Effects of low temperature silage on microbial community and free amino acids of oat silage quality

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Results Fermentation was significantly inhibited at 5°C, with a slower pH decline, lower lactic acid production, and a reduced lactic acid to acetic acid (LA/AA) ratio. Microbial diversity was higher under low-temperature conditions, with Pseudomonas , Enterobacter , and Proteobacteria dominating. Most FAAs, particularly lysine, histidine, and arginine, accumulated at low temperatures. Correlation analysis revealed that Enterobacter and Pseudomonas were positively correlated with many FAAs, indicating their key roles in proteolysis. Conclusions These findings contribute to a deeper understanding of the microbial and biochemical mechanisms of low-temperature silage fermentation and provide a theoretical basis and strategic support for optimizing silage quality in cold regions. low temperature silage oat microbial community free amino acids Figures Figure 1 Figure 2 Figure 3 1. Introduction Oat, a high-yield and high-quality dual-purpose crop for grain and forage, has been widely promoted in cold regions in recent years due to its unique biological characteristics and strong environmental adaptability. In particular, it has become one of the primary forage sources on the Qinghai–Tibet Plateau and its surrounding areas in China(Bao et al., 2023 ; Li et al., 2022a ). However, the oat harvesting season in this region often coincides with prolonged periods of rainy and overcast weather, making traditional sun-drying difficult and increasing the risk of mold development and nutrient loss. Silage offers an effective solution to mitigate the negative effects of inclement weather and helps preserve forage quality and nutritional value. Nevertheless, the entire silage process on the Qinghai–Tibet Plateau is subjected to low ambient temperatures, which adversely affect fermentation(Gong et al., 2023 ). Studies have shown that low-temperature silage fermentation typically results in reduced lactic acid production and elevated pH levels, making silage more susceptible to spoilage and detrimental to livestock health (Chen et al., 2020b ). When ambient temperatures fall below 15°C, the efficiency of conventional fermentation drops significantly, leading to increased dry matter losses (8–15%) and accelerated nutrient degradation (Nokhsorov et al., 2024 ). These factors severely limit the application value of oat silage in livestock production in alpine regions. Microorganisms play pivotal roles in silage fermentation, serving as the primary drivers of the process. Lactic acid bacteria (LAB) represent the most critical microbial group in silage, fermenting water-soluble carbohydrates to generate organic acids and establishing an acidic environment that inhibits the growth of spoilage microorganisms (Wang et al., 2022 ). Research into silage microbial communities has progressively deepened in recent years, revealing the importance of microbial composition and interactions for fermentation quality. Concurrently with enhanced understanding of microbial fermentation mechanisms, researchers are increasingly exploring microbial dynamics under extreme conditions (Xia et al., 2023 ). The impact of low temperatures on silage fermentation manifests primarily through microbial community shifts. Temperature decreases significantly inhibit microbial activity, particularly compromising LAB growth and metabolism. This suppression reduces lactic acid production, resulting in elevated pH and inferior fermentation quality (Zhang et al., 2017). During low-temperature silage fermentation, the metabolic processes of lactic acid bacteria differ fundamentally from those in conventional silage produced at room temperature. (Xu et al., 2019 ). Consequently, low-temperature silage often exhibits inadequate acidification, high pH, and increased vulnerability to spoilage microorganisms, thereby compromising storage stability and nutritional value(Li et al., 2022b ). Free amino acids (FAAs), released from the breakdown of proteins or peptides, serve as direct indicators of proteolytic degradation. During silage fermentation, proteolysis occurs through microbial and plant enzymatic activity, altering FAA concentrations and directly influencing nitrogen utilization efficiency in the fermented feed. Advanced techniques such as high-performance liquid chromatography (HPLC) enable precise quantification of amino acids, while investigations into fermentation conditions and microbial community dynamics are advancing this research field (Gauthankar et al., 2021 ). Studies demonstrate that post-silage FAA profiles vary significantly depending on fermentation conditions, microbial composition, and duration. Zhang et al. (2017) reported that the concentrations of essential amino acids typically decrease after the silage of oat, whereas non-essential amino acids may increase, with specific patterns closely related to the fermentation environment. Guo et al. ( 2018 ) further established that concentration changes of all 20 amino acids correlate strongly with microbial community succession. Specifically, proliferation of Lactobacillus buchneri showed a positive association with histidine and lysine degradation. Despite growing attention to microbial succession and fermentation quality under low-temperature silage conditions, few studies have simultaneously explored the temporal dynamics of microbial community shifts and free amino acid accumulation across different cold-temperature regimes. In particular, the relationships between dominant psychrotolerant bacteria and proteolysis remain poorly understood. Moreover, current research lacks integrated approaches that correlate microbial ecology with nitrogen degradation indicators, such as ammonia-N and FAA composition, under prolonged fermentation. These gaps limit our mechanistic understanding of silage deterioration risks and quality fluctuations in cold-climate forage systems. Therefore, elucidating FAA dynamics in low-temperature silage and their interrelationship with microbial activity holds significant theoretical and practical value for optimizing fermentation techniques and enhancing the quality of oat silage produced under cold conditions. 2. Materials and methods 2.1 Preparation of oat silage Oat (cultivar "Longyan No. 3") seeds were provided by the College of Grassland Science, Gansu Agricultural University (Lanzhou, China). "Longyan No. 3" is a forage oat cultivar originally derived from a local landrace in Gansu Province and officially approved by the National Grass Variety Approval Committee of China in 2010. The plants were cultivated in Dachai Gou Township, Tianzhu Tibetan Autonomous County, Gansu Province, China (E102°15′, N36°45′; altitude 2594 m). The crop was harvested at the milk stage on August 28, 2023, and wilted in a shaded and well-ventilated area until it reached an appropriate dry matter content for silage (346.24 ± 4.85 g/kg fresh matter). The wilted material was then chopped into 3–4 cm lengths using a forage kneading machine. The experiment comprised four temperature treatments: three low-temperature groups (5°C, 10°C, and 15°C) and one control group (25°C). For each treatment, 500 g of chopped oat material was packed into polyethylene plastic bags (250 × 350 mm), vacuum-sealed using a vacuum packaging machine, and transported to the laboratory. The sealed bags were then stored in temperature-controlled incubators preset to the respective treatment temperatures. Samples were collected after 3, 7, 14, 60, and 90 d of silage, with three replicates per time point. 2.2 Determination of fermentation parameters and nutritional composition For pH and chemical analyses, 20 g of fresh sample was homogenized with 180 mL of sterile distilled water for 30 s using a blender. The homogenate was sequentially filtered through four layers of cheesecloth and subsequently through filter paper. The resulting filtrate was immediately analyzed for pH using a calibrated pH meter (PHS-3C, Shanghai Yoke Instrument Co., Ltd., China). The filtrate was then divided into two aliquots: one for organic acid analysis (lactic acid, acetic acid, propionic acid, butyric acid) and another for ammonia nitrogen (NH₃-N) determination. Both aliquots were stored at -20°C until analysis. For organic acid quantification, one aliquot was acidified to approximately pH 2.0 with 7.14 mol/L H₂SO₄, filtered through a 0.22-µm aqueous phase syringe filter, and injected into a high-performance liquid chromatography (HPLC) system (Agilent 1260 series; column: Shodex Rspak KC-811 S-DVB gel column, 300 mm × 8.0 mm; mobile phase: 3 mmol/L HClO₄; column temperature: 50°C; detector: DAD; injection volume: 5 µL; flow rate: 1.0 mL/min; detection wavelength: 210 nm). For NH₃-N analysis, 40 mL of the non-acidified filtrate was mixed with 10 mL of 25% (w/v) trichloroacetic acid (TCA) solution (4:1, v/v) and incubated overnight at 4°C to precipitate true proteins. Following high-speed centrifugation (10,000 r/min, 4°C, 15 min), the supernatant was collected, and NH₃-N concentration was determined using the phenol-hypochlorite method(Chen et al., 2020a ; Zhou et al., 2016 ). For dry matter (DM) determination, 200 g of fresh sample was placed in kraft paper bags and dried in an oven at 65°C for approximately 72 h. The dried samples were ground using a mill and sieved through a 40-mesh screen (0.425 mm pore size) for subsequent analysis of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and water-soluble carbohydrates (WSC). Total nitrogen (TN) content was determined using an automatic Kjeldahl nitrogen analyzer (K9840, Hannon Instruments Co., Ltd., Jinan, China). Crude protein (CP) content was calculated by multiplying TN content by 6.25. NDF and ADF contents were assessed according to the methods described by Van Soest et al. ( 1991 ). For WSC analysis, 100 mg of dried sample powder was weighed into a test tube, mixed with 15 mL of distilled water, and digested in boiling water for complete dissolution. After cooling to room temperature, the solution was filtered, and the filtrate was mixed with anthrone reagent and boiled again. The cooled mixture was then measured for optical density at 620 nm using a spectrophotometer. WSC content was calculated based on a pre-established standard curve(Li et al., 2021a ). 2.3 Bacterial community analysis For genomic DNA extraction from silage samples, 0.5 g of each sample was weighed and placed into 1.5 mL extraction tubes. The extracted genomic DNA was assessed for concentration and purity using UV spectrophotometry, while DNA integrity was evaluated by 1% agarose gel electrophoresis. Upon confirmation that the extracted genomic DNA met the required quality and quantity standards, PCR amplification of the full-length bacterial 16S rRNA gene was conducted using forward primer 27F (5'-AGRGTTYGATYMTGGCTCAG-3') and reverse primer 1492R (5'-RGYTACCTTGTTACGACTT-3'). Single-molecule real-time sequencing was employed, incorporating sample-specific 16-bp barcodes into the primers to enable multiplex sequencing. The thermal cycling protocol consisted of initial denaturation at 95°C for 30 s, followed by annealing at 57°C for 30 s, extension at 72°C for 60 s, and final extension at 72°C for 5 min. PCR amplicons were purified using Agencourt AMPure Beads (Beckman Coulter, Indianapolis, IN) and quantified using the PicoGreen dsDNA AssayKit (Invitrogen, Carlsbad, CA, USA). Following Qubit quantification, the purified PCR products were pooled in equimolar ratios according to the sequencing requirements for each sample. Library construction and quality control were performed using the SMRTbell Template Prep Kit 1.0-SPv3, and sequencing was conducted on the PacBio platform using the DNA/Polymerase Binding Kit 3.0 (PacBio). Post-sequencing, CCS (Circular Consensus Sequencing) reads were subjected to filtering, clustering, and denoising procedures, followed by taxonomic annotation and abundance profiling. Subsequent analyses included Alpha diversity, Beta diversity, correlation analysis, and functional prediction(C. Bai et al., 2022 ). 2.4 Determination of FAAs Content The oat silage samples were flash-frozen in liquid nitrogen and homogenized to a fine powder using a mortar and pestle under continuous liquid nitrogen cooling. The powdered samples were stored at -80°C until further analysis. For amino acid extraction, 100 mg of frozen silage powder was weighed into a 2 mL Eppendorf microcentrifuge tube and mixed with 1 mL of 0.5 M aqueous hydrochloric acid solution. The mixture was vortexed at 8000 rpm for 20 min, sonicated in a 25°C water bath for 20 min, and then centrifuged at 20,000 × g for 20 min. Finally, 250 µL of the supernatant was filtered through a 0.22 µm aqueous phase filter into an HPLC vial and diluted to 1 mL with 80% (v/v) acetonitrile aqueous solution. Authentic standards of 18 amino acids (purity > 99%) were purchased from Merck and Sigma-Aldrich (St. Louis, MO, USA). High-performance liquid chromatography (HPLC) analysis was performed using an Agilent InfinityLab Poroshell 120 HILIC-Z column (2.1 × 100 mm, 2.7 µm). The mobile phase consisted of solvent A (20 mM ammonium formate aqueous solution, pH = 3) and solvent B (20 mM ammonium formate dissolved in acetonitrile/water, 9:1 v/v, pH = 3). The flow rate was set at 0.5 mL/min, with an injection volume of 1 µL. The column temperature was maintained at 25°C. Mass spectrometry (MS) was conducted under electrospray ionization (ESI) in positive ion mode. The gas flow rate was set at 13.0 L/min, with a drying gas temperature of 330°C. The nebulizer pressure was 35 psi, sheath gas temperature was 390°C, and sheath gas flow rate was 12 L/min. The capillary voltage was set to 1500 V. Data acquisition was performed in multiple reaction monitoring (MRM) mode. The preparation of the mobile phases was as follows: a 200 mM ammonium formate stock solution was prepared in water, and the pH was adjusted to 3 using formic acid. Mobile phase A was prepared by diluting the stock solution with water at a 9:1 ratio. Mobile phase B was prepared by diluting the stock solution with acetonitrile at a 9:1 ratio. The final ionic strength of both mobile phases was 20 mM. 2.5 Statistical Analysis A two-way analysis of variance (ANOVA) was performed to evaluate the effects of silage temperature and fermentation duration on chemical composition, fermentation characteristics, and microbial counts. Statistical analyses were conducted using SPSS software (version 26.0; IBM SPSS Inc., Chicago, IL, USA). Differences were considered statistically significant at P < 0.05. 3. Results 3.1 Chemical composition of fresh oat material As shown in Table 1 , the DM content of the oat samples was 346.24 g/kg FM, indicating a moderate moisture level suitable for silage. The initial pH value was 6.27, suggesting low acidity and a slightly alkaline to neutral condition prior to fermentation. The samples exhibited relatively high CP content and moderate levels of WSC, indicating sufficient fermentable substrates to support microbial activity, promote lactic acid fermentation, and stabilize the fermentation environment. The essential amino acids (EAAs) in oat were relatively well balanced, which may enhance the efficiency of protein utilization by ruminants. The content of branched-chain amino acids (BCAAs), such as Val, Leu, and Ile, was relatively high, at 6.84 g/kg, 1.78 g/kg, and 2.63 g/kg, respectively. These amino acids are important for muscle development in animals. Additionally, the content of non-essential amino acids (NEAAs), such as Glu, Ala, and Asp, was also relatively abundant, with glutamic acid and alanine concentrations of 4.14 g/kg and 3.42 g/kg, respectively. These NEAAs contribute to the nitrogen supply in silage and support various metabolic processes in animals. Table 1 Chemical composition of fresh oat material. Item Content Dry matter (g/kg FM) 346.24 pH 6.27 Water-soluble carbohydrates (g/kg DM) 132.15 Crude protein (g/kg DM) 103.4 Neutral detergent fiber (g/kg DM) 528.36 Acid detergent fiber (g/kg DM) 331.42 Amino acid contcnts (g/kg DM) Lysine(Lys) 2.74 Methionine(Met) 0.92 Tryptophan(Trp) 0.88 Threonine (Thr) 3.53 Valine (Val) 6.84 Leucine (Leu) 1.78 Isoleucine(Ile) 2.63 Phenylalanine(Phe) 1.95 Histidine(His) 0.65 Alanine(Ala) 3.42 Aspartic Acid(Asp) 3.07 Glutamic(Glu) 4.14 Glycine(Gly) 0.95 Proline(Pro) 4.02 Serine(Ser) 0.87 Tyrosine(Tyr) 1.25 Cysteine(Cys) 0.86 Arginine(Arg) 3.32 3.2 Changes of fermentation indexes during oat silage Temperature and silage duration significantly influenced the fermentation characteristics of oat silage ( P < 0.001) (Table 2 ). As the silage period progressed, pH values decreased across all temperature treatments. The most pronounced reduction occurred at 25°C, where the pH declined from 5.85 on 3 d to 4.08 on 90 d. At the same time, the LA content reached 51.12 g/kg DM on 90 d, significantly higher than under other temperature conditions. In contrast, the 5°C treatment exhibited marked fermentation inhibition, characterized by the slowest initiation of fermentation and minimal LA accumulation during the first 14 d (only 5.03 g/kg DM), with the final pH remaining relatively high at 4.85. Although fermentation efficiency at 10°C was superior to that at 5°C, signs of low-temperature suppression were still evident, as LA production only increased significantly after 60 d, and the final pH dropped to 4.43. The variation in LA content clearly demonstrated a temperature-gradient effect. AA content also increased over time; however, temperature-related differences were less distinct, ranging from 11.24 g/kg DM at 5°C to 18.13 g/kg DM at 25°C on 90 d. Interestingly, the 15°C treatment yielded the highest AA concentration (21.35 g/kg DM). PA was nearly undetectable during the early stages of silage (3 and 7 d) at 5°C, but began accumulating from 14 d, reaching 1.84 g/kg DM by 90 d. A similar trend to AA was observed, with the 15°C treatment producing the highest PA concentration (3.25 g/kg DM) at 90 d, followed by 10°C (2.98 g/kg DM), both significantly exceeding the level observed under the 25°C treatment. As a critical indicator of fermentation quality, the LA/AA varied significantly across temperatures. Under the 25°C treatment, the ratio increased steadily from 1.31 on 3 d to 2.83 on 90 d. In contrast, the 5°C treatment showed the smallest increase, rising from 1.04 to 2.15. Notably, at 15°C, the LA/AA ratio on 90 d (2.09) was even lower than that at 10°C (2.36). Table 2 Fermentation parameters during the silage of oat silage Item a Temperature Silage Days b SEM P -value d 3 7 14 60 90 D T D×T pH 5°C 6.26Aa 6.11Aa 5.82Ab 5.15Ac 4.85Ad 0.148 < 0.001 < 0.001 < 0.001 10°C 6.23Aa 6.05Ab 5.61Bc 4.66Bd 4.43Be 0.195 15°C 6.16Aa 5.82Bb 5.26Cc 4.41Cd 4.12Ce 0.211 25°C 5.85Ba 5.36Cb 4.65Dc 4.16Cd 4.08Cd 0.184 LA (g/kg DM) 5°C 1.23De 2.56Dd 5.03Dc 16.06Db 24.17Da 2.377 < 0.001 < 0.001 < 0.001 10°C 1.84Ce 4.54Cd 8.76Cc 21.29Cb 34.51Ca 3.251 15°C 2.78Be 7.22Bd 14.23Bc 33.56Bb 44.63Ba 4.284 25°C 4.12Ad 10.75Ac 22.06Ab 49.47Aa 51.12Aa 5.212 AA (g/kg DM) 5°C 1.18De 1.95Dd 3.21Dc 8.65Db 11.24Da 1.067 < 0.001 < 0.001 < 0.001 10°C 1.43Ce 2.39Cd 4.74Cc 10.76Cb 14.66Ca 1.366 15°C 2.18Be 5.62Bd 9.24Bc 13.21Bb 21.35Ba 1.773 25°C 3.15Ad 7.24Ac 11.32Ab 17.45Aa 18.13Aa 1.549 PA (g/kg DM) 5°C 0.00 0.00 0.37Cc 1.41Cb 1.84Da 0.204 < 0.001 < 0.001 < 0.001 10°C 0.00 0.35Cd 0.90Bc 2.32Bb 2.98Ba 0.308 15°C 0.16Be 0.85Bd 1.72Ac 2.56Ab 3.25Aa 0.299 25°C 0.28Ad 1.04Ac 1.74Ab 2.17Ba 2.26Ca 0.201 LA/AA (g/kg DM) 5°C 1.04Be 1.31Cd 1.58Bc 1.86Cb 2.15BCa 0.109 < 0.001 < 0.001 < 0.001 10°C 1.29Ac 1.90Ab 1.85Ab 1.98Cb 2.36Ba 0.095 15°C 1.28Ad 1.29Cd 1.54Bc 2.54Bb 2.09Ca 0.134 25°C 1.31Ac 1.49Bc 1.95Ab 2.84Aa 2.83Aa 0.175 a DM, dry matter; LA/AA, the ratio of lactic acid and acetic acid. b Different capital letters (A-D) indicate significant differences ( P < 0.05) among different silage groups. There is a significant difference ( P < 0.05) between the different lowercase letters (a-e) indicating the number of silage days. c SEM, standard error of the mean. d D, silage day; T, temperature; D×T, interaction between temperature and silage day. 3.3 Changes of nutritional indexes in the later stage of oat silage Temperature and silage duration significantly affected the nutritional composition of oat silage at 60 d and 90 (Table 3 ), with significant interactions (P < 0.05) observed for DM, WSC, CP, and NH₃-N. As the silage period was extended from 60 d to 90 d, DM content showed a decreasing trend under all temperature treatments, with more pronounced losses observed under low temperatures. In particular, the DM content at 5°C decreased by 25.35 g/kg DM, while the decrease at 25°C was only 11.50 g/kg DM. Under low-temperature conditions, carbohydrate consumption proceeded more slowly but persisted for a longer duration. The WSC content declined by only 2.99 g/kg DM at 25°C, whereas it decreased by 23.18 g/kg DM at 5°C. CP content exhibited a consistent pattern across both 60 d and 90 d, with higher temperatures resulting in higher CP concentrations. Notably, CP content remained relatively stable at 25°C (declining by only 2.78 g/kg DM), while a more substantial decrease of 8.07 g/kg DM was observed at 5°C, indicating more severe protein degradation under low-temperature conditions. NDF and ADF contents decreased significantly with increasing temperature, reflecting enhanced cellulose degradation under warmer conditions. After 90 d of silage, the NDF contents in the 25°C and 15°C treatments were significantly lower than that in the 5°C treatment. NH₃-N levels increased significantly over time across all temperatures; however, low-temperature treatments exhibited more pronounced protein degradation. Specifically, NH₃-N content at 5°C increased from 93.56 to 113.25 g/kg TN, a rise of 19.69 g/kg TN, which was substantially greater than the 6.28 g/kg TN increase observed at 25°C. Table 3 Nutritional indicators of oat silage Item a Silage Days Temperature SEM P -value 5°C 10°C 15°C 25°C D T D×T DM (g/kg DM) 60 313.62a 308.24ab 303.56b 307.82b 1.126 < 0.001 0.001 < 0.001 90 288.27c 284.16d 291.55b 296.32a 1.387 WSC (g/kg DM) 60 70.25a 64.17b 58.62c 56.34c 1.508 < 0.001 < 0.001 < 0.001 90 47.07b 42.66c 46.56b 53.35a 1.243 CP (g/kg DM) 60 62.24d 68.80c 75.52b 81.05a 1.916 < 0.001 < 0.001 0.002 90 54.17d 61.52c 67.24b 78.27a 2.676 NDF (g/kg DM) 60 508.98a 491.21b 479.72c 456.60d 5.301 < 0.001 < 0.001 0.195 90 496.15a 477.54b 457.29c 452.33c 5.564 ADF (g/kg DM) 60 312.84a 290.06b 273.25c 265.68c 4.995 0.001 < 0.001 0.285 90 301.36a 282.25b 265.47c 264.33c 4.644 NH 3 -N (g/kg TN) 60 93.56a 85.62b 76.21c 64.54d 3.000 < 0.001 < 0.001 0.003 90 113.25a 96.35b 88.36c 70.82d 4.628 a FM, fresh matter; WSC, water-soluble carbohydrate; CP, crude protein; NDF, neutral detergent fibre; ADF, acid detergent fibre; NH 3 -N, ammonia nitrogen. 3.4 Succession of bacterial community during low-temperature silage To evaluate the effects of different silage conditions on the bacterial community diversity in oat silage, both α-diversity (Shannon index) and β-diversity (principal coordinate analysis, PCoA) were assessed across treatment groups. Figure 1 A illustrates the variation in the Shannon index of oat silage bacterial communities under different temperature and silage duration treatments. Both silage temperature and duration significantly influenced the Shannon index. Overall, an increase in silage temperature was associated with a marked decline in bacterial diversity. After 60 d of silage, the 5°C group exhibited the highest Shannon index, which was significantly greater than that of all other treatments (P < 0.05). In contrast, the 25°C group showed the lowest diversity. The PCoA results (Fig. 1 B) visually revealed distinct differences in bacterial community structures (β-diversity) among the treatment groups. The first principal coordinate (PCoA1), which accounted for 44.7% of the total variation, was the primary factor driving sample separation. Notably, it effectively differentiated the low-temperature groups (5°C and 10°C, predominantly distributed on the negative axis of PCoA1) from the high-temperature group (25°C, mainly located on the positive axis), while the 15°C group occupied an intermediate position. These findings indicate that temperature is the dominant driver shaping the bacterial community structure in oat silage. At the phylum level (Fig. 1 C), the microbial community of fresh oat material (FM) exhibited considerable diversity, with Proteobacteria being the most dominant phylum (55.8%), followed by Firmicutes (31.5%). After silage fermentation, Firmicutes sharply increased in relative abundance and became the overwhelmingly dominant phylum in all silage samples, while Proteobacteria declined significantly across all treatments. At the genus level (Fig. 1 D), the dominant genera in fresh oat included Hafnia , Enterobacter , Pseudomonas , and Pantoea , all affiliated with Proteobacteria , whereas lactic acid bacteria (LAB) were initially present at low abundance. Extending the silage duration from 60 to 90 d at the same temperature generally enhanced the abundance of dominant LAB genera and further suppressed non-LAB populations. Under ambient conditions (25°C), the fermentation process was fully dominated by Lactiplantibacillus , whose relative abundance exceeded 70% after 60 d and further increased by 90 d. Meanwhile, all other genera—particularly those affiliated with Proteobacteria —were reduced to negligible levels. In contrast, under low-temperature conditions (5°C), potentially undesirable genera such as Hafnia and Enterobacter remained relatively abundant even after 60 d of fermentation. As temperature increased to 10°C and 15°C, Lactiplantibacillus exhibited a significant rise in relative abundance, gradually replacing Hafnia and Enterobacter as the dominant genus. At 15°C after 90 d, Lactiplantibacillus had become the prevailing genus in the bacterial community. 3.5 Changes of FAAs content at late stage of low temperature silage To investigate the effect of low temperature on protein degradation, we conducted quantitative analysis of 18 FAAs across temperature treatment groups during the late fermentation stage (60/90 d) (Fig. 2 ). The results showed that both silage temperature and duration significantly altered the concentrations of FAAs. Compared to fresh forage, most FAAs were significantly reduced in temperature-controlled silage (25°C), while low-temperature treatments (5°C/10°C) significantly increased FAAs. Lys content in 90 d 5°C silage was 1.65 times higher than in fresh forage. The contents of most essential amino acids (EAAs) and several non-essential amino acids (NEAAs) decreased significantly with increasing temperature. Lys, His, and Arg exhibited their highest concentrations at 5°C, followed by a significant, stepwise reduction as temperature rose to 25°C (P < 0.05). For instance, after 90 d of silage, the Lys content declined from approximately 4.53 g/kg DM at 5°C to about 1.75 g/kg DM at 25°C. Similarly, Trp, Val, Leu, Phe, Pro, and Met displayed comparable negative correlations with temperature, where lower temperatures significantly increased their concentrations. Conversely, the concentrations of several other amino acids increased significantly with rising temperature. Ala accumulation was particularly pronounced, increasing from approximately 2.37 g/kg DM at 5°C to about 4.32 g/kg DM at 25°C after 90 d of silage. Glu, Asp, Gly, Ser, and Tyr followed the same pattern, reaching their highest concentrations in the 25°C treatment group, which were significantly greater than those in the low-temperature groups (P < 0.05). A few amino acids exhibited distinct patterns. For example, Ile and Thr showed relatively small variations across temperatures and did not exhibit consistent monotonic increasing or decreasing trends like the other amino acids. Regarding silage duration, extending the period from 60 to 90 d at 25°C resulted in non-significant changes in most free amino acid contents. In contrast, under low-temperature silage conditions, prolonging the duration from 60 to 90 d further amplified the temperature-induced trends. 3.6 Correlation between bacterial community and FAAs content To elucidate complex relationships between dominant bacterial genera and FAAs during low-temperature oat silage fermentation, mantel tests revealed significant correlations between bacterial community composition and FAA profiles across all samples. The upper-right quadrant of Fig. 3 presents a Spearman correlation matrix demonstrating inter-FAA associations. Ala, Asp, Glu, Ser, and Tyr exhibited significant mutual positive correlations, with the strongest relationships occurring between Asp-Glu and Ala-Glu. Another group of FAAs—including Lys, His, Arg, and Pro—showed significant negative correlations with Ala, Asp, and Glu. For example, Lys displayed strong negative correlations with Ala, Asp, and Glu, suggesting potential antagonistic metabolic or microbial interactions. Figure 3 also illustrates the correlations between key bacterial genera and the concentrations of individual FAAs. As a dominant genus, Lactiplantibacillus exhibited broad correlations with various amino acids. Notably, it showed strong negative correlations with branched-chain amino acids (BCAAs) such as Leu, Val, and Ile, while displaying positive correlations with acidic amino acids such as Asp and Glu. Enterobacter ial genera including Enterobacter and Pantoea were positively correlated with the majority of FAAs, particularly with small-molecule amino acids such as Ala, Gly, and Ser. Lactic acid bacteria such as Pediococcus and Levilactobacillus exhibited moderate negative correlations with aromatic amino acids including Phe and Tyr. Notably, Pseudomonas showed positive correlations with most amino acids, with the strongest association observed with Arg. In addition, Weissella was strongly associated with sulfur-containing amino acids, namely Met and Cys. 4. Discussions 4.1 Effects of low temperature silage on fermentation characteristics and nutritional indexes of silage The results demonstrated that fermentation temperature is a decisive factor influencing silage quality in oat. The 5°C treatment exhibited delayed fermentation initiation, characterized by low lactic acid accumulation and a significantly higher pH at 90 d than other temperatures—consistent with Liu et al. ( 2024 ), who reported suppressed LAB activity below 10°C. A slow pH decline reduces fermentation efficiency and may promote the growth of harmful microorganisms, increasing the risk of silage spoilage. The lactic acid-to-acetic acid ratio (LA/AA), a key indicator of fermentation type, showed an overall increasing trend across treatments over time, indicating progressive dominance of homolactic fermentation. This aligns with Zhang et al. (2017), where Lactobacillus and other homofermentative LAB became dominant during later stages. Notably, the 90 d LA/AA ratio at 15°C was lower than at 60 d, potentially linked to temperature-dependent microbial community structures. Zhu et al. ( 2021 ) found that under moderate temperature conditions, the co-existence of homofermentative and heterofermentative lactic acid bacteria in relative balance is beneficial for maintaining an appropriate LA/AA ratio, which may explain the observed differences in the 15°C treatment group at specific stages. Regarding PA content, after 90 days of fermentation at low temperatures (10 and 15°C), the PA concentration was higher than that observed under ambient conditions. This finding is consistent with the observations of Li et al. (2021), who reported that under low pH and well-maintained anaerobic conditions, the activity of PA producing bacteria is suppressed. The lower PA content observed at 5°C may be attributed to a pronounced inhibition of the metabolic pathways of PA bacteria due to excessively low temperatures. This study found that the DM content decreased significantly with the extension of the fermentation period, consistent with the findings of Borreani et al. ( 2018 ), who reported that microbial metabolic activity during fermentation leads to organic matter loss and a reduction in DM content. Notably, the DM content in the low-temperature treatment group at 90 days of fermentation was significantly lower than that in the 25°C treatment group. This observation is in agreement with Guo et al. (2014), who suggested that fermentation under suitable ambient temperatures may reduce long-term DM losses by accelerating the attainment of a stable phase. Temperature variations can directly affect microbial metabolic rates, thereby influencing the degradation rate of organic matter and ultimately resulting in differences in DM loss under varying temperature conditions. WSC serve as the primary substrates for silage fermentation, and their content reflects the intensity of the fermentation process. In this study, the WSC content was highest in the 5°C treatment group and gradually decreased with increasing temperature. This result is consistent with the findings of Shah et al. ( 2020 ), who reported that lower temperatures reduce microbial metabolic activity, thereby decreasing WSC consumption. Consequently, under low-temperature conditions, the relatively high WSC content in silage may be attributed to insufficient microbial activity to rapidly utilize these substrates. CP content increased significantly with temperature, consistent with Cheng et al. ( 2022 ) who attributed this to relative enrichment of non-protein nitrogen compounds under ambient conditions. Concurrently, all treatments exhibited declining CP from 60 to 90 d, supporting Zhu et al. (2022) that prolonged fermentation enhances proteolysis and NH 3 -N volatilization. This change may be related to the microbial metabolic processes of proteins, particularly the activity of proteolytic enzymes and the dynamic variations of nitrogen sources during fermentation. 4.2 Effect of low temperature on silage microbial community Temperature plays a pivotal role in shaping the microbial diversity and community structure of oat silage, as evidenced by a significant reduction in the Shannon index with rising temperatures. This trend is consistent with findings from Yang et al. ( 2019 ), who observed a decrease in microbial diversity under ambient temperatures compared to lower temperatures. Guan et al. ( 2018 ) suggested that this loss of diversity is primarily driven by the rapid proliferation of Lactobacillus species and the accumulation of organic acids under warmer conditions, which creates an environment that suppresses the growth of competing microorganisms. The dominance of Lactobacillus strains in such conditions further exacerbates the narrowing of microbial diversity, as these organisms, being acid-tolerant, outcompete other taxa. PcoA revealed distinct clustering of microbial communities across different temperature treatments, reinforcing the idea that temperature is a key ecological factor in microbial community assembly—this is in agreement with the work of Zhu et al. (2025). Notably, the maximal separation observed between the 5°C and 25°C treatment groups in the PCoA plot suggests that temperature-induced shifts in community composition are profound and not merely quantitative. This compositional divergence may reflect complex changes in microbial physiological adaptations and competitive strategies, as temperature affects not only growth rates but also microbial enzymatic activity, nutrient utilization, and tolerance mechanisms Li et al. (2021). At lower temperatures, psychrotolerant and facultative microorganisms likely maintain a more diverse community due to slower metabolic rates, whereas higher temperatures select for more aggressive acid-producing organisms like Lactobacillus , which may lead to a more homogenous, less diverse microbiota. At the phylum level, Firmicutes dominated under ambient temperature, whereas Proteobacteria were markedly enriched at low temperatures, consistent with Ni et al. ( 2017 ) and likely driven by the ability of certain Proteobacteria to express cold-adaptation proteins that maintain membrane fluidity and enzyme activity in low-temperature environments (Xin et al., 2023 ). This thermal niche partitioning reshapes the functional potential of the silage microbiome: while Firmicutes , particularly LAB, accelerate carbohydrate fermentation and acidification, Proteobacteria often exhibit slower acid production but broader catabolic capabilities. At the genus level, Lactiplantibacillus dominated at 25°C, aligning with its homofermentative metabolism that rapidly channels sugars into lactic acid, explaining both the sharp pH decline and elevated LA/AA ratio (Guo et al., 2023 ). The dominance of LAB at this temperature has additional implications—these bacteria have limited proteolytic capacity, targeting mainly small peptides rather than intact proteins (Mu et al., 2022 ). Coupled with the inhibitory effect of the rapid pH drop (4.08) on plant endogenous proteases, this may account for the lower NH₃-N content observed, suggesting that warm fermentation environments could help preserve true protein. Conversely, at 5°C, the microbiota shifted toward Pseudomonas and Leuconostoc . Pseudomonas species, despite thriving under low temperatures, are frequently associated with reduced silage quality due to strong protease activity (Weber et al., 2023 ). Notably, cold-adapted proteases from certain Pseudomonas strains can remain highly active—or even more active—under low temperatures (Yang et al., 2010 ), facilitating extensive protein degradation into amino acids and ammonia, as reflected by the elevated NH₃-N levels. Leuconostoc , a heterofermentative LAB, contributes to acidification but at a slower rate and with lower lactic acid yields, further delaying pH stabilization. Taken together, these patterns suggest that temperature not only dictates which taxa dominate, but also indirectly governs silage nitrogen preservation through both microbial proteolytic capacity and pH-mediated suppression of plant proteases. From a practical perspective, maintaining silage temperatures closer to ambient during early fermentation could enhance protein conservation, whereas prolonged low-temperature conditions risk increased proteolysis and quality loss—especially if cold-tolerant proteolytic Proteobacteria proliferate. Future research should assess whether targeted inoculants or temperature-modulated ensiling can mitigate these risks in cold storage environments. 4.3 Effect of low temperature on FAAs From a nutritional quality perspective, the accumulation of essential amino acids (e.g., Lys, Val, Leu, and Phe) in silage represents a potentially beneficial outcome, as these compounds can enhance the protein value and digestibility of the feed. However, this advantage must be weighed against the biochemical and safety risks associated with prolonged proteolysis, particularly under low-temperature conditions. At reduced temperatures, microbial proteolytic activity remains sustained over extended storage periods, leading to the continuous release of free amino acids. While some degree of amino acid accumulation is desirable, excessive levels can trigger detrimental secondary reactions. One major concern is the Maillard reaction, wherein excess amino acids interact with residual reducing sugars to form advanced glycation end products (AGEs). These AGEs are poorly digestible and can alter the physicochemical properties of silage, manifesting as browning and reduced palatability (Yuan et al., 2012 ). Beyond aesthetic and palatability issues, AGEs have been implicated in oxidative stress and inflammatory responses in animals, potentially reducing the nutritional and health value of the feed. Another risk is the microbial decarboxylation of amino acids into biogenic amines, such as putrescine, cadaverine, and tyramine, via specific microbial decarboxylases (Sun et al., 2023 ). These amines are biologically active compounds that, at high concentrations, can cause toxicity, disrupt rumen function, or interfere with nutrient absorption. Low-temperature conditions may favor the persistence and activity of psychrotrophic or cold-tolerant microbes capable of producing such amines, further amplifying food safety concerns. The temporal dynamics of amino acid changes highlight the interaction between microbial ecology and metabolic pathways. At 25°C, extending fermentation from 60 to 90 d had minimal influence on amino acid concentrations, likely due to the rapid dominance of lactic acid bacteria at early stages. These LAB complete most of the soluble protein breakdown and amino acid metabolism within the initial fermentation window, after which microbial activity and substrate availability stabilize (Bernardes et al., 2018 ). In contrast, at 5°C and 10°C, a 90 d storage period markedly increased the accumulation of most amino acids, suggesting that low-temperature proteolysis is a slow but persistent process. This pattern aligns with the hypothesis that when carbohydrate availability is restricted, microbial communities shift toward proteolysis as an alternative energy acquisition strategy, resulting in cumulative amino acid buildup. Interestingly, certain amino acids, such as Ile and Thr, exhibited relatively minor changes across temperature treatments and lacked a monotonic trend. This variability likely reflects their dual role in fermentation: they both accumulate as end products of proteolysis and are continuously consumed as microbial growth substrates. Moreover, in late fermentation stages, decarboxylase activity may channel these amino acids toward biogenic amine production, thereby obscuring their apparent concentration patterns (Bai et al., 2022 ; Kung et al., 2018 ). These findings underscore a critical limitation of using amino acid content alone as a proxy for protein degradation, as this approach fails to account for downstream metabolic transformations. To more accurately assess proteolysis and protein quality loss, future studies should integrate amino acid profiling with quantification of secondary metabolites, particularly biogenic amines, as well as characterization of the microbial taxa and enzymes responsible for these conversions. Such an integrated approach would provide a more comprehensive understanding of how temperature-dependent microbial activity shapes both the nutritional value and safety profile of silage, and could inform targeted interventions—such as microbial inoculant selection, storage temperature management, or post-fermentation treatment—to optimize feed quality and minimize risks. 4.4 Correlation between FAAs and microbial community The Mantel test and Spearman correlation analysis revealed a robust association between the bacterial community structure and the profiles of FAAs during the low-temperature fermentation of oat silage. These findings significantly enhance our understanding of the mechanisms governing protein degradation and FAA accumulation under cold conditions (Muck et al., 2018 ). Specifically, Lactiplantibacillus displayed a significant negative correlation with branched-chain amino acids (BCAAs), such as Leu and Val, suggesting that it may suppress the accumulation of these amino acids under low-temperature conditions. This could be attributed to the genus' abundance of amino acid transporters and deaminase genes, which enable rapid FAA uptake for growth, thus limiting BCAA accumulation (Zhu et al., 2022). Lactiplantibacillus is typically dominant in lactic acid fermentation at moderate temperatures, but its role in low-temperature silage could be more complex, where it may preferentially metabolize certain amino acids early in fermentation, leading to the reduced availability of BCAAs. In contrast, Enterobacter exhibited a positive correlation with most amino acids, particularly smaller ones such as Ala, Gly, and Ser under cold conditions (He et al., 2019 ). This finding is consistent with previous studies, which have highlighted that Enterobacteriaceae possess strong proteolytic and decarboxylase activities, enabling them to thrive when LAB are suppressed (Zhou et al., 2016 ). At lower temperatures, the metabolic activity of LAB may be reduced, providing a favorable environment for psychrotolerant Enterobacter species with active protease systems. These bacteria can efficiently break down proteins into amino acids, promoting their accumulation in silage, which is reflected in the significant accumulation trends observed in the low-temperature treatment groups. Furthermore, Pediococcus and Levilactobacillus were negatively correlated with aromatic amino acids such as Phe and Tyr, suggesting a potential role for these genera in the degradation of these compounds. Since aromatic amino acids are essential for feed protein quality, their excessive breakdown could significantly reduce the nutritional value of silage (You et al., 2022 ). Previous research has shown that Pediococcus species secrete aromatic amino acid transaminases that degrade Phe and Tyr, further supporting our findings (Scherer et al., 2015 ). While the breakdown of these amino acids may help balance microbial metabolism during fermentation, their over-degradation could be detrimental to silage nutritional quality. Therefore, careful monitoring of these genera is necessary to mitigate nutrient loss during cold-temperature silage fermentation. Pseudomonas species, known for their robust proteolytic activity, may also play a role in elevating silage pH through arginine deamination, disrupting the anaerobic conditions essential for proper fermentation and thereby increasing the risk of spoilage. Controlling the growth of Pseudomonas is critical for improving the quality of silage under low-temperature conditions, as their metabolic activity can lead to undesirable changes in pH and the production of toxic metabolites, further complicating the silage fermentation process. Weissella , on the other hand, exhibited strong correlations with sulfur-containing amino acids such as Met and Cys, indicating a potential involvement in sulfur metabolism. Some strains of Weissella can produce volatile compounds, such as hydrogen sulfide, through cysteine desulfhydration (Ávila and Carvalho, 2020 ), which could negatively affect silage flavor and, in some cases, contribute to the production of off-flavors. The role of Weissella in sulfur metabolism suggests that its presence may influence the sensory properties of silage, further highlighting the need to carefully consider microbial strain selection in silage management. Overall, these findings underline the complex interplay between microbial community composition and amino acid profiles during low-temperature fermentation of oat silage. Low temperatures not only affect the metabolic activities of LAB but also foster the growth of psychrotolerant microbes, which play pivotal roles in the breakdown and accumulation of amino acids. Future studies should explore how microbial community structure can be modulated to improve silage quality, particularly by controlling the growth of spoilage-associated species such as Pseudomonas , and optimizing the roles of beneficial microbes like Pediococcus and Lactiplantibacillus . 5. Conclusion Temperature significantly influenced the fermentation trajectory, microbial structure, and free amino acid (FAA) metabolism of oat silage. At 5°C, inhibited LAB activity led to reduced lactic acid production, elevated pH, and increased ammonia-N levels—hallmarks of fermentation inefficiency. Microbial analysis revealed a clear shift: Lactiplantibacillus predominated at 25°C, whereas psychrotrophic, proteolytic taxa such as Pseudomonas and Enterobacter dominated at low temperature. These genera showed strong positive associations with essential FAAs (e.g., Lys, His, Arg), indicating that low-temperature silage is prone to proteolysis-driven nitrogen loss. These findings confirm that temperature acts as a primary regulator of microbial functionality and protein retention during ensiling. Therefore, cold-region forage systems require precision microbial interventions. Cold-adapted LAB with enhanced acidogenic and FAA-assimilating traits, combined with protease-inhibiting additives, offer promising strategies to improve silage quality under thermal stress. Authors’ contributions X.L: Conceptualization, methodology, software, formal analysis, data curation, writing—original draft preparation, writing—review and editing. J.B: validation. X.Q: resources. J.C: supervision, project administration. D.L: writing—review and editing. G.Z: Conceptualization, writing—review and editing, supervision, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript. Declarations Clinical trial number Not applicable. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding Project supported by the National Natural Science Foundation of China (Grant No. 32160810). Author Contribution X.L: Conceptualization, methodology, software, formal analysis, data curation, writing—original draft preparation, writing—review and editing. J.B: validation. X.Q: resources. J.C: supervision, project administration. D.L: writing—review and editing. G.Z: Conceptualization, writing—review and editing, supervision, project administration, funding acquisition. 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07:21:11","extension":"html","order_by":55,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":177543,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7475710/v1/653ff18a56c9487e478072ad.html"},{"id":91820704,"identity":"234e9d83-6336-44ba-be8e-63866b41e06c","added_by":"auto","created_at":"2025-09-22 07:21:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":349789,"visible":true,"origin":"","legend":"\u003cp\u003eStructure of bacterial community in oat silage during silage. (A) Alpha diversity (Shannon index) of bacterial community. (B) Beta diversity (PCoA). (C) Bacterial phylum level community structure. (D) Bacterial water community structure\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7475710/v1/c56715ae2e0aed7b8cfc0335.png"},{"id":91820716,"identity":"4ee7f249-5fa2-42c0-82c4-f21d1d74efe0","added_by":"auto","created_at":"2025-09-22 07:21:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":157359,"visible":true,"origin":"","legend":"\u003cp\u003eChanges of FAAs content in late silage\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7475710/v1/57ca97aba0d89dfd54b77868.png"},{"id":91821850,"identity":"f512ba38-fb24-400e-b9eb-a6672fcdbcec","added_by":"auto","created_at":"2025-09-22 07:37:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":179831,"visible":true,"origin":"","legend":"\u003cp\u003eMantel tests analysis ( correlation between microorganisms and free amino acids )\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7475710/v1/c44979e6a6f7a69f0acd49d8.png"},{"id":98243915,"identity":"6305f025-638a-4898-9077-b083dc09a511","added_by":"auto","created_at":"2025-12-15 16:11:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1706246,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7475710/v1/d25e5efd-265b-4b06-9e1b-fcc9de5fbc80.pdf"},{"id":91821608,"identity":"89802d8b-4471-49ac-9ad6-94f3684c1e69","added_by":"auto","created_at":"2025-09-22 07:29:07","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":101675,"visible":true,"origin":"","legend":"","description":"","filename":"GRAPHICALABSTRACT.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7475710/v1/666761b78a69ba73246eafaa.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of low temperature silage on microbial community and free amino acids of oat silage quality","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOat, a high-yield and high-quality dual-purpose crop for grain and forage, has been widely promoted in cold regions in recent years due to its unique biological characteristics and strong environmental adaptability. In particular, it has become one of the primary forage sources on the Qinghai\u0026ndash;Tibet Plateau and its surrounding areas in China(Bao et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). However, the oat harvesting season in this region often coincides with prolonged periods of rainy and overcast weather, making traditional sun-drying difficult and increasing the risk of mold development and nutrient loss. Silage offers an effective solution to mitigate the negative effects of inclement weather and helps preserve forage quality and nutritional value. Nevertheless, the entire silage process on the Qinghai\u0026ndash;Tibet Plateau is subjected to low ambient temperatures, which adversely affect fermentation(Gong et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Studies have shown that low-temperature silage fermentation typically results in reduced lactic acid production and elevated pH levels, making silage more susceptible to spoilage and detrimental to livestock health (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). When ambient temperatures fall below 15\u0026deg;C, the efficiency of conventional fermentation drops significantly, leading to increased dry matter losses (8\u0026ndash;15%) and accelerated nutrient degradation (Nokhsorov et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These factors severely limit the application value of oat silage in livestock production in alpine regions.\u003c/p\u003e\u003cp\u003eMicroorganisms play pivotal roles in silage fermentation, serving as the primary drivers of the process. Lactic acid bacteria (LAB) represent the most critical microbial group in silage, fermenting water-soluble carbohydrates to generate organic acids and establishing an acidic environment that inhibits the growth of spoilage microorganisms (Wang et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Research into silage microbial communities has progressively deepened in recent years, revealing the importance of microbial composition and interactions for fermentation quality. Concurrently with enhanced understanding of microbial fermentation mechanisms, researchers are increasingly exploring microbial dynamics under extreme conditions (Xia et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The impact of low temperatures on silage fermentation manifests primarily through microbial community shifts. Temperature decreases significantly inhibit microbial activity, particularly compromising LAB growth and metabolism. This suppression reduces lactic acid production, resulting in elevated pH and inferior fermentation quality (Zhang et al., 2017). During low-temperature silage fermentation, the metabolic processes of lactic acid bacteria differ fundamentally from those in conventional silage produced at room temperature. (Xu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Consequently, low-temperature silage often exhibits inadequate acidification, high pH, and increased vulnerability to spoilage microorganisms, thereby compromising storage stability and nutritional value(Li et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFree amino acids (FAAs), released from the breakdown of proteins or peptides, serve as direct indicators of proteolytic degradation. During silage fermentation, proteolysis occurs through microbial and plant enzymatic activity, altering FAA concentrations and directly influencing nitrogen utilization efficiency in the fermented feed. Advanced techniques such as high-performance liquid chromatography (HPLC) enable precise quantification of amino acids, while investigations into fermentation conditions and microbial community dynamics are advancing this research field (Gauthankar et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Studies demonstrate that post-silage FAA profiles vary significantly depending on fermentation conditions, microbial composition, and duration. Zhang et al. (2017) reported that the concentrations of essential amino acids typically decrease after the silage of oat, whereas non-essential amino acids may increase, with specific patterns closely related to the fermentation environment. Guo et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) further established that concentration changes of all 20 amino acids correlate strongly with microbial community succession. Specifically, proliferation of \u003cem\u003eLactobacillus buchneri\u003c/em\u003e showed a positive association with histidine and lysine degradation.\u003c/p\u003e\u003cp\u003eDespite growing attention to microbial succession and fermentation quality under low-temperature silage conditions, few studies have simultaneously explored the temporal dynamics of microbial community shifts and free amino acid accumulation across different cold-temperature regimes. In particular, the relationships between dominant psychrotolerant bacteria and proteolysis remain poorly understood. Moreover, current research lacks integrated approaches that correlate microbial ecology with nitrogen degradation indicators, such as ammonia-N and FAA composition, under prolonged fermentation. These gaps limit our mechanistic understanding of silage deterioration risks and quality fluctuations in cold-climate forage systems. Therefore, elucidating FAA dynamics in low-temperature silage and their interrelationship with microbial activity holds significant theoretical and practical value for optimizing fermentation techniques and enhancing the quality of oat silage produced under cold conditions.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.1 Preparation of\u003c/b\u003e oat \u003cb\u003esilage\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eOat (cultivar \"Longyan No. 3\") seeds were provided by the College of Grassland Science, Gansu Agricultural University (Lanzhou, China). \"Longyan No. 3\" is a forage oat cultivar originally derived from a local landrace in Gansu Province and officially approved by the National Grass Variety Approval Committee of China in 2010. The plants were cultivated in Dachai Gou Township, Tianzhu Tibetan Autonomous County, Gansu Province, China (E102\u0026deg;15\u0026prime;, N36\u0026deg;45\u0026prime;; altitude 2594 m). The crop was harvested at the milk stage on August 28, 2023, and wilted in a shaded and well-ventilated area until it reached an appropriate dry matter content for silage (346.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85 g/kg fresh matter). The wilted material was then chopped into 3\u0026ndash;4 cm lengths using a forage kneading machine. The experiment comprised four temperature treatments: three low-temperature groups (5\u0026deg;C, 10\u0026deg;C, and 15\u0026deg;C) and one control group (25\u0026deg;C). For each treatment, 500 g of chopped oat material was packed into polyethylene plastic bags (250 \u0026times; 350 mm), vacuum-sealed using a vacuum packaging machine, and transported to the laboratory. The sealed bags were then stored in temperature-controlled incubators preset to the respective treatment temperatures. Samples were collected after 3, 7, 14, 60, and 90 d of silage, with three replicates per time point.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Determination of fermentation parameters and nutritional composition\u003c/h2\u003e\u003cp\u003eFor pH and chemical analyses, 20 g of fresh sample was homogenized with 180 mL of sterile distilled water for 30 s using a blender. The homogenate was sequentially filtered through four layers of cheesecloth and subsequently through filter paper. The resulting filtrate was immediately analyzed for pH using a calibrated pH meter (PHS-3C, Shanghai Yoke Instrument Co., Ltd., China). The filtrate was then divided into two aliquots: one for organic acid analysis (lactic acid, acetic acid, propionic acid, butyric acid) and another for ammonia nitrogen (NH₃-N) determination. Both aliquots were stored at -20\u0026deg;C until analysis. For organic acid quantification, one aliquot was acidified to approximately pH 2.0 with 7.14 mol/L H₂SO₄, filtered through a 0.22-\u0026micro;m aqueous phase syringe filter, and injected into a high-performance liquid chromatography (HPLC) system (Agilent 1260 series; column: Shodex Rspak KC-811 S-DVB gel column, 300 mm \u0026times; 8.0 mm; mobile phase: 3 mmol/L HClO₄; column temperature: 50\u0026deg;C; detector: DAD; injection volume: 5 \u0026micro;L; flow rate: 1.0 mL/min; detection wavelength: 210 nm). For NH₃-N analysis, 40 mL of the non-acidified filtrate was mixed with 10 mL of 25% (w/v) trichloroacetic acid (TCA) solution (4:1, v/v) and incubated overnight at 4\u0026deg;C to precipitate true proteins. Following high-speed centrifugation (10,000 r/min, 4\u0026deg;C, 15 min), the supernatant was collected, and NH₃-N concentration was determined using the phenol-hypochlorite method(Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor dry matter (DM) determination, 200 g of fresh sample was placed in kraft paper bags and dried in an oven at 65\u0026deg;C for approximately 72 h. The dried samples were ground using a mill and sieved through a 40-mesh screen (0.425 mm pore size) for subsequent analysis of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and water-soluble carbohydrates (WSC). Total nitrogen (TN) content was determined using an automatic Kjeldahl nitrogen analyzer (K9840, Hannon Instruments Co., Ltd., Jinan, China). Crude protein (CP) content was calculated by multiplying TN content by 6.25. NDF and ADF contents were assessed according to the methods described by Van Soest et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). For WSC analysis, 100 mg of dried sample powder was weighed into a test tube, mixed with 15 mL of distilled water, and digested in boiling water for complete dissolution. After cooling to room temperature, the solution was filtered, and the filtrate was mixed with anthrone reagent and boiled again. The cooled mixture was then measured for optical density at 620 nm using a spectrophotometer. WSC content was calculated based on a pre-established standard curve(Li et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Bacterial community analysis\u003c/h2\u003e\u003cp\u003eFor genomic DNA extraction from silage samples, 0.5 g of each sample was weighed and placed into 1.5 mL extraction tubes. The extracted genomic DNA was assessed for concentration and purity using UV spectrophotometry, while DNA integrity was evaluated by 1% agarose gel electrophoresis. Upon confirmation that the extracted genomic DNA met the required quality and quantity standards, PCR amplification of the full-length bacterial 16S rRNA gene was conducted using forward primer 27F (5'-AGRGTTYGATYMTGGCTCAG-3') and reverse primer 1492R (5'-RGYTACCTTGTTACGACTT-3'). Single-molecule real-time sequencing was employed, incorporating sample-specific 16-bp barcodes into the primers to enable multiplex sequencing. The thermal cycling protocol consisted of initial denaturation at 95\u0026deg;C for 30 s, followed by annealing at 57\u0026deg;C for 30 s, extension at 72\u0026deg;C for 60 s, and final extension at 72\u0026deg;C for 5 min. PCR amplicons were purified using Agencourt AMPure Beads (Beckman Coulter, Indianapolis, IN) and quantified using the PicoGreen dsDNA AssayKit (Invitrogen, Carlsbad, CA, USA). Following Qubit quantification, the purified PCR products were pooled in equimolar ratios according to the sequencing requirements for each sample. Library construction and quality control were performed using the SMRTbell Template Prep Kit 1.0-SPv3, and sequencing was conducted on the PacBio platform using the DNA/Polymerase Binding Kit 3.0 (PacBio). Post-sequencing, CCS (Circular Consensus Sequencing) reads were subjected to filtering, clustering, and denoising procedures, followed by taxonomic annotation and abundance profiling. Subsequent analyses included Alpha diversity, Beta diversity, correlation analysis, and functional prediction(C. Bai et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Determination of FAAs Content\u003c/h2\u003e\u003cp\u003eThe oat silage samples were flash-frozen in liquid nitrogen and homogenized to a fine powder using a mortar and pestle under continuous liquid nitrogen cooling. The powdered samples were stored at -80\u0026deg;C until further analysis. For amino acid extraction, 100 mg of frozen silage powder was weighed into a 2 mL Eppendorf microcentrifuge tube and mixed with 1 mL of 0.5 M aqueous hydrochloric acid solution. The mixture was vortexed at 8000 rpm for 20 min, sonicated in a 25\u0026deg;C water bath for 20 min, and then centrifuged at 20,000 \u0026times; g for 20 min. Finally, 250 \u0026micro;L of the supernatant was filtered through a 0.22 \u0026micro;m aqueous phase filter into an HPLC vial and diluted to 1 mL with 80% (v/v) acetonitrile aqueous solution. Authentic standards of 18 amino acids (purity\u0026thinsp;\u0026gt;\u0026thinsp;99%) were purchased from Merck and Sigma-Aldrich (St. Louis, MO, USA).\u003c/p\u003e\u003cp\u003eHigh-performance liquid chromatography (HPLC) analysis was performed using an Agilent InfinityLab Poroshell 120 HILIC-Z column (2.1 \u0026times; 100 mm, 2.7 \u0026micro;m). The mobile phase consisted of solvent A (20 mM ammonium formate aqueous solution, pH\u0026thinsp;=\u0026thinsp;3) and solvent B (20 mM ammonium formate dissolved in acetonitrile/water, 9:1 v/v, pH\u0026thinsp;=\u0026thinsp;3). The flow rate was set at 0.5 mL/min, with an injection volume of 1 \u0026micro;L. The column temperature was maintained at 25\u0026deg;C. Mass spectrometry (MS) was conducted under electrospray ionization (ESI) in positive ion mode. The gas flow rate was set at 13.0 L/min, with a drying gas temperature of 330\u0026deg;C. The nebulizer pressure was 35 psi, sheath gas temperature was 390\u0026deg;C, and sheath gas flow rate was 12 L/min. The capillary voltage was set to 1500 V. Data acquisition was performed in multiple reaction monitoring (MRM) mode. The preparation of the mobile phases was as follows: a 200 mM ammonium formate stock solution was prepared in water, and the pH was adjusted to 3 using formic acid. Mobile phase A was prepared by diluting the stock solution with water at a 9:1 ratio. Mobile phase B was prepared by diluting the stock solution with acetonitrile at a 9:1 ratio. The final ionic strength of both mobile phases was 20 mM.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e\u003cp\u003eA two-way analysis of variance (ANOVA) was performed to evaluate the effects of silage temperature and fermentation duration on chemical composition, fermentation characteristics, and microbial counts. Statistical analyses were conducted using SPSS software (version 26.0; IBM SPSS Inc., Chicago, IL, USA). Differences were considered statistically significant at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Chemical composition of fresh oat material\u003c/h2\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the DM content of the oat samples was 346.24 g/kg FM, indicating a moderate moisture level suitable for silage. The initial pH value was 6.27, suggesting low acidity and a slightly alkaline to neutral condition prior to fermentation. The samples exhibited relatively high CP content and moderate levels of WSC, indicating sufficient fermentable substrates to support microbial activity, promote lactic acid fermentation, and stabilize the fermentation environment. The essential amino acids (EAAs) in oat were relatively well balanced, which may enhance the efficiency of protein utilization by ruminants. The content of branched-chain amino acids (BCAAs), such as Val, Leu, and Ile, was relatively high, at 6.84 g/kg, 1.78 g/kg, and 2.63 g/kg, respectively. These amino acids are important for muscle development in animals. Additionally, the content of non-essential amino acids (NEAAs), such as Glu, Ala, and Asp, was also relatively abundant, with glutamic acid and alanine concentrations of 4.14 g/kg and 3.42 g/kg, respectively. These NEAAs contribute to the nitrogen supply in silage and support various metabolic processes in animals.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eChemical composition of fresh oat material.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eContent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDry matter (g/kg FM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e346.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater-soluble carbohydrates (g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e132.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrude protein (g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e103.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutral detergent fiber (g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e528.36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcid detergent fiber (g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e331.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAmino acid contcnts (g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLysine(Lys)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethionine(Met)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTryptophan(Trp)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThreonine (Thr)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eValine (Val)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeucine (Leu)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIsoleucine(Ile)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhenylalanine(Phe)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistidine(His)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlanine(Ala)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAspartic Acid(Asp)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlutamic(Glu)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlycine(Gly)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProline(Pro)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerine(Ser)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTyrosine(Tyr)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCysteine(Cys)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArginine(Arg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Changes of fermentation indexes during oat silage\u003c/h2\u003e\u003cp\u003eTemperature and silage duration significantly influenced the fermentation characteristics of oat silage (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As the silage period progressed, pH values decreased across all temperature treatments. The most pronounced reduction occurred at 25\u0026deg;C, where the pH declined from 5.85 on 3 d to 4.08 on 90 d. At the same time, the LA content reached 51.12 g/kg DM on 90 d, significantly higher than under other temperature conditions. In contrast, the 5\u0026deg;C treatment exhibited marked fermentation inhibition, characterized by the slowest initiation of fermentation and minimal LA accumulation during the first 14 d (only 5.03 g/kg DM), with the final pH remaining relatively high at 4.85. Although fermentation efficiency at 10\u0026deg;C was superior to that at 5\u0026deg;C, signs of low-temperature suppression were still evident, as LA production only increased significantly after 60 d, and the final pH dropped to 4.43. The variation in LA content clearly demonstrated a temperature-gradient effect. AA content also increased over time; however, temperature-related differences were less distinct, ranging from 11.24 g/kg DM at 5\u0026deg;C to 18.13 g/kg DM at 25\u0026deg;C on 90 d. Interestingly, the 15\u0026deg;C treatment yielded the highest AA concentration (21.35 g/kg DM). PA was nearly undetectable during the early stages of silage (3 and 7 d) at 5\u0026deg;C, but began accumulating from 14 d, reaching 1.84 g/kg DM by 90 d. A similar trend to AA was observed, with the 15\u0026deg;C treatment producing the highest PA concentration (3.25 g/kg DM) at 90 d, followed by 10\u0026deg;C (2.98 g/kg DM), both significantly exceeding the level observed under the 25\u0026deg;C treatment. As a critical indicator of fermentation quality, the LA/AA varied significantly across temperatures. Under the 25\u0026deg;C treatment, the ratio increased steadily from 1.31 on 3 d to 2.83 on 90 d. In contrast, the 5\u0026deg;C treatment showed the smallest increase, rising from 1.04 to 2.15. Notably, at 15\u0026deg;C, the LA/AA ratio on 90 d (2.09) was even lower than that at 10\u0026deg;C (2.36).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFermentation parameters during the silage of oat silage\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eItem\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTemperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003eSilage Days\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSEM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eD\u0026times;T\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.26Aa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.11Aa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.82Ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.15Ac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.85Ad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.23Aa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.05Ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.61Bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.66Bd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.43Be\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.195\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.16Aa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.82Bb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.26Cc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.41Cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.12Ce\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.85Ba\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.36Cb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.65Dc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.16Cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.08Cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eLA\u003c/p\u003e\u003cp\u003e(g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.23De\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.56Dd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.03Dc\u003c/p\u003e\u003c/td\u003e\u003ctd 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align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.29Ac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.90Ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.85Ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.98Cb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.36Ba\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.28Ad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29Cd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.54Bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.54Bb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.09Ca\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.31Ac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49Bc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.95Ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.84Aa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.83Aa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eDM, dry matter; LA/AA, the ratio of lactic acid and acetic acid.\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eDifferent capital letters (A-D) indicate significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among different silage groups. There is a significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the different lowercase letters (a-e) indicating the number of silage days.\u003c/p\u003e\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eSEM, standard error of the mean.\u003c/p\u003e\u003cp\u003e\u003csup\u003ed\u003c/sup\u003eD, silage day; T, temperature; D\u0026times;T, interaction between temperature and silage day.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Changes of nutritional indexes in the later stage of oat silage\u003c/h2\u003e\u003cp\u003eTemperature and silage duration significantly affected the nutritional composition of oat silage at 60 d and 90 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), with significant interactions (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) observed for DM, WSC, CP, and NH₃-N. As the silage period was extended from 60 d to 90 d, DM content showed a decreasing trend under all temperature treatments, with more pronounced losses observed under low temperatures. In particular, the DM content at 5\u0026deg;C decreased by 25.35 g/kg DM, while the decrease at 25\u0026deg;C was only 11.50 g/kg DM. Under low-temperature conditions, carbohydrate consumption proceeded more slowly but persisted for a longer duration. The WSC content declined by only 2.99 g/kg DM at 25\u0026deg;C, whereas it decreased by 23.18 g/kg DM at 5\u0026deg;C. CP content exhibited a consistent pattern across both 60 d and 90 d, with higher temperatures resulting in higher CP concentrations. Notably, CP content remained relatively stable at 25\u0026deg;C (declining by only 2.78 g/kg DM), while a more substantial decrease of 8.07 g/kg DM was observed at 5\u0026deg;C, indicating more severe protein degradation under low-temperature conditions. NDF and ADF contents decreased significantly with increasing temperature, reflecting enhanced cellulose degradation under warmer conditions. After 90 d of silage, the NDF contents in the 25\u0026deg;C and 15\u0026deg;C treatments were significantly lower than that in the 5\u0026deg;C treatment. NH₃-N levels increased significantly over time across all temperatures; however, low-temperature treatments exhibited more pronounced protein degradation. Specifically, NH₃-N content at 5\u0026deg;C increased from 93.56 to 113.25 g/kg TN, a rise of 19.69 g/kg TN, which was substantially greater than the 6.28 g/kg TN increase observed at 25\u0026deg;C.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNutritional indicators of oat silage\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eItem\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSilage Days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e\u003cp\u003eTemperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSEM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25\u0026deg;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eD\u0026times;T\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003cp\u003e(g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e313.62a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e308.24ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e303.56b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e307.82b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e288.27c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e284.16d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e291.55b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e296.32a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.387\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eWSC\u003c/p\u003e\u003cp\u003e(g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70.25a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64.17b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58.62c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e56.34c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47.07b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.66c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46.56b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e53.35a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.243\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCP\u003c/p\u003e\u003cp\u003e(g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.24d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.80c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75.52b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e81.05a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.916\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54.17d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61.52c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67.24b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78.27a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.676\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNDF\u003c/p\u003e\u003cp\u003e(g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e508.98a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e491.21b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e479.72c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e456.60d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.195\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e496.15a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e477.54b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e457.29c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e452.33c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.564\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eADF\u003c/p\u003e\u003cp\u003e(g/kg DM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e312.84a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e290.06b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e273.25c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e265.68c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.285\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e301.36a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e282.25b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e265.47c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e264.33c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.644\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e-N\u003c/p\u003e\u003cp\u003e(g/kg TN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.56a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85.62b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76.21c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64.54d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e113.25a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96.35b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e88.36c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e70.82d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.628\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eFM, fresh matter; WSC, water-soluble carbohydrate; CP, crude protein; NDF, neutral detergent fibre; ADF, acid detergent fibre; NH\u003csub\u003e3\u003c/sub\u003e-N, ammonia nitrogen.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Succession of bacterial community during low-temperature silage\u003c/h2\u003e\u003cp\u003eTo evaluate the effects of different silage conditions on the bacterial community diversity in oat silage, both α-diversity (Shannon index) and β-diversity (principal coordinate analysis, PCoA) were assessed across treatment groups. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA illustrates the variation in the Shannon index of oat silage bacterial communities under different temperature and silage duration treatments. Both silage temperature and duration significantly influenced the Shannon index. Overall, an increase in silage temperature was associated with a marked decline in bacterial diversity. After 60 d of silage, the 5\u0026deg;C group exhibited the highest Shannon index, which was significantly greater than that of all other treatments (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In contrast, the 25\u0026deg;C group showed the lowest diversity. The PCoA results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) visually revealed distinct differences in bacterial community structures (β-diversity) among the treatment groups. The first principal coordinate (PCoA1), which accounted for 44.7% of the total variation, was the primary factor driving sample separation. Notably, it effectively differentiated the low-temperature groups (5\u0026deg;C and 10\u0026deg;C, predominantly distributed on the negative axis of PCoA1) from the high-temperature group (25\u0026deg;C, mainly located on the positive axis), while the 15\u0026deg;C group occupied an intermediate position. These findings indicate that temperature is the dominant driver shaping the bacterial community structure in oat silage.\u003c/p\u003e\u003cp\u003eAt the phylum level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), the microbial community of fresh oat material (FM) exhibited considerable diversity, with \u003cem\u003eProteobacteria\u003c/em\u003e being the most dominant phylum (55.8%), followed by \u003cem\u003eFirmicutes\u003c/em\u003e (31.5%). After silage fermentation, \u003cem\u003eFirmicutes\u003c/em\u003e sharply increased in relative abundance and became the overwhelmingly dominant phylum in all silage samples, while \u003cem\u003eProteobacteria\u003c/em\u003e declined significantly across all treatments. At the genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), the dominant genera in fresh oat included \u003cem\u003eHafnia\u003c/em\u003e, \u003cem\u003eEnterobacter\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, and \u003cem\u003ePantoea\u003c/em\u003e, all affiliated with \u003cem\u003eProteobacteria\u003c/em\u003e, whereas lactic acid bacteria (LAB) were initially present at low abundance. Extending the silage duration from 60 to 90 d at the same temperature generally enhanced the abundance of dominant LAB genera and further suppressed non-LAB populations. Under ambient conditions (25\u0026deg;C), the fermentation process was fully dominated by \u003cem\u003eLactiplantibacillus\u003c/em\u003e, whose relative abundance exceeded 70% after 60 d and further increased by 90 d. Meanwhile, all other genera\u0026mdash;particularly those affiliated with \u003cem\u003eProteobacteria\u003c/em\u003e\u0026mdash;were reduced to negligible levels. In contrast, under low-temperature conditions (5\u0026deg;C), potentially undesirable genera such as \u003cem\u003eHafnia\u003c/em\u003e and \u003cem\u003eEnterobacter\u003c/em\u003e remained relatively abundant even after 60 d of fermentation. As temperature increased to 10\u0026deg;C and 15\u0026deg;C, \u003cem\u003eLactiplantibacillus\u003c/em\u003e exhibited a significant rise in relative abundance, gradually replacing \u003cem\u003eHafnia\u003c/em\u003e and \u003cem\u003eEnterobacter\u003c/em\u003e as the dominant genus. At 15\u0026deg;C after 90 d, \u003cem\u003eLactiplantibacillus\u003c/em\u003e had become the prevailing genus in the bacterial community.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Changes of FAAs content at late stage of low temperature silage\u003c/h2\u003e\u003cp\u003eTo investigate the effect of low temperature on protein degradation, we conducted quantitative analysis of 18 FAAs across temperature treatment groups during the late fermentation stage (60/90 d) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The results showed that both silage temperature and duration significantly altered the concentrations of FAAs. Compared to fresh forage, most FAAs were significantly reduced in temperature-controlled silage (25\u0026deg;C), while low-temperature treatments (5\u0026deg;C/10\u0026deg;C) significantly increased FAAs. Lys content in 90 d 5\u0026deg;C silage was 1.65 times higher than in fresh forage. The contents of most essential amino acids (EAAs) and several non-essential amino acids (NEAAs) decreased significantly with increasing temperature. Lys, His, and Arg exhibited their highest concentrations at 5\u0026deg;C, followed by a significant, stepwise reduction as temperature rose to 25\u0026deg;C (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For instance, after 90 d of silage, the Lys content declined from approximately 4.53 g/kg DM at 5\u0026deg;C to about 1.75 g/kg DM at 25\u0026deg;C. Similarly, Trp, Val, Leu, Phe, Pro, and Met displayed comparable negative correlations with temperature, where lower temperatures significantly increased their concentrations. Conversely, the concentrations of several other amino acids increased significantly with rising temperature. Ala accumulation was particularly pronounced, increasing from approximately 2.37 g/kg DM at 5\u0026deg;C to about 4.32 g/kg DM at 25\u0026deg;C after 90 d of silage. Glu, Asp, Gly, Ser, and Tyr followed the same pattern, reaching their highest concentrations in the 25\u0026deg;C treatment group, which were significantly greater than those in the low-temperature groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A few amino acids exhibited distinct patterns. For example, Ile and Thr showed relatively small variations across temperatures and did not exhibit consistent monotonic increasing or decreasing trends like the other amino acids. Regarding silage duration, extending the period from 60 to 90 d at 25\u0026deg;C resulted in non-significant changes in most free amino acid contents. In contrast, under low-temperature silage conditions, prolonging the duration from 60 to 90 d further amplified the temperature-induced trends.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Correlation between bacterial community and FAAs content\u003c/h2\u003e\u003cp\u003eTo elucidate complex relationships between dominant bacterial genera and FAAs during low-temperature oat silage fermentation, mantel tests revealed significant correlations between bacterial community composition and FAA profiles across all samples. The upper-right quadrant of Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents a Spearman correlation matrix demonstrating inter-FAA associations. Ala, Asp, Glu, Ser, and Tyr exhibited significant mutual positive correlations, with the strongest relationships occurring between Asp-Glu and Ala-Glu. Another group of FAAs\u0026mdash;including Lys, His, Arg, and Pro\u0026mdash;showed significant negative correlations with Ala, Asp, and Glu. For example, Lys displayed strong negative correlations with Ala, Asp, and Glu, suggesting potential antagonistic metabolic or microbial interactions. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e also illustrates the correlations between key bacterial genera and the concentrations of individual FAAs. As a dominant genus, \u003cem\u003eLactiplantibacillus\u003c/em\u003e exhibited broad correlations with various amino acids. Notably, it showed strong negative correlations with branched-chain amino acids (BCAAs) such as Leu, Val, and Ile, while displaying positive correlations with acidic amino acids such as Asp and Glu. \u003cem\u003eEnterobacter\u003c/em\u003eial genera including \u003cem\u003eEnterobacter\u003c/em\u003e and \u003cem\u003ePantoea\u003c/em\u003e were positively correlated with the majority of FAAs, particularly with small-molecule amino acids such as Ala, Gly, and Ser. Lactic acid bacteria such as \u003cem\u003ePediococcus\u003c/em\u003e and \u003cem\u003eLevilactobacillus\u003c/em\u003e exhibited moderate negative correlations with aromatic amino acids including Phe and Tyr. Notably, \u003cem\u003ePseudomonas\u003c/em\u003e showed positive correlations with most amino acids, with the strongest association observed with Arg. In addition, \u003cem\u003eWeissella\u003c/em\u003e was strongly associated with sulfur-containing amino acids, namely Met and Cys.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussions","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Effects of low temperature silage on fermentation characteristics and nutritional indexes of silage\u003c/h2\u003e\u003cp\u003eThe results demonstrated that fermentation temperature is a decisive factor influencing silage quality in oat. The 5\u0026deg;C treatment exhibited delayed fermentation initiation, characterized by low lactic acid accumulation and a significantly higher pH at 90 d than other temperatures\u0026mdash;consistent with Liu et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who reported suppressed LAB activity below 10\u0026deg;C. A slow pH decline reduces fermentation efficiency and may promote the growth of harmful microorganisms, increasing the risk of silage spoilage. The lactic acid-to-acetic acid ratio (LA/AA), a key indicator of fermentation type, showed an overall increasing trend across treatments over time, indicating progressive dominance of homolactic fermentation. This aligns with Zhang et al. (2017), where \u003cem\u003eLactobacillus\u003c/em\u003e and other homofermentative LAB became dominant during later stages. Notably, the 90 d LA/AA ratio at 15\u0026deg;C was lower than at 60 d, potentially linked to temperature-dependent microbial community structures. Zhu et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that under moderate temperature conditions, the co-existence of homofermentative and heterofermentative lactic acid bacteria in relative balance is beneficial for maintaining an appropriate LA/AA ratio, which may explain the observed differences in the 15\u0026deg;C treatment group at specific stages. Regarding PA content, after 90 days of fermentation at low temperatures (10 and 15\u0026deg;C), the PA concentration was higher than that observed under ambient conditions. This finding is consistent with the observations of Li et al. (2021), who reported that under low pH and well-maintained anaerobic conditions, the activity of PA producing bacteria is suppressed. The lower PA content observed at 5\u0026deg;C may be attributed to a pronounced inhibition of the metabolic pathways of PA bacteria due to excessively low temperatures.\u003c/p\u003e\u003cp\u003eThis study found that the DM content decreased significantly with the extension of the fermentation period, consistent with the findings of Borreani et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who reported that microbial metabolic activity during fermentation leads to organic matter loss and a reduction in DM content. Notably, the DM content in the low-temperature treatment group at 90 days of fermentation was significantly lower than that in the 25\u0026deg;C treatment group. This observation is in agreement with Guo et al. (2014), who suggested that fermentation under suitable ambient temperatures may reduce long-term DM losses by accelerating the attainment of a stable phase. Temperature variations can directly affect microbial metabolic rates, thereby influencing the degradation rate of organic matter and ultimately resulting in differences in DM loss under varying temperature conditions. WSC serve as the primary substrates for silage fermentation, and their content reflects the intensity of the fermentation process. In this study, the WSC content was highest in the 5\u0026deg;C treatment group and gradually decreased with increasing temperature. This result is consistent with the findings of Shah et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who reported that lower temperatures reduce microbial metabolic activity, thereby decreasing WSC consumption. Consequently, under low-temperature conditions, the relatively high WSC content in silage may be attributed to insufficient microbial activity to rapidly utilize these substrates. CP content increased significantly with temperature, consistent with Cheng et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) who attributed this to relative enrichment of non-protein nitrogen compounds under ambient conditions. Concurrently, all treatments exhibited declining CP from 60 to 90 d, supporting Zhu et al. (2022) that prolonged fermentation enhances proteolysis and NH\u003csub\u003e3\u003c/sub\u003e-N volatilization. This change may be related to the microbial metabolic processes of proteins, particularly the activity of proteolytic enzymes and the dynamic variations of nitrogen sources during fermentation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Effect of low temperature on silage microbial community\u003c/h2\u003e\u003cp\u003eTemperature plays a pivotal role in shaping the microbial diversity and community structure of oat silage, as evidenced by a significant reduction in the Shannon index with rising temperatures. This trend is consistent with findings from Yang et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who observed a decrease in microbial diversity under ambient temperatures compared to lower temperatures. Guan et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) suggested that this loss of diversity is primarily driven by the rapid proliferation of \u003cem\u003eLactobacillus\u003c/em\u003e species and the accumulation of organic acids under warmer conditions, which creates an environment that suppresses the growth of competing microorganisms. The dominance of \u003cem\u003eLactobacillus\u003c/em\u003e strains in such conditions further exacerbates the narrowing of microbial diversity, as these organisms, being acid-tolerant, outcompete other taxa. PcoA revealed distinct clustering of microbial communities across different temperature treatments, reinforcing the idea that temperature is a key ecological factor in microbial community assembly\u0026mdash;this is in agreement with the work of Zhu et al. (2025). Notably, the maximal separation observed between the 5\u0026deg;C and 25\u0026deg;C treatment groups in the PCoA plot suggests that temperature-induced shifts in community composition are profound and not merely quantitative. This compositional divergence may reflect complex changes in microbial physiological adaptations and competitive strategies, as temperature affects not only growth rates but also microbial enzymatic activity, nutrient utilization, and tolerance mechanisms Li et al. (2021). At lower temperatures, psychrotolerant and facultative microorganisms likely maintain a more diverse community due to slower metabolic rates, whereas higher temperatures select for more aggressive acid-producing organisms like \u003cem\u003eLactobacillus\u003c/em\u003e, which may lead to a more homogenous, less diverse microbiota.\u003c/p\u003e\u003cp\u003eAt the phylum level, \u003cem\u003eFirmicutes\u003c/em\u003e dominated under ambient temperature, whereas \u003cem\u003eProteobacteria\u003c/em\u003e were markedly enriched at low temperatures, consistent with Ni et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and likely driven by the ability of certain \u003cem\u003eProteobacteria\u003c/em\u003e to express cold-adaptation proteins that maintain membrane fluidity and enzyme activity in low-temperature environments (Xin et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This thermal niche partitioning reshapes the functional potential of the silage microbiome: while \u003cem\u003eFirmicutes\u003c/em\u003e, particularly LAB, accelerate carbohydrate fermentation and acidification, \u003cem\u003eProteobacteria\u003c/em\u003e often exhibit slower acid production but broader catabolic capabilities. At the genus level, \u003cem\u003eLactiplantibacillus\u003c/em\u003e dominated at 25\u0026deg;C, aligning with its homofermentative metabolism that rapidly channels sugars into lactic acid, explaining both the sharp pH decline and elevated LA/AA ratio (Guo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The dominance of LAB at this temperature has additional implications\u0026mdash;these bacteria have limited proteolytic capacity, targeting mainly small peptides rather than intact proteins (Mu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Coupled with the inhibitory effect of the rapid pH drop (4.08) on plant endogenous proteases, this may account for the lower NH₃-N content observed, suggesting that warm fermentation environments could help preserve true protein. Conversely, at 5\u0026deg;C, the microbiota shifted toward \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eLeuconostoc\u003c/em\u003e. \u003cem\u003ePseudomonas\u003c/em\u003e species, despite thriving under low temperatures, are frequently associated with reduced silage quality due to strong protease activity (Weber et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, cold-adapted proteases from certain \u003cem\u003ePseudomonas\u003c/em\u003e strains can remain highly active\u0026mdash;or even more active\u0026mdash;under low temperatures (Yang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), facilitating extensive protein degradation into amino acids and ammonia, as reflected by the elevated NH₃-N levels. \u003cem\u003eLeuconostoc\u003c/em\u003e, a heterofermentative LAB, contributes to acidification but at a slower rate and with lower lactic acid yields, further delaying pH stabilization. Taken together, these patterns suggest that temperature not only dictates which taxa dominate, but also indirectly governs silage nitrogen preservation through both microbial proteolytic capacity and pH-mediated suppression of plant proteases. From a practical perspective, maintaining silage temperatures closer to ambient during early fermentation could enhance protein conservation, whereas prolonged low-temperature conditions risk increased proteolysis and quality loss\u0026mdash;especially if cold-tolerant proteolytic \u003cem\u003eProteobacteria\u003c/em\u003e proliferate. Future research should assess whether targeted inoculants or temperature-modulated ensiling can mitigate these risks in cold storage environments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Effect of low temperature on FAAs\u003c/h2\u003e\u003cp\u003eFrom a nutritional quality perspective, the accumulation of essential amino acids (e.g., Lys, Val, Leu, and Phe) in silage represents a potentially beneficial outcome, as these compounds can enhance the protein value and digestibility of the feed. However, this advantage must be weighed against the biochemical and safety risks associated with prolonged proteolysis, particularly under low-temperature conditions. At reduced temperatures, microbial proteolytic activity remains sustained over extended storage periods, leading to the continuous release of free amino acids. While some degree of amino acid accumulation is desirable, excessive levels can trigger detrimental secondary reactions. One major concern is the Maillard reaction, wherein excess amino acids interact with residual reducing sugars to form advanced glycation end products (AGEs). These AGEs are poorly digestible and can alter the physicochemical properties of silage, manifesting as browning and reduced palatability (Yuan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Beyond aesthetic and palatability issues, AGEs have been implicated in oxidative stress and inflammatory responses in animals, potentially reducing the nutritional and health value of the feed. Another risk is the microbial decarboxylation of amino acids into biogenic amines, such as putrescine, cadaverine, and tyramine, via specific microbial decarboxylases (Sun et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These amines are biologically active compounds that, at high concentrations, can cause toxicity, disrupt rumen function, or interfere with nutrient absorption. Low-temperature conditions may favor the persistence and activity of psychrotrophic or cold-tolerant microbes capable of producing such amines, further amplifying food safety concerns. The temporal dynamics of amino acid changes highlight the interaction between microbial ecology and metabolic pathways. At 25\u0026deg;C, extending fermentation from 60 to 90 d had minimal influence on amino acid concentrations, likely due to the rapid dominance of lactic acid bacteria at early stages. These LAB complete most of the soluble protein breakdown and amino acid metabolism within the initial fermentation window, after which microbial activity and substrate availability stabilize (Bernardes et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, at 5\u0026deg;C and 10\u0026deg;C, a 90 d storage period markedly increased the accumulation of most amino acids, suggesting that low-temperature proteolysis is a slow but persistent process. This pattern aligns with the hypothesis that when carbohydrate availability is restricted, microbial communities shift toward proteolysis as an alternative energy acquisition strategy, resulting in cumulative amino acid buildup. Interestingly, certain amino acids, such as Ile and Thr, exhibited relatively minor changes across temperature treatments and lacked a monotonic trend. This variability likely reflects their dual role in fermentation: they both accumulate as end products of proteolysis and are continuously consumed as microbial growth substrates. Moreover, in late fermentation stages, decarboxylase activity may channel these amino acids toward biogenic amine production, thereby obscuring their apparent concentration patterns (Bai et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kung et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These findings underscore a critical limitation of using amino acid content alone as a proxy for protein degradation, as this approach fails to account for downstream metabolic transformations. To more accurately assess proteolysis and protein quality loss, future studies should integrate amino acid profiling with quantification of secondary metabolites, particularly biogenic amines, as well as characterization of the microbial taxa and enzymes responsible for these conversions. Such an integrated approach would provide a more comprehensive understanding of how temperature-dependent microbial activity shapes both the nutritional value and safety profile of silage, and could inform targeted interventions\u0026mdash;such as microbial inoculant selection, storage temperature management, or post-fermentation treatment\u0026mdash;to optimize feed quality and minimize risks.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Correlation between FAAs and microbial community\u003c/h2\u003e\u003cp\u003eThe Mantel test and Spearman correlation analysis revealed a robust association between the bacterial community structure and the profiles of FAAs during the low-temperature fermentation of oat silage. These findings significantly enhance our understanding of the mechanisms governing protein degradation and FAA accumulation under cold conditions (Muck et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Specifically, \u003cem\u003eLactiplantibacillus\u003c/em\u003e displayed a significant negative correlation with branched-chain amino acids (BCAAs), such as Leu and Val, suggesting that it may suppress the accumulation of these amino acids under low-temperature conditions. This could be attributed to the genus' abundance of amino acid transporters and deaminase genes, which enable rapid FAA uptake for growth, thus limiting BCAA accumulation (Zhu et al., 2022). \u003cem\u003eLactiplantibacillus\u003c/em\u003e is typically dominant in lactic acid fermentation at moderate temperatures, but its role in low-temperature silage could be more complex, where it may preferentially metabolize certain amino acids early in fermentation, leading to the reduced availability of BCAAs. In contrast, \u003cem\u003eEnterobacter\u003c/em\u003e exhibited a positive correlation with most amino acids, particularly smaller ones such as Ala, Gly, and Ser under cold conditions (He et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This finding is consistent with previous studies, which have highlighted that \u003cem\u003eEnterobacteriaceae\u003c/em\u003e possess strong proteolytic and decarboxylase activities, enabling them to thrive when LAB are suppressed (Zhou et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). At lower temperatures, the metabolic activity of LAB may be reduced, providing a favorable environment for psychrotolerant \u003cem\u003eEnterobacter\u003c/em\u003e species with active protease systems. These bacteria can efficiently break down proteins into amino acids, promoting their accumulation in silage, which is reflected in the significant accumulation trends observed in the low-temperature treatment groups. Furthermore, \u003cem\u003ePediococcus\u003c/em\u003e and \u003cem\u003eLevilactobacillus\u003c/em\u003e were negatively correlated with aromatic amino acids such as Phe and Tyr, suggesting a potential role for these genera in the degradation of these compounds. Since aromatic amino acids are essential for feed protein quality, their excessive breakdown could significantly reduce the nutritional value of silage (You et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Previous research has shown that \u003cem\u003ePediococcus\u003c/em\u003e species secrete aromatic amino acid transaminases that degrade Phe and Tyr, further supporting our findings (Scherer et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While the breakdown of these amino acids may help balance microbial metabolism during fermentation, their over-degradation could be detrimental to silage nutritional quality. Therefore, careful monitoring of these genera is necessary to mitigate nutrient loss during cold-temperature silage fermentation. \u003cem\u003ePseudomonas\u003c/em\u003e species, known for their robust proteolytic activity, may also play a role in elevating silage pH through arginine deamination, disrupting the anaerobic conditions essential for proper fermentation and thereby increasing the risk of spoilage. Controlling the growth of \u003cem\u003ePseudomonas\u003c/em\u003e is critical for improving the quality of silage under low-temperature conditions, as their metabolic activity can lead to undesirable changes in pH and the production of toxic metabolites, further complicating the silage fermentation process. \u003cem\u003eWeissella\u003c/em\u003e, on the other hand, exhibited strong correlations with sulfur-containing amino acids such as Met and Cys, indicating a potential involvement in sulfur metabolism. Some strains of \u003cem\u003eWeissella\u003c/em\u003e can produce volatile compounds, such as hydrogen sulfide, through cysteine desulfhydration (\u0026Aacute;vila and Carvalho, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which could negatively affect silage flavor and, in some cases, contribute to the production of off-flavors. The role of \u003cem\u003eWeissella\u003c/em\u003e in sulfur metabolism suggests that its presence may influence the sensory properties of silage, further highlighting the need to carefully consider microbial strain selection in silage management. Overall, these findings underline the complex interplay between microbial community composition and amino acid profiles during low-temperature fermentation of oat silage. Low temperatures not only affect the metabolic activities of LAB but also foster the growth of psychrotolerant microbes, which play pivotal roles in the breakdown and accumulation of amino acids. Future studies should explore how microbial community structure can be modulated to improve silage quality, particularly by controlling the growth of spoilage-associated species such as \u003cem\u003ePseudomonas\u003c/em\u003e, and optimizing the roles of beneficial microbes like \u003cem\u003ePediococcus\u003c/em\u003e and \u003cem\u003eLactiplantibacillus\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eTemperature significantly influenced the fermentation trajectory, microbial structure, and free amino acid (FAA) metabolism of oat silage. At 5\u0026deg;C, inhibited LAB activity led to reduced lactic acid production, elevated pH, and increased ammonia-N levels\u0026mdash;hallmarks of fermentation inefficiency. Microbial analysis revealed a clear shift: \u003cem\u003eLactiplantibacillus\u003c/em\u003e predominated at 25\u0026deg;C, whereas psychrotrophic, proteolytic taxa such as \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eEnterobacter\u003c/em\u003e dominated at low temperature. These genera showed strong positive associations with essential FAAs (e.g., Lys, His, Arg), indicating that low-temperature silage is prone to proteolysis-driven nitrogen loss. These findings confirm that temperature acts as a primary regulator of microbial functionality and protein retention during ensiling. Therefore, cold-region forage systems require precision microbial interventions. Cold-adapted LAB with enhanced acidogenic and FAA-assimilating traits, combined with protease-inhibiting additives, offer promising strategies to improve silage quality under thermal stress.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAuthors\u0026rsquo; contributions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eX.L: Conceptualization, methodology, software, formal analysis, data curation, writing\u0026mdash;original draft preparation, writing\u0026mdash;review and editing. J.B: validation. X.Q: resources. J.C: supervision, project administration. D.L: writing\u0026mdash;review and editing. G.Z: Conceptualization, writing\u0026mdash;review and editing, supervision, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eProject supported by the National Natural Science Foundation of China (Grant No. 32160810).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX.L: Conceptualization, methodology, software, formal analysis, data curation, writing\u0026mdash;original draft preparation, writing\u0026mdash;review and editing. J.B: validation. X.Q: resources. J.C: supervision, project administration. D.L: writing\u0026mdash;review and editing. G.Z: Conceptualization, writing\u0026mdash;review and editing, supervision, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets supporting the findings of this study are available in the NCBI Sequence Read Archive (SRA) database (Accession Number: PRJNA1311492), https://dataview.ncbi.nlm.nih.gov/object/PRJNA1311492.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e\u0026Aacute;vila CLS, Carvalho BF. Silage fermentation-updates focusing on the performance of micro-organisms. 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Effect of Low-Temperature-Tolerant Lactic Acid Bacteria on the Fermentation Quality and Bacterial Community of oat Silage at 5\u0026deg;C vs. 15\u0026deg;C Ferment. 2022a;8:158. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/fermentation8040158\u003c/span\u003e\u003cspan address=\"10.3390/fermentation8040158\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"low temperature silage, oat, microbial community, free amino acids","lastPublishedDoi":"10.21203/rs.3.rs-7475710/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7475710/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThis study evaluated the effects of different temperatures (5\u0026deg;C, 10\u0026deg;C, 15\u0026deg;C, and 25\u0026deg;C) on the fermentation characteristics, microbial communities, and free amino acids (FAAs) dynamics of oat(\u003cem\u003eAvena sativa\u003c/em\u003e) silage.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eFermentation was significantly inhibited at 5\u0026deg;C, with a slower pH decline, lower lactic acid production, and a reduced lactic acid to acetic acid (LA/AA) ratio. Microbial diversity was higher under low-temperature conditions, with \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eEnterobacter\u003c/em\u003e, and \u003cem\u003eProteobacteria\u003c/em\u003e dominating. Most FAAs, particularly lysine, histidine, and arginine, accumulated at low temperatures. Correlation analysis revealed that \u003cem\u003eEnterobacter\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e were positively correlated with many FAAs, indicating their key roles in proteolysis.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese findings contribute to a deeper understanding of the microbial and biochemical mechanisms of low-temperature silage fermentation and provide a theoretical basis and strategic support for optimizing silage quality in cold regions.\u003c/p\u003e","manuscriptTitle":"Effects of low temperature silage on microbial community and free amino acids of oat silage quality","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 07:20:55","doi":"10.21203/rs.3.rs-7475710/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-21T12:21:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-20T15:40:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99822114089431135778320502365010268539","date":"2025-10-03T09:21:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271213697995221196173555115546167184659","date":"2025-10-01T06:03:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T07:36:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269022513854697261679531722754402983796","date":"2025-09-22T13:55:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-14T02:38:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-04T06:55:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-04T06:23:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T02:06:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2025-09-04T02:03:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"15e6b1cd-0aef-4880-915b-91932dd06f28","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:03:32+00:00","versionOfRecord":{"articleIdentity":"rs-7475710","link":"https://doi.org/10.1186/s12866-025-04559-3","journal":{"identity":"bmc-microbiology","isVorOnly":false,"title":"BMC Microbiology"},"publishedOn":"2025-12-11 15:57:19","publishedOnDateReadable":"December 11th, 2025"},"versionCreatedAt":"2025-09-22 07:20:55","video":"","vorDoi":"10.1186/s12866-025-04559-3","vorDoiUrl":"https://doi.org/10.1186/s12866-025-04559-3","workflowStages":[]},"version":"v1","identity":"rs-7475710","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7475710","identity":"rs-7475710","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}