing the field after winter with a cultivator, followed by ploughing with a subsoiler plough to a depth of 12 cm. Before sowing buckwheat, the soil was treated with a cultivating unit consisting of a rotary harrow and a crushing roller. The sowing of buckwheat was done with a plot seeder. Paths between the plots were tended during the growing season. No mineral or organic fertilisers or any pesticides were used in the experiment.\u003c/p\u003e \u003cp\u003eWeather conditions\u003c/p\u003e \u003cp\u003eAs part of the experimental design, we took into account meteorological data on the weather during the experimental period (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Meteorological conditions were analysed using data provided by the meteorological station (AsterMet) in Swojczyce (Wrocław). We used Selyaninov's hydrothermal coefficient (HTC) to describe the impact of weather conditions on the plant development, using the following formula:\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\u003eWeather conditions and HTC in 2019\u0026ndash;2022 provided by the meteorological station (AsterMet) in Swojczyce (Wrocław).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"18\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMonth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c13\" namest=\"c8\"\u003e \u003cp\u003eRainfall (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003eHTC (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c18\" namest=\"c18\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003cp\u003e1990 \u0026minus;\u0026thinsp;2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003cp\u003e1990 \u0026minus;\u0026thinsp;2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e2022\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\u003eIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e32.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e14.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e76.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e59.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e58.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e17.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e94.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e39.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e74.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e19.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e44.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e41.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e132.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e86.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVIII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e19.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e59.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e92.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e63.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIX\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e14.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e92.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e82.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e50.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eX\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e32.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e40.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e/ sum\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(IV-X)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e14.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e306.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e430.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e206.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e408.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e377.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eK\u0026thinsp;=\u0026thinsp;P / (0.1\u0026times;T)\u003c/h2\u003e \u003cp\u003ewhere: K \u0026ndash; Selyaninov's hydrothermal coefficient, P \u0026ndash; total rainfall per month, T \u0026ndash; sum of daily average temperatures per month\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Weather conditions and HTC in 2019\u0026ndash;2022 provided by the meteorological station (AsterMet) in Swojczyce (Wrocław).\u003c/p\u003e \u003cp\u003eCharacterization of soil microbiological properties\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction, PCR and Illumina amplicon sequencing\u003c/h2\u003e \u003cp\u003eTotal DNA for metagenomic analysis was extracted from the soil samples using the PowerSoil\u0026reg; DNA Isolation Kit (MO BIO) according to the manufacturer\u0026rsquo;s instructions. The extracted genomic DNA was quantified and checked for quality at A\u003csub\u003e260/280nm\u003c/sub\u003e (1.7\u0026ndash;2.0) and diluted in sterile water to 10 ng \u0026micro;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Meta-barcoding analysis of the microbial community was performed based on the variable regions: V3 - V4 of the 16S rRNA gene for bacteria and hypervariable region of ITS1 for fungi. Specific primer sequences 341F and 785R (16S analysis); ITS1FI2 and 5.8S (ITS1 analysis) were used to amplify the selected region and prepare the library. PCR was performed using Q5 Hot Start High-Fidelity 2X Master Mix, reaction conditions according to manufacturer\u0026rsquo;s recommendations. Next \u0026ndash; generation sequencing was performed by Genomed S.A. (Warsaw, Poland) on a MiSeq sequencers (Illumina, San Diego, CA, USA) in paired-end (PE) technology, 2 \u0026times; 300 nt, using the Illumina v 3 kit (San Diego, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic analysis\u003c/h2\u003e \u003cp\u003eBioinformatics analysis ensuring the classification of reads was carried out with the QIIME 2 software package based on the reference sequence database Silva 138 (for bacteria) and UNITE v8.2 (for fungi). The DADA2 package was also used, which allowed for the specification of sequences of biological origin from those newly created in the sequencing process. This package was also used to isolate unique sequences of biological origin, i.e. ASV (amplicon sequence variant). The analysis consisted of the following stages: reading quality control, initial data processing using the Cutadapt tool, selecting unique ASV and OTU (operational taxonomic units) sequences and assigning taxonomies to the generated sequences based on reference databases. In addition, α-diversity indices (Shannon diversity H\u0026prime;, Simpson index D and observed AVS/OTU) were assessed from the Illumina MiSeq results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eQuantification of Cultivable Bacteria and Fungi\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn order to determine the colony-forming units of bacteria and fungi in the test soils (AK, AP, T1 and T2), we did surface culture combined with the technique of successive dilutions on medium developed by Bunt and Rovira\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and Martin\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e \u003csub\u003e,\u003c/sub\u003erespectively. Analyses were performed in 3 average samples taken from each test plot. Results are presented in units forming colonies in 1 g of soil (CFU \u0026times; g\u003csup\u003e-1\u003c/sup\u003e). Actual results were subject to three-way analysis of variance (ANOVA) with post-hoc Tukey HSD test.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSoil dehydrogenase activity (DHA) and T-GRSP concentration\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDehydrogenase activity (DHA) was analysed according to PN-ISO 23753-1 (2008) using 2,3,5-triphenyltetrazolium chloride (TTC), reduced via enzymatic activity to triphenylformazan (TPF). We added 5 mL of a 3% solution of TTC (Merck, Germany) to the soil using 1:1 ratio (g:mL), mixed them thoroughly and incubated at 25\u0026deg;C for 16 h. The released triphenylformazane (TPF, Merck, Germany) was extracted using methanol and spectrophotometrically analysed (Ray Leight, VIS 723G) at 485 nm. The control sample was soil without added TTC. The amount of TPF released was expressed as microgram per gram of dry soil per hour.\u003c/p\u003e \u003cp\u003eTotal glomalin-related soil proteins (T-GRSP) were also determined and extracted from soil samples using the method developed by Wright and Upadhyay (1999)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e including our alterations. Soil samples (10 g) were flooded with 0.05M citrate buffer, pH 8.0, and autoclaved at 121\u0026deg;C for 60 min. The extraction was repeated several times until the organic fraction was completely eluted from the soil. Following each autoclaving, the supernatant containing T-GRSP was poured off and centrifuged at 10 000 rpm for 10 min. Soil samples were covered with sterile buffer and autoclaved again. The extracts, collected after each heating and centrifugation, were combined, and stored at 4\u0026deg;C until analysis. T-GRSP content in the supernatants was quantified via the Bradford method using bovine serum albumin (Sigma-Aldrich, Inc., Saint Louis, USA) as a standard.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal component analysis of soil microbial properties\u003c/h2\u003e \u003cp\u003eWe performed PCA multivariate statistical analysis of the tested soil samples\u0026rsquo; variability to determine the relation among the measured activities. Mean values from three replicates were used for PCA analysis. Data were standardized prior to the analysis. All statistical analyses were performed using Statistica 13.1 software (StatSoft, Inc., Tulsa, OK, USA).\u003c/p\u003e \u003cp\u003eColonisation of buckwheat roots by filamentous fungi\u003c/p\u003e \u003cp\u003eWe assessed the degree of colonisation of buckwheat roots by potential pathogenic fungi. Filamentous fungi were isolated from buckwheat roots collected at flowering (T2) and their genus and/or species were established based on their morphological characteristics. \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e For this purpose, root sections that had been previously disinfected with 0.5% NaOCl (for 15 min, rinsed 4 times with sterile distilled water) were plated on PDA medium (BTL, Ł\u0026oacute;dź) supplemented with streptomycin (30 \u0026micro;g mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The plates were incubated at 28\u0026deg;C for 72 h. The fungi were then reisolated onto PDA medium. Ten replicates (60 inoculations each) were performed from each sample. Results are presented as percentage of root colonisation by fungi.\u003c/p\u003e \u003cp\u003eAnalysis of buckwheat biometric traits and the yield\u003c/p\u003e \u003cp\u003eBefore harvesting the buckwheat, we randomly sampled 10 plants from each plot. The samples were sourced from the middle rows to mitigate the border effect. The biometric analysis included: plant height, number of branches, number of twigs, number of inflorescences, number of kernels and weight of full kernels per plant. The yield per plot was adjusted to 15% moisture content and converted to tonnes per hectare. To assess the effect of cultivation method and time by years of study, we performed a two-factor ANOVA analysis using Statistica 13.1. When differences between means were found to be significant, they were compared using the HSD-Tukey test, with a significance level of α\u0026thinsp;=\u0026thinsp;0.05. Actual DHA and T-GRSP results were subject to a three-way analysis of variance (ANOVA) with post-hoc Tukey HSD test. Homogenous groups has been established from largest to the smallest.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eCharacterization of soil microbiological properties\u003c/p\u003e\n\u003ch3\u003eDiversity and structure of microbiome and mycobiome\u003c/h3\u003e\n\u003cp\u003eThe results obtained using the NGS analysis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) showed variability in the bacterial population in the plant root zone between the test plots and the reference plots, as shown by the Shannon (H') and Simpson (D) indices. The highest Shannon index value was obtained in soil samples sourced on the first sampling date (T1) for the AP combination in 2021. A similar relationship was established for soil samples collected in 2022, when the highest Shannon index value was obtained for T1 sampling and for the AP combination. Simpson's index was less differentiated, though once again the highest index value was observed in 2021 for the samples sourced on the first date (T1) for the AP combination. The lowest diversity indices values (both Simpson's and Shannon's) were found in samples collected in 2022 for the AK combination on the second date, or during the second soil sampling campaign (T2). The index valued calculated for fungi based on NGS analysis also showed variability in fungal populations between cropping systems. The AP variant resulted in the highest Shannon index value in samples collected in 2022 on the first date (T1), but the index also showed seasonal dynamics. Furthermore, the Shannon index values were lower in the AP plots when compared to the AK plots on all other sampling dates. The richness of the observed AVS for bacterial populations was higher in soil samples collected from paulownia and buckwheat intercropping variant compared to the control samples, on all sampling dates. However, a different relationship was observed for fungal populations.\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\u003eEstimation of alpha diversity index and richness (number of AVSs and OTUs of bacterial and fungal microbiomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eBACTERIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eFUNGI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShannon Diversity Index (H\u0026rsquo;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSimpson\u0026rsquo;s Index (D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eObserved AVSs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eShannon Diversity Index (H\u0026rsquo;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSimpson\u0026rsquo;s Index (D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eObserved OTUs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e2022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAP \u0026ndash; intercropping; AK \u0026ndash; control; T1, T2 \u0026ndash; the first and second soil sampling date; AVS \u0026ndash; Amplicon Sequencing Variants; OUT - Operational Taxonomic Units\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Estimation of alpha diversity index and richness (number of AVSs and OTUs of bacterial and fungal microbiomes.\u003c/p\u003e \u003cp\u003eNine bacterial phyla proved to be most prevalent in the rhizosphere soil samples: Actinobacteriota, Proteobacteria, Chloroflexi, Gemmatimonadota, Bacteroidota, Firmicutes, Myxococcota, Verrucomicrobiota and Planctomycetota. Other phyla usually did not exceed 5% relative abundance (Fig.\u0026nbsp;1). In all combinations under study, the largest group was the Actinomycetes, up to 45% (2022/T2/AK). Proteobacteria were also a significant group in all combinations (about 20\u0026ndash;30%, depending on the combination). Samples collected in 2021 had lower relative abundance of Actinobacteria based on 16S rRNA gene fragment sequencing analysis for bacteria compared to samples from the 2022 collection in all combinations. 16S rRNA sequencing also showed that the intercropping variant in the 2022 collection samples had no effect on Proteobacteria, regardless of sampling date. In contrast, for the 2021 samples, we noted an increase in this population for the intercropping (AP) samples collected at the first sampling time compared to the AK combination. We observed no such difference at the second sampling date (T2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1\u003c/b\u003e. The relative abundance of bacteria at the phylum level\u003c/p\u003e \u003cp\u003eThe dominant fungi included four phyla: Ascomycota, Basidiomycota, Mortierellomycota, Mucoromycota. Unclassified fungi also formed a significant part of the population (Fig.\u0026nbsp;2). In all combinations studied, Ascomycota were the largest group, accounting for up to about 65% (2022/T2/AK). Relative abundance of Ascomycota was lowest in 2021 samples collected from AP at T2. In 2022, Ascomycota were slightly lower in AP than in AK on both sampling dates. Analysing different variants in the plot experiment, we noted that in 2021 the Basidiomycota phylum was the least abundant in AP in the first sampling (T1) compared to the other variants and sampling dates. In contrast, the Mortierellomycota phylum was most abundant in the 2022 samples collected on the first sampling date (T1) for the AK combination. The Mucoromycota phylum was much less abundant than the other three main fungal phyla, but its proportion increased significantly in the AP variant in the second sampling of 2022 (T2). The largest group of unclassified fungi was observed in the soil samples collected in 2021 on the second sampling date (T2) in AP (approximately 30% of the total population of the sample).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2.\u003c/b\u003e The relative abundance of fungi at the phylum level\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3.\u003c/b\u003e Microbial community heatmap of top 15 bacteria on the general level. Different colors represent relative abundance of bacteria (%). Red means higher relative abundance, whereas green means lower relative abundance\u003c/p\u003e \u003cp\u003eThe top 15 genera in bacteria communities under study are presented in Fig.\u0026nbsp;3. Sequences assigned to \u003cem\u003eNocardioides\u003c/em\u003e were most abundant in all communities throughout the experiment, accounting for 2.10% \u0026minus;\u0026thinsp;6.23% of the total high-quality sequences. \u003cem\u003eCandidatus_Solibacter\u003c/em\u003e was one of the dominant genus (2,43% relative abundance) in control sample sourced on T1 2022. \u003cem\u003ePseudarthrobacter\u003c/em\u003e was abundant in AP T2 2021 and AP T2 2022 samples, as well as in both T2 2022 samples, whereas \u003cem\u003eStreptomyces\u003c/em\u003e was characteristic for the rhizosphere microbiomes in T2 2022 samples.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 4.\u003c/b\u003e Microbial community heatmap of top 15 fungi on the genera level. Different colors represent the relative abundance of fungi (%). Red means higher relative abundance, whereas green means lower relative abundance.\u003c/p\u003e \u003cp\u003eHeatmap analysis of relative abundances of the most abundant genera showed clear differences in the fungal community structures between all samples (Fig.\u0026nbsp;4). Genera whose abundance were above 2% in all samples were: \u003cem\u003eExophiala\u003c/em\u003e, \u003cem\u003eFusarium\u003c/em\u003e and \u003cem\u003eMortierella\u003c/em\u003e. We wish to highlight that \u003cem\u003eMortierella\u003c/em\u003e was the dominant genus, accounting for 9.69% \u0026minus;\u0026thinsp;23.56% of the total high-quality sequences. \u003cem\u003eBotryotinia\u003c/em\u003e was abundant in AK T1 2021 sample, whereas genus \u003cem\u003ePenicillium\u003c/em\u003e in AK T2 2022 sample.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eQuantification of Cultivable Bacteria and Fungi\u003c/h2\u003e \u003cp\u003eBacterial counts ranged from 2.4 \u0026times;10\u003csup\u003e4\u003c/sup\u003e to 2.1 \u0026times;10\u003csup\u003e6\u003c/sup\u003e CFU in 1 g of soil, and fungal counts ranged from 1.0 to 5.0 \u0026times;10\u003csup\u003e4\u003c/sup\u003e CFU in 1 g of soil (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Compared to the control, intercropping (AP) did not significantly affect the number of bacteria and fungi, both in the first and second year of the study. However, the number of CFUs was influenced by the sampling date and the year of the study. It is noteworthy that at both T1 and T2 for both cultivation methods, a significant increase in bacterial counts was observed in the second year of the study compared to 2021. In 2021, fungal CFU counts presented no statistically significant differences between the control sample and the soil sample where buckwheat was grown with paulownia on both sampling dates. In contrast, there was a statistically significant increase in the number of fungal CFUs on T2 in 2022 compared to the previous year (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003eTotal abundances of bacteria and fungi in the field experiment.\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal bacterial count\u003c/p\u003e \u003cp\u003e(CFU g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal fungal count\u003c/p\u003e \u003cp\u003e(CFU g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u0026times;10\u003csup\u003e4\u003c/sup\u003e c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.8\u0026times;10\u003csup\u003e4\u003c/sup\u003e abc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u0026times;10\u003csup\u003e4\u003c/sup\u003e c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.3\u0026times;10\u003csup\u003e4\u003c/sup\u003e abc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u0026times;10\u003csup\u003e6\u003c/sup\u003e ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u0026times;10\u003csup\u003e4\u003c/sup\u003e cd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u0026times;10\u003csup\u003e6\u003c/sup\u003e b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0\u0026times;10\u003csup\u003e4\u003c/sup\u003e d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u0026times;10\u003csup\u003e6\u003c/sup\u003e ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8\u0026times;10\u003csup\u003e4\u003c/sup\u003e bcd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u0026times;10\u003csup\u003e6\u003c/sup\u003e ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u0026times;10\u003csup\u003e4\u003c/sup\u003e cd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u0026times;10\u003csup\u003e6\u003c/sup\u003e ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.0\u0026times;10\u003csup\u003e4\u003c/sup\u003e a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u0026times;10\u003csup\u003e6\u003c/sup\u003e a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.8\u0026times;10\u003csup\u003e4\u003c/sup\u003e ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAK \u0026ndash; control site; AP \u0026ndash; intercropping; T1, T2 \u0026ndash; the first and second soil sampling date; Values are the mean of four replicates of each sample. Values followed by different letters in columns indicate significant differences according to three-way ANOVA with post-hoc Tukey HSD test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Total abundances of bacteria and fungi in the field experiment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSoil biological activity\u003c/h2\u003e \u003cp\u003eSoil biological activity was determined in the soil samples based on dehydrogenase activity (DHA) and total glomalin concentration (T-GRSP). The results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\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\u003eDehydrogenase activity (DHA) and total glomalin concentration (T-GRSP) in the air-dried soil.\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDHA\u003c/p\u003e \u003cp\u003e(\u0026micro;g TPF g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal GRSP\u003c/p\u003e \u003cp\u003e(\u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1699.0 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.9 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1522.9 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1492.1 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1533.2 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1460.2 ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.8 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1471.6 ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1088.0 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1233.2 bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAK \u0026ndash; control site; AP \u0026ndash; intercropping; T1, T2 \u0026ndash; the first and second soil sampling dates; DHA \u0026ndash; dehydrogenase activity expressed as the amount of released \u0026micro;g triphenylformazan (TPF) per hour per gram of soil; GRSP \u0026ndash; glomalin-related soil protein content per gram of air-dried soil. Values followed by different letters in columns indicate significant differences according to three-way ANOVA with post-hoc Tukey HSD test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Dehydrogenase activity (DHA) and total glomalin concentration (T-GRSP) in the air-dried soil.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003eS. Summary of three-way analysis of variance (ANOVA) results testing the effects of cultivation (monoculture and intercropping), year (2021 and 2022), and sampling periods (T1 and T2) on total bacterial count, total fungal count, dehydrogenase activity and T-GRSP. Data shown represent F-value and significance levels for each factor and interaction.\u003c/p\u003e \u003cp\u003eDehydrogenase activity in the intercropping (AP) and control (AK) samples ranged from 2.0 to 12.8 \u0026micro;g TPF g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Dehydrogenase activity was higher in the intercropping samples compared to the control, but statistically significant differences were observed for the first sampling date (T1). The highest DHA activity was observed in the intercropping samples in 2022 from the first sampling date (AP, T1). At the flowering stage of buckwheat (T2), enzyme activity decreased regardless of the cultivation method.\u003c/p\u003e \u003cp\u003eThe T-GRSP concentration ranged from 1039.2 to 1699.0 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The concentration of glomalin depended on the sampling date and not on the cultivation method. The highest concentration of T-GRSP was found in 2021 in the control sample (AK) from the first sampling date (T1). The following year, T-GRSP concentrations decreased compared to those in samples sourced on the first sampling date (T1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal component analysis (PCA)\u003c/h2\u003e \u003cp\u003eThe relationships in all soil samples and their properties were assessed using principal components analysis (PCA) (Fig.\u0026nbsp;5). The first two principal components (PCs) accounted for 44.27% and 25.04% of the total variance of the tested samples. The analysis showed that the 2021 samples clustered based on the sampling year, while sampling date proved to be differentiating factor for the 2022 samples.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 5\u003c/b\u003e. Biplot diagram of principal components analysis (PCA), describing the microbial properties of soil samples collected from different cultivation sites (monoculture AK and intercropping AP), year (2021 and 2022) and sampling period (T1 and T2)\u003c/p\u003e \u003cp\u003eBuckwheat root colonization by fungi\u003c/p\u003e \u003cp\u003eWe assessed the degree of colonisation of buckwheat roots by potentially pathogenic fungi. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the percentage of fungi on buckwheat roots at flowering (T2). Buckwheat roots in both the first and the second year of the study were most abundantly colonised by fungi of the genus \u003cem\u003eFusarium\u003c/em\u003e. The most abundant species we isolated were \u003cem\u003eF. oxysporum\u003c/em\u003e, accounting for 54 to 67% of the total number of fungi. We also isolated the potentially pathogenic species \u003cem\u003eF. culmorum\u003c/em\u003e and \u003cem\u003eF. avenaceum\u003c/em\u003e (between 4 and 10%). In both the first and second year of the study, buckwheat roots were colonised by saprotrophs of the genus \u003cem\u003eTrichoderma\u003c/em\u003e ranging from 3 to 20%. However, their number decreased in the second year of the study to 8% in the intercropping sample and to 3% compared to the control crop. In the first year of the study, \u003cem\u003ePenicillium notatum\u003c/em\u003e fungi were recorded in the intercropping sample (13%). An increased percentage of \u003cem\u003eExserohilum pedicellatum\u003c/em\u003e (from 2 to 10%) was also found on buckwheat roots in the 2022 crop year. Other potentially pathogenic fungi such as \u003cem\u003eF. solani\u003c/em\u003e, \u003cem\u003eRhizoctonia solani\u003c/em\u003e, \u003cem\u003ePhoma\u003c/em\u003e spp. or \u003cem\u003ePythium\u003c/em\u003e spp. colonised buckwheat roots sporadically (\u0026lt;\u0026thinsp;1%) in both AK and AP crops.\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\u003ePercentage of filamentous fungi isolated from buckwheat roots by culture method.\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFungi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAP\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\u003eColletotrichum\u003c/b\u003e \u003cb\u003esp.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCylindrocarpon\u003c/b\u003e \u003cb\u003esp.\u003c/b\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\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExserohilum pedicellatum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\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\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFusarium avenaceum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFusarium culmorum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\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\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFusarium oxysporum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFusarium solani\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFusarium sporotrichoides\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMucor mucedo\u003c/b\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\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePenicillium notatum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePenicillium purpurogeum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePenicillium vermiculatum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePenicillium\u003c/b\u003e \u003cb\u003esp.\u003c/b\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\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhoma\u003c/b\u003e \u003cb\u003esp.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePythium\u003c/b\u003e \u003cb\u003esp.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRhizoctonia solani\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRhizopus nigricans\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrichoderma hamatum\u003c/b\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\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrichoderma harzianum\u003c/b\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\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrichoderma viride\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther fungi\u003c/b\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\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAP \u0026ndash; intercropping; AK \u0026ndash; control; T1 and T2 \u0026ndash; the first and second buckwheat roots sampling date; symbol \u0026bdquo;\u0026ndash; \u0026rdquo; indicates that no fungi were isolated from the sample\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Percentage of filamentous fungi isolated from buckwheat roots by culture method.\u003c/p\u003e \u003cp\u003eBiometric traits and yield of buckwheat\u003c/p\u003e \u003cp\u003eThe cultivation variant, i.e. intercropping of buckwheat with paulownia and no intercropping, did not significantly affect any of the studied buckwheat traits, i.e. plant height, number of branches on the main shoot, number of branches, inflorescences, number of kernels, total kernels weight per plant. Despite lack of significant statistical differences, in many cases the values of biometric traits were higher when buckwheat was grown with paulownia, compared to the control site, i.e. the number of full kernels per plant and the total kernels weight per plant. Over the years of the study, time has significantly affected the kernels yield and the values for some of the traits studied, such as the number of branches per plant, the number of kernels and the total kernels weight per plant (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). In 2022, we registered a nearly 100% higher yield of kernels per hectare.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelect morphological and flowering biology-related traits of buckwheat and buckwheat yield (averages for specific combinations and years).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlant height\u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of branches on main shoot\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of branches\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNumber of inflorescences\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eNumber of full seeds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eTotal seed mass per plant\u003c/p\u003e \u003cp\u003e(g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eBuckwheat yield\u003c/p\u003e \u003cp\u003e(t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eCultivation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.513\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNIR\u003csub\u003e,\u003c/sub\u003e LSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNIR, LSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eAP - intercropping, AK \u0026ndash; control, ns \u0026ndash; statistically insignificant,\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNIR- the least statistical difference, LSD - least significant difference\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Select morphological and flowering biology-related traits of buckwheat and buckwheat yield (averages for specific combinations and years).\u003c/p\u003e \u003cp\u003eThe average height of the trees at the beginning of the growing season in 2021 was 145 cm, while at the end of the 2022 season it was 311 cm. Tree crown sizes in October 2021 had an average of: 108 cm (height) \u0026times; 157 (width) cm, and in 2022: 156 cm \u0026times; 209 cm. Trunk girths at breast height (at 130 cm from the ground level) at the end of the 2021 and 2022 seasons were respectively: 16.4 cm and 17.9 cm.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present multidisciplinary study, we determined the effects of Tree Based Intercropping (TBI) of paulownia trees on soil physicochemical and microbial properties and the biometric traits of buckwheat. To the best of our knowledge, our study is the first to consider the microbiological aspect of soils in the intercropping of buckwheat and paulownia in European conditions. In northern China, \u003cem\u003ePaulownia elongata\u003c/em\u003e trees are intercropped with wheat or beans. Typically, scientists investigate intercropping with hybrid poplar clones, black walnut, white ash, red alder.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Intercropping is an important element of modern agricultural systems, having an impact on yields, soil quality, and soil microbial community's activity and structure.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSoil pH is considered to be the main soil variable. It interacts with microorganisms, thus determining plant growth and biomass yield.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e In the present study, we observed that both buckwheat monoculture and intercropping resulted in lower soil pH. However, the soil pH in both crops oscillated at the same level in the last year of the study. These results are consistent with previous studies on cassava and soybean intercropping and pepper and garlic intercropping \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, which showed the intercropping system to lower soil pH. These findings are also supported by Bughio et al. (2013)\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, who indicated that soil pH decreases with an increase in leaf litter from \u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e. Furthermore, Khan et al. (2010)\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e found that several soil physicochemical properties in \u003cem\u003eRobinia pseudoacacia\u003c/em\u003e plantations, such as pH, were modified by leaf decomposition. Hinsinger et al. (2006)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and Hagen-Thorn et al. (2004)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e showed that tree roots acidify the soil through the release of acidic compounds and through microbial respiration. In general, all plants produce and release secondary compounds that may show the potential to alter the chemical properties of the substrate on which they grow. Furthermore, a major mechanism ensuring the efficiency of phosphorus uptake by buckwheat may be the plant's ability to acidify the rhizosphere.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Lower soil pH may be associated with greater nutrient availability and their consequent direct uptake through plant roots.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSoil microbial diversity and activity is a significant aspect of soil quality affected by TBI. So far, the relationship between soil microbial properties and the diversification of intercropping has remained understudied. Over the past two decades, soil microbial communities in temperate zone agroforestry systems have been researched, mostly via traditional methods.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e More recently, Banerjee et al. (2016)\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e studied bacterial communities in Canadian agroforestry systems using both quantitative PCR and 454 pyrosequencing of bacterial 16S rRNA. Still, we lack comprehensive, involving both high-throughput metagenomic sequencing techniques of bacterial and fungal populations and traditional techniques to measure microbial abundance and enzymatic activity, as well as plant biometry in temperate zone agroforestry systems.\u003c/p\u003e \u003cp\u003eLand use patterns have a significant impact on the composition and diversity of soil microorganisms, which are extremely sensitive to changes in the soil environment.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Our metagenomic sequence analysis of 16S rRNA gene fragments and ITS regions has provided unique data on bacterial and fungal population diversity and structure. Intercropping increased the diversity of rhizosphere bacterial populations, while the opposite trend was observed for fungal populations, evidenced by the values of the Shannon and Simpson indices. Bigger bacterial diversity may be due to increased carbon and nutrient supply from litter, dead root cells and tree root secretions. \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e In addition, although the crop plant biomass is negligible compared to trees, the decomposition of litter from crop plants with a high diversity of secondary metabolites can impact soil microbial communities.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Tree rows exert strong influence over soil microbial communities and provide habitat for a microbiome that differs in composition from the microbiome of neighbouring crops. Consequently, the introduction of the soil microbiome associated with tree rows onto arable land through agroforestry increases the overall diversity of the system. Our findings related to the diversity and number of OTUs of the mycobiome are in line with previous studies, which have shown that fungal communities under trees gradually diversified. Young tree cultivation within an agroforestry system do not affect the rhizosphere fungal community, and no increase in fungal populations was detected in young agroforestry systems. Clivot et al., (2020)\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e with Beule and Karlovsky (2021)\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e only detecting strong promotion of soil fungi after 10 years of poplar cultivation. This may be due to the adaptation to the heterogeneous understorey space of tree biomass and understorey vegetation or stochastic phenomena as a result of limited exchange between fungal populations. Analysing the microbiome structure of our soil samples, we noted that the microbiome of the rhizosphere soil from intercropping and buckwheat monoculture was dominated by bacteria classified as Actinobabateria, Proteobacteria, Acidobacteria, and the mycobiome by Ascomycota, Basidiomycota and Mortiellomycota. In our own study (Woźniak et al., 2019)\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, we reported that the rhizosphere of \u003cem\u003ePaulownia\u003c/em\u003e trees was dominated by the above-mentioned types of bacteria and fungi. Wang et al. (2022)\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e found that in the rhizosphere of buckwheat the dominant phylum were Actinobacteria, Proteobacteria and Acidobacteria and fungi classified as Ascomycota, Basidiomycota and Mortierellomycota. The dominance of Actinobacteria and Proteobacteria is probably related to the nutrient-rich conditions of the rhizosphere. \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e However, Ascomycota and Basidiomycota fungi play an important role in maintaining soil stability, in plant biomass decomposition and plant interactions. \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Mortierellomycota, on the other hand, are fungi other than saprotrophs, living in the soil on decaying leaves and other organic materials. In addition, Basidiomycota these fungi promote plant growth in different types of crops, so they can be considered as a potential bioindicator for crop production and soil health assessment. \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e It has already been noted that high relative abundance of Mortierellomycota can be evidence of good soil health. \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e In our study, we recorded increased relative abundance of i.e. \u003cem\u003eCandidatus Solibacter\u003c/em\u003e, \u003cem\u003eNocardioides\u003c/em\u003e, \u003cem\u003ePseudarthrobacter\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e. These microorganisms, considered to be PGPR (plant growth-promoting rhizobacteria), are widely recognised to exhibit plant growth-promoting activities by e.g. mobilising nutrients, mediating phytostimulation and plant biocontrol. \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e The accumulation of these microorganisms in rhizosphere soil may be a factor that can positively affect buckwheat biometrics. The study by Peng et al. (2022)\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e also showed that intercropping promotes the enrichment of PGPR. In addition, in our metagenomic study we observed a decrease in the relative abundance of i.e., \u003cem\u003eFusarium\u003c/em\u003e genus - common soilborne plant pathogens - in intercropping. \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e It is likely that intercropping can effectively reduce disease incidence in crop fields. Mechanisms supporting this effect include: modification of the crop microclimate; secretion of allopathic compounds; positive effects on antagonistic microbial communities; and diversification of soil microbial communities. \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eUndoubtedly, the intercropping of trees and plants influences quantitative and qualitative changes in soil microbial life. Most studies show a significant increase in the number of microorganisms in the soil in two-plant intercropping. In our study, we noted that growing buckwheat with paulownia had a positive effect on the increase in the number of bacteria CFU. In addition, there was an increase in the number of fungi CFU in the intercropping during the flowering period of buckwheat in the second year of the study, compared to 2021. It is likely that the higher abundance of bacteria and fungi could be the result of direct contact between plant roots in the intercropping system, which stimulates plant roots to release more nutrients.\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e Similar results were obtained by Beule et al. 2020\u003csup\u003e55\u003c/sup\u003e, who observed an increase in bacterial abundance in poplar-based agroforestry systems compared to neighbouring monocultures in arable fields. Furthermore, the results of Lee and Jose (2003)\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e indicate that the age of the agroforestry system influences the increase in microbial biomass. In a study by Li et al. (2013)\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, the number of soil fungi, bacteria and actinomycetes in intercropping of two species, i.e. soybean and sugarcane, increased by 115.5%, 43.6% and 57.3%, respectively, compared with monoculture. Our study showed that the CFU counts of bacteria and fungi were dependent on the sampling date, being generally higher at the flowering stage of buckwheat (T2), which is consistent with the study of Wang et al. (2019)\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Increasing soil microbial abundance is extremely important as it can influence plant health and soil quality, thus ensuring the stability and productivity of natural ecosystems. \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSoil enzyme activity, including dehydrogenases, is an important indicator of organic matter decomposition and nutrient dynamics. Dehydrogenase activity (DHA) is often used as a high-sensitivity indicator of soil fertility.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In our study, we noted that intercropping increases DHA activity, which is particularly evident on T1, in spring, when the optimum temperature under conditions of sufficient moisture may be a factor favouring higher enzymatic activity. \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e In our own study (Woźniak et al., 2022)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, we reported that young plantations of paulownia trees have a positive effect on some soil microbial parameters, i.e. dehydrogenase activity. Similarly, Wan and Chen (2004)\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e observed higher enzymatic activity in tree-based intercropping including \u003cem\u003ePaulownia\u003c/em\u003e spp. probably due to increased carbon content, nutrients, leaf residues and root secretions in the soil. The high organic content of the soil contributes to a significant increase in the number of microorganisms and changes in their community structure, thereby improving the microbial activity of the soil. \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e It appears that intercropping can provide sufficient energy to soil microorganisms that play a key role in the accumulation, decomposition and transformation of organic carbon in the soil. \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eGlomalin related soil protein (GRSP) is a glycoprotein produced by arbuscular mycorrhizal fungi (AMF), which are widespread in various terrestrial ecosystems and can form symbiotic associations with the roots of more than 80% of land plants\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Many authors point to GRSP as a good indicator of soil stability and fungal activity. \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e Our study showed that higher amounts of GRSP were recorded in the intercropping at T2 compared to the control objects. This may be due to the plant roots secreting more C and energetic substances that promote AMF growth and reproduction, which may increase mycelial density and length and thus GRSP amounts.\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e Furthermore, the results of our study confirm previous findings that GRSP shows sensitivity to seasonal variation and land use change. \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e Our results are also consistent with those of Zhao et al. (2020)\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e on the impact of maize and soybean intercropping on GRSP. It is also notable that AMF can expand the uptake area of plant roots to improve water and mineral absorption, promoting plant growth. \u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eYengwe et al. (2018)\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e assessed the potential of \u003cem\u003eFaidherbia albida\u003c/em\u003e in intercropping with maize in Zambia and found that the presence of \u003cem\u003eF. albida\u003c/em\u003e litter can provide more than 18 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and increase microbial diversity and abundance. In contrast, according to Lucas-Borja et al. (2011)\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e, paulownia plantations worsened soil health (characterised by soil enzyme activity) compared to \u003cem\u003eAleppo pine\u003c/em\u003e plantations or undisturbed soil area. However, paulownia plantations contribute to better soil health than do maize cultivation (intensive soil use). In a study by Woźniak et al. (2022)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, following one year of observation, we concluded that some soil microbial parameters (activity of dehydrogenases and acid phosphatases, catabolic activity according to Biolog EcoPlates) decreased along with increasing distance from the nearest tree, which is related to the decreasing content of nutrients contributed by root secretions and leaf residues.\u003c/p\u003e \u003cp\u003eIntercropping affects crop yields depending on a number of factors, i.e. plant growing conditions, species, soil and climatic conditions. Research shows that the results vary. The yield and the biometric traits of intercropped plants depend largely on the species composition and the coexistence mechanisms developed by the plants. In a study by Dang et al. (2020)\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, intercropping led to significant improvements in biometric and compositional traits of millet grain yield, number of ears per plant and their length, grain mass per plant and 1000 grain weight, with increases in grain yield of 5.6\u0026ndash;20.7% in 2017, 7.9\u0026ndash;53.9% in 2018 and 28.3\u0026ndash;75.4% in 2019. Mung bean seed yield was lower in this cropping system due to the spatial structure of the millet crown. \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e Almond trees intercropped with mung bean had the highest vegetative growth performance, compared to growing almond trees alone. Intercropping of beans with almond trees had a significant effect on the yield and quality of snap beans contributing to enhanced pod parameters, i.e. length, diameter, fresh weight, dry weight, total yield, protein, fibre in both seasons. In a study by Yin and He (1997)\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e, 9-year-old paulownia trees led to a 23% reduction in wheat yields in a paulownia-wheat intercropping system in China. Similar results were obtained by Chirko et al. (1996)\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e, who proved that shading provided by 11-year-old paulownia trees in a paulownia-wheat intercropping system reduced yields by only 7%. However, the system had no effect on reducing the number of grains per square metre and of dry matter per 1000 grains. A study by Li et al. (2008)\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e showed that wheat yield was reduced by up to 50% in the paulownia-wheat intercropping system, and a similar reduction in wheat yield was also found in the walnut-wheat system with an 8 m spacing between tree rows. \u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e Liu et al. (2013)\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e found that sugarcane yields in intercropping were significantly higher than in monoculture.\u003c/p\u003e \u003cp\u003eDifferent results have been reported in the studies by Zhu et al. (2012)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e and Shukla et al. (2019)\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. A study by Zhu et al. (2012)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e showed that 2-year-old mulberry trees did not have a significant effect on millet yield, but mulberry tree leaf production increased by 30%. Shukla et al. (2019)\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e found that yields of all crops tested in the agroforestry system were lower in shaded sites compared with sites with full light exposure. In our study, we found no statistically significant effect of intercropping on biometric traits of buckwheat or its yield. The buckwheat yield was decisively influenced by conditions that occurred in specific years of our research, with significantly better conditions for yield and development of this plant occurring in the 2022 season. The close dependence of buckwheat yield on weather conditions has been confirmed by other studies. \u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePseudo-cereal plants, as well as buckwheat, can be infected by various species of pathogenic fungi, which affect the yield and deteriorate its quality. One of the most serious diseases of cereal plants is \u003cem\u003eFusarium wilt\u003c/em\u003e, which is dangerous as it generates mycotoxins. \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e The present study showed that fungi of the genus \u003cem\u003eFusarium\u003c/em\u003e colonised buckwheat roots most abundantly, regardless of the crop used. However, the study did not show symptoms characteristic of infestation by these fungi, such as wilting and withering of leaves or browning and rotting of roots. The predominant species were \u003cem\u003eF. oxysporum\u003c/em\u003e considered to be part of a natural microflora colonising plant roots. \u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e Some species may be potentially pathogenic, as are the few isolated species of \u003cem\u003eF. culmorum\u003c/em\u003e and \u003cem\u003eF. avenaceum\u003c/em\u003e. We should stress that in the second year of our study, we recorded a nearly 5-fold increase in \u003cem\u003eExserohilum pedicellatum\u003c/em\u003e on buckwheat roots in intercropping sample (AP) - an organism which can cause \u003cem\u003eExserohilum\u003c/em\u003e root rot. \u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e,\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur research indicates that, in general, the paulownia and buckwheat intercropping system had a positive effect on soil microbial properties, which provide a high-sensitivity indicator of soil quality. However, our results are inconclusive, necessitating more studies that would take into account long-term and lasting effects of intercropping. Nevertheless, our study, including both high-throughput metagenomic sequencing techniques of bacterial and fungal populations combined with traditional techniques for measuring microbial abundance and enzymatic activity, showed that the TBI system tested in temperate climates had a positive effect on the abundance, diversity and function of soil bacteria when compared to monocultures in arable fields, potentially contributing to the biological fertility of soil in these systems. Our study also indicated that there were greater changes in the abundance and diversity of bacterial than in fungal populations, depending on the cultivation method. This may suggest that the mycobiome is less sensitive to land use change and that it diversifies gradually. Our results also suggest that both the mycobiome and the TBI microbiome were abundant in terms of plant growth promoting microbes positively influencing plant growth and yields. Given the seasonal and annual trend of each parameter we analysed, temporal fluctuation is a key factor influencing soil biological properties. We have thus demonstrated that microorganisms have the ability to modulate their activity in response to changing nutrient conditions. Growing buckwheat in-between \u003cem\u003ePaulownia\u003c/em\u003e tree rows did not result in a deterioration of the biometric and yield characteristics of this annual crop. Growing trees and crops in close spatial proximity allows for different interspecies interactions that can result in complementary resource use. Our study can provide a foundation for the development of innovative management strategies for the cultivation of trees for biomass energy production. Our aim has also been to provide scientific evidence in support of TBI systems implementation based on paulownia trees in temperate climates.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCredit authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWoźniak Małgorzata:\u003c/strong\u003e Data curation, Formal analysis, Investigation, Resources, Validation, Visualization, Software, Writing - original draft, Writing - review \u0026amp; editing, Supervision; \u003cstrong\u003eJama-Rodzeńska Anna:\u003c/strong\u003e Data curation, Formal analysis, Investigation, Resources; Funding acquisition, Project administration, Writing - original draft, Writing - review \u0026amp; editing; Supervision; \u003cstrong\u003eGębarowska Elżbieta:\u003c/strong\u003e Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Writing - original draft, Writing - review \u0026amp; editing; \u003cstrong\u003eLiszewski Marek\u003c/strong\u003e: Conceptualization, Data curation, Investigation, Resources, Methodology, Project administration, Resources, Supervision; \u003cstrong\u003eSiebielec Sylwia:\u003c/strong\u003e Resources, Writing - original draft; \u003cstrong\u003eKaczmarek-Pinczewska Agata\u003c/strong\u003e: Data curation; \u003cstrong\u003eKucińska Jolanta:\u003c/strong\u003e Data curation; \u003cstrong\u003eGałka Bernard:\u003c/strong\u003e Formal analysis; \u003cstrong\u003eZalewski Dariusz:\u003c/strong\u003e Formal analysis, Software; \u003cstrong\u003eBąbelewski Przemysław:\u003c/strong\u003e Funding acquisition, Project administration, Investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Wrocław University of Environmental and Life Sciences (Poland) as part of the research project no N090/0008/2024\u003c/p\u003e\n\u003cp\u003eThe APC/BPC is financed/co-financed by Wroclaw University of Environmental and Life Sciences and by the National Centrum of Science DEC-2022/06/X/ST10/00047.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNair, P.K.R, Gordone, A.M, Mosquera-Losadac, M.R Agroforestry. 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Identity and pathogenicity of fungi associated with crown and root rot of dryland winter wheat in Azerbaijan. \u003cem\u003ePlant Disease\u003c/em\u003e, \u003cstrong\u003e104,\u003c/strong\u003e 8, 2149-2157. https://doi.org/10.1094/PDIS-08-19-1799-RE (2020).\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":"agroforestry, biodiversity, buckwheat, intercropping, paulownia, soil microbial activity","lastPublishedDoi":"10.21203/rs.3.rs-4611632/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4611632/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe aim of this study was to capture microbiological changes in the soil environment during intercropping of paulownia with buckwheat using randomized block method experiment conducted at Wroclaw University of Environmental and Life Sciences in 2019\u0026ndash;2022. The soil samples were characterized by measuring abundance of microorganisms determining the microbial and fungal community structure using Illumina MiSeq sequencing, the activity of dehydrogenase (DHA) and total glomalin-related soil proteins (T-GRSP). In addition, we assessed the buckwheat roots' colonisation by fungi, as well as yield and biometric traits of the plant. The calculated alpha indicators of the bacterial microbiome diversity and abundance show higher bacterial diversity in the intercropping samples, when compared to the control site. NGS (Next-Generation Sequencing) analysis showed that Actionobacteria, Proteobacteria and Acidobacteria were dominant in the microbiome in every variant of the experiment, regardless of the crop. By contrast, the mycobiome was dominated by fungi classified as the Ascomycota and Mortierellomycota. At the first sampling date (T1), intercropping sample analysis showed significant increase in DHA activity, but not in glomalin concentration. As a rule, the biometric traits\u0026rsquo; values were higher when buckwheat was intercropped with paulownia compared to the control culture, both in terms of buckwheat yield and the total kernels of weight per plant.\u003c/p\u003e","manuscriptTitle":"Effect of intercropping of paulownia and buckwheat on soil microbial biodiversity and enzymatic activity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-16 14:56:48","doi":"10.21203/rs.3.rs-4611632/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":"f36216b8-c5e7-46db-bb59-4213d6976eb9","owner":[],"postedDate":"July 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-29T12:38:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-16 14:56:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4611632","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4611632","identity":"rs-4611632","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}