Integrated analysis of microbiome and metabolomics: mechanism of different pre-fermented juice regulating protein degradation during mulberry silage

Integrated analysis of microbiome and metabolomics: mechanism of different pre-fermented juice regulating protein degradation during mulberry silage | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integrated analysis of microbiome and metabolomics: mechanism of different pre-fermented juice regulating protein degradation during mulberry silage Hua-liang Chen, Guang-hao Xia, Yuan-yuan Yang, Fu-rong Han, Yang Gu, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9200621/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Mulberry ( L.) is a valuable woody protein feed that alleviates protein feed shortages, yet its silage production faces key challenges including high moisture content, scarce native lactic acid bacteria, and severe protein degradation. This study innovatively adopted alternative raw materials to prepare pre-fermented juices, with grape pomace pre-fermented juice (treatment G) and red clover pre-fermented juice (treatment R) compared against mulberry pre-fermented juice (treatment M) and an untreated control (CK). Combined with bacterial community and metabolomic analyses, we evaluated the effects of these treatments on mulberry silage quality over a 60-day ensiling period. Results showed that treatment R delivered the best performance: it enriched , upregulated isoflavonoids including formononetin, glycitein and biochanin A, reduced silage pH to 3.99, increased lactic acid content, and inhibited protein degradation by suppressing protease activities. Treatment M promoted the growth of and the accumulation of beneficial metabolites such as 3,4-dihydroxybenzaldehyde, while treatment G showed moderate effects. All pre-fermented juices improved silage fermentation quality and nutrient retention. This study clarifies the microbial-metabolite regulatory mechanisms underlying mulberry ensiling, provides a low-cost and eco-friendly silage production technology, and promotes the sustainable utilization of mulberry in ruminant production. Pre-fermented juice Silage Protein preservation Metabolite Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Mulberry ( Morus alba L.) stands out as a promising woody protein resource due to its high yield, ease of cultivation, and broad adaptability. It is rich in diverse bioactive compounds and amino acids, with a crude protein content ranging from 16% to 25% [ 1 ], and the proportion of true protein reaching as high as 88.50% [ 2 ]. These characteristics make mulberry a potential solution for alleviating the shortage of protein feed. However, the practical application of fresh mulberry forage for silage is hindered by several challenges. Fresh mulberry has a high moisture content (75%–85%) and a low abundance of naturally occurring lactic acid bacteria (LAB) on its surface, as well as strong buffering capacity [ 3 ]. These factors predispose mulberry silage to undesirable clostridial fermentation during ensiling, which can result in protein degradation, butyric acid production, and dry matter loss [ 4 , 5 ], Moreover, certain clostridia may produce toxins that negatively impact animal health and productivity, and even pose food safety risks within the dairy industry supply chain [ 6 , 7 ]. Therefore, it is essential to develop technological solutions tailored to the unique characteristics of mulberry, with the goal of enhancing silage fermentation quality and inhibiting protein degradation. Pre-fermented juice, produced through the anaerobic fermentation of wild lactic acid bacteria naturally present on plant surfaces, has emerged as a promising microbial inoculant for improving silage fermentation. Functionally similar to lactic acid bacteria additives, pre-fermented juice offers notable advantages, including a simpler production process, lower cost, and environmental friendliness. It can rapidly integrate with the indigenous microbial communities on silage materials, effectively lowering the pH of the fermentation environment, increasing lactic acid content, inhibiting clostridial activity, and reducing protein loss [ 8 – 10 ]. As such, its application in mulberry silage holds significant promise for enhancing silage quality and preserving protein content. Previous studies on pre-fermented juice have mainly used the original ensiling material itself as the fermentation source. Whether preparing pre-fermented juice from alternative materials could further improve the silage quality of woody plants has been rarely reported. Therefore, in this study, red clover and grape pomace were selected as alternative materials for the preparation of pre-fermented juice. Grape pomace is rich in various polyphenolic compounds, such as gallic acid, p-hydroxybenzoic acid, vanillic acid, and epicatechin, which give it significant antimicrobial activity and the ability to effectively inhibit the growth of bacteria and fungi [ 11 , 12 ]. During the ensiling process, these polyphenols also help protect feed protein and reduce its degradation during fermentation [ 13 ]. Similarly, red clover contains a polyphenol oxidase (PPO) system that can convert endogenous o-diphenols in plants into o-quinones; the resulting o-quinones can bind to leaf proteins, thereby significantly reducing protein breakdown during ensiling [ 14 – 16 ]. Currently, most studies on pre-fermented juice have concentrated on optimizing its preparation and evaluating its effects on overall silage quality. However, there is a lack of in-depth mechanistic understanding regarding how pre-fermented juice regulates the dynamic succession of microbial communities and key fermentation metabolic pathways during ensiling. With the rapid development of microbiomics and metabolomics, it is now possible to analyze changes in microbial communities and metabolic products throughout the fermentation process, providing powerful tools to unravel the underlying principles of silage fermentation and its complex micro-ecology. Therefore, the present study was designed to investigate the effects of different formulations of pre-fermented juice prepared from mulberry leaves, red clover and grape pomace on the fermentation quality of mulberry silage. The specific objectives are as follows: (1) to improve the silage quality of mulberry forage and reduce protein loss during ensiling by applying pre-fermented juice; and (2) to elucidate the mechanisms by which different pre-fermented juices influence the dynamic changes in bacterial communities and metabolic profiles during the ensiling of mulberry. The findings are expected to identify suitable pre-fermented juice additives for mulberry silage and promote the efficient utilization of mulberry in ruminant production. 2. Materials and methods 2. 1. Pre-fermented juices and silage preparation 50 g of fresh mulberry leaves, red clover and grape pomace separately, each mixed with 250 mL of sterile distilled water. The mixtures were homogenized thoroughly in a tissue masher for 2 min to obtain juice, followed by filtration through three layers of cheesecloth to collect the filtrate. Then, 2 g of glucose was added to each 100 mL of the filtrate, and the mixture was anaerobically fermented at 37 °C in an anaerobic incubator for 3 days, thus yielding the corresponding pre-fermented juices. Fresh mulberry forage was cut into 2–3 cm fragments and homogenized thoroughly, then divided into four groups with 5 mL/kg of the corresponding substance added to each group: Group M (mulberry pre-fermented juice), Group G (grape pomace pre-fermented juice), Group R (red clover pre-fermented juice), and Group CK (sterile distilled water). After complete mixing, 500 g of each mixture was quickly packed into 22.5 cm × 35.0 cm polyethylene plastic bags and vacuum-sealed. Each group had four replicates, and all samples were stored in the dark at room temperature (15–25 °C), with sampling conducted at 3, 7, 15, 30 and 60 days of ensiling, totaling 80 samples (4 treatments × 4 replicates × 5 sampling time points). 2. 2. Fermentation profiles and microbial population analysis Each bag of sample (20 g) was thoroughly mixed with 180 mL of sterile distilled water and left to stand at 4 °C for 24 hours. The mixture was then filtered through four layers of medical gauze to obtain the extract. The pH of the extract was measured using a glass-electrode pH meter (PHS-3C, Shanghai, China). The concentrations of four organic acids—lactic acid (LA), acetic acid (AA), propionic acid (PA), and butyric acid (BA)—were determined by high-performance liquid chromatography (HPLC). Chromatographic conditions were as follows: Agilent TC-C18 (2) column, column temperature 50 °C, mobile phase 3 mmol/L perchloric acid, flow rate 1 mL/min, and detection wavelength 210 nm. The microbial counts in fresh and ensiled mulberry samples were determined by plate counting. Each bag of sample (10 g) was thoroughly mixed with 90 mL of sterilised saline solution (8.5 g/L NaCl), filtered through four layers of sterile medical gauze, and the filtrate was serially diluted from 10⁻¹ to 10⁻⁸. For each dilution, 10 μL of the microbial suspension was spread onto solid media plates for cultivation. LAB were counted after anaerobic incubation on MRS agar plates at 37 °C for 48 hours. Escherichia coli were counted after incubation on eosin methylene blue (EMB) agar plates at 30 °C for 24 hours. Yeasts and molds were counted after incubation on Bengal red agar plates at 25 °C for 96 hours. 2. 3. Nitrogen fractions and protease activity assay 20 g of each silage sample was accurately weighed and thoroughly mixed with 180 mL of sterile distilled water, stored at 4 °C for 24 h, and filtered through four layers of cheesecloth, with the filtrate collected. 40 μL of the filtrate was mixed with 10 mL of trichloroacetic acid and incubated at 4 °C for 12 h to achieve complete precipitation of true protein; the content of nonprotein nitrogen (NPN) was calculated by subtracting the content of true protein nitrogen in the precipitate from total nitrogen (TN). The supernatant after precipitation was collected and centrifuged at 18000×g for 15 min at 4 °C, and the supernatant was collected again. The content of free amino acid nitrogen (FAA-N) was determined via the ninhydrin-hydrazine sulfate colorimetric method[17], and that of ammonia nitrogen (NH 3 -N) was determined via the phenol-hypochlorite colorimetric method. The content of peptide nitrogen (Peptide-N) was calculated as the value obtained by subtracting the contents of FAA-N and NH₃-N from the NPN content[18]. 10 g of the sample was thoroughly mixed with 50 mL of 0.1 mol/L sodium phosphate buffer (pH 6.5), centrifuged at 10000×g for 10 min at 4 °C, and the supernatant was collected as the crude enzyme extract. Aminopeptidase activity was determined using L-leucine-4-nitroanilide as the substrate, with the activity unit expressed as the absorbance value at 410 nm per gram of silage dry matter per hour (units/(h·g DM)). Carboxypeptidase activity was determined using L-carboxyphenoxy-L-phenyl-alanine as the substrate, with the activity unit expressed as the amount of free amino acids released per gram of silage dry matter per hour (μmol amino acids/(h·g DM)). Acid proteinase activity was determined using azocasein as the substrate, with the activity unit expressed as the absorbance value at 340 nm per gram of silage dry matter per hour (units/(h·g DM))[19]. 2. 4. Bacterial microbiota analysis Silages (5 g per sample) were collected in sterile EP tubes and immediately stored in a −80 °C refrigerator for subsequent bacterial microbiota analysis. DNA was extracted via DNA isolation kits (DP712; Beijing, China) following the standard instructions. After extracting genomic DNA from the samples, following the methods of Zhu et al. (2022), specific primers with barcodes (341F: CCTAYGGGRBGCASCAG and 806R: GGACTACNNGGGGTATCTAAT) were used to amplify the V3-V4 region of the 16S rRNA gene. The PCR procedures were as follows: 98 °C for 1 min for initial denaturation; 30 cycles of 98 °C for 10 s (subsequent denaturation), 50 °C for 30 s (annealing), and 72 °C for 30 s (elongation); and a final extension at 72 °C for 5 min. The PCR products were quantified and qualified first, then purified with a Qiagen Gel Extraction Kit (DP241; Beijing, China). Libraries were prepared and qualified, and finally, paired-end sequencing (PE250) was performed on the Illumina NovaSeq 6000 platform (Novogene Co. Ltd., Beijing, China) to sequence the libraries. 2. 5. Metabolite analysis After freeze-drying, the silage samples were ground into powder. A 100 mg aliquot of sample powder was weighed and placed in a 1.5 mL Eppendorf (EP) tube, followed by the addition of 500 μL of 80% methanol aqueous solution. The mixture was thoroughly vortexed and then placed in an ice bath for 5 minutes. It was subsequently centrifuged at 15,000 × g for 20 minutes at 4 °C. The supernatant was collected and diluted to a final methanol concentration of 53%, and the centrifugation step was repeated as described above. The resulting supernatant was collected for LC-MS/MS analysis. Metabolite detection was performed using a Vanquish ultra-high performance liquid chromatography (UHPLC) system (Thermo Fisher, Germany) coupled with a Q Exactive™ HF-X mass spectrometer (Thermo Fisher, Germany) in an LC-MS/MS configuration. Chromatographic separation was achieved using a Hypersil Gold column (100 × 2.1 mm, 1.9 μm; Thermo Fisher, USA). 2. 6. Statistical analysis Preliminary statistical analysis of the data was performed using Microsoft Excel 2010, followed by two-way analysis of variance (ANOVA) using SPSS software (SPSS 26.0, Chicago, USA). Differences were considered statistically significant at P < 0.05. Multiple comparisons of group means were conducted using Duncan’s test. All identified metabolites were annotated using the LIPIDMaps database, KEGG (Kyoto Encyclopedia of Genes and Genomes) database, and HMDB (Human Metabolome Database). Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were employed to explore the differences in metabolic patterns among groups. Differential metabolites between groups were determined by defining the criteria of FC (Fold Change) > 2 or FC 1, and P < 0.05. Volcano plots were drawn using the R package ggplot2 to show the number of up-regulated or down-regulated differential metabolites, and pathway enrichment analysis was conducted based on the KEGG database using the R package cluster Profiler. All statistical analyses were completed in R software (version 4.5.1). 3. Results 3. 1. Fermentation quality of mulberry ensiling During the ensiling process, the pH values of the M, R, and G treatments consistently remained lower than CK (P<0.05), with the R treatment showing the lowest pH and CK the highest at 60 days (P<0.05). LA content increased over time in all treatments. At 60 days, the R treatment had the highest LA content, followed by M, while CK had the lowest (P<0.05). AA and PA contents were significantly higher in the M and R treatments than in the CK and G treatments. BA was not detected in CK, M, or R, but appeared in G after 30 days (Table 1). Regarding microbial populations (Table 2), LAB counts peaked at 15 days across all treatments, with R treatment reaching the highest level(P<0.05), followed by M, and CK the lowest. Yeast and mold counts declined rapidly after 7 days, becoming undetectable (ND) or <2.00 log10cfu/g FM in all treatments post-15 days (P<0.05). Coliform bacteria counts increased initially and then decreased; M/R treatments effectively suppressed coliform proliferation, exhibiting significantly lower counts than CK at 60 days (P<0.05). Table 1. Effect of different treatments on the variation of fermentation parameters during mulberry ensiling Items Treatment Day of ensiling SEM P-value 3 7 15 30 60 D T D×T pH CK 5.34Aab 5.43Aa 5.17Abc 4.99Acd 4.97Ad 0.05 *** *** NS M 4.64Ca 4.62Ca 4.44Cb 4.34Cbc 4.29Cc R 4.28Dab 4.38Da 4.19Db 4.07Dc 3.99Dc G 5.03Ba 4.84Bb 4.75Bb 4.77Bb 4.78Bb LA (%DM) CK 2.85Ab 5.43Bab 5.34Aab 7.68Ba 9.58Ca 1.51 *** *** *** M 4.82Ab 7.41ABb 7.90Ab 18.44Aa 22.00Ba R 5.35Ac 10.31Ac 9.64Ac 22.04Ab 28.09Aa G 3.71Ac 7.69ABbc 7.24Abc 10.71Bab 12.58Ca AA (%DM) CK 0.56Cc 0.81Cc 1.93Cb 2.09Bb 2.63Da 0.43 *** *** *** M 1.74Ac 2.06Ac 5.67Ab 8.73Aa 10.90Aa R 1.25Bd 1.34Bd 3.17Bc 4.65Bb 6.81Ba G 0.73Cc 1.00Cc 2.73Bb 3.46Bab 3.68Ca PA (%DM) CK 0.55Ab 0.51Ab 0.91Ca 1.11Ca 1.12Ba 0.29 *** *** *** M 0.53Ac 0.60Ac 1.57Ab 4.20Aa 4.36Aa R 0.49Ab 0.54Ab 1.29Bb 3.23Ba 3.97Aa G 0.51Ad 0.59Ad 0.98Cc 1.77Cb 2.35Ba BA (%DM) CK ND ND ND ND ND - - - - M ND ND ND ND ND R ND ND ND ND ND G ND ND ND 0.28 0.30 Note: Different lowercase letters indicate significant differences between different ensiling days in the same treatment, and different uppercase letters indicate significant differences between different treatments in the same ensiling day. SEM: standard error of the means; D: fermentation duration; T: treatment; D×T: interaction between fermentation duration and treatment. CK: control; M: adding previously fermented mulberry juice; R: adding previously fermented red clover juice; G: adding previously fermented grape pomace juice. Abbreviations in the following tables are the same means. Table 2 Effects of different treatments on the variation of microbial populations during mulberry ensiling Items Treatment Day of ensiling SEM P-value 3 7 15 30 60 D T D×T LAB (log10cfu/g FM) CK 5.71De 6.90Db 7.66Ca 6.74De 6.19Dd 0.037 *** *** *** M 6.39Ad 7.62Ab 8.00Ba 7.11Be 7.08Bc R 6.29Bd 7.32Bb 8.26Aa 7.36Ab 7.21Ac G 5.86Cd 7.03Cb 7.61Ca 6.98Cb 6.73Cc Yeast (log10cfu/g FM) CK 3.97C 3.76B <2.00 <2.00 ND - - - - M 4.17B 3.53B <2.00 <2.00 ND R 4.16B 3.22C <2.00 <2.00 ND G 4.36A 4.95A <2.00 <2.00 ND Coliform bacteria (log10cfu/g FM) CK 6.23Ac 6.85Ab 7.25Aa 6.16Ac 6.02Ac 0.094 *** *** *** M 5.77Ca 5.75Ba 5.05Bb 4.39Bc 4.35Cc R 5.66Da 5.72Ba 5.14Bb 4.22Bc 4.03Dc G 6.13Bb 6.92Aa 6.85Aa 5.96Ab 5.66Bc Mold (log10cfu/g FM) CK 4.23A 3.90A <2.00 ND ND - - - - M 4.16A 3.66B <2.00 ND ND R 4.03B 3.74B <2.00 ND ND G 3.71C 3.49C <2.00 ND ND 3. 2. Effects of pre-fermented juice on protein degradation during the ensiling of mulberry Both ensiling duration and additive treatments significantly modified the nitrogen fraction profiles in mulberry silage (Fig. 1). NPN, NH3-N, and FAA-N contents increased progressively with fermentation time across all treatments. Specifically, R and M treatments effectively inhibited the accumulation of NPN, NH3-N(P<0.05), and FAA-N, with R consistently maintaining the lowest levels of these fractions throughout ensiling(P<0.05). In contrast, the G treatment exerted a weaker inhibitory effect, with NPN, NH3-N, and FAA-N contents remaining comparable to those in CK (P<0.05). Acid protease activity decreased significantly with ensiling duration, and no significant differences were observed among treatments (P<0.001). Carboxypeptidase activity also declined over time (P<0.05). CK maintained the highest activity throughout ensiling, while R treatment exhibited the lowest activity at day 60 (20.71%), followed by M and G treatments (P<0.05). Aminopeptidase activity declined sharply with ensiling time, reaching undetectable levels in M and R treatments by day 60. CK retained the highest activity at day 60 (2.25%), whereas R and M treatments significantly suppressed aminopeptidase activity (P<0.05) (Fig. 2). 3. 3. Effects of pre-fermented juices on the microflora of mulberry silage PCoA results revealed that the bacterial communities of the M and R treatments were distinctly separated from those of the CK during the ensiling process (Fig. 3). At the phylum level, Proteobacteria and Firmicutes were the dominant bacterial phyla during mulberry ensiling. Following 3 days of ensiling, the relative abundance of Firmicutes increased across all treatments, becoming the dominant phylum in the R and M groups. In contrast, Firmicutes remained at a low level in the CK group throughout fermentation, and while it increased gradually in the G group (from 10.68% to 27.40% by day 30), it did not achieve dominance.At the genus level, Enterobacter dominated the CK group throughout ensiling, accompanied by low abundances of LAB (e.g., Enterococcus , Lactococcus ). In CK, the relative abundance of Lactococcus increased from 2.24% (day 3) to 6.46% (day 15) before declining to 3.97% (day 60). In the G group, Enterobacter remained dominant, while Enterococcus abundance increased from 4.22% to 16.72% and Lactococcus from 5.05% to 9.52% between days 3 and 30, with both genera exceeding the levels observed in CK after day 7. In the M group, Pediococcus dominated initially, reaching up to 90.81% by day 7, but was replaced by Lactobacillus as the dominant genus after day 30. Enterococcus dominated the bacterial community in the R group throughout the entire ensiling process (Fig. 3B). Kruskal-Wallis tests revealed significant treatment effects on the relative abundances of key bacterial genera during ensiling (Fig. 4). Lactobacillus differed at days 30 (p = 0.0051) and 60 (p = 0.0065), with R treatment highest at day 60. Lactococcus varied at days 30 (p = 0.056) and 60 (p = 0.031), with CK and G more abundant at day 30 and CK dominant at day 60. Enterobacter differed at day 60 (p = 0.055), with CK and G higher than M and R. Pediococcus differed at days 3 (p = 0.0066) and 30 (p = 0.006), with G highest at day 3 and CK at day 30. Enterococcus differed at all time points (p ≤ 0.015), with R consistently highest. Overall, treatments (CK, G, M, R) distinctly altered community composition, with the most pronounced effects on Enterococcus and Lactobacillus . 3. 4. Effects of pre-fermented juices on the metabolome of mulberry silage A total of 1,649 metabolites were identified in mulberry silage during the fermentation process, and this metabolite count was significantly higher than that reported in other conventional silage feedstocks, including alfalfa (167 metabolites)[20], napier grass (426 metabolites)[21], and sorghum (408 metabolites)[22]. Principal component analysis (PCA) demonstrated that both fermentation duration and the type of pre-fermented juice fermentation broth exerted significant effects on the metabolite profiles of mulberry silage, with the M, R, and G treatment groups presenting distinctly separated metabolite distribution patterns throughout the ensiling period. Pathway enrichment analysis further revealed that a large number of metabolites were differentially regulated (either upregulated or downregulated) in each treatment group during fermentation, highlighting the dynamic nature of silage fermentation metabolism. On the 3rd day of fermentation, the R treatment significantly modulated the amino acid biosynthesis pathway, accompanied by marked upregulation of key intermediate metabolites involved in amino acid anabolism, namely citrulline, 4-hydroxy-2-oxoglutaric acid, and pantetheine. Throughout the entire fermentation process, the R treatment persistently and significantly upregulated isoflavonoid compounds such as glycitein, biochanin A, and formononetin, while the M treatment significantly elevated the content of 3,4-dihydroxybenzaldehyde across the whole ensiling stage and notably increased 3-phenyllactic acid levels at the initial fermentation phase. For the G treatment, it significantly regulated arachidonic acid metabolism within the unsaturated fatty acid biosynthesis pathway and substantially enhanced arachidonic acid content in mulberry silage. Comparative metabolomic analysis among the R, G, and M treatments at 3 d, 30 d, and 60 d of fermentation (Table 3) revealed that the R treatment displayed the most pronounced metabolic differences as early as the 3 d fermentation stage, and this treatment significantly upregulated a suite of beneficial metabolites during fermentation, including wogonin, formononetin, glycitein, biochanin A, cordycepin, 2'-deoxyadenosine, ferulic acid, and chlorogenic acid. Among these differential metabolites, the legume-specific isoflavonoids (wogonin, formononetin, glycitein, and biochanin A) in the R treatment exhibited the highest fold changes (log₂FC=3.39~7.80) and variable importance in projection (VIP) values (5.29~5.93) (Table S1). Table 3 High-frequency differential metabolites in R vs G/M treatments during 3/30/60d silage fermentation Name Treatment Compound_ID Molecular Formula Formononetin 3、30、60(R-G)；3、30(R-M) Com_716_pos C16H12O4 Glycitein 30、60(R-G)；3、30(R-M) Com_941_neg C16H12O5 Biochanin A 30(R-G)；3、30、60(R-M) Com_2267_pos C16H12O5 Cordycepin 3、60(R-G)；30(R-M) Com_327_pos C10H13N5O3 Chlorogenic acid 30(R-G)；3、60(R-M) Com_678_neg C16H18O9 2'-Deoxyadenosine 3、60(R-G)；30(R-M) Com_325_pos C10H13N5O4 Lithocholic acid 30(R-G)；30、60(R-M) Com_8369_pos C24H40O3 N8-acetylspermidine 30、60(R-G)；3(R-M) Com_7772_pos C9H21N3O Ferulic acid 3(R-G)；30、60(R-M) Com_638_neg C10H10O4 Wogonin 30、60(R-G)；3(R-M) Com_17888_pos C16H12O5 3. 5. Correlation analysis of bacterial communities with metabolites, fermentation parameters, and nitrogen fractions during the silage fermentation process of mulberry Bacterial communities are the core drivers of feed mulberry silage fermentation. To clarify their regulatory roles in silage metabolite composition, fermentation quality, and protein degradation, correlation analysis was conducted between the top 10 dominant bacterial genes (by relative abundance) and selected differential metabolites（metabolites with significant differences and significant effects on fermentation）, key fermentation parameters, and nitrogen fractions. Results showed that Pediococcus was significantly positively correlated with TN and negatively correlated with protein degradation products such as NPN and FAA-N (P < 0.05); its dominance in the early fermentation stage effectively inhibited excessive protein degradation. Enterococcus was significantly positively correlated with LA and TN, while negatively correlated with pH and NH₃-N (P < 0.05); it also exhibited positive correlations with metabolites with antioxidant and antibacterial activities (e.g., biochanin A, formononetin). The sustained dominance of Enterococcus in the R group not only improved silage fermentation quality and reduced protein degradation but also enhanced the antioxidant and antibacterial capacities of silage. Enterobacter was significantly positively correlated with pH and BA, and negatively correlated with LA, AA, and the aforementioned antioxidant metabolites. As the dominant genus in the CK and G groups, Enterobacter consumed LA and AA, leading to increased silage pH, deteriorated fermentation quality, and impaired aerobic stability [23]. Lactobacillus was significantly positively correlated with LA, AA, and FAA-N, and negatively correlated with pH, TN, and Peptide-N (P < 0.05); it also showed positive correlations with beneficial metabolites (e.g., biotin, coumaric acid) and a negative correlation with citric acid. Some Lactobacillus (e.g., Lactobacillus buchneri , Lactobacillus brevis ) produced AA via hetero-fermentation, which inhibited the oxidative metabolism of nutrients and improved the nutritional value and palatability of silage [24]. 4. Discussion Assessment of silage fermentation primarily relies on measuring pH and determining the levels of organic acids produced [ 25 ]. During fermentation, the pH values of all treatment groups continuously decreased, with the M, R, and G treatments showing a significantly faster decline than the CK. However, the high pH and low LA concentration in the CK indicate that natural silage struggles to overcome the high buffering capacity of forage mulberry [ 26 ]. In contrast, the M, R, and G treatments demonstrated that the pre-fermented juice could effectively decreased the pH of the ensiling system by promoting the production of LA and other organic acids, thereby inhibiting harmful microorganisms and improving fermentation quality[ 9 , 10 ]. Notably, the R treatment in this study was most effective in rapidly reducing acidity and accumulating lactic acid. After 60 days of ensiling, the addition of pre-fermented juice significantly increased the production of AA and PA. Both of these organic acids possess antifungal properties [ 27 ], suggesting that pre-fermented juice has the potential to enhance the aerobic stability of forage mulberry silage. During the ensiling process, LAB drive the decrease in pH by converting WSC into LA. LAB possess complex antimicrobial mechanisms and can produce antimicrobial compounds, including bacteriocins, which work together to inhibit harmful microorganisms and thus ensure the quality and stability of the silage [ 24 , 28 , 29 ]. All treatments significantly increased the number of lactic acid bacteria, accelerated the inhibition of Yeast and Mold, and more effectively reduced the number of Coliform bacteria. The R treatment showed the best performance in chemical indicators (low pH and high LA content), which is directly related to its establishment and maintenance of the strongest lactic acid bacteria dominance at the microbial level. In contrast, the G treatment showed relatively average performance in both chemical and microbial indicators, which may be due to antagonism between the exogenous lactic acid bacteria and the indigenous microorganisms on the raw material. Coliform bacteria compete with LAB for substrates, leading to nutrient loss and undesirable fermentation in silage [ 30 ]. As aerobic fungi with poor acid tolerance, mold growth is inhibited by the anaerobic and acidified environment of silage. With the progression of fermentation, the oxygen concentration in the system continuously decreases and the environment becomes increasingly acidified, resulting in no mold detected in the final fermented products. This effectively mitigates the risk of mycotoxin contamination and ensures the safety and stability of silage. Studies have demonstrated that coliform bacteria are difficult to inhibit when pH > 4.0 [ 31 ], while only the R treatment in this study had silage pH ≤ 4.0, with a significantly lower coliform count than other groups. In summary, pre-fermented juice inhibits harmful microorganisms by regulating pH and the fermentation environment, thereby effectively improving the fermentation quality and safety of mulberry silage. When ensiling forages or woody plants with high protein content, a major challenge is the rapid and extensive protein degradation that can occur both before and during fermentation[ 3 ]. During the ensiling process, the synergistic action of plant proteases and microorganisms is the primary cause of protein degradation and the consequent decline in forage quality. This process typically occurs in two stages. First, endogenous plant proteases hydrolyze proteins into peptides and free amino acids. Subsequently, microorganisms further deaminate these products, generating ammonia, amines, and other non-protein nitrogen compounds, resulting in a waste of protein resources [ 32 , 33 ]. Therefore, changes in nitrogen fractions can effectively elucidate the dynamics of protein degradation during the ensiling process [ 34 ]. In addition, at least three types of proteolytic enzymes are present in forage crops: acidic proteinases, carboxypeptidases, and aminopeptidases [ 35 ]. Changes in the activities of these enzymes can also serve as indicators of the extent of protein degradation during anaerobic fermentation. The superior performance of the R group may be attributed to its unique components and multiple mechanisms of action. First, the abundant polyphenol oxidase in red clover directly protects proteins[ 36 ]. Second, the addition of fermentation liquid accelerates acidification in the system, inhibiting the activity of acid-sensitive proteases such as aminopeptidases. In addition, the fermentation liquid may introduce secondary metabolites such as plant tannins, which can bind to and inhibit protease activity [ 37 ]. Furthermore, the treatment may also suppress the proliferation of harmful microorganisms such as Escherichia coli, reducing the deamination of amino acids. These mechanisms work together to slow down the protein degradation pathway. Silage fermentation is fundamentally a process of microbial community succession, which directly determines fermentation quality [ 24 ]. PCoA results from this study showed clear separation of microbial communities among all treatment groups, indicating that pre-fermented juice differentially regulates the bacterial structure of mulberry silage. Firmicutes, which include acid-producing bacteria, are essential for silage, while Proteobacteria contain many undesirable microbes that cause nutrient loss [ 38 ]. In natural silage, Firmicutes typically increase and become dominant, but this pattern was not observed in the CK, likely due to the woody feature of the mulberry. Both M and R treatments significantly increased the abundance of Firmicutes, with the R group exceeding 70 per cent by the end of fermentation. This suggests that M and R treatments optimize silage fermentation by promoting Firmicutes and inhibiting Proteobacteria. The effectiveness of silage fermentation largely depends on the activity of LAB. Numerous studies have confirmed that LAB play a crucial role throughout the entire anaerobic fermentation process by optimizing fermentation characteristics, enhancing the diversity of beneficial microorganisms, and inhibiting the proliferation of pathogenic microbes[ 39 – 42 ]. These actions significantly improve the quality of fermented feed. The core functional species primarily include Enterococcus , Lactiplantibacillus , Pediococcus , Lactococcus , and Bacillus [ 43 ]. In this study, the dominant bacterial genus in the CK was Enterobacter . As a facultative anaerobe, Enterobacter competes with LAB for fermentation substrates and produces ammonia and biogenic amines through amino acid deamination and decarboxylation reactions. This not only reduces the nutritional value of silage but also negatively affects its palatability [ 44 ]. These findings indicate that natural ensiling of mulberry forage is less efficient, with LAB struggling to dominate the fermentation process. According to the succession patterns of the fermentation microbiota, genera such as Weissella and Pediococcus , which are dominant LAB in the early stage of ensiling, can initially participate in fermentation but are less acid-tolerant. As LA accumulates and the environmental pH continues to decrease, their activity is gradually inhibited, and they are subsequently replaced by more acid-tolerant LAB [ 45 ]. In the R treatment group, the direct enhancement of Enterococcus abundance allowed this genus to dominate the bacterial community throughout the fermentation process, effectively suppressing the proliferation of undesirable bacteria and maintaining relatively low bacterial diversity. It is noteworthy that Enterococcus , as a homofermentative LAB, is commonly used as a silage inoculant [ 24 ]. Its increased abundance during anaerobic fermentation is of practical importance for promoting acidification and improving fermentation quality. Although the addition of G increased the relative abundance of both Enterococcus and Lactococcus , it did not enable LAB to dominate the microbial community. This may be attributed to antagonistic interactions between the LAB in grape pomace fermentation liquid and the indigenous microbial community on the surface of mulberry forage, preventing LAB from becoming the dominant group during the ensiling process [ 24 ].This study confirmed that naturally occurring LAB struggle to dominate the microbial community during mulberry silage fermentation. Both M and R treatments effectively promoted LAB growth, establishing their dominance while significantly reducing the relative abundance of Enterobacter. Pre-fermented juices prepared from different materials showed distinct regulatory effects on the silage microbial community. The remarkable discrepancy in metabolite abundance between mulberry silage and other silage types is closely associated with the unique physicochemical and compositional traits of mulberry as a silage raw material, while the distinct metabolic profiles observed in the M, R, and G treatments confirm that these three pre-fermented juice formulations regulate silage fermentation via disparate metabolic regulatory pathways. The widespread differential regulation of metabolites in each treatment group validates that silage fermentation is a highly dynamic biological process involving simultaneous metabolite biosynthesis and degradation[ 20 ], and pathway enrichment analysis serves as a pivotal tool to decipher the underlying metabolic mechanisms driving this process. The significant upregulation of 4-hydroxy-2-oxoglutaric acid (a core precursor in the glutamate biosynthesis pathway) under the R treatment at the early fermentation stage is a critical metabolic event, as glutamate acts as a premium nitrogen source for LAB, effectively facilitating the proliferation of beneficial microorganisms, accelerating LA accumulation, and consequently lowering silage pH [ 46 ]; this metabolic mechanism fully accounts for the significantly higher LA content in the R group relative to other treatments during the initial fermentation phase. The sustained upregulation of legume-derived isoflavonoids (glycitein, biochanin A, formononetin) in the R treatment throughout fermentation is conducive to silage quality preservation, as these compounds possess broad-spectrum antimicrobial and antioxidant stress properties [ 47 ], which enhance the antioxidant capacity of mulberry silage, suppress the proliferation of undesirable microorganisms, and thereby improve fermentation stability and overall quality. For the M treatment, the persistent upregulation of 3,4-dihydroxybenzaldehyde (a phenolic metabolite derived from amino acid metabolism) delivers dual benefits for silage fermentation and animal health: this compound not only optimizes fermentation quality via antioxidant and nutrient-protective effects, but also mitigates oxidative stress, alleviates inflammatory responses, and modulates gut microbiota composition to boost animal health [ 48 ] additionally, the increased 3-phenyllactic acid content at the initial fermentation stage inhibits the growth of spoilage miscellaneous bacteria via its intrinsic antimicrobial activity, promoting the smooth and efficient initiation of mulberry silage fermentation [ 20 , 49 ]. The G treatment-mediated enhancement of arachidonic acid content enriches the nutritional value of mulberry silage, as arachidonic acid is an essential polyunsaturated fatty acid for animals, and its free form participates in vital physiological processes including anti-cancer activity, inflammatory modulation, and immune regulation, effectively reducing disease risk and mortality [ 50 ]. The early-onset significant metabolic differences in the R treatment at 3 d fermentation indicate that this formulation has a robust metabolic foundation for rapidly triggering high-quality silage fermentation, with its core superiority over the G and M treatments lying in the targeted enrichment of beneficial metabolites. Specifically, the high-abundance isoflavonoids in the R treatment scavenge free radicals in the fermentation system, specifically inhibit the growth of spoilage bacteria such as Clostridium spp., and form stable protein complexes to achieve antioxidant protection and nutrient retention[ 47 ], meanwhile, N8-acetylspermidine promotes protein synthesis by stabilizing protein spatial conformation and optimizes microbial metabolism to foster a favorable microenvironment for beneficial bacterial proliferation [ 51 ], cordycepin acts as an energy metabolism precursor to improve energy utilization efficiency and accelerate the proliferation of LAB and other beneficial bacteria [ 52 ], and chlorogenic acid (a phenylpropanoid compound) further reinforces the protective effects via its strong antioxidant, antibacterial, and free radical-scavenging activities[ 53 ]. Collectively, the synergistic action of these upregulated beneficial metabolites in the R treatment constitutes the key metabolic mechanism underlying its superior performance in inhibiting undesirable microbial growth, minimizing nutrient loss, and elevating the overall quality of mulberry silage. 5. Conclusion Different pre-fermented juices regulated the bacterial community structure and metabolite composition during mulberry ensiling in distinct ways, thereby modulating the protein degradation process, and the R treatment exhibited the optimal regulatory effect. This treatment not only significantly promoted LA synthesis and led to a rapid drop in the pH of the silage system, but also optimised the microbial community structure by enriching dominant LAB, such as Enterococcus , and inhibiting the proliferation of harmful bacteria, including Enterobacter . Meanwhile, it markedly upregulated beneficial isoflavonoid metabolites (wogonin, formononetin, glycitein and biochanin A) and effectively suppressed protease activity, ultimately exerting a synergistic effect to reduce protein loss during ensiling to a great extent. The M and G treatments also improved the fermentation quality of mulberry silage, yet their regulatory effects were inferior to those of the R treatment. Declarations During the preparation of this work, the author(s) used Grammarly in order to find the language and grammatical errors and improve the manuscript accordingly. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Credit Author Statement H.L.C: Writing – review & editing, Writing – original draft, visualization, investigation, data curation; G.H.X: Methodology, Writing – review & editing,investigation, data curation; Y.Y.Y, F.R.H, Y.G: Methodology, conceptualization; Y.L.Z, Y.X.X, H.S: Resources, Funding acquisition; C.C, F.Y.Y: Supervision, resources, Funding acquisition; J.H: Supervision, resources, funding acquisition, Writing – review & editing. Acknowledgments This research was funded by the National Key R&D Program of China (2022YFD1300901) the National Natural Science Foundation of China (32460359); the Guizhou Provincial Science and Technology Project (Qian Ke He Platform Talent – BQW [2024] 003)； the Guizhou University National Leading Talents Research Initiative (GZU Leading Talents Document (2023) No. 05); the Central Financial Project for Agricultural Ecological Resources Conservation (Comprehensive Utilization of Crop Straw), No. GZMD2025-P282-1 References Yan CH, Chen FH, Yang YL, Shen LW, Xun XM, Zhang ZA, et al. Biochemical and protein nutritional potential of mulberry ( Morus alba L.) leaf: partial substitution improves the nutrition of conventional protein. Journal of the Science of Food and Agriculture. 2024;104(4):2204-14; doi: 10.1002/jsfa.13103. He LW, Chen N, Lv HJ, Wang C, Zhou W, Chen XY, et al. 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University","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Hao","suffix":""}],"badges":[],"createdAt":"2026-03-23 12:39:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9200621/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9200621/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107185119,"identity":"f6f3cd3a-339c-4be1-add6-de3ca613bbf0","added_by":"auto","created_at":"2026-04-17 18:40:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":250419,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different treatments on the variation of nitrogen compounds during mulberry ensiling\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/c27232cfb03665454295b7e5.png"},{"id":107185116,"identity":"2c878895-3be5-4a5c-bdcc-1a6f7fd0b8bd","added_by":"auto","created_at":"2026-04-17 18:40:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":293621,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different treatments on the variation of protease activities during mulberry fermentation\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/4ec83a7f49343f9172e11fac.png"},{"id":107185123,"identity":"31c44270-cf4f-4003-806c-475c3f072061","added_by":"auto","created_at":"2026-04-17 18:40:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1000568,"visible":true,"origin":"","legend":"\u003cp\u003eThe differences in the microflora of mulberry silage under different treatments. (A) Principal coordinate analysis (PCoA) of the bacterial microbiota; (B) PCoA of the bacterial microbiota at different fermentation stages; (C)Relative abundance at the bacterial phylum and genus levels.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/4dc1e33b4d86265a6661b996.png"},{"id":107185122,"identity":"673cc4c9-ab50-47eb-b00d-6f43f76590b8","added_by":"auto","created_at":"2026-04-17 18:40:07","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1005223,"visible":true,"origin":"","legend":"\u003cp\u003eKruskal-Wallis test-based box plots of relative abundances of key bacterial genera in mulberry silage at 3, 30, and 60 d under different pre-fermented juice treatments\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/117703c0530175909b415cb2.jpeg"},{"id":107185121,"identity":"d24bbef3-bab8-47a9-aea2-c86a5e48b670","added_by":"auto","created_at":"2026-04-17 18:40:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4207278,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolite dissimilarities of mulberry silage (a) Principal component analysis (PCA) of metabolic profiles in mulberry silage; (b) Volcano plot analysis; (c) Bar chart of differential metabolite count statistics; (d) Pathway enrichment analysis under different treatments.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/94ec22af6b464276e12173e9.png"},{"id":107481685,"identity":"f34f74d1-fc04-48db-a80b-098bd02baaef","added_by":"auto","created_at":"2026-04-22 02:19:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":724096,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of bacterial genus correlated with metabolites and fermentation parameters, and nitrogen components during mulberry ensiling. (a) Correlation analysis of the top 10 bacterial genus in relative abundance with fermentation parameters and nitrogen components during mulberry ensiling; (b) Correlation analysis of functional metabolites with fermentation parameters and nitrogen components during mulberry ensiling. The red square represents positive correlation, and the blue square represents negative correlation.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/bd2f753175838996a55ec7c5.png"},{"id":108006077,"identity":"7ebd0a03-cfaf-4f95-b153-8622f84d1f17","added_by":"auto","created_at":"2026-04-28 12:52:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7780201,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/0c730186-b925-4b11-ac31-7ea82583b53a.pdf"},{"id":107185118,"identity":"378e9b43-3e3e-4ae0-95ae-55be356adb07","added_by":"auto","created_at":"2026-04-17 18:40:07","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":57006,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.RGMDIFF.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/e7d057dca5e3d64f9d74e9fd.xlsx"},{"id":107185117,"identity":"e149b170-a6c6-46f6-88b5-252945ecde23","added_by":"auto","created_at":"2026-04-17 18:40:07","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":214940,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicalabstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-9200621/v1/3e77b228b8a06d22d1f62b84.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated analysis of microbiome and metabolomics: mechanism of different pre-fermented juice regulating protein degradation during mulberry silage","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMulberry (\u003cem\u003eMorus alba\u003c/em\u003e L.) stands out as a promising woody protein resource due to its high yield, ease of cultivation, and broad adaptability. It is rich in diverse bioactive compounds and amino acids, with a crude protein content ranging from 16% to 25% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and the proportion of true protein reaching as high as 88.50% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These characteristics make mulberry a potential solution for alleviating the shortage of protein feed. However, the practical application of fresh mulberry forage for silage is hindered by several challenges. Fresh mulberry has a high moisture content (75%\u0026ndash;85%) and a low abundance of naturally occurring lactic acid bacteria (LAB) on its surface, as well as strong buffering capacity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These factors predispose mulberry silage to undesirable \u003cem\u003eclostridial\u003c/em\u003e fermentation during ensiling, which can result in protein degradation, butyric acid production, and dry matter loss [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], Moreover, certain \u003cem\u003eclostridia\u003c/em\u003e may produce toxins that negatively impact animal health and productivity, and even pose food safety risks within the dairy industry supply chain [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, it is essential to develop technological solutions tailored to the unique characteristics of mulberry, with the goal of enhancing silage fermentation quality and inhibiting protein degradation.\u003c/p\u003e \u003cp\u003ePre-fermented juice, produced through the anaerobic fermentation of wild lactic acid bacteria naturally present on plant surfaces, has emerged as a promising microbial inoculant for improving silage fermentation. Functionally similar to lactic acid bacteria additives, pre-fermented juice offers notable advantages, including a simpler production process, lower cost, and environmental friendliness. It can rapidly integrate with the indigenous microbial communities on silage materials, effectively lowering the pH of the fermentation environment, increasing lactic acid content, inhibiting clostridial activity, and reducing protein loss [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As such, its application in mulberry silage holds significant promise for enhancing silage quality and preserving protein content.\u003c/p\u003e \u003cp\u003ePrevious studies on pre-fermented juice have mainly used the original ensiling material itself as the fermentation source. Whether preparing pre-fermented juice from alternative materials could further improve the silage quality of woody plants has been rarely reported. Therefore, in this study, red clover and grape pomace were selected as alternative materials for the preparation of pre-fermented juice. Grape pomace is rich in various polyphenolic compounds, such as gallic acid, p-hydroxybenzoic acid, vanillic acid, and epicatechin, which give it significant antimicrobial activity and the ability to effectively inhibit the growth of bacteria and fungi [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. During the ensiling process, these polyphenols also help protect feed protein and reduce its degradation during fermentation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Similarly, red clover contains a polyphenol oxidase (PPO) system that can convert endogenous o-diphenols in plants into o-quinones; the resulting o-quinones can bind to leaf proteins, thereby significantly reducing protein breakdown during ensiling [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrently, most studies on pre-fermented juice have concentrated on optimizing its preparation and evaluating its effects on overall silage quality. However, there is a lack of in-depth mechanistic understanding regarding how pre-fermented juice regulates the dynamic succession of microbial communities and key fermentation metabolic pathways during ensiling. With the rapid development of microbiomics and metabolomics, it is now possible to analyze changes in microbial communities and metabolic products throughout the fermentation process, providing powerful tools to unravel the underlying principles of silage fermentation and its complex micro-ecology.\u003c/p\u003e \u003cp\u003eTherefore, the present study was designed to investigate the effects of different formulations of pre-fermented juice prepared from mulberry leaves, red clover and grape pomace on the fermentation quality of mulberry silage. The specific objectives are as follows: (1) to improve the silage quality of mulberry forage and reduce protein loss during ensiling by applying pre-fermented juice; and (2) to elucidate the mechanisms by which different pre-fermented juices influence the dynamic changes in bacterial communities and metabolic profiles during the ensiling of mulberry. The findings are expected to identify suitable pre-fermented juice additives for mulberry silage and promote the efficient utilization of mulberry in ruminant production.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e2. 1. Pre-fermented juices and silage preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e50 g of fresh mulberry leaves, red clover and grape pomace separately, each mixed with 250 mL of sterile distilled water. The mixtures were homogenized thoroughly in a tissue masher for 2 min to obtain juice, followed by filtration through three layers of cheesecloth to collect the filtrate. Then, 2 g of glucose was added to each 100 mL of the filtrate, and the mixture was anaerobically fermented at 37 \u0026deg;C in an anaerobic incubator for 3 days, thus yielding the corresponding pre-fermented juices.\u003c/p\u003e\n\u003cp\u003eFresh mulberry forage was cut into 2\u0026ndash;3 cm fragments and homogenized thoroughly, then divided into four groups with 5 mL/kg of the corresponding substance added to each group: Group M (mulberry pre-fermented juice), Group G (grape pomace pre-fermented juice), Group R (red clover pre-fermented juice), and Group CK (sterile distilled water). After complete mixing, 500 g of each mixture was quickly packed into 22.5 cm \u0026times; 35.0 cm polyethylene plastic bags and vacuum-sealed. Each group had four replicates, and all samples were stored in the dark at room temperature (15\u0026ndash;25 \u0026deg;C), with sampling conducted at 3, 7, 15, 30 and 60 days of ensiling, totaling 80 samples (4 treatments \u0026times; 4 replicates \u0026times; 5 sampling time points).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. 2. Fermentation profiles and microbial population analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach bag of sample (20 g) was thoroughly mixed with 180 mL of sterile distilled water and left to stand at 4 \u0026deg;C for 24 hours. The mixture was then filtered through four layers of medical gauze to obtain the extract. The pH of the extract was measured using a glass-electrode pH meter (PHS-3C, Shanghai, China). The concentrations of four organic acids\u0026mdash;lactic acid (LA), acetic acid (AA), propionic acid (PA), and butyric acid (BA)\u0026mdash;were determined by high-performance liquid chromatography (HPLC). Chromatographic conditions were as follows: Agilent TC-C18 (2) column, column temperature 50 \u0026deg;C, mobile phase 3 mmol/L perchloric acid, flow rate 1 mL/min, and detection wavelength 210 nm.\u003c/p\u003e\n\u003cp\u003eThe microbial counts in fresh and ensiled mulberry samples were determined by plate counting. Each bag of sample (10 g) was thoroughly mixed with 90 mL of sterilised saline solution (8.5 g/L NaCl), filtered through four layers of sterile medical gauze, and the filtrate was serially diluted from 10⁻\u0026sup1; to 10⁻⁸. For each dilution, 10 \u0026mu;L of the microbial suspension was spread onto solid media plates for cultivation. LAB were counted after anaerobic incubation on MRS agar plates at 37 \u0026deg;C for 48 hours. \u003cem\u003eEscherichia coli\u003c/em\u003e were counted after incubation on eosin methylene blue (EMB) agar plates at 30 \u0026deg;C for 24 hours. Yeasts and molds were counted after incubation on Bengal red agar plates at 25 \u0026deg;C for 96 hours.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. 3. Nitrogen fractions and protease activity assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e20 g of each silage sample was accurately weighed and thoroughly mixed with 180 mL of sterile distilled water, stored at 4 \u0026deg;C for 24 h, and filtered through four layers of cheesecloth, with the filtrate collected. 40 \u0026mu;L of the filtrate was mixed with 10 mL of trichloroacetic acid and incubated at 4 \u0026deg;C for 12 h to achieve complete precipitation of true protein; the content of nonprotein nitrogen (NPN) was calculated by subtracting the content of true protein nitrogen in the precipitate from total nitrogen (TN). The supernatant after precipitation was collected and centrifuged at 18000\u0026times;g for 15 min at 4 \u0026deg;C, and the supernatant was collected again. The content of free amino acid nitrogen (FAA-N) was determined via the ninhydrin-hydrazine sulfate colorimetric method[17], and that of ammonia nitrogen (NH\u003csub\u003e3\u003c/sub\u003e-N) was determined via the phenol-hypochlorite colorimetric method. The content of peptide nitrogen (Peptide-N) was calculated as the value obtained by subtracting the contents of FAA-N and NH₃-N from the NPN content[18].\u003c/p\u003e\n\u003cp\u003e10 g of the sample was thoroughly mixed with 50 mL of 0.1 mol/L sodium phosphate buffer (pH 6.5), centrifuged at 10000\u0026times;g for 10 min at 4 \u0026deg;C, and the supernatant was collected as the crude enzyme extract. Aminopeptidase activity was determined using L-leucine-4-nitroanilide as the substrate, with the activity unit expressed as the absorbance value at 410 nm per gram of silage dry matter per hour (units/(h\u0026middot;g DM)). Carboxypeptidase activity was determined using L-carboxyphenoxy-L-phenyl-alanine as the substrate, with the activity unit expressed as the amount of free amino acids released per gram of silage dry matter per hour (\u0026mu;mol amino acids/(h\u0026middot;g DM)). Acid proteinase activity was determined using azocasein as the substrate, with the activity unit expressed as the absorbance value at 340 nm per gram of silage dry matter per hour (units/(h\u0026middot;g DM))[19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. 4. Bacterial microbiota analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSilages (5 g per sample) were collected in sterile EP tubes and immediately stored in a \u0026minus;80 \u0026deg;C refrigerator for subsequent bacterial microbiota analysis. DNA was extracted via DNA isolation kits (DP712; Beijing, China) following the standard instructions. After extracting genomic DNA from the samples, following the methods of Zhu et al. (2022), specific primers with barcodes (341F: CCTAYGGGRBGCASCAG and 806R: GGACTACNNGGGGTATCTAAT) were used to amplify the V3-V4 region of the 16S rRNA gene. The PCR procedures were as follows: 98 \u0026deg;C for 1 min for initial denaturation; 30 cycles of 98 \u0026deg;C for 10 s (subsequent denaturation), 50 \u0026deg;C for 30 s (annealing), and 72 \u0026deg;C for 30 s (elongation); and a final extension at 72 \u0026deg;C for 5 min. The PCR products were quantified and qualified first, then purified with a Qiagen Gel Extraction Kit (DP241; Beijing, China). Libraries were prepared and qualified, and finally, paired-end sequencing (PE250) was performed on the Illumina NovaSeq 6000 platform (Novogene Co. Ltd., Beijing, China) to sequence the libraries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. 5. Metabolite analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter freeze-drying, the silage samples were ground into powder. A 100 mg aliquot of sample powder was weighed and placed in a 1.5 mL Eppendorf (EP) tube, followed by the addition of 500 \u0026mu;L of 80% methanol aqueous solution. The mixture was thoroughly vortexed and then placed in an ice bath for 5 minutes. It was subsequently centrifuged at 15,000 \u0026times; g for 20 minutes at 4 \u0026deg;C. The supernatant was collected and diluted to a final methanol concentration of 53%, and the centrifugation step was repeated as described above. The resulting supernatant was collected for LC-MS/MS analysis.\u003c/p\u003e\n\u003cp\u003eMetabolite detection was performed using a Vanquish ultra-high performance liquid chromatography (UHPLC) system (Thermo Fisher, Germany) coupled with a Q Exactive\u0026trade; HF-X mass spectrometer (Thermo Fisher, Germany) in an LC-MS/MS configuration. Chromatographic separation was achieved using a Hypersil Gold column (100 \u0026times; 2.1 mm, 1.9 \u0026mu;m; Thermo Fisher, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. 6. Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreliminary statistical analysis of the data was performed using Microsoft Excel 2010, followed by two-way analysis of variance (ANOVA) using SPSS software (SPSS 26.0, Chicago, USA). Differences were considered statistically significant at P \u0026lt; 0.05. Multiple comparisons of group means were conducted using Duncan\u0026rsquo;s test.\u003c/p\u003e\n\u003cp\u003eAll identified metabolites were annotated using the LIPIDMaps database, KEGG (Kyoto Encyclopedia of Genes and Genomes) database, and HMDB (Human Metabolome Database). Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were employed to explore the differences in metabolic patterns among groups. Differential metabolites between groups were determined by defining the criteria of FC (Fold Change) \u0026gt; 2 or FC \u0026lt; 0.5, VIP (Variable Importance in Projection) \u0026gt; 1, and P \u0026lt; 0.05. Volcano plots were drawn using the R package ggplot2 to show the number of up-regulated or down-regulated differential metabolites, and pathway enrichment analysis was conducted based on the KEGG database using the R package cluster Profiler. All statistical analyses were completed in R software (version 4.5.1).\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3. 1. Fermentation quality of mulberry ensiling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the ensiling process, the pH values of the M, R, and G treatments consistently remained lower than CK (P\u0026lt;0.05), with the R treatment showing the lowest pH and CK the highest at 60 days (P\u0026lt;0.05). LA content increased over time in all treatments. At 60 days, the R treatment had the highest LA content, followed by M, while CK had the lowest (P\u0026lt;0.05). AA and PA contents were significantly higher in the M and R treatments than in the CK and G treatments. BA was not detected in CK, M, or R, but appeared in G after 30 days (Table 1).\u003c/p\u003e\n\u003cp\u003eRegarding microbial populations (Table 2), LAB counts peaked at 15 days across all treatments, with R treatment reaching the highest level(P\u0026lt;0.05), followed by M, and CK the lowest. Yeast and mold counts declined rapidly after 7 days, becoming undetectable (ND) or \u0026lt;2.00 log10cfu/g FM in all treatments post-15 days (P\u0026lt;0.05). Coliform bacteria counts increased initially and then decreased; M/R treatments effectively suppressed coliform proliferation, exhibiting significantly lower counts than CK at 60 days (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eTable 1. Effect of different treatments on the variation of fermentation parameters during mulberry ensiling\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" style=\"width: 315px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDay of ensiling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSEM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u0026times;T\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 56px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.34Aab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e5.43Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.17Abc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.99Acd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.97Ad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.64Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e4.62Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.44Cb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.34Cbc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.29Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.28Dab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e4.38Da\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.19Db\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.07Dc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.99Dc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.03Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e4.84Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.75Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.77Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.78Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 56px;\"\u003e\n \u003cp\u003eLA (%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.85Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e5.43Bab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.34Aab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7.68Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e9.58Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1.51\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.82Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e7.41ABb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e7.90Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e18.44Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e22.00Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.35Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e10.31Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e9.64Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e22.04Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e28.09Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.71Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e7.69ABbc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e7.24Abc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e10.71Bab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e12.58Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 56px;\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003cp\u003e(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.56Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.81Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.93Cb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.09Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.63Da\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.43\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.74Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e2.06Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.67Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8.73Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e10.90Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.25Bd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.34Bd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.17Bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.65Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e6.81Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.73Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.73Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.46Bab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.68Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 56px;\"\u003e\n \u003cp\u003ePA\u003c/p\u003e\n \u003cp\u003e(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.55Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.51Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.91Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.11Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.12Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.53Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.60Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.57Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.20Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.36Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.49Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.54Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.29Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.23Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.97Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 69px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.51Ad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.59Ad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.98Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.77Cb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2.35Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 56px;\"\u003e\n \u003cp\u003eBA\u003c/p\u003e\n \u003cp\u003e(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 43px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 69px;\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.28\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: Different lowercase letters indicate significant differences between different ensiling days in the same treatment, and different uppercase letters indicate significant differences between different treatments in the same ensiling day. SEM: standard error of the means; D: fermentation duration; T: treatment; D\u0026times;T: interaction between fermentation duration and treatment. CK: control; M: adding previously fermented mulberry juice; R: adding previously fermented red clover juice; G: adding previously fermented grape pomace juice. Abbreviations in the following tables are the same means.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 Effects of different treatments on the variation of microbial populations during mulberry ensiling\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"646\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" style=\"width: 294px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDay of ensiling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSEM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 176px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u0026times;T\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eLAB (log10cfu/g FM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.71De\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.90Db\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.66Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.74De\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.19Dd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.39Ad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.62Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e8.00Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.11Be\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.08Bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.29Bd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.32Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e8.26Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.36Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.21Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.86Cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.03Cb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.61Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.98Cb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.73Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eYeast (log10cfu/g FM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.97C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.76B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.17B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.53B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.16B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.22C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.36A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.95A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eColiform bacteria (log10cfu/g FM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.23Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.85Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e7.25Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.16Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.02Ac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.77Ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.75Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.05Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.39Bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.35Cc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.66Da\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.72Ba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.14Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.22Bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.03Dc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.13Bb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.92Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e6.85Aa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.96Ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e5.66Bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eMold (log10cfu/g FM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.23A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.90A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.16A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.66B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e4.03B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.74B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.71C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3.49C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e\u0026lt;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. 2. Effects of pre-fermented juice on protein degradation during the ensiling of mulberry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth ensiling duration and additive treatments significantly modified the nitrogen fraction profiles in mulberry silage (Fig. 1). NPN, NH3-N, and FAA-N contents increased progressively with fermentation time across all treatments. Specifically, R and M treatments effectively inhibited the accumulation of NPN, NH3-N(P\u0026lt;0.05), and FAA-N, with R consistently maintaining the lowest levels of these fractions throughout ensiling(P\u0026lt;0.05). In contrast, the G treatment exerted a weaker inhibitory effect, with NPN, NH3-N, and FAA-N contents remaining comparable to those in CK (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eAcid protease activity decreased significantly with ensiling duration, and no significant differences were observed among treatments (P\u0026lt;0.001). Carboxypeptidase activity also declined over time (P\u0026lt;0.05). CK maintained the highest activity throughout ensiling, while R treatment exhibited the lowest activity at day 60 (20.71%), followed by M and G treatments (P\u0026lt;0.05). Aminopeptidase activity declined sharply with ensiling time, reaching undetectable levels in M and R treatments by day 60. CK retained the highest activity at day 60 (2.25%), whereas R and M treatments significantly suppressed aminopeptidase activity (P\u0026lt;0.05) (Fig. 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. 3. Effects of pre-fermented juices on the microflora of mulberry silage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePCoA results revealed that the bacterial communities of the M and R treatments were distinctly separated from those of the CK during the ensiling process (Fig. 3).\u003c/p\u003e\n\u003cp\u003eAt the phylum level, Proteobacteria and Firmicutes were the dominant bacterial phyla during mulberry ensiling. Following 3 days of ensiling, the relative abundance of Firmicutes increased across all treatments, becoming the dominant phylum in the R and M groups. In contrast, Firmicutes remained at a low level in the CK group throughout fermentation, and while it increased gradually in the G group (from 10.68% to 27.40% by day 30), it did not achieve dominance.At the genus level, \u003cem\u003eEnterobacter\u003c/em\u003e dominated the CK group throughout ensiling, accompanied by low abundances of LAB (e.g., \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eLactococcus\u003c/em\u003e). In CK, the relative abundance of\u003cem\u003e\u0026nbsp;Lactococcus\u003c/em\u003e increased from 2.24% (day 3) to 6.46% (day 15) before declining to 3.97% (day 60). In the G group, \u003cem\u003eEnterobacter\u003c/em\u003e remained dominant, while \u003cem\u003eEnterococcus\u003c/em\u003e abundance increased from 4.22% to 16.72% and \u003cem\u003eLactococcus\u003c/em\u003e from 5.05% to 9.52% between days 3 and 30, with both genera exceeding the levels observed in CK after day 7. In the M group, \u003cem\u003ePediococcus\u003c/em\u003e dominated initially, reaching up to 90.81% by day 7, but was replaced by \u003cem\u003eLactobacillus\u003c/em\u003e as the dominant genus after day 30. \u003cem\u003eEnterococcus\u003c/em\u003e dominated the bacterial community in the R group throughout the entire ensiling process (Fig. 3B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKruskal-Wallis tests revealed significant treatment effects on the relative abundances of key bacterial genera during ensiling (Fig. 4). \u003cem\u003eLactobacillus\u003c/em\u003e differed at days 30 (p = 0.0051) and 60 (p = 0.0065), with R treatment highest at day 60. \u003cem\u003eLactococcus\u003c/em\u003e varied at days 30 (p = 0.056) and 60 (p = 0.031), with CK and G more abundant at day 30 and CK dominant at day 60. \u003cem\u003eEnterobacter\u003c/em\u003e differed at day 60 (p = 0.055), with CK and G higher than M and R. \u003cem\u003ePediococcus\u003c/em\u003e differed at days 3 (p = 0.0066) and 30 (p = 0.006), with G highest at day 3 and CK at day 30. \u003cem\u003eEnterococcus\u003c/em\u003e differed at all time points (p \u0026le; 0.015), with R consistently highest. Overall, treatments (CK, G, M, R) distinctly altered community composition, with the most pronounced effects on \u003cem\u003eEnterococcus\u003c/em\u003e and \u003cem\u003eLactobacillus\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. 4. Effects of pre-fermented juices on the metabolome of mulberry silage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,649 metabolites were identified in mulberry silage during the fermentation process, and this metabolite count was significantly higher than that reported in other conventional silage feedstocks, including alfalfa (167 metabolites)[20], napier grass (426 metabolites)[21], and sorghum (408 metabolites)[22]. Principal component analysis (PCA) demonstrated that both fermentation duration and the type of pre-fermented juice fermentation broth exerted significant effects on the metabolite profiles of mulberry silage, with the M, R, and G treatment groups presenting distinctly separated metabolite distribution patterns throughout the ensiling period. Pathway enrichment analysis further revealed that a large number of metabolites were differentially regulated (either upregulated or downregulated) in each treatment group during fermentation, highlighting the dynamic nature of silage fermentation metabolism. On the 3rd day of fermentation, the R treatment significantly modulated the amino acid biosynthesis pathway, accompanied by marked upregulation of key intermediate metabolites involved in amino acid anabolism, namely citrulline, 4-hydroxy-2-oxoglutaric acid, and pantetheine. Throughout the entire fermentation process, the R treatment persistently and significantly upregulated isoflavonoid compounds such as glycitein, biochanin A, and formononetin, while the M treatment significantly elevated the content of 3,4-dihydroxybenzaldehyde across the whole ensiling stage and notably increased 3-phenyllactic acid levels at the initial fermentation phase. For the G treatment, it significantly regulated arachidonic acid metabolism within the unsaturated fatty acid biosynthesis pathway and substantially enhanced arachidonic acid content in mulberry silage. Comparative metabolomic analysis among the R, G, and M treatments at 3 d, 30 d, and 60 d of fermentation (Table 3) revealed that the R treatment displayed the most pronounced metabolic differences as early as the 3 d fermentation stage, and this treatment significantly upregulated a suite of beneficial metabolites during fermentation, including wogonin, formononetin, glycitein, biochanin A, cordycepin, 2\u0026apos;-deoxyadenosine, ferulic acid, and chlorogenic acid. Among these differential metabolites, the legume-specific isoflavonoids (wogonin, formononetin, glycitein, and biochanin A) in the R treatment exhibited the highest fold changes (log₂FC=3.39~7.80) and variable importance in projection (VIP) values (5.29~5.93) (Table S1).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;3\u0026nbsp;High-frequency differential metabolites in R vs G/M treatments during 3/30/60d silage fermentation\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"546\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 126px;\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 187px;\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003eCompound_ID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMolecular Formula\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eFormononetin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3、30、60(R-G)；3、30(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_716_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC16H12O4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eGlycitein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e30、60(R-G)；3、30(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_941_neg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC16H12O5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eBiochanin A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e30(R-G)；3、30、60(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_2267_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC16H12O5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCordycepin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3、60(R-G)；30(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_327_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC10H13N5O3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eChlorogenic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e30(R-G)；3、60(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_678_neg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC16H18O9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e2\u0026apos;-Deoxyadenosine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3、60(R-G)；30(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_325_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC10H13N5O4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eLithocholic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e30(R-G)；30、60(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_8369_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC24H40O3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eN8-acetylspermidine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e30、60(R-G)；3(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_7772_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC9H21N3O\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eFerulic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e3(R-G)；30、60(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_638_neg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC10H10O4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eWogonin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003e30、60(R-G)；3(R-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCom_17888_pos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eC16H12O5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3. 5. Correlation analysis of bacterial communities with metabolites, fermentation parameters, and nitrogen fractions during the silage fermentation process of mulberry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBacterial communities are the core drivers of feed mulberry silage fermentation. To clarify their regulatory roles in silage metabolite composition, fermentation quality, and protein degradation, correlation analysis was conducted between the top 10 dominant bacterial genes (by relative abundance) and selected differential metabolites（metabolites with significant differences and significant effects on fermentation）, key fermentation parameters, and nitrogen fractions. Results showed that \u003cem\u003ePediococcus\u003c/em\u003e was significantly positively correlated with TN and negatively correlated with protein degradation products such as NPN and FAA-N (P \u0026lt; 0.05); its dominance in the early fermentation stage effectively inhibited excessive protein degradation. \u003cem\u003eEnterococcus\u003c/em\u003e was significantly positively correlated with LA and TN, while negatively correlated with pH and NH₃-N (P \u0026lt; 0.05); it also exhibited positive correlations with metabolites with antioxidant and antibacterial activities (e.g., biochanin A, formononetin). The sustained dominance of \u003cem\u003eEnterococcus\u003c/em\u003e in the R group not only improved silage fermentation quality and reduced protein degradation but also enhanced the antioxidant and antibacterial capacities of silage. \u003cem\u003eEnterobacter\u003c/em\u003e was significantly positively correlated with pH and BA, and negatively correlated with LA, AA, and the aforementioned antioxidant metabolites. As the dominant genus in the CK and G groups, \u003cem\u003eEnterobacter\u003c/em\u003e consumed LA and AA, leading to increased silage pH, deteriorated fermentation quality, and impaired aerobic stability [23]. \u003cem\u003eLactobacillus\u003c/em\u003e was significantly positively correlated with LA, AA, and FAA-N, and negatively correlated with pH, TN, and Peptide-N (P \u0026lt; 0.05); it also showed positive correlations with beneficial metabolites (e.g., biotin, coumaric acid) and a negative correlation with citric acid. Some \u003cem\u003eLactobacillus\u003c/em\u003e (e.g., \u003cem\u003eLactobacillus buchneri\u003c/em\u003e, \u003cem\u003eLactobacillus brevis\u003c/em\u003e) produced AA via hetero-fermentation, which inhibited the oxidative metabolism of nutrients and improved the nutritional value and palatability of silage [24].\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAssessment of silage fermentation primarily relies on measuring pH and determining the levels of organic acids produced [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. During fermentation, the pH values of all treatment groups continuously decreased, with the M, R, and G treatments showing a significantly faster decline than the CK. However, the high pH and low LA concentration in the CK indicate that natural silage struggles to overcome the high buffering capacity of forage mulberry [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In contrast, the M, R, and G treatments demonstrated that the pre-fermented juice could effectively decreased the pH of the ensiling system by promoting the production of LA and other organic acids, thereby inhibiting harmful microorganisms and improving fermentation quality[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Notably, the R treatment in this study was most effective in rapidly reducing acidity and accumulating lactic acid. After 60 days of ensiling, the addition of pre-fermented juice significantly increased the production of AA and PA. Both of these organic acids possess antifungal properties [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], suggesting that pre-fermented juice has the potential to enhance the aerobic stability of forage mulberry silage.\u003c/p\u003e \u003cp\u003eDuring the ensiling process, LAB drive the decrease in pH by converting WSC into LA. LAB possess complex antimicrobial mechanisms and can produce antimicrobial compounds, including bacteriocins, which work together to inhibit harmful microorganisms and thus ensure the quality and stability of the silage [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. All treatments significantly increased the number of lactic acid bacteria, accelerated the inhibition of Yeast and Mold, and more effectively reduced the number of Coliform bacteria. The R treatment showed the best performance in chemical indicators (low pH and high LA content), which is directly related to its establishment and maintenance of the strongest lactic acid bacteria dominance at the microbial level. In contrast, the G treatment showed relatively average performance in both chemical and microbial indicators, which may be due to antagonism between the exogenous lactic acid bacteria and the indigenous microorganisms on the raw material.\u003c/p\u003e \u003cp\u003eColiform bacteria compete with LAB for substrates, leading to nutrient loss and undesirable fermentation in silage [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. As aerobic fungi with poor acid tolerance, mold growth is inhibited by the anaerobic and acidified environment of silage. With the progression of fermentation, the oxygen concentration in the system continuously decreases and the environment becomes increasingly acidified, resulting in no mold detected in the final fermented products. This effectively mitigates the risk of mycotoxin contamination and ensures the safety and stability of silage. Studies have demonstrated that coliform bacteria are difficult to inhibit when pH\u0026thinsp;\u0026gt;\u0026thinsp;4.0 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], while only the R treatment in this study had silage pH\u0026thinsp;\u0026le;\u0026thinsp;4.0, with a significantly lower coliform count than other groups. In summary, pre-fermented juice inhibits harmful microorganisms by regulating pH and the fermentation environment, thereby effectively improving the fermentation quality and safety of mulberry silage.\u003c/p\u003e \u003cp\u003eWhen ensiling forages or woody plants with high protein content, a major challenge is the rapid and extensive protein degradation that can occur both before and during fermentation[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. During the ensiling process, the synergistic action of plant proteases and microorganisms is the primary cause of protein degradation and the consequent decline in forage quality. This process typically occurs in two stages. First, endogenous plant proteases hydrolyze proteins into peptides and free amino acids. Subsequently, microorganisms further deaminate these products, generating ammonia, amines, and other non-protein nitrogen compounds, resulting in a waste of protein resources [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Therefore, changes in nitrogen fractions can effectively elucidate the dynamics of protein degradation during the ensiling process [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, at least three types of proteolytic enzymes are present in forage crops: acidic proteinases, carboxypeptidases, and aminopeptidases [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Changes in the activities of these enzymes can also serve as indicators of the extent of protein degradation during anaerobic fermentation. The superior performance of the R group may be attributed to its unique components and multiple mechanisms of action. First, the abundant polyphenol oxidase in red clover directly protects proteins[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Second, the addition of fermentation liquid accelerates acidification in the system, inhibiting the activity of acid-sensitive proteases such as aminopeptidases. In addition, the fermentation liquid may introduce secondary metabolites such as plant tannins, which can bind to and inhibit protease activity [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Furthermore, the treatment may also suppress the proliferation of harmful microorganisms such as Escherichia coli, reducing the deamination of amino acids. These mechanisms work together to slow down the protein degradation pathway.\u003c/p\u003e \u003cp\u003eSilage fermentation is fundamentally a process of microbial community succession, which directly determines fermentation quality [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. PCoA results from this study showed clear separation of microbial communities among all treatment groups, indicating that pre-fermented juice differentially regulates the bacterial structure of mulberry silage. Firmicutes, which include acid-producing bacteria, are essential for silage, while Proteobacteria contain many undesirable microbes that cause nutrient loss [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In natural silage, Firmicutes typically increase and become dominant, but this pattern was not observed in the CK, likely due to the woody feature of the mulberry. Both M and R treatments significantly increased the abundance of Firmicutes, with the R group exceeding 70 per cent by the end of fermentation. This suggests that M and R treatments optimize silage fermentation by promoting Firmicutes and inhibiting Proteobacteria. The effectiveness of silage fermentation largely depends on the activity of LAB. Numerous studies have confirmed that LAB play a crucial role throughout the entire anaerobic fermentation process by optimizing fermentation characteristics, enhancing the diversity of beneficial microorganisms, and inhibiting the proliferation of pathogenic microbes[\u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. These actions significantly improve the quality of fermented feed. The core functional species primarily include \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eLactiplantibacillus\u003c/em\u003e, \u003cem\u003ePediococcus\u003c/em\u003e, \u003cem\u003eLactococcus\u003c/em\u003e, and \u003cem\u003eBacillus\u003c/em\u003e [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, the dominant bacterial genus in the CK was \u003cem\u003eEnterobacter\u003c/em\u003e. As a facultative anaerobe, \u003cem\u003eEnterobacter\u003c/em\u003e competes with LAB for fermentation substrates and produces ammonia and biogenic amines through amino acid deamination and decarboxylation reactions. This not only reduces the nutritional value of silage but also negatively affects its palatability [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. These findings indicate that natural ensiling of mulberry forage is less efficient, with LAB struggling to dominate the fermentation process. According to the succession patterns of the fermentation microbiota, genera such as \u003cem\u003eWeissella\u003c/em\u003e and \u003cem\u003ePediococcus\u003c/em\u003e, which are dominant LAB in the early stage of ensiling, can initially participate in fermentation but are less acid-tolerant. As LA accumulates and the environmental pH continues to decrease, their activity is gradually inhibited, and they are subsequently replaced by more acid-tolerant LAB [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In the R treatment group, the direct enhancement of \u003cem\u003eEnterococcus\u003c/em\u003e abundance allowed this genus to dominate the bacterial community throughout the fermentation process, effectively suppressing the proliferation of undesirable bacteria and maintaining relatively low bacterial diversity. It is noteworthy that \u003cem\u003eEnterococcus\u003c/em\u003e, as a homofermentative LAB, is commonly used as a silage inoculant [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Its increased abundance during anaerobic fermentation is of practical importance for promoting acidification and improving fermentation quality. Although the addition of G increased the relative abundance of both \u003cem\u003eEnterococcus\u003c/em\u003e and \u003cem\u003eLactococcus\u003c/em\u003e, it did not enable LAB to dominate the microbial community. This may be attributed to antagonistic interactions between the LAB in grape pomace fermentation liquid and the indigenous microbial community on the surface of mulberry forage, preventing LAB from becoming the dominant group during the ensiling process [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].This study confirmed that naturally occurring LAB struggle to dominate the microbial community during mulberry silage fermentation. Both M and R treatments effectively promoted LAB growth, establishing their dominance while significantly reducing the relative abundance of Enterobacter. Pre-fermented juices prepared from different materials showed distinct regulatory effects on the silage microbial community.\u003c/p\u003e \u003cp\u003eThe remarkable discrepancy in metabolite abundance between mulberry silage and other silage types is closely associated with the unique physicochemical and compositional traits of mulberry as a silage raw material, while the distinct metabolic profiles observed in the M, R, and G treatments confirm that these three pre-fermented juice formulations regulate silage fermentation via disparate metabolic regulatory pathways.\u003c/p\u003e \u003cp\u003eThe widespread differential regulation of metabolites in each treatment group validates that silage fermentation is a highly dynamic biological process involving simultaneous metabolite biosynthesis and degradation[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and pathway enrichment analysis serves as a pivotal tool to decipher the underlying metabolic mechanisms driving this process. The significant upregulation of 4-hydroxy-2-oxoglutaric acid (a core precursor in the glutamate biosynthesis pathway) under the R treatment at the early fermentation stage is a critical metabolic event, as glutamate acts as a premium nitrogen source for LAB, effectively facilitating the proliferation of beneficial microorganisms, accelerating LA accumulation, and consequently lowering silage pH [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]; this metabolic mechanism fully accounts for the significantly higher LA content in the R group relative to other treatments during the initial fermentation phase. The sustained upregulation of legume-derived isoflavonoids (glycitein, biochanin A, formononetin) in the R treatment throughout fermentation is conducive to silage quality preservation, as these compounds possess broad-spectrum antimicrobial and antioxidant stress properties [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], which enhance the antioxidant capacity of mulberry silage, suppress the proliferation of undesirable microorganisms, and thereby improve fermentation stability and overall quality. For the M treatment, the persistent upregulation of 3,4-dihydroxybenzaldehyde (a phenolic metabolite derived from amino acid metabolism) delivers dual benefits for silage fermentation and animal health: this compound not only optimizes fermentation quality via antioxidant and nutrient-protective effects, but also mitigates oxidative stress, alleviates inflammatory responses, and modulates gut microbiota composition to boost animal health [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] additionally, the increased 3-phenyllactic acid content at the initial fermentation stage inhibits the growth of spoilage miscellaneous bacteria via its intrinsic antimicrobial activity, promoting the smooth and efficient initiation of mulberry silage fermentation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The G treatment-mediated enhancement of arachidonic acid content enriches the nutritional value of mulberry silage, as arachidonic acid is an essential polyunsaturated fatty acid for animals, and its free form participates in vital physiological processes including anti-cancer activity, inflammatory modulation, and immune regulation, effectively reducing disease risk and mortality [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe early-onset significant metabolic differences in the R treatment at 3 d fermentation indicate that this formulation has a robust metabolic foundation for rapidly triggering high-quality silage fermentation, with its core superiority over the G and M treatments lying in the targeted enrichment of beneficial metabolites. Specifically, the high-abundance isoflavonoids in the R treatment scavenge free radicals in the fermentation system, specifically inhibit the growth of spoilage bacteria such as Clostridium spp., and form stable protein complexes to achieve antioxidant protection and nutrient retention[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], meanwhile, N8-acetylspermidine promotes protein synthesis by stabilizing protein spatial conformation and optimizes microbial metabolism to foster a favorable microenvironment for beneficial bacterial proliferation [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], cordycepin acts as an energy metabolism precursor to improve energy utilization efficiency and accelerate the proliferation of LAB and other beneficial bacteria [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], and chlorogenic acid (a phenylpropanoid compound) further reinforces the protective effects via its strong antioxidant, antibacterial, and free radical-scavenging activities[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Collectively, the synergistic action of these upregulated beneficial metabolites in the R treatment constitutes the key metabolic mechanism underlying its superior performance in inhibiting undesirable microbial growth, minimizing nutrient loss, and elevating the overall quality of mulberry silage.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eDifferent pre-fermented juices regulated the bacterial community structure and metabolite composition during mulberry ensiling in distinct ways, thereby modulating the protein degradation process, and the R treatment exhibited the optimal regulatory effect. This treatment not only significantly promoted LA synthesis and led to a rapid drop in the pH of the silage system, but also optimised the microbial community structure by enriching dominant LAB, such as \u003cem\u003eEnterococcus\u003c/em\u003e, and inhibiting the proliferation of harmful bacteria, including \u003cem\u003eEnterobacter\u003c/em\u003e. Meanwhile, it markedly upregulated beneficial isoflavonoid metabolites (wogonin, formononetin, glycitein and biochanin A) and effectively suppressed protease activity, ultimately exerting a synergistic effect to reduce protein loss during ensiling to a great extent. The M and G treatments also improved the fermentation quality of mulberry silage, yet their regulatory effects were inferior to those of the R treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eDuring the preparation of this work, the author(s) used Grammarly in order to find the language and grammatical errors and improve the manuscript accordingly. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit Author Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.L.C: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, visualization, investigation, data curation; G.H.X: Methodology, Writing \u0026ndash; review \u0026amp; editing,investigation, data curation; Y.Y.Y, F.R.H, Y.G: Methodology, conceptualization; Y.L.Z, Y.X.X, H.S: Resources, Funding acquisition; C.C, F.Y.Y: Supervision, resources, Funding acquisition; J.H: Supervision, resources, funding acquisition, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Key R\u0026amp;D Program of China (2022YFD1300901) the National Natural Science Foundation of China (32460359); the Guizhou Provincial Science and Technology Project (Qian Ke He Platform Talent \u0026ndash; BQW [2024] 003)； the Guizhou University National Leading Talents Research Initiative (GZU Leading Talents Document (2023) No. 05); the Central Financial Project for Agricultural Ecological Resources Conservation (Comprehensive Utilization of Crop Straw), No. GZMD2025-P282-1\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYan CH, Chen FH, Yang YL, Shen LW, Xun XM, Zhang ZA, et al. 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Molecules. 2022;27(11):3400.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"chemical-and-biological-technologies-in-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Chemical and Biological Technologies in Agriculture](https://chembioagro.springeropen.com/)","snPcode":"40538","submissionUrl":"https://submission.nature.com/new-submission/40538/3","title":"Chemical and Biological Technologies in Agriculture","twitterHandle":"@SpringerPlants","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pre-fermented juice, Silage, Protein preservation, Metabolite","lastPublishedDoi":"10.21203/rs.3.rs-9200621/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9200621/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Mulberry ( L.) is a valuable woody protein feed that alleviates protein feed shortages, yet its silage production faces key challenges including high moisture content, scarce native lactic acid bacteria, and severe protein degradation. This study innovatively adopted alternative raw materials to prepare pre-fermented juices, with grape pomace pre-fermented juice (treatment G) and red clover pre-fermented juice (treatment R) compared against mulberry pre-fermented juice (treatment M) and an untreated control (CK). Combined with bacterial community and metabolomic analyses, we evaluated the effects of these treatments on mulberry silage quality over a 60-day ensiling period. Results showed that treatment R delivered the best performance: it enriched , upregulated isoflavonoids including formononetin, glycitein and biochanin A, reduced silage pH to 3.99, increased lactic acid content, and inhibited protein degradation by suppressing protease activities. Treatment M promoted the growth of and the accumulation of beneficial metabolites such as 3,4-dihydroxybenzaldehyde, while treatment G showed moderate effects. All pre-fermented juices improved silage fermentation quality and nutrient retention. This study clarifies the microbial-metabolite regulatory mechanisms underlying mulberry ensiling, provides a low-cost and eco-friendly silage production technology, and promotes the sustainable utilization of mulberry in ruminant production.","manuscriptTitle":"Integrated analysis of microbiome and metabolomics: mechanism of different pre-fermented juice regulating protein degradation during mulberry silage","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 18:39:49","doi":"10.21203/rs.3.rs-9200621/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-24T11:37:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-24T02:45:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T10:10:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329681183517959424784982285291060843136","date":"2026-04-12T07:37:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T02:45:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109520479228670678507795693010765731496","date":"2026-04-10T01:36:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126236740002806014981313301914138619047","date":"2026-04-09T13:30:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T12:54:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-01T06:18:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-31T15:56:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chemical and Biological Technologies in Agriculture","date":"2026-03-29T05:35:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"chemical-and-biological-technologies-in-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Chemical and Biological Technologies in Agriculture](https://chembioagro.springeropen.com/)","snPcode":"40538","submissionUrl":"https://submission.nature.com/new-submission/40538/3","title":"Chemical and Biological Technologies in Agriculture","twitterHandle":"@SpringerPlants","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f55fde59-692e-494b-a1dc-1e9a901a3dc9","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T13:24:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 18:39:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9200621","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9200621","identity":"rs-9200621","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}