Microbial Community Structure and Carbon-Nitrogen Coupling Mechanisms in Mixed Silage of Oats and Forage Peas in Corral of the Qinghai-Tibet Plateau

Microbial Community Structure and Carbon-Nitrogen Coupling Mechanisms in Mixed Silage of Oats and Forage Peas in Corral of the Qinghai-Tibet Plateau | 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 Microbial Community Structure and Carbon-Nitrogen Coupling Mechanisms in Mixed Silage of Oats and Forage Peas in Corral of the Qinghai-Tibet Plateau ZHAO Yajiao, MA Yuyan, XU Chengmei, LIN Gang, WU Tao, WANG Shitao, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7436223/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Seasonal forage shortages pose a significant challenge to livestock production on the Qinghai-Tibet Plateau. To address this issue, this study developed an integrated land utilization strategy combining "cultivation + on-site ensiling" using mixed oats and forage peas. The research evaluated how different mixed-cropping ratios and lactic acid bacteria (LAB) inoculation affect silage production in this high-altitude region. Results In silage grown in corral plots, the 1:1 oat-pea ratio (OP) showed clear advantages over monocropped oats, increasing crude protein by 29.43% while reducing acid detergent fiber (ADF) by 14.37% and neutral detergent fiber (NDF) by 11.21%. LAB inoculation improved the fermentation quality of corral-grown silage. In inoculated oat silage, the relative abundance of Lactiplantibacillus increased significantly to 66.54%, which suppressed spoilage bacteria (e.g., Hafnia-Obesumbacterium ) and reduced the ammonia nitrogen-to-total nitrogen ratio by 15–20%. The OP treatment minimized dry matter loss among corral-grown silages. LAB inoculation increased propionic and acetic acid production by 25%. Furthermore, functional fungi (e.g., Pleurotus , reaching 7.94% relative abundance in inoculated OP2 silage) contributed to fiber degradation. Metabolic prediction indicated that LAB inoculation increased nitrogen compound degradation by 17% and stimulated secondary metabolite synthesis. Bacterial communities correlated with soluble carbohydrate and lactic acid levels, whereas fungal communities regulated fiber breakdown. Redundancy analysis showed that fiber content explained over 50% of fungal community variation in corral silage. Conclusions The 1:1 oat-pea ratio with LAB inoculation optimizes silage production specifically for corral systems, achieving carbon-nitrogen balance and microbial synergy. This corral-based approach provides a sustainable solution for alpine livestock resilience, transforming underutilized confinement areas into high-quality forage resources. silage lactic acid bacteria mixed-cropping oat pea Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Background The Qinghai-Tibet Plateau serves as China's crucial ecological barrier and primary pastoral zone. This region has a distinct alpine climate with three key features: high elevation, low temperatures, and brief growing seasons. Haiyan County in Qinghai Province shows these characteristics most markedly. Here, natural grasslands remain productive for fewer than 120 days annually. This limited growing window drastically reduces forage availability and hinders supplemental feeding programs[ 1 ]. Currently, the region suffers from acute winter-spring forage deficits. Local livestock production relies extensively on imported winter fodder. This dependence carries substantial financial and operational risks, severely limiting sustainable development of animal husbandry operations[ 2 ]. Concurrently, rapid population growth and livestock expansion on the Qinghai-Tibet Plateau have intensified human impacts. Overgrazing, excessive fencing, and grassland conversion have accelerated ecosystem degradation. These pressures reduce grass diversity, compact soils, and diminish water retention. Such changes critically threaten steppe ecosystem functions[ 3 ]. Furthermore, national conservation policies strictly prohibit natural grassland conversion to cropland. They also restrict large-scale artificial grassland development. These constraints make improved forage self-sufficiency critical. The challenge lies in boosting production without expanding cultivation areas or exceeding ecological limits. This balance is essential for sustainable grassland management and pastoral development. The Qinghai-Tibet Plateau faces dual pressures from ecological conservation needs and grassland degradation. Developing integrated cultivated grassland systems on idle lands offers a viable solution to forage shortages. Particularly promising are corral lands - the nutrient-rich residual areas left after winter livestock confinement. These spatially isolated parcels typically lie fallow after herds move to summer pastures. Unmanaged corral lands suffer several ecological impacts. Exposed soils lose nutrients through leaching while becoming vulnerable to weed invasions and pest infestations. This degradation leads to progressive soil erosion and resource depletion. However, strategic forage cultivation in these areas can reverse these trends. Implementing corral land forage systems provides multiple advantages. The vegetation cover enhances summer-autumn ground protection and aids ecological restoration. Simultaneously, it enables local production of quality winter silage for ruminants. This approach boosts forage output without expanding cultivation areas while supporting sustainable grassland management.Recent studies confirm the effectiveness of mixed cropping systems using cold-tolerant species. Oats ( Avena sativa ), triticale ( Triticosecale ), and forage peas ( Pisum sativum ) demonstrate particularly stable biomass yields and excellent ensiling characteristics under plateau conditions.[ 4,5 ]. Consequently, the integrated system of "corral land cultivation with on-site ensiling" represents an innovative strategy for enhancing grassland resource utilization in high-altitude pastoral regions. Successful silage production in high-altitude alpine regions must account for three critical factors: rapid plant growth, nutritional complementarity, and fermentation stability. Oats, a grass species renowned for their environmental adaptability and high biomass yield, serve as an ideal substrate due to their high soluble carbohydrate content[ 6] . In contrast, leguminous plants such as forage peas supply high levels of crude protein and non-starch polysaccharides, which serve as both a nitrogen source and fermentable carbon substrates[ 7] . The oat-pea intercropping system confers multiple advantages. This approach enhances the overall nutritional profile and optimizes the feedstock's carbon-to-nitrogen (C/N) ratio. A balanced C/N ratio fosters the proliferation of lactic acid bacteria while simultaneously suppressing spoilage microorganisms, thereby significantly improving silage quality[5, 8] .Studies indicate that a 1:1 oat-to-pea ratio achieves optimum nutritional balance and fermentation stability, promoting lactic acid bacteria (LAB) populations to over 80% relative abundance. This microbial dominance effectively suppresses harmful bacteria such as Clostridium spp., establishing this combination as a highly efficient forage system [8]. However, the low temperatures (15–20°C) typical of the Qinghai-Tibet Plateau hinder natural fermentation. Under these conditions, indigenous lactic acid bacteria (LAB) exhibit low population densities and reduced metabolic activity, leading to delayed acidification and increased susceptibility to spoilage microorganisms. These issues are compounded in legume-dominant mixtures by their higher protein content[ 9 ]. The inoculation of tailored lactic acid bacteria (LAB) strains, such as Lactiplantibacillus plantarum and Pediococcus pentosaceu s, effectively mitigates these limitations. These microbial additives enhance fermentation by accelerating acidification[ 10] , modifying the microbial community structure[ 11 ], and ultimately improving forage safety and storage stability. Therefore, this study was conducted in the corral lands of Haiyan County on the Qinghai-Tibet Plateau. Using oats and forage peas as the experimental forage combination, we systematically designed silage treatments with varying mixed cropping ratios and with or without lactic acid bacteria (LAB) inoculation. By measuring physicochemical parameters, conducting high-throughput microbial sequencing, and predicting metabolic functions, this study comprehensively evaluated how these treatments affect silage nutritional quality and microbial community structure. The primary objectives of this study were to elucidate the synergistic mechanisms by which mixed cropping ratios and lactic acid bacteria (LAB) inoculation improve silage quality, and to delineate the role of LAB in regulating microbial functional expression and carbon‑nitrogen metabolic pathways. Ultimately, this research aims to establish a scientific foundation and practical methodology for enhancing corral land utilization and producing high‑quality silage in alpine pastoral regions. This work not only advances the theoretical framework of grass‑legume mixed cropping systems with silage regulation, but also provides a scalable model for sustainable forage production in cold environments. Materials and methods 1.1 Overview of the experimental site The experimental site was located in the corral lands of Haiyan County, within the Haibei Tibetan Autonomous Prefecture of Qinghai Province (36.93°N, 100.86°E; altitude: 3132.0 m). The region experiences a plateau sub-arid climate, characterized by dry and windy springs, cool summers, brief autumns, and prolonged winters. The mean annual temperature is 1.5 °C, with approximately 2980 hours of sunshine per year. A true frost-free period is absent, and natural disasters including hail, frost, drought, and sandstorms are common. Precipitation and temperature records for Haiyan County in 2024 are provided in Figure 2. 1.2 Test materials The test oat variety was selected as "Qingyin No.1 (Avena sativacv, cv. QingyinNo.1)", It's an early-maturing variety. and the forage pea variety was "QingjianNo.1" ( Pisum sativum cv. QingjianNo.1)., which was provided by Grassland Research Institute of Qinghai Academy of Animal Husbandry and Veterinary Sciences. Lactic acid bacteria group: freeze-dried Lactic acid bacteria including Lactobacillus plantarum , Lactobacillus buchneri , Pediococcus pentosaceus , provided by Shandong Weikai Haisi Bioengineering Co.(Location, China). 1.3 Experimental design and methods 1.3.1 Planting and management The experiment was initiated in mid-May 2024 using a randomized block design. Three oat–forage pea mixed cropping ratios were evaluated: O2P (oat:pea = 2:1), OP (oat:pea = 1:1), and OP2 (oat:pea = 1:2). Monocultures of oat (MO) and forage pea (MP) served as controls. Each treatment was replicated three times, with individual plot dimensions of 6 m × 11m (66 m²). Seeding rates for monoculture oat and pea were based on locally recommended rates for forage production. For the 1:1 mixed cropping treatment (OP), the oat seeding rate was reduced to 50% of the monoculture rate (93.75 kg/ha), while the forage pea seeding rate was similarly set to 50% of its monoculture rate (60 kg/ha). Detailed seeding rates for all treatments are summarized in Table 1. Seeds were broadcast by hand, and no further field management was applied during the experiment. Table 1 Mixiture ratio and cropping amount of oats and peas Code Mixture radio Seeding rate (kg/ha) Oat Pea MO 1:0 187.5 0 O2P 2:1 125 40 OP 1:1 93.75 60 OP2 1:2 62.5 80 MP 0:1 0 120 1.3.2 Silage preparation Forage was harvested when oats reached the milk-ripe stage and peas were at the flowering stage, maintaining a stubble height of 5 cm. Oats and peas were harvested as a mixed stand according to the predetermined cropping ratios. The harvested forage was chopped to a uniform length of 2–3 cm for wrapped silage production. Two silage processing methods were employed: direct ensiling (without additives) and ensiling with lactic acid bacteria (LAB) inoculation. The untreated silage treatments were labeled as MO, O2P, OP, OP2, and MP, corresponding to their respective cropping systems. For the LAB-inoculated treatments, freeze-dried LAB powder (containing 2 × 10⁹ CFU/g) was dissolved in sterile distilled water and applied evenly to the chopped forage. Control (non-inoculated) groups received an equivalent amount of sterile distilled water to maintain uniform moisture conditions. The final LAB concentration in inoculated silage was 2 × 10⁵ CFU per gram of fresh matter (FM). These treatments were designated as LMO, LO2P, LOP, LOP2, and LMP, respectively. For each treatment, 500 g of processed forage was packed into polyethylene bags (26 cm × 35 cm) and vacuum-sealed. Each treatment was replicated three times. Silage nutritional composition and fermentation parameters were analyzed after 45 days of ensiling. 1.3.3 Raw material profile The raw materials were initially dried at 105 °C for 1 hour to arrest biological activity, followed by further drying at 70 °C until constant weight was achieved for accurate dry matter determination. Nutritional composition was subsequently assessed, and the results are summarized in Table 2. Table 2 Nutritional quality of mixed cropping oats and peas used in this study as raw materials CP(%DM) EE(%DM) NDF(%DM) ADF(%DM) Ash(%DM) MO 8.08 2.15 52.54 28.84 10.47 O2P 9.42 2.69 51.42 27.72 9.74 OP 9.98 3.37 47.51 25.75 8.16 OP2 10.64 3.63 45.88 25.41 8.66 MP 13.86 4.04 37.61 22.05 9.02 1.4 Indicator Measurement and Methods 1.4.1 Fermentation quality A 10 g sample of silage was homogenized with 90 mL of distilled water and shaken continuously for 24 hours. The resulting slurry was filtered through four layers of gauze followed by qualitative filter paper to obtain a clear extract for fermentation analysis. The pH of the extract was immediately measured using a calibrated pH meter. For organic acid analysis, a 1 mL aliquot was filtered through a 0.22 μm membrane into a vial and subjected to high-performance liquid chromatography (HPLC) for quantification of lactic acid (LA), acetic acid (AA), propionic acid (PA), and butyric acid (BA). Ammonia nitrogen (AN) was determined according to the method of Broderick and Kang. [ 12] . The dry matter (DM) content was determined by drying a representative silage sample to constant weight in a 65°C oven[ 13] . The dry matter loss (DML) rate was calculated according to the following formula: where DML represents dry matter loss, M1 stands for the dry matter content before ensiling, and M2 stands for the dry matter content after ensiling. 1.4.2 Nutritional quality Silage samples were dried to constant weight at 70 °C using a forced-air oven, then ground and homogenized for nutritional analysis. Crude protein (CP) content was determined by the Kjeldahl method[ 14 ]. Neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined according to the method of Van Soest et al[ 15 ],. Water-soluble carbohydrate (WSC) content was determined using the Somogyi method [ 16 ]. 1.4.3 Microbiological analysis Total genomic DNA was extracted from 0.5 g of each sample using the Omega DNA extraction kit (Cat. No. M0491L, BioTek) according to the manufacturer's protocol. The integrity of the extracted DNA was assessed via 0.8% agarose gel electrophoresis, and concentration was quantified using a Nanodrop spectrophotometer. Bacterial and fungal community profiles were analyzed by Illumina MiSeq sequencing. The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified with primers 341F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGGTWTCTAAT). For fungal communities, the ITS1 region was amplified using primers ITS1F (GGAAGTAAAAGTCGTAACAAGG) and ITS2R (GCTGCGTTCTTCATCGATGC). Raw sequencing data were processed and analyzed using QIIME 2 (v2019.4). 1.5 Data analysis Data were collated and statistically summarized using Microsoft Excel 2019. Significance tests and two-way analysis of variance (ANOVA) were carried out with SPSS 24.0, followed by Tukey’s honestly significant difference test for multiple comparisons. Results are expressed as arithmetic means, and figures were prepared using Origin 2021. Differences were considered statistically significant at p < 0.05, highly significant at p < 0.01, and marginally significant (indicating a trend) at 0.05 ≤ p < 0.10. Mantel tests were conducted in R using the linkET package to assess direct and indirect relationships between microbial communities and silage traits including nutritional and fermentation parameters. Metabolic functional profiles of bacterial and fungal communities were predicted using the Metabolic Prediction Tool developed by Shanghai Parsonage. Results and analysis 2.1 Nutritional quality 2.1.1 Soluble carbohydrate and crude protein content As shown in Figure 3A, in the absence of lactic acid bacteria (LAB) inoculation, the monocropped oat (MO) treatment exhibited the highest water-soluble carbohydrate (WSC) content, while the monocropped pea (MP) treatment showed the lowest WSC content among non-inoculated groups. Within non-inoculated treatments, the WSC contents in the O2P, OP, and OP2 groups were significantly higher than that in the MP group by 25.48%, 18.18%, and 10.84%, respectively (p < 0.05). Under LAB inoculation, the WSC content was further increased: the O2P, OP, and OP2 groups showed increases of 36.32%, 25.84%, and 14.03%, respectively, compared to the MP group (p < 0.05). Figure 3B shows that the crude protein (CP) content increased with the proportion of peas in the mixture. In non-inoculated treatments, the CP content of the O2P, OP, and OP2 groups was significantly higher than that of the MO group by 11.23%, 29.43%, and 39.50%, respectively (p < 0.05). Similarly, under LAB inoculation, the O2P, OP, and OP2 groups also exhibited significantly greater CP content than the MO group (p < 0.05). 2.1.2 Acid/neutral detergent fiber content As shown in Figures 4A and 4B, in non-inoculated treatments, the acid detergent fiber (ADF) content was significantly lower in the O2P, OP, and OP2 groups than in the monocropped oat (MO) group, with reductions of 12.34%, 14.37%, and 26.33%, respectively (p < 0.05). Similarly, the neutral detergent fiber (NDF) content was significantly reduced in these mixed-cropping groups relative to the MO group by 4.80%, 11.21%, and 29.83%, respectively (p < 0.05). Under LAB inoculation, the ADF content remained significantly lower in the O2P, OP, and OP2 groups compared to the MO group, with decreases of 10.37%, 12.74%, and 34.38% (p < 0.05). A similar trend was observed for NDF content, where the O2P, OP, and OP2 groups showed significant reductions of 6.85%, 12.11%, and 27.81%, respectively, relative to the MO group (p < 0.05). 2.2 Fermentation quality For the ammonia nitrogen/total nitrogen (AN/TN) ratio (Figure 5B), LAB-inoculated treatments exhibited significantly lower values than non-inoculated treatments at the same mixed cropping ratio. Dry matter loss (DML) (Figure 5C) was highest in the MP group and lowest in the OP group under non-inoculated conditions, while under LAB inoculation, the OP2 group showed the highest DML with the OP group remaining the lowest across all treatments. Regarding lactic acid (LA) content (Figure 5D), the lowest values in non-inoculated treatments were observed in the O2P group, whereas the highest LA content under LAB inoculation occurred in the MO group. Additionally, acetic acid (AA) (Figure 5E) and propionic acid (PA) (Figure 5F) contents were significantly higher in LAB-inoculated than in non-inoculated treatments. 2.3 Changes in microbial community structure 2.3.1 Relative abundance of bacterial and fungal species composition Figure 6A illustrates significant variation in the relative abundance of dominant bacterial genera across silage treatments. In non-inoculated groups, Lactiplantibacillus (32.78%) and Lentilactobacillus (18.46%) dominated the MO treatment, with Hafnia-Obesumbacterium comprising 17.37%. The OP treatment was characterized by Lentilactobacillus (19.11%) and Hafnia-Obesumbacterium (18.83%). In O2P, Lactiplantibacillus (30.05%) and Lentilactobacillus (27.07%) constituted the core taxa, while MP was co-dominated by Hafnia-Obesumbacterium (24.91%), Lactiplantibacillus (19.89%), and Lentilactobacillus (28.51%). LAB inoculation markedly shifted bacterial community structure. The LMO treatment showed a substantial increase in Lactiplantibacillus (66.54%). In LO2P, Lactiplantibacillus remained dominant (66.24%), with Lentilactobacillus at 12.07%. The LOP2 treatment exhibited synergistic dominance of Lactiplantibacillus (47.99%) and Lentilactobacillus (42.91%), together exceeding 90% of the community. In LMP, Lactiplantibacillus became the dominant genus. Fungal community composition also varied considerably across treatments (Figure 6B). In non-inoculated groups, MO was dominated by Wickerhamomyces (30.61%) and Cladosporium (11.04%). OP showed increased Cladosporium (15.93%) and Fusarium (3.02%), with Wickerhamomyces at 19.88%. O2P was dominated by Plectosphaerella (21.04%), followed by Vishniacozyma (14.99%). OP2 was characterized by Wickerhamomyces (16.41%), Cladosporium (13.88%), and Alternaria (14.24%). MP showed distinctively high abundances of Pseudopeyronellaea (5.26%) and Pleurotus (5.07%), with Wickerhamomyces at 23.37%. LAB inoculation induced clear shifts in fungal communities. LMO showed increased Alternaria (14.59%), Aspergillus (5.33%), and Pleurotus (5.05%). LO2P exhibited the highest Wickerhamomyces abundance (43.38%) among all treatments, while Plectosphaerella decreased sharply to 1.14%. LOP had higher Wickerhamomyces and Aspergillus but reduced Cladosporium (8.21%). LOP2 showed the highest Pleurotus abundance (7.94%) and reduced Alternaria . LMP displayed increased Wickerhamomyces and Aspergillus but the lowest Fusarium abundance. Genus-specific dominance patterns were evident: Plectosphaerella in O2P, Alternaria in OP2, Pseudopeyronellaea and Pleurotus in MP, and Cephalotrichum and Vishniacozyma in MO. 2.3.2 Bacterial and fungal α-diversity Figure 7 displays the alpha diversity of bacterial communities in silage samples under different oat-pea mixed cropping ratios, with and without lactic acid bacteria (LAB) inoculation. Statistical analysis indicated significant differences in the Chao1 index between LAB-inoculated and non-inoculated groups, suggesting that LAB inoculation reduced bacterial species richness. Good’s coverage index was consistently high across all treatments but differed significantly between groups (P = 0.030). The Faith_pd index showed distinct distribution patterns between inoculation groups, though this difference was not statistically significant (P = 0.130). Significant differences were observed in both the Shannon index (P = 0.004) and Pielou’s evenness index (P = 0.004), reflecting variations in community diversity and evenness. The observed species index showed a trend toward significance (P = 0.071). Figure 8 shows the alpha diversity of fungal communities in silage samples across various oat-pea mixed cropping ratios, with and without lactic acid bacteria (LAB) inoculation. The Chao1 index exhibited a non-significant trend between inoculation groups (P = 0.09), despite visible differences in distribution. Good’s coverage was consistently high across treatments, with no significant difference between groups (P = 0.29). Similarly, no significant differences were observed in the Pielou evenness, Shannon, Simpson, or observed species indices. 2.2.3 Bacterial and fungal β-diversity As shown in Figure 9, the stress values for both bacterial (Stress = 0.076) and fungal (Stress = 0.121) community ordination were below 0.2, indicating reliable representation of multivariate patterns. For bacterial communities, the MDS1 axis revealed clear separation between LAB-inoculated and non-inoculated groups. Fungal communities also showed substantial compositional shifts in response to LAB inoculation across treatments. Specifically, LMO and LOP clustered closely along both MDS1 and MDS2 axes, while LMP formed a distinct cluster. Furthermore, LOP2 was clearly separated from all other groups along the MDS3 axis. 2.2.4 Key species differences and marker species analysis Significant differences in genus-level composition were observed for both bacterial and fungal communities across the silage treatments. In bacterial communities (Figure 10A), clear distinctions were evident between LAB-inoculated and non-inoculated groups. Lactiplantibacillus increased substantially across all LAB-inoculated treatments, with the most pronounced increases occurring in the MO and OP groups. The abundance of Lentilactobacillus was influenced by cropping ratio: it increased slightly in the OP2 treatment after LAB inoculation but decreased in other groups. Hafnia-Obesumbacterium showed the greatest reduction in the MP treatment following LAB addition. Additionally, sequences assigned to Chloroplast and Mitochondria were significantly more abundant in the LMP treatment, while rare genera such as Citrobacte r were relatively enriched in LO2P. For fungal communities (Figure 10B), Wickerhamomyces was strongly dominant in the MO treatment. The MP group showed significantly higher abundances of Pleurotus and Pseudopeyronellaea than other treatments. The OP treatment was characterized by substantial increases in Plectosphaerella and Vishniacozyma ; O2P showed elevated abundances of Cladosporium and Thermomyces ; and OP2 exhibited increased Alternaria and Trichothecium . LAB inoculation significantly altered fungal composition: Alternaria and Trichothecium increased markedly in LMO; Wickerhamomyces increased sharply while Plectosphaerella decreased dramatically in LOP; Aspergillus increased whereas Thermomyces decreased in LO2P; Pleurotus abundance rose significantly in LOP2; and Wickerhamomyces increased while Stemphylium decreased in LMP. 2.2.5 Microbial function prediction As shown in Figure 11A, functional prediction of the bacterial community indicated that biosynthesis pathways were predominantly associated with cellular metabolism and prokaryotic group metabolism. The O2P and OP2 groups showed slightly higher abundances of biosynthesis pathways compared to the MO and MP groups. Notably, the abundance of secondary metabolite synthesis functions was 15% higher in LAB-inoculated treatments (LOP, LO2P) than in non-inoculated treatments. Within degradation-utilization-assimilation pathways, core functions were related to alcohol degradation and aromatic hydrocarbon degradation. The MP group had significantly higher abundance of carbohydrate derivative degradation functions than the MO group. The OP group showed approximately 15% greater abundance of hydrocarbon degradation functions compared to O2P, while LAB inoculation increased the abundance of nitrogen compound degradation functions by about 17% in the LOP group. Among precursor metabolite and energy generation pathways, the tricarboxylic acid (TCA) cycle and glycolysis were identified as core functions. The MP group exhibited significantly higher TCA cycle activity than the MO group, and the OP2 group showed approximately 33% higher abundance of pentose phosphate pathway functions compared to O2P. LAB inoculation increased the abundance of fermentation-related functions by approximately 25%. Furthermore, functional abundances related to glycan metabolism, macromolecule modification, and metabolic clusters varied considerably across treatments, with high pea proportion treatments promoting synergistic interactions between biosynthesis and energy metabolism pathways. As illustrated in Figure 11B, fungal community functional prediction revealed that carbohydrate synthesis functions dominated biosynthesis pathways. The MO group had 12.5% higher abundance of amino acid synthesis functions than the MP group, while the OP group showed 19.0% higher abundance compared to O2P. LAB inoculation increased secondary metabolite synthesis functions by 25% in the LOP group. In degradation-utilization-assimilation pathways, carbohydrate degradation functions were most abundant. The MP group exhibited 26.7% higher fatty acid degradation function abundance than the MO group, while the OP2 group showed 38.9% higher C1 compound utilization function abundance compared to OP. LAB inoculation increased inorganic nutrient metabolism functions by 33.3% in the LMP group. Glycolysis was identified as the core functional pathway in precursor metabolite and energy generation. Additionally, functional abundances related to glycan metabolism and metabolic clusters also varied significantly across treatments.s. 2.4 Quantification of synergistic effects 2.4.1 Mantel analysis In the correlation analysis between fungal communities and silage quality (Figure 12), acid detergent fiber (ADF) demonstrated a strongly significant positive correlation with fungal communities (r = 0.231, P = 0.002), and neutral detergent fiber (NDF) also showed a significant positive correlation (r = 0.187, P = 0.012). In contrast, correlations of crude protein (CP) and water-soluble carbohydrates (WSC) with fungal communities were relatively weak. Regarding fermentation parameters, lactic acid (LA) exhibited a strongly significant negative correlation with fungal communities (r = -0.264, P = 0.001), while pH showed a significant positive correlation (r = 0.168, P = 0.027). Acetic acid (AA) and the ammonia nitrogen/total nitrogen ratio (AN/TN) also demonstrated significant positive correlations with fungal communities. A significant positive correlation was found between bacterial and fungal communities (r = 0.198, P = 0.005). Lactic acid (LA) appeared to enhance bacterial dominance through indirect effects, while pH exerted opposing regulatory effects on the successional dynamics of both bacterial and fungal communities. Functional differentiation was observed in how silage quality parameters influenced microbial communities: bacterial communities were more responsive to water-soluble carbohydrates (WSC) and lactic acid (LA), whereas fungal communities were primarily associated with structural carbohydrate degradation. Among these factors, lactic acid (LA) and pH were identified as core regulators of microbial community dynamics: LA suppressed fungal development and reinforced bacterial dominance, while pH mediated contrasting successional patterns in both communities. 2.4.2 Redundancy analysis Redundancy analysis (RDA) results (Figure 13) indicated that for the bacterial community (Figure 13A), RDA1 and RDA2 explained 18.22% and 11.55% of the total variation, respectively, cumulatively accounting for 30.77%. Water-soluble carbohydrates (WSC) and lactic acid (LA) were identified as the primary drivers, synergistically promoting the proliferation of lactic acid bacteria. pH and crude protein (CP) significantly influenced separation along the RDA2 axis, with the MP, LMO, and LOP groups—characterized by high CP and pH—clearly distinguished from other treatments. Acid detergent fiber (ADF) and neutral detergent fiber (NDF) had comparatively weaker effects on bacterial community composition. For the fungal community (Figure 13B), RDA1 and RDA2 accounted for 37.39% and 15.04% of the variation, respectively, with a cumulative explanation rate of 52.43%. ADF and NDF were the main influencing factors, with the MO and O2P groups enriched along the positive RDA1 axis. pH and ammonia nitrogen/total nitrogen (AN/TN) played defining roles along RDA2, where the MP and LMP groups—associated with high pH and AN/TN—clustered along the positive axis. In contrast to their strong effects on bacteria, WSC and LA exhibited weaker influences on fungal community assembly. Discussion 3.1 Synergistic regulation of silage fermentation quality by mixed-sowing ratios and addition of lactic acid bacteria The present study demonstrates that the mixed cropping ratios of oats and forage peas significantly influence silage fermentation quality and nutritional characteristics by modulating the carbon-nitrogen balance and structural carbohydrate composition of the raw materials. As the proportion of peas increased, crude protein (CP) content rose, while water-soluble carbohydrate (WSC) content declined, highlighting the complementary nutritional contributions of legume-grass intercropping. [ 17 ]. A higher pea proportion delayed the rate of pH decline due to its stronger buffering capacity, thereby prolonging protease activity. This extended enzymatic action led to an increased ammonia nitrogen/total nitrogen (AN/TN) ratio and higher dry matter loss (DML)[ 18 ]. Meanwhile, inadequate water-soluble carbohydrate (WSC) availability restricted the proliferation of lactic acid bacteria (LAB), thereby reducing their ability to suppress spoilage microorganisms.[ 19 ]. The 1:1 mixed cropping ratio of oats and forage peas achieved an optimal balance between nutrient supply and fermentation stability. Crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), ammonia nitrogen/total nitrogen (AN/TN) ratio, and dry matter loss (DML) all remained at moderate levels, favoring overall silage quality. This result aligns with the findings of Zhang et al. [ 20 ], who reported that optimal silage quality is attained at mixed cropping ratios of 6:4 or 5:5. Moderate mixed cropping enhances fermentation efficiency by optimizing the C/N ratio, and the 1:1 ratio further extends this conclusion to systems prioritizing both nutritional and fermentative performance. Compared to non-inoculated treatments, LAB-inoculated treatments exhibited a modest increase in crude protein (CP) content—though not statistically significant—along with significant reductions in neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents, as well as a decrease in water-soluble carbohydrate (WSC) content. These findings align with those reported by Jayakrishnan Nair et al [ 21 ]. and ALLI et al[ 22 ] . The observed effects may be attributed to the low ambient temperatures in the region, which limit the natural attachment of lactic acid bacteria to forage. In contrast, LAB inoculation ensured a sufficient population of bacteria for the ensiling process[ 23 ]. By inhibiting the growth of spoilage microorganisms, LAB inoculation reduced protein degradation, ultimately resulting in higher protein retention in inoculated silage compared to non-inoculated silage. Furthermore, the elevated acidity in the LAB-inoculated silage altered the fiber structure, increasing its susceptibility to microbial and enzymatic degradation. Consequently, the fiber content was lower in the inoculated silage than in its non-inoculated counterpart [ 24 ]. 3.2 Effects of mixing ratio and lactobacilli addition on microbial community structure In this study, mixed cropping ratios and inoculation with lactic acid bacteria (LAB significantly influenced the structure and function of silage microbial communities by modifying substrate characteristics and microenvironments. For bacterial communities, LAB inoculation was the key factor shaping community assembly. The relative abundance of Lactiplantibacillus increased significantly in LAB-inoculated silage, indicating that exogenous inoculation enhanced its dominance. In non-inoculated groups, the fluctuating abundance of this genus likely resulted from its low initial natural abundance and constraints imposed by complex substrate conditions. Lentilactobacillus responded synergistically to cropping ratios, reaching its highest abundance in the non-inoculated 1:1 mixed cropping group, suggesting that the carbon-to-nitrogen ratio at this proportion supported its metabolic needs. In the inoculated 1:2 mixed cropping group, Lentilactobacillus and Lactiplantibacillus established a stable “acid-production and degradation” functional partnership, highlighting how specific mixed ratios optimize microbial interactions. These findings align with previous work by Wu et al.[ 25 ]. In the non-inoculated 1:1 mixed cropping group, the dominance of Lentilactobacillus was attributed to a carbon-nitrogen ratio that aligned with its metabolic requirements. In contrast, following LAB inoculation in the 1:2 mixed cropping group, a stable functional consortium emerged with Lactiplantibacillus , resulting from synergistic optimization between the inoculant and the mixed cropping ratio. [ 26 ]. Mixed cropping ratios directly shaped bacterial community composition by influencing substrate chemistry. As the proportion of peas increased, the abundance of spoilage-associated genera such as Hafnia-Obesumbacterium declined markedly, likely due to the enhanced buffering capacity of high-protein substrates that delayed acidification. Conversely, Pediococcus became enriched in the 1:1 mixed cropping group, consistent with the intermediate levels of water-soluble carbohydrates and fiber. LAB inoculation further reduced the prevalence of endogenous non-target bacteria and suppressed spoilage organisms through rapid acid production. Martin B [ 27 ] noted that peas are susceptible to spoilage at early maturity, when their dry matter concentration remains low, as high protein content delays acidification—aligning with the observed reduction in spoilage bacteria such as Hafnia . Fungal communities exhibited more complex niche differentiation in response to treatment conditions. Mixed cropping ratios directly influenced taxonomic composition: Plectosphaerella was most abundant in the non-inoculated 2:1 mixed cropping group, likely due to its adaptability to degrading grassy fiber. LAB inoculation modulated fungal assemblages through a dual mechanism—not only reducing α-diversity and enriching acid-tolerant yeasts such as Wickerhamomyces, but also selectively preserving functionally important taxa. For instance, in the LAB-inoculated 1:2 mixed cropping group, the abundance of Pleurotus increased to 7.94%, suggesting a potential role in converting structural carbohydrates via lignin degradation. This “inhibition-retention” balance may be attributed to the strong acid tolerance of Pleurotus, the dependence on its degradative activity in high-fiber substrates, and the use of a moderate inoculation rate that permitted fungal functionality. Chen et al. [ 28 ] reported that inoculation with LAB (e.g., Lactiplantibacillus plantarum) significantly increased the relative abundance of lactobacilli, suppressed spoilage bacteria such as Proteobacteria, and promoted homofermentative metabolism dominated by lactic acid production—a conclusion further supported by Feng et al. [ 29 ]. 3.3 Coupling of microbial function and fermentation quality In this study, inoculation with lactic acid bacteria (LAB) significantly influenced silage quality through direct modulation of microbial communities, demonstrating a characteristic trade-off between accelerated acidification and fermentation precision. LAB inoculation led to a significant positive correlation between the abundance of Lactiplantibacillus and lactic acid (LA) content, and a significant negative correlation with pH. Rapid acidification effectively suppressed spoilage bacteria such as Hafnia-Obesumbacterium, resulting in a marked reduction in the ammonia nitrogen to total nitrogen ratio (AN/TN)—a finding consistent with the results reported by Zhang et al.[ 30] . Similarly, Qiang et al. demonstrated in a study of alfalfa and Suaeda glauca mixed silage that LAB inoculation significantly reduced the abundance of undesirable bacteria, including Enterobacteriaceae .[ 31 ]. Muck et al. [ 32 ] observed that bacteria—particularly lactic acid bacteria (LAB)—prefer soluble substrates such as water-soluble carbohydrates (WSC) and lactic acid (LA), which they utilize in rapid fermentation to produce acids and lower pH. Homofermentative LAB (e.g., Lactiplantibacillus plantarum ) accelerate acidification by rapidly consuming WSC to produce lactic acid, whereas heterofermentative LAB (e.g., Lentilactobacillus buchneri ) enhance aerobic stability by converting lactic acid into acetic acid and 1,2-propanediol. In contrast, fungi (yeasts and molds) dominate the degradation of structural substrates such as acid detergent fiber (ADF) and neutral detergent fiber (NDF), and become more active under elevated pH or ammonia nitrogen (AN) conditions[ 33 ]. In the present study, bacteria preferentially utilized soluble substrates including water-soluble carbohydrates (WSC), lactic acid (LA), and fermentation acids, whereas fungi were dominant in degrading structural substrates such as acid detergent fiber (ADF) and neutral detergent fiber (NDF) and were influenced by variations in pH, ammonia nitrogen (AN), and total nitrogen (TN). Mixed cropping ratios mediated community assembly by modulating substrate carbon/nitrogen (C/N) ratios (e.g., WSC/ADF and crude protein (CP)). Meanwhile, LAB inoculation directionally shaped microbial communities through a dual mechanism of “carbon source competition plus acidification-mediated inhibition”, thereby providing a strategic basis for optimizing silage microbial function. Notably, propionic acid (PA) and acetic acid (AA) levels increased following LAB inoculation, which correlated with a metabolic shift toward heterofermentation by Lentilactobacillus under low-WSC conditions. Furthermore, the low-temperature environment of the Qinghai–Tibet Plateau selectively constrained homofermentative bacteria, which exhibit optimal activity at 25–30°C, thereby creating an ecological niche that favored heterofermentative metabolism. Lin et al.[ 34 ] demonstrated that heterofermentative bacteria (e.g., Lentilactobacillus) can emerge as the dominant species during later stages of silage fermentation under low-temperature conditions. Li et al. [ 35 ] further indicated that low temperatures suppress the glycolytic efficiency of homofermentative bacteria, leading facultative heterofermenters to metabolize and produce acetic acid under carbohydrate-limited conditions. Lin et al demonstrated that heterofermentative bacteria (e.g., Lentilactobacillu s) may become dominant strains in the late stage of silage under low-temperature conditions. In this experiment, the bacterial inoculum contained heterofermentative contaminants. Insufficient water-soluble carbohydrates (WSC) in monocropped oat and non-inoculated 1:1 mixed cropping groups limited the substrates available for homofermentation; however, feedstocks with intrinsically high WSC content were able to circumvent this limitation. Accordingly, LAB inoculation strategies should prioritize pure homofermentative strains tailored to both environmental conditions and substrate composition to balance acidification efficiency with fermentation precision. Bacterial communities established a self-reinforcing cycle of “high lactic acid–low pH” driven by the availability of WSC and lactic acid (LA), whereas fungal communities contributed to fiber degradation modulated by acid detergent fiber (ADF) and pH. Together, these microbial groups collaboratively influenced silage quality through an interactive network of “bacterial fermentation–fungal degradation”. Mantel tests confirmed that bacterial community composition was significantly correlated with WSC and LA, while fungal communities were strongly associated with ADF, corroborating the directional regulation of microbial function by substrate characteristics. Conclusion This study elucidates the synergistic effects of mixed cropping ratios and lactic acid bacteria (LAB) inoculation on silage quality in oat/forage pea mixed silage produced in a plateau corral environment. The results demonstrate that a 1:1 oat-to-pea mixing ratio significantly increased crude protein (CP) content, optimized ammonia nitrogen to total nitrogen (AN/TN) ratio and dry matter loss (DML), and elevated propionic acid (PA) and acetic acid (AA) concentrations. Mixed cropping ratios directed the selection of functional microbial communities based on substrate composition, while LAB inoculation reshaped bacterial community structure. Fungal communities exhibited functional compensation: acid-tolerant fungi contributed to fiber degradation without substantially increasing DML. An interactive “bacterial fermentation–fungal degradation” network mediated silage quality through cascading substrate-microbe interactions. In conclusion, the combination of 1:1 oat-pea mixed cropping and LAB inoculation achieved an optimal balance among nutritional complementation, fermentation precision, and microbial functionality, establishing it as a recommendable silage strategy for plateau regions. These findings provide a theoretical basis for targeted microbial management in legume-grass mixed silage systems and offer practical insights for high-quality forage production on the Qinghai–Tibet Plateau. This study has the following limitations: Firstly, the experiment was only conducted at specific sites in Haiyan County on the Qinghai-Tibet Plateau. Affected by the local climate, soil, and microbial background, the extrapolation of the research conclusions to other regions requires cautious verification. Secondly, the observation time is limited; only samples after 45 days of fermentation were analyzed, failing to cover the mechanisms of changes in microbial communities and quality during long-term storage stability and after aerobic exposure. Thirdly, microbial function analysis relies on metagenomic predictions, lacking direct verification at the molecular levels such as transcriptomics and proteomics, and some functional inferences need to be confirmed in subsequent studies. Declarations Ethics approval and consent to participate: Not applicable. Consent for publication : Not applicable. Availability of data and materials: Data is contained within the article or supplementary material.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the author Y.M. Competing interests: The authors declare no conflicts of interest. Funding: This research was funded by Two-Level Fiscal Support Project of Qinghai University (SSYS-2025-04); Key Laboratory of Grassland Ecosystem (Ministry of Education) "Unveiling and Leading" Project (KLGE-2024-04); Gansu Provincial Youth Doctor Support Program for Higher Education Institutions (2024QB-076). Author Contributions: Conceptualization, Y.M. and Y.Z.; methodology, Y. M., Y. Z. and G. L.; software, Y.M.; validation, Y.M., Y.Z.; formal analysis, Y.M.; investigation, Y.M..; resources, Y. M, Y. Z. and C.X; data curation, Y. Z. and Y. M.; writing—original draft preparation, Y. Z. and Y.M.; writing—review and editing, Y.Z.; visualization, Y.M.; supervision, Y. 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Acta Prataculturae Sinica, 2022, 31(12): 158-170. https://doi.org/10.11686/cyxb2022087 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 20 Oct, 2025 Reviews received at journal 15 Oct, 2025 Reviews received at journal 26 Sep, 2025 Reviewers agreed at journal 24 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers invited by journal 17 Sep, 2025 Editor assigned by journal 11 Sep, 2025 Submission checks completed at journal 10 Sep, 2025 First submitted to journal 09 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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14:59:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":150603,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different mixed-cropping ratios of oats and forage peas and the addition of lactic acid bacteria on the relative abundance of bacteria at the genus level (A) and the relative abundance of fungal at the genus level (B) in silage.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/2e1fa715d48f55cb0caa9508.png"},{"id":92273468,"identity":"f375457c-edb1-4a67-9292-3a717e9f560b","added_by":"auto","created_at":"2025-09-26 15:07:21","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":239499,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha diversity of bacterial communities under different mixed-sowing ratios of oats and forage peas and with the addition of lactic acid bacteria in silage.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/9539cb01fff42ac6597a1d7f.png"},{"id":92271867,"identity":"1046fe6f-61c4-40ba-98ad-0b1cef1b0a88","added_by":"auto","created_at":"2025-09-26 14:51:20","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":186471,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha diversity of fungal communities under different mixed-sowing ratios of oats and forage peas and with the addition of lactic acid bacteria in silage.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/5575c4dfcba589c11934643f.png"},{"id":92271881,"identity":"69282c01-3f38-4594-85d5-fc3e16f12b6d","added_by":"auto","created_at":"2025-09-26 14:51:20","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":63529,"visible":true,"origin":"","legend":"\u003cp\u003eBeta diversity of bacterial communities (A) and fungal communities (B) under different mixed-cropping ratios of oats and forage peas and with the addition of lactic acid bacteria in silage.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/1d58cd99081d0efdb2abae67.png"},{"id":92271865,"identity":"7f88b001-277b-461e-870e-d55726b6b415","added_by":"auto","created_at":"2025-09-26 14:51:20","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":264606,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of species composition of bacterial communities (A) and fungal communities (B) under different mixed-sowing ratios of oats and forage peas and with the addition of lactic acid bacteria.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/58569d5149ca4d85e1e5ed0a.png"},{"id":92271868,"identity":"cb416ef8-e944-43dc-85a9-1b0b9a3cabb6","added_by":"auto","created_at":"2025-09-26 14:51:20","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":235947,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical analysis of metabolic pathways of bacterial communities (A) and fungal communities (B) under different mixed-cropping ratios of oats and forage peas and with the addition of lactic acid bacteria.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/6e1f04c929b69fdf9fc8c5ad.png"},{"id":92271901,"identity":"4909c9c9-0f93-4f98-8ffb-4110a095572f","added_by":"auto","created_at":"2025-09-26 14:51:21","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":137440,"visible":true,"origin":"","legend":"\u003cp\u003eMantel analysis of nutritional quality, fermentation quality, bacterial communities and fungal communities under different mixed-cropping ratios of oats and forage peas and with the addition of lactic acid bacteria.\u003c/p\u003e\n\u003cp\u003eNote: P-values are used to reflect the significance of the results (*, **, *** correspond to P\u0026lt;0.05, P\u0026lt;0.01, P\u0026lt;0.001, respectively)\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/c3f3f5f0b67c9408d6ba0eef.png"},{"id":92271870,"identity":"55417084-4e7e-4788-bab2-638ee3d87d74","added_by":"auto","created_at":"2025-09-26 14:51:20","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":81112,"visible":true,"origin":"","legend":"\u003cp\u003eRedundancy analysis of nutritional quality, fermentation quality with bacterial communities (A) and fungal communities (B) under different mixed-sowing ratios of oats and forage peas and with the addition of lactic acid bacteria.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/dc462b2189913ffc0ded3e12.png"},{"id":92273944,"identity":"80e22171-cb5e-4af8-9a0e-58b90f53dfb1","added_by":"auto","created_at":"2025-09-26 15:20:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2485231,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7436223/v1/635b5faf-083a-4fbf-b23f-e00dc488376a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Microbial Community Structure and Carbon-Nitrogen Coupling Mechanisms in Mixed Silage of Oats and Forage Peas in Corral of the Qinghai-Tibet Plateau","fulltext":[{"header":"Background","content":"\u003cp\u003eThe Qinghai-Tibet Plateau serves as China\u0026apos;s crucial ecological barrier and primary pastoral zone. This region has a distinct alpine climate with three key features: high elevation, low temperatures, and brief growing seasons. Haiyan County in Qinghai Province shows these characteristics most markedly. Here, natural grasslands remain productive for fewer than 120 days annually. This limited growing window drastically reduces forage availability and hinders supplemental feeding programs[\u003csup\u003e1\u003c/sup\u003e]. Currently, the region suffers from acute winter-spring forage deficits. Local livestock production relies extensively on imported winter fodder. This dependence carries substantial financial and operational risks, severely limiting sustainable development of animal husbandry operations[\u003csup\u003e2\u003c/sup\u003e]. Concurrently, rapid population growth and livestock expansion on the Qinghai-Tibet Plateau have intensified human impacts. Overgrazing, excessive fencing, and grassland conversion have accelerated ecosystem degradation. These pressures reduce grass diversity, compact soils, and diminish water retention. Such changes critically threaten steppe ecosystem functions[\u003csup\u003e3\u003c/sup\u003e]. Furthermore, national conservation policies strictly prohibit natural grassland conversion to cropland. They also restrict large-scale artificial grassland development. These constraints make improved forage self-sufficiency critical. The challenge lies in boosting production without expanding cultivation areas or exceeding ecological limits. This balance is essential for sustainable grassland management and pastoral development.\u003c/p\u003e\n\u003cp\u003eThe Qinghai-Tibet Plateau faces dual pressures from ecological conservation needs and grassland degradation. Developing integrated cultivated grassland systems on idle lands offers a viable solution to forage shortages. Particularly promising are corral lands - the nutrient-rich residual areas left after winter livestock confinement. These spatially isolated parcels typically lie fallow after herds move to summer pastures.\u003c/p\u003e\n\u003cp\u003eUnmanaged corral lands suffer several ecological impacts. Exposed soils lose nutrients through leaching while becoming vulnerable to weed invasions and pest infestations. This degradation leads to progressive soil erosion and resource depletion. However, strategic forage cultivation in these areas can reverse these trends.\u0026nbsp;Implementing corral land forage systems provides multiple advantages. The vegetation cover enhances summer-autumn ground protection and aids ecological restoration. Simultaneously, it enables local production of quality winter silage for ruminants. This approach boosts forage output without expanding cultivation areas while supporting sustainable grassland management.Recent studies confirm the effectiveness of mixed cropping systems using cold-tolerant species. Oats (\u003cem\u003eAvena sativa\u003c/em\u003e), triticale (\u003cem\u003eTriticosecale\u003c/em\u003e), and forage peas (\u003cem\u003ePisum sativum\u003c/em\u003e) demonstrate particularly stable biomass yields and excellent ensiling characteristics under plateau conditions.[\u003csup\u003e4,5\u003c/sup\u003e]. Consequently, the integrated system of \u0026quot;corral land cultivation with on-site ensiling\u0026quot; represents an innovative strategy for enhancing grassland resource utilization in high-altitude pastoral regions.\u003c/p\u003e\n\u003cp\u003eSuccessful silage production in high-altitude alpine regions must account for three critical factors: rapid plant growth, nutritional complementarity, and fermentation stability. Oats, a grass species renowned for their environmental adaptability and high biomass yield, serve as an ideal substrate due to their high soluble carbohydrate content[\u003csup\u003e6]\u003c/sup\u003e. In contrast, leguminous plants such as forage peas supply high levels of crude protein and non-starch polysaccharides, which serve as both a nitrogen source and fermentable carbon substrates[\u003csup\u003e7]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe oat-pea intercropping system confers multiple advantages. This approach enhances the overall nutritional profile and optimizes the feedstock\u0026apos;s carbon-to-nitrogen (C/N) ratio. A balanced C/N ratio fosters the proliferation of lactic acid bacteria while simultaneously suppressing spoilage microorganisms, thereby significantly improving silage quality[5,\u003csup\u003e8]\u003c/sup\u003e.Studies indicate that a 1:1 oat-to-pea ratio achieves optimum nutritional balance and fermentation stability, promoting lactic acid bacteria (LAB) populations to over 80% relative abundance. This microbial dominance effectively suppresses harmful bacteria such as Clostridium spp., establishing this combination as a highly efficient forage system [8].\u003c/p\u003e\n\u003cp\u003eHowever, the low temperatures (15\u0026ndash;20\u0026deg;C) typical of the Qinghai-Tibet Plateau hinder natural fermentation. Under these conditions, indigenous lactic acid bacteria (LAB) exhibit low population densities and reduced metabolic activity, leading to delayed acidification and increased susceptibility to spoilage microorganisms. These issues are compounded in legume-dominant mixtures by their higher protein content[\u003csup\u003e9\u003c/sup\u003e]. The inoculation of tailored lactic acid bacteria (LAB) strains, such as \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e and \u003cem\u003ePediococcus pentosaceu\u003c/em\u003es, effectively mitigates these limitations. These microbial additives enhance fermentation by accelerating acidification[\u003csup\u003e10]\u003c/sup\u003e, modifying the microbial community structure[\u003csup\u003e11\u003c/sup\u003e], and ultimately improving forage safety and storage stability.\u003c/p\u003e\n\u003cp\u003eTherefore, this study was conducted in the corral lands of Haiyan County on the Qinghai-Tibet Plateau. Using oats and forage peas as the experimental forage combination, we systematically designed silage treatments with varying mixed cropping ratios and with or without lactic acid bacteria (LAB) inoculation. By measuring physicochemical parameters, conducting high-throughput microbial sequencing, and predicting metabolic functions, this study comprehensively evaluated how these treatments affect silage nutritional quality and microbial community structure.\u003c/p\u003e\n\u003cp\u003eThe primary objectives of this study were to elucidate the synergistic mechanisms by which mixed cropping ratios and lactic acid bacteria (LAB) inoculation improve silage quality, and to delineate the role of LAB in regulating microbial functional expression and carbon‑nitrogen metabolic pathways. Ultimately, this research aims to establish a scientific foundation and practical methodology for enhancing corral land utilization and producing high‑quality silage in alpine pastoral regions. This work not only advances the theoretical framework of grass‑legume mixed cropping systems with silage regulation, but also provides a scalable model for sustainable forage production in cold environments.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003ch2\u003e1.1 Overview of the experimental site\u003c/h2\u003e\n\u003cp\u003eThe experimental site was located in the corral lands of Haiyan County, within the Haibei Tibetan Autonomous Prefecture of Qinghai Province (36.93\u0026deg;N, 100.86\u0026deg;E; altitude: 3132.0 m). The region experiences a plateau sub-arid climate, characterized by dry and windy springs, cool summers, brief autumns, and prolonged winters. The mean annual temperature is 1.5 \u0026deg;C, with approximately 2980 hours of sunshine per year. A true frost-free period is absent, and natural disasters including hail, frost, drought, and sandstorms are common. Precipitation and temperature records for Haiyan County in 2024 are provided in Figure 2.\u003c/p\u003e\n\u003ch2\u003e1.2 Test materials\u003c/h2\u003e\n\u003cp\u003eThe test oat variety was selected as \u0026quot;Qingyin No.1 (Avena sativacv, cv. QingyinNo.1)\u0026quot;, It\u0026apos;s an early-maturing variety. and the forage pea variety was \u0026quot;QingjianNo.1\u0026quot; (\u003cem\u003ePisum sativum\u0026nbsp;\u003c/em\u003ecv.\u003cem\u003e\u0026nbsp;\u003c/em\u003eQingjianNo.1)., which was provided by Grassland Research Institute of Qinghai Academy of Animal Husbandry and Veterinary Sciences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLactic acid bacteria group: freeze-dried Lactic acid bacteria including \u003cem\u003eLactobacillus plantarum\u003c/em\u003e, \u003cem\u003eLactobacillus buchneri\u003c/em\u003e, \u003cem\u003ePediococcus pentosaceus\u003c/em\u003e, provided by Shandong Weikai Haisi Bioengineering Co.(Location, China).\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;1.3 Experimental design and methods\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;1.3.1 Planting and management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was initiated in mid-May 2024 using a randomized block design. Three oat\u0026ndash;forage pea mixed cropping ratios were evaluated: O2P (oat:pea = 2:1), OP (oat:pea = 1:1), and OP2 (oat:pea = 1:2). Monocultures of oat (MO) and forage pea (MP) served as controls. Each treatment was replicated three times, with individual plot dimensions of 6 m \u0026times; 11m (66 m\u0026sup2;).\u003c/p\u003e\n\u003cp\u003eSeeding rates for monoculture oat and pea were based on locally recommended rates for forage production. For the 1:1 mixed cropping treatment (OP), the oat seeding rate was reduced to 50% of the monoculture rate (93.75 kg/ha), while the forage pea seeding rate was similarly set to 50% of its monoculture rate (60 kg/ha). Detailed seeding rates for all treatments are summarized in Table 1. Seeds were broadcast by hand, and no further field management was applied during the experiment.\u003c/p\u003e\n\u003cp\u003eTable 1 Mixiture ratio and cropping amount of oats and peas\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"95%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 18px;\"\u003e\n \u003cp\u003eCode\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 24px;\"\u003e\n \u003cp\u003eMixture radio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003eSeeding rate (kg/ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eOat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003ePea\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eMO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e1:0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e187.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eO2P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e2:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e1:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e93.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eOP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e1:2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e62.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003eMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e0:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e\u0026nbsp;1.3.2 Silage preparation\u003c/h3\u003e\n\u003cp\u003eForage was harvested when oats reached the milk-ripe stage and peas were at the flowering stage, maintaining a stubble height of 5 cm. Oats and peas were harvested as a mixed stand according to the predetermined cropping ratios. The harvested forage was chopped to a uniform length of 2\u0026ndash;3 cm for wrapped silage production. Two silage processing methods were employed: direct ensiling (without additives) and ensiling with lactic acid bacteria (LAB) inoculation.\u003c/p\u003e\n\u003cp\u003eThe untreated silage treatments were labeled as MO, O2P, OP, OP2, and MP, corresponding to their respective cropping systems. For the LAB-inoculated treatments, freeze-dried LAB powder (containing 2 \u0026times; 10⁹ CFU/g) was dissolved in sterile distilled water and applied evenly to the chopped forage. Control (non-inoculated) groups received an equivalent amount of sterile distilled water to maintain uniform moisture conditions. The final LAB concentration in inoculated silage was 2 \u0026times; 10⁵ CFU per gram of fresh matter (FM). These treatments were designated as LMO, LO2P, LOP, LOP2, and LMP, respectively.\u003c/p\u003e\n\u003cp\u003eFor each treatment, 500 g of processed forage was packed into polyethylene bags (26 cm \u0026times; 35 cm) and vacuum-sealed. Each treatment was replicated three times. Silage nutritional composition and fermentation parameters were analyzed after 45 days of ensiling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;1.3.3 Raw material profile\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw materials were initially dried at 105 \u0026deg;C for 1 hour to arrest biological activity, followed by further drying at 70 \u0026deg;C until constant weight was achieved for accurate dry matter determination. Nutritional composition was subsequently assessed, and the results are summarized in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 2 Nutritional quality of mixed cropping oats and peas used in this study as raw materials\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"411\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eCP(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eEE(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eNDF(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eADF(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eAsh(%DM)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eO2P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003e1.4 Indicator Measurement and Methods\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;1.4.1 Fermentation quality\u003c/p\u003e\n\u003cp\u003eA 10 g sample of silage was homogenized with 90 mL of distilled water and shaken continuously for 24 hours. The resulting slurry was filtered through four layers of gauze followed by qualitative filter paper to obtain a clear extract for fermentation analysis. The pH of the extract was immediately measured using a calibrated pH meter. For organic acid analysis, a 1 mL aliquot was filtered through a 0.22 \u0026mu;m membrane into a vial and subjected to high-performance liquid chromatography (HPLC) for quantification of lactic acid (LA), acetic acid (AA), propionic acid (PA), and butyric acid (BA). Ammonia nitrogen (AN) was determined according to the method of Broderick and Kang.\u0026nbsp;[\u003csup\u003e12]\u003c/sup\u003e. The dry matter (DM) content was determined by drying a representative silage sample to constant weight in a 65\u0026deg;C oven[\u003csup\u003e13]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe dry matter loss (DML) rate was calculated according to the following formula:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere DML represents dry matter loss, M1 stands for the dry matter content before ensiling, and M2 stands for the dry matter content after ensiling.\u003c/p\u003e\n\u003cp\u003e1.4.2 Nutritional quality\u003c/p\u003e\n\u003cp\u003eSilage samples were dried to constant weight at 70 \u0026deg;C using a forced-air oven, then ground and homogenized for nutritional analysis. Crude protein (CP) content was determined by the Kjeldahl method[\u003csup\u003e14\u003c/sup\u003e]. Neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined according to the method of Van Soest et al[\u003csup\u003e15\u003c/sup\u003e],. Water-soluble carbohydrate (WSC) content was determined using the Somogyi method [\u003csup\u003e16\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;1.4.3 Microbiological analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal genomic DNA was extracted from 0.5 g of each sample using the Omega DNA extraction kit (Cat. No. M0491L, BioTek) according to the manufacturer\u0026apos;s protocol. The integrity of the extracted DNA was assessed via 0.8% agarose gel electrophoresis, and concentration was quantified using a Nanodrop spectrophotometer.\u003c/p\u003e\n\u003cp\u003eBacterial and fungal community profiles were analyzed by Illumina MiSeq sequencing. The V3\u0026ndash;V4 hypervariable regions of the bacterial 16S rRNA gene were amplified with primers 341F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGGTWTCTAAT). For fungal communities, the ITS1 region was amplified using primers ITS1F (GGAAGTAAAAGTCGTAACAAGG) and ITS2R (GCTGCGTTCTTCATCGATGC). Raw sequencing data were processed and analyzed using QIIME 2 (v2019.4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.5 Data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were collated and statistically summarized using Microsoft Excel 2019. Significance tests and two-way analysis of variance (ANOVA) were carried out with SPSS 24.0, followed by Tukey\u0026rsquo;s honestly significant difference test for multiple comparisons. Results are expressed as arithmetic means, and figures were prepared using Origin 2021. Differences were considered statistically significant at p \u0026lt; 0.05, highly significant at p \u0026lt; 0.01, and marginally significant (indicating a trend) at 0.05 \u0026le; p \u0026lt; 0.10.\u003c/p\u003e\n\u003cp\u003eMantel tests were conducted in R using the linkET package to assess direct and indirect relationships between microbial communities and silage traits including nutritional and fermentation parameters. Metabolic functional profiles of bacterial and fungal communities were predicted using the Metabolic Prediction Tool developed by Shanghai Parsonage.\u003c/p\u003e"},{"header":"Results and analysis","content":"\u003cp\u003e2.1 Nutritional quality\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;2.1.1 Soluble carbohydrate and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecrude protein content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 3A, in the absence of lactic acid bacteria (LAB) inoculation, the monocropped oat (MO) treatment exhibited the highest water-soluble carbohydrate (WSC) content, while the monocropped pea (MP) treatment showed the lowest WSC content among non-inoculated groups. Within non-inoculated treatments, the WSC contents in the O2P, OP, and OP2 groups were significantly higher than that in the MP group by 25.48%, 18.18%, and 10.84%, respectively (p \u0026lt; 0.05). Under LAB inoculation, the WSC content was further increased: the O2P, OP, and OP2 groups showed increases of 36.32%, 25.84%, and 14.03%, respectively, compared to the MP group (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eFigure 3B shows that the crude protein (CP) content increased with the proportion of peas in the mixture. In non-inoculated treatments, the CP content of the O2P, OP, and OP2 groups was significantly higher than that of the MO group by 11.23%, 29.43%, and 39.50%, respectively (p \u0026lt; 0.05). Similarly, under LAB inoculation, the O2P, OP, and OP2 groups also exhibited significantly greater CP content than the MO group (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.2 Acid/neutral detergent fiber content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Figures 4A and 4B, in non-inoculated treatments, the acid detergent fiber (ADF) content was significantly lower in the O2P, OP, and OP2 groups than in the monocropped oat (MO) group, with reductions of 12.34%, 14.37%, and 26.33%, respectively (p \u0026lt; 0.05). Similarly, the neutral detergent fiber (NDF) content was significantly reduced in these mixed-cropping groups relative to the MO group by 4.80%, 11.21%, and 29.83%, respectively (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eUnder LAB inoculation, the ADF content remained significantly lower in the O2P, OP, and OP2 groups compared to the MO group, with decreases of 10.37%, 12.74%, and 34.38% (p \u0026lt; 0.05). A similar trend was observed for NDF content, where the O2P, OP, and OP2 groups showed significant reductions of 6.85%, 12.11%, and 27.81%, respectively, relative to the MO group (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e2.2 Fermentation quality\u003c/p\u003e\n\u003cp\u003eFor the ammonia nitrogen/total nitrogen (AN/TN) ratio (Figure 5B), LAB-inoculated treatments exhibited significantly lower values than non-inoculated treatments at the same mixed cropping ratio.\u003c/p\u003e\n\u003cp\u003eDry matter loss (DML) (Figure 5C) was highest in the MP group and lowest in the OP group under non-inoculated conditions, while under LAB inoculation, the OP2 group showed the highest DML with the OP group remaining the lowest across all treatments.\u003c/p\u003e\n\u003cp\u003eRegarding lactic acid (LA) content (Figure 5D), the lowest values in non-inoculated treatments were observed in the O2P group, whereas the highest LA content under LAB inoculation occurred in the MO group.\u003c/p\u003e\n\u003cp\u003eAdditionally, acetic acid (AA) (Figure 5E) and propionic acid (PA) (Figure 5F) contents were significantly higher in LAB-inoculated than in non-inoculated treatments.\u003c/p\u003e\n\u003cp\u003e2.3 Changes in microbial community structure\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;2.3.1 Relative abundance of bacterial and fungal species composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 6A illustrates significant variation in the relative abundance of dominant bacterial genera across silage treatments. In non-inoculated groups, \u003cem\u003eLactiplantibacillus\u003c/em\u003e (32.78%) and \u003cem\u003eLentilactobacillus\u003c/em\u003e (18.46%) dominated the MO treatment, with \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e comprising 17.37%. The OP treatment was characterized by \u003cem\u003eLentilactobacillus\u003c/em\u003e (19.11%) and \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e (18.83%). In O2P, \u003cem\u003eLactiplantibacillus\u003c/em\u003e (30.05%) and \u003cem\u003eLentilactobacillus\u003c/em\u003e (27.07%) constituted the core taxa, while MP was co-dominated by \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e (24.91%), \u003cem\u003eLactiplantibacillus\u003c/em\u003e (19.89%), and \u003cem\u003eLentilactobacillus\u003c/em\u003e (28.51%).\u003c/p\u003e\n\u003cp\u003eLAB inoculation markedly shifted bacterial community structure. The LMO treatment showed a substantial increase in \u003cem\u003eLactiplantibacillus\u003c/em\u003e (66.54%). In LO2P, \u003cem\u003eLactiplantibacillus\u003c/em\u003e remained dominant (66.24%), with \u003cem\u003eLentilactobacillus\u003c/em\u003e at 12.07%. The LOP2 treatment exhibited synergistic dominance of \u003cem\u003eLactiplantibacillus\u003c/em\u003e (47.99%) and \u003cem\u003eLentilactobacillus\u003c/em\u003e (42.91%), together exceeding 90% of the community. In LMP, \u003cem\u003eLactiplantibacillus\u003c/em\u003e became the dominant genus.\u003c/p\u003e\n\u003cp\u003eFungal community composition also varied considerably across treatments (Figure 6B). In non-inoculated groups, MO was dominated by \u003cem\u003eWickerhamomyces\u003c/em\u003e (30.61%) and \u003cem\u003eCladosporium\u003c/em\u003e (11.04%). OP showed increased \u003cem\u003eCladosporium\u003c/em\u003e (15.93%) and \u003cem\u003eFusarium\u003c/em\u003e (3.02%), with \u003cem\u003eWickerhamomyces\u003c/em\u003e at 19.88%. O2P was dominated by \u003cem\u003ePlectosphaerella\u003c/em\u003e (21.04%), followed by \u003cem\u003eVishniacozyma\u003c/em\u003e (14.99%). OP2 was characterized by \u003cem\u003eWickerhamomyces\u003c/em\u003e (16.41%), \u003cem\u003eCladosporium\u003c/em\u003e (13.88%), and \u003cem\u003eAlternaria\u003c/em\u003e (14.24%). MP showed distinctively high abundances of \u003cem\u003ePseudopeyronellaea\u003c/em\u003e (5.26%) and \u003cem\u003ePleurotus\u003c/em\u003e (5.07%), with \u003cem\u003eWickerhamomyces\u003c/em\u003e at 23.37%.\u003c/p\u003e\n\u003cp\u003eLAB inoculation induced clear shifts in fungal communities. LMO showed increased \u003cem\u003eAlternaria\u003c/em\u003e (14.59%), \u003cem\u003eAspergillus\u003c/em\u003e (5.33%), and \u003cem\u003ePleurotus\u003c/em\u003e (5.05%). LO2P exhibited the highest \u003cem\u003eWickerhamomyces\u0026nbsp;\u003c/em\u003eabundance (43.38%) among all treatments, while \u003cem\u003ePlectosphaerella\u003c/em\u003e decreased sharply to 1.14%. LOP had higher \u003cem\u003eWickerhamomyces\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e but reduced \u003cem\u003eCladosporium\u003c/em\u003e (8.21%). LOP2 showed the highest \u003cem\u003ePleurotus\u003c/em\u003e abundance (7.94%) and reduced \u003cem\u003eAlternaria\u003c/em\u003e. LMP displayed increased \u003cem\u003eWickerhamomyces\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e but the lowest \u003cem\u003eFusarium\u003c/em\u003e abundance.\u003c/p\u003e\n\u003cp\u003eGenus-specific dominance patterns were evident: \u003cem\u003ePlectosphaerella\u003c/em\u003e in O2P, \u003cem\u003eAlternaria\u003c/em\u003e in OP2, \u003cem\u003ePseudopeyronellaea\u003c/em\u003e and \u003cem\u003ePleurotus\u003c/em\u003e in MP, and \u003cem\u003eCephalotrichum\u003c/em\u003e and \u003cem\u003eVishniacozyma\u003c/em\u003e in MO.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.2 Bacterial and fungal \u0026alpha;-diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 7 displays the alpha diversity of bacterial communities in silage samples under different oat-pea mixed cropping ratios, with and without lactic acid bacteria (LAB) inoculation. Statistical analysis indicated significant differences in the Chao1 index between LAB-inoculated and non-inoculated groups, suggesting that LAB inoculation reduced bacterial species richness.\u003c/p\u003e\n\u003cp\u003eGood\u0026rsquo;s coverage index was consistently high across all treatments but differed significantly between groups (P = 0.030). The Faith_pd index showed distinct distribution patterns between inoculation groups, though this difference was not statistically significant (P = 0.130). Significant differences were observed in both the Shannon index (P = 0.004) and Pielou\u0026rsquo;s evenness index (P = 0.004), reflecting variations in community diversity and evenness. The observed species index showed a trend toward significance (P = 0.071).\u003c/p\u003e\n\u003cp\u003eFigure 8 shows the alpha diversity of fungal communities in silage samples across various oat-pea mixed cropping ratios, with and without lactic acid bacteria (LAB) inoculation. The Chao1 index exhibited a non-significant trend between inoculation groups (P = 0.09), despite visible differences in distribution.\u003c/p\u003e\n\u003cp\u003eGood\u0026rsquo;s coverage was consistently high across treatments, with no significant difference between groups (P = 0.29). Similarly, no significant differences were observed in the Pielou evenness, Shannon, Simpson, or observed species indices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3 Bacterial and fungal \u0026beta;-diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 9, the stress values for both bacterial (Stress = 0.076) and fungal (Stress = 0.121) community ordination were below 0.2, indicating reliable representation of multivariate patterns. For bacterial communities, the MDS1 axis revealed clear separation between LAB-inoculated and non-inoculated groups. Fungal communities also showed substantial compositional shifts in response to LAB inoculation across treatments. Specifically, LMO and LOP clustered closely along both MDS1 and MDS2 axes, while LMP formed a distinct cluster. Furthermore, LOP2 was clearly separated from all other groups along the MDS3 axis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.4 Key species differences and marker species analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant differences in genus-level composition were observed for both bacterial and fungal communities across the silage treatments.\u003c/p\u003e\n\u003cp\u003eIn bacterial communities (Figure 10A), clear distinctions were evident between LAB-inoculated and non-inoculated groups. \u003cem\u003eLactiplantibacillus\u003c/em\u003e increased substantially across all LAB-inoculated treatments, with the most pronounced increases occurring in the MO and OP groups. The abundance of \u003cem\u003eLentilactobacillus\u003c/em\u003e was influenced by cropping ratio: it increased slightly in the OP2 treatment after LAB inoculation but decreased in other groups. \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e showed the greatest reduction in the MP treatment following LAB addition. Additionally, sequences assigned to Chloroplast and Mitochondria were significantly more abundant in the LMP treatment, while rare genera such as \u003cem\u003eCitrobacte\u003c/em\u003er were relatively enriched in LO2P.\u003c/p\u003e\n\u003cp\u003eFor fungal communities (Figure 10B), \u003cem\u003eWickerhamomyces\u003c/em\u003e was strongly dominant in the MO treatment. The MP group showed significantly higher abundances of \u003cem\u003ePleurotus\u003c/em\u003e and \u003cem\u003ePseudopeyronellaea\u003c/em\u003e than other treatments. The OP treatment was characterized by substantial increases in \u003cem\u003ePlectosphaerella\u003c/em\u003e and \u003cem\u003eVishniacozyma\u003c/em\u003e; O2P showed elevated abundances of \u003cem\u003eCladosporium\u003c/em\u003e and \u003cem\u003eThermomyces\u003c/em\u003e; and OP2 exhibited increased \u003cem\u003eAlternaria\u003c/em\u003e and \u003cem\u003eTrichothecium\u003c/em\u003e. LAB inoculation significantly altered fungal composition: \u003cem\u003eAlternaria\u003c/em\u003e and \u003cem\u003eTrichothecium\u003c/em\u003e increased markedly in LMO; \u003cem\u003eWickerhamomyces\u003c/em\u003e increased sharply while \u003cem\u003ePlectosphaerella\u003c/em\u003e decreased dramatically in LOP; \u003cem\u003eAspergillus\u003c/em\u003e increased whereas \u003cem\u003eThermomyces\u003c/em\u003e decreased in LO2P; \u003cem\u003ePleurotus\u003c/em\u003e abundance rose significantly in LOP2; and \u003cem\u003eWickerhamomyces\u003c/em\u003e increased while \u003cem\u003eStemphylium\u003c/em\u003e decreased in LMP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.5 Microbial function prediction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 11A, functional prediction of the bacterial community indicated that biosynthesis pathways were predominantly associated with cellular metabolism and prokaryotic group metabolism. The O2P and OP2 groups showed slightly higher abundances of biosynthesis pathways compared to the MO and MP groups. Notably, the abundance of secondary metabolite synthesis functions was 15% higher in LAB-inoculated treatments (LOP, LO2P) than in non-inoculated treatments.\u003c/p\u003e\n\u003cp\u003eWithin degradation-utilization-assimilation pathways, core functions were related to alcohol degradation and aromatic hydrocarbon degradation. The MP group had significantly higher abundance of carbohydrate derivative degradation functions than the MO group. The OP group showed approximately 15% greater abundance of hydrocarbon degradation functions compared to O2P, while LAB inoculation increased the abundance of nitrogen compound degradation functions by about 17% in the LOP group.\u003c/p\u003e\n\u003cp\u003eAmong precursor metabolite and energy generation pathways, the tricarboxylic acid (TCA) cycle and glycolysis were identified as core functions. The MP group exhibited significantly higher TCA cycle activity than the MO group, and the OP2 group showed approximately 33% higher abundance of pentose phosphate pathway functions compared to O2P. LAB inoculation increased the abundance of fermentation-related functions by approximately 25%. Furthermore, functional abundances related to glycan metabolism, macromolecule modification, and metabolic clusters varied considerably across treatments, with high pea proportion treatments promoting synergistic interactions between biosynthesis and energy metabolism pathways.\u003c/p\u003e\n\u003cp\u003eAs illustrated in Figure 11B, fungal community functional prediction revealed that carbohydrate synthesis functions dominated biosynthesis pathways. The MO group had 12.5% higher abundance of amino acid synthesis functions than the MP group, while the OP group showed 19.0% higher abundance compared to O2P. LAB inoculation increased secondary metabolite synthesis functions by 25% in the LOP group.\u003c/p\u003e\n\u003cp\u003eIn degradation-utilization-assimilation pathways, carbohydrate degradation functions were most abundant. The MP group exhibited 26.7% higher fatty acid degradation function abundance than the MO group, while the OP2 group showed 38.9% higher C1 compound utilization function abundance compared to OP. LAB inoculation increased inorganic nutrient metabolism functions by 33.3% in the LMP group.\u003c/p\u003e\n\u003cp\u003eGlycolysis was identified as the core functional pathway in precursor metabolite and energy generation. Additionally, functional abundances related to glycan metabolism and metabolic clusters also varied significantly across treatments.s.\u003c/p\u003e\n\u003ch2\u003e2.4 Quantification of synergistic effects\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;2.4.1 Mantel analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the correlation analysis between fungal communities and silage quality (Figure 12), acid detergent fiber (ADF) demonstrated a strongly significant positive correlation with fungal communities (r = 0.231, P = 0.002), and neutral detergent fiber (NDF) also showed a significant positive correlation (r = 0.187, P = 0.012). In contrast, correlations of crude protein (CP) and water-soluble carbohydrates (WSC) with fungal communities were relatively weak.\u003c/p\u003e\n\u003cp\u003eRegarding fermentation parameters, lactic acid (LA) exhibited a strongly significant negative correlation with fungal communities (r = -0.264, P = 0.001), while pH showed a significant positive correlation (r = 0.168, P = 0.027). Acetic acid (AA) and the ammonia nitrogen/total nitrogen ratio (AN/TN) also demonstrated significant positive correlations with fungal communities.\u003c/p\u003e\n\u003cp\u003eA significant positive correlation was found between bacterial and fungal communities (r = 0.198, P = 0.005). Lactic acid (LA) appeared to enhance bacterial dominance through indirect effects, while pH exerted opposing regulatory effects on the successional dynamics of both bacterial and fungal communities.\u003c/p\u003e\n\u003cp\u003eFunctional differentiation was observed in how silage quality parameters influenced microbial communities: bacterial communities were more responsive to water-soluble carbohydrates (WSC) and lactic acid (LA), whereas fungal communities were primarily associated with structural carbohydrate degradation. Among these factors, lactic acid (LA) and pH were identified as core regulators of microbial community dynamics: LA suppressed fungal development and reinforced bacterial dominance, while pH mediated contrasting successional patterns in both communities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.2 Redundancy analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRedundancy analysis (RDA) results (Figure 13) indicated that for the bacterial community (Figure 13A), RDA1 and RDA2 explained 18.22% and 11.55% of the total variation, respectively, cumulatively accounting for 30.77%. Water-soluble carbohydrates (WSC) and lactic acid (LA) were identified as the primary drivers, synergistically promoting the proliferation of lactic acid bacteria. pH and crude protein (CP) significantly influenced separation along the RDA2 axis, with the MP, LMO, and LOP groups\u0026mdash;characterized by high CP and pH\u0026mdash;clearly distinguished from other treatments. Acid detergent fiber (ADF) and neutral detergent fiber (NDF) had comparatively weaker effects on bacterial community composition.\u003c/p\u003e\n\u003cp\u003eFor the fungal community (Figure 13B), RDA1 and RDA2 accounted for 37.39% and 15.04% of the variation, respectively, with a cumulative explanation rate of 52.43%. ADF and NDF were the main influencing factors, with the MO and O2P groups enriched along the positive RDA1 axis. pH and ammonia nitrogen/total nitrogen (AN/TN) played defining roles along RDA2, where the MP and LMP groups\u0026mdash;associated with high pH and AN/TN\u0026mdash;clustered along the positive axis. In contrast to their strong effects on bacteria, WSC and LA exhibited weaker influences on fungal community assembly.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e 3.1 Synergistic regulation of silage fermentation quality by mixed-sowing ratios and addition of lactic acid bacteria\u003c/p\u003e\n\u003cp\u003eThe present study demonstrates that the mixed cropping ratios of oats and forage peas significantly influence silage fermentation quality and nutritional characteristics by modulating the carbon-nitrogen balance and structural carbohydrate composition of the raw materials. As the proportion of peas increased, crude protein (CP) content rose, while water-soluble carbohydrate (WSC) content declined, highlighting the complementary nutritional contributions of legume-grass intercropping. [\u003csup\u003e17\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eA higher pea proportion delayed the rate of pH decline due to its stronger buffering capacity, thereby prolonging protease activity. This extended enzymatic action led to an increased ammonia nitrogen/total nitrogen (AN/TN) ratio and higher dry matter loss (DML)[\u003csup\u003e18\u003c/sup\u003e]. Meanwhile, inadequate water-soluble carbohydrate (WSC) availability restricted the proliferation of lactic acid bacteria (LAB), thereby reducing their ability to suppress spoilage microorganisms.[\u003csup\u003e19\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eThe 1:1 mixed cropping ratio of oats and forage peas achieved an optimal balance between nutrient supply and fermentation stability. Crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), ammonia nitrogen/total nitrogen (AN/TN) ratio, and dry matter loss (DML) all remained at moderate levels, favoring overall silage quality. This result aligns with the findings of Zhang et al. [\u003csup\u003e20\u003c/sup\u003e], who reported that optimal silage quality is attained at mixed cropping ratios of 6:4 or 5:5. Moderate mixed cropping enhances fermentation efficiency by optimizing the C/N ratio, and the 1:1 ratio further extends this conclusion to systems prioritizing both nutritional and fermentative performance.\u003c/p\u003e\n\u003cp\u003eCompared to non-inoculated treatments, LAB-inoculated treatments exhibited a modest increase in crude protein (CP) content\u0026mdash;though not statistically significant\u0026mdash;along with significant reductions in neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents, as well as a decrease in water-soluble carbohydrate (WSC) content. These findings align with those reported by Jayakrishnan Nair et al\u0026nbsp;[\u003csup\u003e21\u003c/sup\u003e]. and ALLI et al[\u003csup\u003e22\u003c/sup\u003e]\u0026nbsp;. The observed effects may be attributed to the low ambient temperatures in the region, which limit the natural attachment of lactic acid bacteria to forage. In contrast, LAB inoculation ensured a sufficient population of bacteria for the ensiling process[\u003csup\u003e23\u003c/sup\u003e]. By inhibiting the growth of spoilage microorganisms, LAB inoculation reduced protein degradation, ultimately resulting in higher protein retention in inoculated silage compared to non-inoculated silage.\u003c/p\u003e\n\u003cp\u003eFurthermore, the elevated acidity in the LAB-inoculated silage altered the fiber structure, increasing its susceptibility to microbial and enzymatic degradation. Consequently, the fiber content was lower in the inoculated silage than in its non-inoculated counterpart\u0026nbsp;[\u003csup\u003e24\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;3.2 Effects of mixing ratio and lactobacilli addition on microbial community structure\u003c/p\u003e\n\u003cp\u003eIn this study, mixed cropping ratios and inoculation with lactic acid bacteria (LAB significantly influenced the structure and function of silage microbial communities by modifying substrate characteristics and microenvironments. For bacterial communities, LAB inoculation was the key factor shaping community assembly. The relative abundance of \u003cem\u003eLactiplantibacillus\u003c/em\u003e increased significantly in LAB-inoculated silage, indicating that exogenous inoculation enhanced its dominance. In non-inoculated groups, the fluctuating abundance of this genus likely resulted from its low initial natural abundance and constraints imposed by complex substrate conditions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLentilactobacillus\u003c/em\u003e responded synergistically to cropping ratios, reaching its highest abundance in the non-inoculated 1:1 mixed cropping group, suggesting that the carbon-to-nitrogen ratio at this proportion supported its metabolic needs. In the inoculated 1:2 mixed cropping group, \u003cem\u003eLentilactobacillus\u003c/em\u003e and \u003cem\u003eLactiplantibacillus\u003c/em\u003e established a stable \u0026ldquo;acid-production and degradation\u0026rdquo; functional partnership, highlighting how specific mixed ratios optimize microbial interactions. These findings align with previous work by Wu et al.[\u003csup\u003e25\u003c/sup\u003e].\u0026nbsp;In the non-inoculated 1:1 mixed cropping group, the dominance of \u003cem\u003eLentilactobacillus\u003c/em\u003e was attributed to a carbon-nitrogen ratio that aligned with its metabolic requirements. In contrast, following LAB inoculation in the 1:2 mixed cropping group, a stable functional consortium emerged with \u003cem\u003eLactiplantibacillus\u003c/em\u003e, resulting from synergistic optimization between the inoculant and the mixed cropping ratio. [\u003csup\u003e26\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eMixed cropping ratios directly shaped bacterial community composition by influencing substrate chemistry. As the proportion of peas increased, the abundance of spoilage-associated genera such as\u0026nbsp;\u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e declined markedly, likely due to the enhanced buffering capacity of high-protein substrates that delayed acidification. Conversely,\u0026nbsp;\u003cem\u003ePediococcus\u003c/em\u003e became enriched in the 1:1 mixed cropping group, consistent with the intermediate levels of water-soluble carbohydrates and fiber. LAB inoculation further reduced the prevalence of endogenous non-target bacteria and suppressed spoilage organisms through rapid acid production.\u0026nbsp;Martin B [\u003csup\u003e27\u003c/sup\u003e] noted that peas are susceptible to spoilage at early maturity, when their dry matter concentration remains low, as high protein content delays acidification\u0026mdash;aligning with the observed reduction in spoilage bacteria such as \u003cem\u003eHafnia\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eFungal communities exhibited more complex niche differentiation in response to treatment conditions. Mixed cropping ratios directly influenced taxonomic composition: Plectosphaerella was most abundant in the non-inoculated 2:1 mixed cropping group, likely due to its adaptability to degrading grassy fiber. LAB inoculation modulated fungal assemblages through a dual mechanism\u0026mdash;not only reducing \u0026alpha;-diversity and enriching acid-tolerant yeasts such as Wickerhamomyces, but also selectively preserving functionally important taxa. For instance, in the LAB-inoculated 1:2 mixed cropping group, the abundance of Pleurotus increased to 7.94%, suggesting a potential role in converting structural carbohydrates via lignin degradation. This \u0026ldquo;inhibition-retention\u0026rdquo; balance may be attributed to the strong acid tolerance of Pleurotus, the dependence on its degradative activity in high-fiber substrates, and the use of a moderate inoculation rate that permitted fungal functionality.\u003c/p\u003e\n\u003cp\u003eChen et al. [\u003csup\u003e28\u003c/sup\u003e] reported that inoculation with LAB (e.g., Lactiplantibacillus plantarum) significantly increased the relative abundance of lactobacilli, suppressed spoilage bacteria such as Proteobacteria, and promoted homofermentative metabolism dominated by lactic acid production\u0026mdash;a conclusion further supported by Feng et al. [\u003csup\u003e29\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;3.3 Coupling of microbial function and fermentation quality\u003c/p\u003e\n\u003cp\u003eIn this study, inoculation with lactic acid bacteria (LAB) significantly influenced silage quality through direct modulation of microbial communities, demonstrating a characteristic trade-off between accelerated acidification and fermentation precision. LAB inoculation led to a significant positive correlation between the abundance of \u003cem\u003eLactiplantibacillus\u003c/em\u003e and lactic acid (LA) content, and a significant negative correlation with pH. Rapid acidification effectively suppressed spoilage bacteria such as \u003cem\u003eHafnia-Obesumbacterium,\u0026nbsp;\u003c/em\u003eresulting in a marked reduction in the ammonia nitrogen to total nitrogen ratio (AN/TN)\u0026mdash;a finding consistent with the results reported by Zhang et al.[\u003csup\u003e30]\u003c/sup\u003e. Similarly, Qiang et al. demonstrated in a study of alfalfa and Suaeda glauca mixed silage that LAB inoculation significantly reduced the abundance of undesirable bacteria, including \u003cem\u003eEnterobacteriaceae\u003c/em\u003e.[\u003csup\u003e31\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eMuck et al.\u0026nbsp;[\u003csup\u003e32\u003c/sup\u003e] observed that bacteria\u0026mdash;particularly lactic acid bacteria (LAB)\u0026mdash;prefer soluble substrates such as water-soluble carbohydrates (WSC) and lactic acid (LA), which they utilize in rapid fermentation to produce acids and lower pH. Homofermentative LAB (e.g.,\u0026nbsp;\u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e) accelerate acidification by rapidly consuming WSC to produce lactic acid, whereas heterofermentative LAB (e.g.,\u0026nbsp;\u003cem\u003eLentilactobacillus buchneri\u003c/em\u003e) enhance aerobic stability by converting lactic acid into acetic acid and 1,2-propanediol. In contrast, fungi (yeasts and molds) dominate the degradation of structural substrates such as acid detergent fiber (ADF) and neutral detergent fiber (NDF), and become more active under elevated pH or ammonia nitrogen (AN) conditions[\u003csup\u003e33\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eIn the present study, bacteria preferentially utilized soluble substrates including water-soluble carbohydrates (WSC), lactic acid (LA), and fermentation acids, whereas fungi were dominant in degrading structural substrates such as acid detergent fiber (ADF) and neutral detergent fiber (NDF) and were influenced by variations in pH, ammonia nitrogen (AN), and total nitrogen (TN). Mixed cropping ratios mediated community assembly by modulating substrate carbon/nitrogen (C/N) ratios (e.g., WSC/ADF and crude protein (CP)). Meanwhile, LAB inoculation directionally shaped microbial communities through a dual mechanism of \u0026ldquo;carbon source competition plus acidification-mediated inhibition\u0026rdquo;, thereby providing a strategic basis for optimizing silage microbial function.\u003c/p\u003e\n\u003cp\u003eNotably, propionic acid (PA) and acetic acid (AA) levels increased following LAB inoculation, which correlated with a metabolic shift toward heterofermentation by \u003cem\u003eLentilactobacillus\u003c/em\u003e under low-WSC conditions. Furthermore, the low-temperature environment of the Qinghai\u0026ndash;Tibet Plateau selectively constrained homofermentative bacteria, which exhibit optimal activity at 25\u0026ndash;30\u0026deg;C, thereby creating an ecological niche that favored heterofermentative metabolism.\u0026nbsp;Lin et al.[\u003csup\u003e34\u003c/sup\u003e] demonstrated that heterofermentative bacteria (e.g., Lentilactobacillus) can emerge as the dominant species during later stages of silage fermentation under low-temperature conditions. Li et al. [\u003csup\u003e35\u003c/sup\u003e] further indicated that low temperatures suppress the glycolytic efficiency of homofermentative bacteria, leading facultative heterofermenters to metabolize and produce acetic acid under carbohydrate-limited conditions. Lin et al demonstrated that heterofermentative bacteria (e.g., \u003cem\u003eLentilactobacillu\u003c/em\u003es) may become dominant strains in the late stage of silage under low-temperature conditions.\u003c/p\u003e\n\u003cp\u003eIn this experiment, the bacterial inoculum contained heterofermentative contaminants. Insufficient water-soluble carbohydrates (WSC) in monocropped oat and non-inoculated 1:1 mixed cropping groups limited the substrates available for homofermentation; however, feedstocks with intrinsically high WSC content were able to circumvent this limitation. Accordingly, LAB inoculation strategies should prioritize pure homofermentative strains tailored to both environmental conditions and substrate composition to balance acidification efficiency with fermentation precision.\u003c/p\u003e\n\u003cp\u003eBacterial communities established a self-reinforcing cycle of \u0026ldquo;high lactic acid\u0026ndash;low pH\u0026rdquo; driven by the availability of WSC and lactic acid (LA), whereas fungal communities contributed to fiber degradation modulated by acid detergent fiber (ADF) and pH. Together, these microbial groups collaboratively influenced silage quality through an interactive network of \u0026ldquo;bacterial fermentation\u0026ndash;fungal degradation\u0026rdquo;. Mantel tests confirmed that bacterial community composition was significantly correlated with WSC and LA, while fungal communities were strongly associated with ADF, corroborating the directional regulation of microbial function by substrate characteristics.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study elucidates the synergistic effects of mixed cropping ratios and lactic acid bacteria (LAB) inoculation on silage quality in oat/forage pea mixed silage produced in a plateau corral environment. The results demonstrate that a 1:1 oat-to-pea mixing ratio significantly increased crude protein (CP) content, optimized ammonia nitrogen to total nitrogen (AN/TN) ratio and dry matter loss (DML), and elevated propionic acid (PA) and acetic acid (AA) concentrations.\u003c/p\u003e\u003cp\u003eMixed cropping ratios directed the selection of functional microbial communities based on substrate composition, while LAB inoculation reshaped bacterial community structure. Fungal communities exhibited functional compensation: acid-tolerant fungi contributed to fiber degradation without substantially increasing DML. An interactive \u0026ldquo;bacterial fermentation\u0026ndash;fungal degradation\u0026rdquo; network mediated silage quality through cascading substrate-microbe interactions.\u003c/p\u003e\u003cp\u003eIn conclusion, the combination of 1:1 oat-pea mixed cropping and LAB inoculation achieved an optimal balance among nutritional complementation, fermentation precision, and microbial functionality, establishing it as a recommendable silage strategy for plateau regions. These findings provide a theoretical basis for targeted microbial management in legume-grass mixed silage systems and offer practical insights for high-quality forage production on the Qinghai\u0026ndash;Tibet Plateau.\u003c/p\u003e\u003cp\u003eThis study has the following limitations: Firstly, the experiment was only conducted at specific sites in Haiyan County on the Qinghai-Tibet Plateau. Affected by the local climate, soil, and microbial background, the extrapolation of the research conclusions to other regions requires cautious verification. Secondly, the observation time is limited; only samples after 45 days of fermentation were analyzed, failing to cover the mechanisms of changes in microbial communities and quality during long-term storage stability and after aerobic exposure. Thirdly, microbial function analysis relies on metagenomic predictions, lacking direct verification at the molecular levels such as transcriptomics and proteomics, and some functional inferences need to be confirmed in subsequent studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e Data is contained within the article or supplementary material.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the author Y.M.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by Two-Level Fiscal Support Project of Qinghai University (SSYS-2025-04); Key Laboratory of Grassland Ecosystem (Ministry of Education) \u0026quot;Unveiling and Leading\u0026quot; Project (KLGE-2024-04); Gansu Provincial Youth Doctor Support Program for Higher Education Institutions (2024QB-076).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, Y.M. and Y.Z.; methodology, Y. M., Y. Z. and G. L.; software, Y.M.; validation, Y.M., Y.Z.; formal analysis, Y.M.; investigation, Y.M..; resources, Y. M, Y. Z. and C.X; data curation, Y. Z. and Y. M.; writing\u0026mdash;original draft preparation, Y. Z. and Y.M.; writing\u0026mdash;review and editing, Y.Z.; visualization, Y.M.; supervision, Y. Z.; project administration, C.X., S.W. and T.W.; funding acquisition, Y. Z. ,W. L.and X. P. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLong MC. The development status, existing problems and suggestions of the cattle and sheep industry in Haiyan County, Qinghai. 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Acta Prataculturae Sinica, 2023, 32(8): 164-175. https://doi.org/10.1007/S00203-021-02658-Z\u003c/li\u003e\n\u003cli\u003eLin DD, Ju ZL, Chai JK, Zhao GQ. Screening and identification of low temperature tolerant lactic acid bacterial epiphytes from oats. Acta Prataculturae Sinica, 2022, 31(5): 103-114. https://doi.org/10.11686/cyxb2021358\u003c/li\u003e\n\u003cli\u003eLi HP, Guan H, Jia ZF, Liu WH, Ma X, Liu Y, Wang H, Ma L, Zhou QP. Screening of antifreeze-thawed lactic acid bacteria and their effects on oat silage fermentation quality and aerobic stability. Acta Prataculturae Sinica, 2022, 31(12): 158-170. https://doi.org/10.11686/cyxb2022087\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"silage, lactic acid bacteria, mixed-cropping, oat, pea","lastPublishedDoi":"10.21203/rs.3.rs-7436223/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7436223/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeasonal forage shortages pose a significant challenge to livestock production on the Qinghai-Tibet Plateau. To address this issue, this study developed an integrated land utilization strategy combining \"cultivation + on-site ensiling\" using mixed oats and forage peas. The research evaluated how different mixed-cropping ratios and lactic acid bacteria (LAB) inoculation affect silage production in this high-altitude region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn silage grown in corral plots, the 1:1 oat-pea ratio (OP) showed clear advantages over monocropped oats, increasing crude protein by 29.43% while reducing acid detergent fiber (ADF) by 14.37% and neutral detergent fiber (NDF) by 11.21%.\u003c/p\u003e\n\u003cp\u003eLAB inoculation improved the fermentation quality of corral-grown silage. In inoculated oat silage, the relative abundance of \u003cem\u003eLactiplantibacillus\u003c/em\u003eincreased significantly to 66.54%, which suppressed spoilage bacteria (e.g., \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e) and reduced the ammonia nitrogen-to-total nitrogen ratio by 15–20%.\u003c/p\u003e\n\u003cp\u003eThe OP treatment minimized dry matter loss among corral-grown silages. LAB inoculation increased propionic and acetic acid production by 25%. Furthermore, functional fungi (e.g., \u003cem\u003ePleurotus\u003c/em\u003e, reaching 7.94% relative abundance in inoculated OP2 silage) contributed to fiber degradation.\u003c/p\u003e\n\u003cp\u003eMetabolic prediction indicated that LAB inoculation increased nitrogen compound degradation by 17% and stimulated secondary metabolite synthesis. Bacterial communities correlated with soluble carbohydrate and lactic acid levels, whereas fungal communities regulated fiber breakdown. Redundancy analysis showed that fiber content explained over 50% of fungal community variation in corral silage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 1:1 oat-pea ratio with LAB inoculation optimizes silage production specifically for corral systems, achieving carbon-nitrogen balance and microbial synergy. This corral-based approach provides a sustainable solution for alpine livestock resilience, transforming underutilized confinement areas into high-quality forage resources.\u003c/p\u003e","manuscriptTitle":"Microbial Community Structure and Carbon-Nitrogen Coupling Mechanisms in Mixed Silage of Oats and Forage Peas in Corral of the Qinghai-Tibet Plateau","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-26 14:51:15","doi":"10.21203/rs.3.rs-7436223/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-20T07:55:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-15T16:13:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-26T21:46:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102537538787774587343092657215477544377","date":"2025-09-24T16:28:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51241022267274676680098396281002813930","date":"2025-09-17T20:27:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-17T14:07:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-11T08:37:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-10T05:47:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chemical and Biological Technologies in Agriculture","date":"2025-09-09T09:49:30+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":"8239045b-4bdb-41ef-b3c8-e84b0f74f0ca","owner":[],"postedDate":"September 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-12T09:53:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-26 14:51:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7436223","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7436223","identity":"rs-7436223","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}