Skip to main content
Download PDF

Effects of different temperature and density on quality and microbial population of wilted alfalfa silage

BMC Microbiology volume 24, Article number: 380 (2024) Cite this article

Abstract

In this experiment, alfalfa silage with different packing densities (500 kg/m3、600 kg/m3 and 700 kg/m3) was prepared under the conditions of outdoor high temperature and indoor room temperature, respectively. At the same time, the same lactobacillus additive was used for fermentation in each density treatment group. The chemical composition, fermentation quality and microbial community of alfalfa silage were analyzed. The results showed that the contents of dry matter (DM) and water-soluble carbohydrate (WSC) decreased with the increase of density during fermentation at high temperature. At the same time, when the density is 600 kg/m³, CP (crude protein) content is the highest, ADF (acid detergent fiber) content is the lowest. The contents and pH values of neutral detergent fiber (NDF), lactic acid (LA) and lactic acid bacteria (LAB) were significantly affected by temperature (p < 0.05). Density had significant effects on DM, NDF, WSC and LA contents (p < 0.05). The interaction between temperature and density had significant effects on the content of ADF and LAB (p < 0.05). At the same time, the abundance of Lactiplantibacillus plantarum in high temperature fermented silage was lower than that in normal temperature fermented feed. The number of Lactiplantibacillus plantarum in room temperature treatment group decreased with the increase of density. In summary, this study clarified the effects of different temperature and density on alfalfa fermentation quality and microbial community, and clarified that the density should be reasonably controlled within 600 kg/m³ during alfalfa silage, providing theoretical support for production practice.

Peer Review reports

Introduction

Ensiling, a method used to preserve green forage crops in anaerobic conditions [1], offers several advantages, such as minimal nutrient loss and good palatability [2]. It is commonly employed to address feed shortages during the spring and winter seasons by extending the storage time of feed. However, silage fermentation is highly influenced by temperature [3], and different temperatures can lead to differences in microbial species and community dynamics during the fermentation process. Unfavorable factors, such as the growth and reproduction of detrimental bacteria, may occur under higher temperatures and humid conditions [4].The optimal temperature range for the dominant lactic acid bacteria involved in the silage fermentation process is generally considered to be between 20 and 30 °C. Deviations from this range, whether higher or lower, can affect their growth and reproduction, subsequently influencing the fermentation quality of silage feed [5]. However, it is important to note that the optimal temperature for silage may vary depending on the type of material being used. Studies have shown that the optimal temperature of corn stalk silage is 25 ℃ [6], while the optimal temperature range of whole corn silage is 20–25 ℃ [7].

Factors that contribute to silage deterioration include oxygen content (exposure time), microbial community composition, substrate type, and fermentation temperature [8]. During the large-scale harvesting of alfalfa in the summer, temperatures can surpass 30 °C, posing challenges in maintaining precise temperature control during alfalfa silage production. Furthermore, the storage method employed, particularly the use of silos, has an impact on fermentation quality. A lower stacking density during the fermentation process can elevate the residual oxygen content in the feed, which hinders the complete anaerobic stage of early fermentation and facilitates the growth of harmful microorganisms [9]. Additionally, a reduced stacking density can lead to a decrease in the recovery rate of dry matter (DM) and nutrient loss [10]. The rigid stems of alfalfa cannot be finely chopped for large-scale silage production, resulting in potential air retention during compaction. Consequently, high-density silage can effectively minimize oxygen infiltration and mitigate feed quality degradation and mold formation caused by oxidation reactions. However, it is important to note that a higher density does not necessarily guarantee superior quality of alfalfa silage. Excessive density may compromise the integrity of leaf and stem structures, leading to leakage of alfalfa juice and diminished feed quality. The effect of temperature on microorganisms in silage process cannot be ignored, and the different compaction density directly affects the quality of silage. However, the comprehensive effects of temperature and density on the quality and microbial community of alfalfa silage are limited. Therefore, it is of great significance to study the changes of alfalfa silage quality and microbial community structure under different temperature and density conditions.We established various treatment groups with different densities to investigate the optimal silage density for alfalfa. We believe that alfalfa silage quality will exhibit significant differences under varying temperature and density conditions, and its microbial composition will also change. Based on this, we set up multiple experimental groups to systematically study the impact of temperature and density on the quality of alfalfa silage and the evolution of microbial communities. This research aims to clarify the patterns of microbial diversity and quality changes during the alfalfa silage process, exploring the optimal density for alfalfa silage, and providing a theoretical basis for practical production.

In north China, alfalfa harvest season is mainly concentrated in summer, and the maximum outdoor ambient temperature during the experiment can reach about 35 ℃. However, during the ensiling process, the temperature fluctuated, so the average temperature of the high temperature treatment group was 25–35 ℃; The average temperature of the normal temperature treatment group was 20 ℃.

Materials and methods

Materials and chemicals

The experiment was conducted from June to August 2022 at a research base located in Hohhot, Inner Mongolia Autonomous Region. The geographical coordinates range from 110°46’ to 112°10’ east and from 40°51’ to 41°8’ north. This region is situated within the Eurasian continent and is characterized by a temperate continental monsoon climate with precipitation ranging from 335.2 to 534.6 mm. The average outdoor temperature in summer is 22 –26 °C, up to 35 °C.The experimental area covered 666 m² of saline-alkali soil. The harvest date was June 28, 2022, and the alfalfa was cut at the early flowering stage of the first cutting. The selected alfalfa variety was WL168.The seeds were supplied by Inner Mongolia Zhengda Co., Ltd. and originated in the United States.

After harvest, a part of the fresh samples were placed in sterilized storage tubes and transported to the Key Laboratory of Grassland and Resources and Environment College of Inner Mongolia Agricultural University for storage at -80 °C.The remaining grass samples were spread on clean plastic sheets and naturally dried to a moisture content of approximately 60%. The dried samples were then cut into 2–3 cm lengths using a shredder.

The processed alfalfa samples were divided into three equal portions and subjected to secondary fermentation by evenly spraying them with a composite inoculant containing Lactiplantibacillus plantarum and Lentilactobacillus buchneri. (Production enterprise: Inner Mongolia Hemei Kesheng Biotechnology Co., Ltd; Production address: Hohhot, Inner Mongolia) The targeted bacterial population in the sprayed inoculant was set at 1 × 106 cfu/g. The microbial inoculant was dissolved in sterile water at a ratio of 30 ml per kilogram of forage. The solution was then evenly sprayed onto the forage samples while continuously mixing the samples to ensure thorough and uniform distribution of the inoculant. The first part had a stacking density of 500 kg/m³ (500 g of grass samples filled into a 1 L polyethylene barrel), the second part had a stacking density of 600 kg/m³ (600 g of grass samples filled into a 1 L polyethylene barrel), and the third part had a stacking density of 700 kg/m³ (700 g of grass samples filled into a 1 L polyethylene barrel). Each density treatment group was further divided into two temperature gradients (3 density treatment groups * 2 temperatures * 3 replicates).

After filling, the top of each barrel was sealed with a sealing cover equipped with a sealing rubber and plunger ring, and the barrel opening was wrapped with plastic film to prevent the entry of oxygen. The ambient temperature treatment group was placed indoors for fermentation, while the high-temperature treatment group was exposed to outdoor fermentation. During the experiment, which took place in summer, the outdoor temperature could reach 35 °C. The ambient temperature treatment group was placed indoors for fermentation, with an average indoor temperature of 20 °C.

After 60 days of ensiling, the barrels were opened to evaluate the quality of alfalfa silage under high-temperature conditions with stacking densities of 500 kg/m3, 600 kg/m3, and 700 kg/m3 (referred to as G500, G600, and G700, respectively), as well as under ambient temperature conditions with stacking densities of 500 kg/m3, 600 kg/m3, and 700 kg/m3 (referred to as C500, C600, and C700, respectively). Additionally, 20 g of each sample was placed in storage tubes and stored at -80 °C. These samples were sent to Majorbio Bio-pharm Technology (Majorbio Bio-pharm Technology Co., Ltd., Shanghai, China) for sequencing analysis.

Sample collection and measurements

Each sample of fresh alfalfa and silage underwent three parallel determinations, which included analyses of chemical composition, fermentation characteristics, and microbial analysis. The dry matter (DM) content was determined by drying the samples in an oven at 65 °C for 48 h by Zhang, et al. [11]. After drying, the samples were crushed in a grinder through a 1 mm sieve and placed in a ziplock bag for later use.The crude protein (CP) content was determined using a Kjeldahl nitrogen analyzer (Gerhart Vapodest 50 s, Germany) in accordance with the guidelines provided by the Association of Official Analytical Chemists (AOAC, 1990). The water-soluble carbohydrate (WSC) content was assessed using the anthrone colorimetric method as outlined by Thomas [12]. The neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined using an Ankom A2000i fiber analyzer (A2000i, Ankom Technology, Macedon, NY, United States).

To evaluate the fermentation characteristics of the silage, 10 g of the sample was mixed with sterilized distilled water and incubated at 4 °C after thorough shaking. The resulting solution was then filtered through four layers of cheesecloth. The pH value of the silage extract was measured using a calibrated glass electrode pH meter (STARTED 100/B, OHAUS, Shanghai, China).

The concentrations of lactic acid (LA), acetic acid (AA), propionic acid (PA), and butyric acid (BA) were quantitatively determined using liquid chromatography, following the method described by You et al. [13].Additionally, the ammonia nitrogen (NH3-N) concentration was measured using the phenol-hypochlorite method as outlined by Broderick and Kang [14].For the analysis of microbial populations, 10 g of the silage sample was thoroughly mixed with 90 ml of sterilized distilled water, and the resulting mixture was then filtered. To perform microbial counting, a 10-fold serial dilution was carried out using 1 ml of the solution.The counting of lactic acid bacteria (LAB) was conducted by placing the plates on De Man Rogosa Sharpe agar in an anaerobic chamber (C-31, Mitsubishi Gas Chemical Co., Tokyo, Japan) and incubating them at 37 °C for 48 h. Enumeration of coliform bacteria was achieved by incubating the plates (violet red bile agar) at 37 °C for 48 h. As for yeast and mold counting, the corresponding plates (potato dextrose agar) were placed in a regular incubator (Gp-01, Huangshi Hengfeng Medical Equipment Co., Ltd., Huangshi, China) under aerobic conditions and incubated at 30 °C for 48 h, following the method described by Fu et al. [15] .The colony-forming units (cfu) were expressed as the logarithm of the fresh material (FM).

Sequencing and analysis of microbial population

Commercial sample DNA extraction kits, E.Z.N.A. R (Omega Bio-tek, Norcross, GA, USA), were utilized for the extraction of total DNA from both the raw alfalfa samples and silage feed samples. Subsequently, the concentration and purity of the extracted DNA were assessed using a NanoDrop 2000 UV-Vis spectrophotometer (Thermo Fisher Scientific, Wilmington, United States).For PCR amplification, the V3-V4 region of the 16S rDNA was targeted, employing the followingprimers:338F: 5’-ACTCCTACGGGGGAGGCAGCAG-3’ and 806R: 5’-GGACTACHVGGGTWTCTAAT-3’. The PCR amplification process was carried out by Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China).To ensure data quality, the raw fastq files underwent quality filtering using Trimmomatic, followed by merging using FLASH. Operational taxonomic units (OTUs) were clustered using UpARSE, and chimeric sequences were identified and subsequently removed using UCHIME.Finally, the RDp classifier algorithm was employed to analyze the 16 S rRNA gene sequences against the Silva (SSU123) 16 S rRNA database, utilizing a confidence threshold of 70% for classifying each sequence.The range of numbers of raw sequence reads control is 48,708–89,659, and clean sequence reads control is 48,013–88,398.

Statistical analysis

The chemical composition, fermentation quality, and microbial characteristics of the silage feed were analyzed using the two-factor analysis program in SAS version 9.2. To determine significant differences, Tukey’s test was employed, with a significance level of p < 0.05. The reported data values represent the average values and standard errors of the means obtained from different treatments. For the analysis of microbial community data, the Majorbio I-Sanger Cloud platform, an online platform, was utilized (https://www.majorbio.com/).

Results

Chemical and microbial composition of fresh alfalfa samples

Table 1 presents the chemical composition and microbial population of the alfalfa raw samples prior to ensiling. The DM content was determined to be 427.5 g/kg DM, while the WSC content was measured at 15.9 g/kg DM. Furthermore, the CP, NDF, and ADF contents were found to be 205.2 g/kg DM, 382.9 g/kg DM, and 313.0 g/kg DM, respectively. Regarding the microbial population, the counts of lactic acid bacteria, aerobic bacteria, coliform bacteria, yeast, and mold on the raw samples were recorded as 5.41, 6.33, 2.77, 5.96, and 3.16 log10 colony-forming units (cfu) per gram of fresh material (FM), respectively.

Table 1 Nutrient content and microbial population of alfalfa fresh materials
Full size table

Chemical composition and fermentation quality analysis of alfalfa silage

The chemical characteristics of alfalfa silage fermented for 60 days at different temperatures and densities are shown in Table 2. Temperature had no significant effect on DM content in silage (p > 0.05). Density had significant effect on DM content (p < 0.001). Under high temperature conditions, DM content decreased with the increase of density. Temperature and density had no significant effect on CP content. In our study, when fermentation was carried out at room temperature, CP content was higher when the density was 500 kg/m3. The content of CP was higher when the density was 600 kg/m³ during fermentation at high temperature. Both temperature and density had significant effects on ADF content (p < 0.01). No matter the fermentation at high temperature or normal temperature, the concentration of 600 kg/m3 had the lowest ADF content. Temperature had a significant effect on NDF content (p < 0.01), density had a significant effect on WSC content (p < 0.05). The pH value of fermentation at high temperature is higher than that of fermentation at room temperature. The content of LA decreased with the increase of density, regardless of whether the fermentation was carried out at high temperature or room temperature. The interaction of temperature and density had significant effect on the content of lactic acid bacteria and aerobic bacteria (p < 0.05).

Table 2 Effects of different temperatures and density on the chemical composition, fermentation quality, and microbial composition of alfalfa silage after a 60-day period
Full size table

Microbial diversity of alfalfa raw samples and silage feed

Table 3 illustrates the results of second-generation sequencing of the full-length 16 S rRNA gene conducted on both the alfalfa fresh material and silage feed. The sequencing coverage for all samples exceeded 99%, indicating that the sequencing depth adequately captured the representation of the bacterial community, enabling effective analysis of bacterial community diversity. Comparing the results to the alfalfa raw samples, the ace, chao1, shannon, and sobs values of the feed after ensiling exhibited a decrease. Specifically, the ace values ranged between 102.24 and 184.05, the chao1 values ranged from 94.36 to 102.20, the shannon values ranged from 0.63 to 0.89, and the sobs values ranged from 64.00 to 103.00.

Table 3 Alpha-diversity of bacterial communities in alfalfa fresh materials and silage
Full size table

Microbial diversity analysis was performed using principal Coordinate Analysis (PCoA) to examine variations between individuals or populations. Each data point represents a sample, and points of the same color correspond to the same group. The proximity between two points indicates the similarity in their community composition. Figure 1 A demonstrates that no significant separation was observed among the bacterial communities of the alfalfa raw samples. However, clear separation occurred after ensiling. In comparison to fermentation under normal temperature conditions, microbial community separation was less pronounced in the feed subjected to high-temperature fermentation. In Fig. 1B, bacterial community separation was observed in all treatment groups after ensiling, except for treatment group C500. Notably, when the stacking density reached 600 kg/m3, a distinct separation was observed between bacterial communities under both high-temperature and normal temperature conditions.

Fig. 1
figure 1

Principal coordinate analysis (PCoA) plot illustrating the variations in bacterial community structure among different temperature and density treatments. (A), the changes of bacterial community structure between the high-temperature treatment group, the normal temperature treatment group and the original sample; (B), changes in bacterial community structure among treatment groups of different densities at different temperatures. Y: fresh material; G: All treatment groups for outdoor high temperature fermentation; C: All treatment groups fermented at room temperature; C500:room temperature treatment group with a density of 500 kg/m3; C600: room temperature treatment group with a density of 600 kg/m3; C700: room temperature treatment group with a density of 700 kg/m3; G500: high temperature treatment group with a density of 500 kg/m3; G600:high temperature treatment group with a density of 600 kg/m³; G700: high temperature treatment group with a density of 700 kg/m3

Full size image

Composition and variation of bacterial community in alfalfa silage feed

The dynamics of bacterial community composition at the genus level in alfalfa raw samples and silage feed, subjected to different temperature and additive treatments, as revealed by microbial second-generation sequencing, are depicted in Fig. 2A. In the alfalfa raw samples, the major genera identified were unclassified_d_Bacteria (41.88%) and others (18.10%), with the predominant genus being Citrobacter (17.27%), accompanied by a small proportion of Lactobacillus (0.67%). Following ensiling, the dominant genus across all treatment groups was Lactobacillus (G500: 96.61%; C500: 97.52%; G600: 97.07%; C600: 89.56%; G700: 98.10%; C700: 98.27%). Figure 2B presents the dynamics of bacterial community composition at the species level between the alfalfa raw samples and silage feed (Fig. 2B) .In the alfalfa raw samples, the main species identified were bacterium (27.02%) and others (19.98%). Additionally, Citrobacter_sp. accounted for 17.21%, while Lactiplantibacillus plantarum represented 0.40% of the species composition. After ensiling fermentation, the major species in all treatment groups were Lactiplantibacillus plantarum and Lentilactobacillus buchneri. Notably, in the silage feed fermented under high temperature conditions, the content of Lactiplantibacillus plantarum was lower compared to that fermented under normal temperature conditions. Moreover, an increasing stacking density demonstrated a decreasing trend in the content of Lactiplantibacillus plantarum. However, the lowest content of Lactiplantibacillus plantarum was observed when the stacking density reached 600 kg/m³ under high-temperature conditions. The dynamic bacterial community evolution in fresh alfalfa material and silage at the door level is shown in Fig. 3. Among the original alfalfa, the dominant phylum unclassified_d_Bacteria (42%) and Proteobacteria (37%) are the dominant obacteria. However, Firmicutes were predominant in all treatment groups after silage (G500,98%; C500,98%; G600,97%; C600,91%; G700, 99%; C700,99%).

Fig. 2
figure 2

The bacterial community composition at the genus (A) and species (B) levels in fresh alfalfa samples and alfalfa silage feed was determined using microbial amplicon sequencing. Y: Fresh materials; C500:room temperature treatment group with a density of 500 kg/m3; C600: room temperature treatment group with a density of 600 kg/m3; C700: room temperature treatment group with a density of 700 kg/m3; G500: high temperature treatment group with a density of 500 kg/m3; G600:high temperature treatment group with a density of 600 kg/m3; G700: high temperature treatment group with a density of 700 kg/m3

Full size image
Fig. 3
figure 3

The circos plot displayed the variations in relative abundance of microbial communities at the phylum level, where the size of each bar represented the relative abundance of that phylum in the samples

Full size image

Relationship between chemical composition, fermentation quality, and bacterial community

Correlation analysis was conducted to depict the relationship between the chemical composition, fermentation parameters, and major fermentation products at the genus level (Fig. 4). The results are presented as follows: DM exhibited a positive correlation with Clostridium and Coprococcus. CP displayed positive correlations with Pseudoclavibacter, Microbacterium, Agrococcus, Massilia, Lysobacter, and Brevundimonas. Similarly, NDF and ADF were found to have negative correlations with Frigoribacterium, Agrobacterium, Microbacterium, Coprococcus, and Weissella, while showing positive correlations with Pediococcus. WSC demonstrated a positive correlation specifically with Weissella. pH values exhibited a positive correlation with Lactococcus and Leucobacter, while displaying negative correlations with Coprococcus, Rhabdanaerobium, Weissella, and Curtobacterium. LA showed negative correlations with Pseudomonas and Frigoribacterium. AA displayed a positive correlation with Rhabdanaerobium, while having a negative correlation with Pediococcus. PA demonstrated positive correlations with Rhabdanaerobium and Weissella, while exhibiting negative correlations with Rhodococcus_f_Nocardiaceae and Salana.

Fig. 4
figure 4

A correlation heat map was drawn by the correlation coefficients between the dominant microorganisms of topN and environmental factors, effectively illustrating the complex relationship between chemical composition, fermentation quality and bacterial community. The heat map uses a color scheme, with red indicating positive correlation and blue indicating negative correlation. The significance level is shown as follows: *p ≤ 0.05; P * * 0.01 or less; ***p ≤ 0.001. In the Spearman correlation heatmap, the range of values reflects the strength and direction of the monotonic relationship between two variables. 0 to 0.5: These values still indicate a positive correlation, but the relationship is weak. The closer the value is to 0, the weaker the correlation. 0: A value of 0 means there is no monotonic relationship between the two variables. This does not imply there is no relationship at all; rather, if a relationship exists, it is not monotonic. -0.5 to 0: This range indicates a weak to moderate negative monotonic relationship. As one variable increases, the other tends to decrease, but the relationship is not very strong. -1 to -0.5: This range shows a strong negative monotonic relationship. Values close to -1.0 indicate a very strong negative correlation, meaning that as one variable increases, the other decreases significantly

Full size image

Discussion

Chemical composition and fermentation quality analysis of alfalfa silage

The presence of lactic acid bacteria (LAB) on the raw material plays a crucial role in silage fermentation [16]. previous studies have indicated that the minimum LAB count on the raw material should exceed 5.0 log10cfu per gram of fresh matter. In this study, the LAB count on the alfalfa material was 5.41 log10cfu per gram FM, meeting this requirement. Soluble carbohydrates are important energy sources for plant development and metabolism [3]. As expected, the content of WSC decreased after ensiling, primarily due to the conversion of soluble carbohydrates into lactic acid by microorganisms as fermentation substrates under anaerobic conditions [13]. Under ambient temperature conditions, DM content has been found to be negatively correlated with density, which is consistent with the study by Ruppel et al. [17]. However, previous studies have shown that silage with higher density exhibited higher DM recovery rates compared to silage with lower density [18], which contradicts the findings of this study. The discrepancy may be attributed to differences in forage species, ensiling methods, and densities used in the respective studies. Temperature and density did not influence the CP content in this study, which aligns with previous research [19]. This may be because CP content is not directly affected by fermentation but instead increases linearly with the increase of gas and effluent losses during ensiling [20]. The NDF content was significantly higher in the high-density treatment group (700 kg/m3) compared to the low-density treatment groups (500 kg/m3 and 600 kg/m3), which is inconsistent with the findings of Sun et al. [21]. The variation in the raw material variety used could explain this discrepancy.

In practical silage production, fermentation temperature fluctuates daily, which affects the fermentation process. previous studies have found correlations between the daily fluctuation of fermentation temperature in silage experiments and external conditions [22]. In this study, the high-temperature treatment group experienced temperature fluctuations, which had a negative impact on silage fermentation quality. Experimental results showed that the acetic acid and butyric acid content in the high-temperature treatment group were relatively higher, further confirming the negative effect of temperature fluctuations on the silage fermentation process. The pH value is a fundamental indicator for evaluating the fermentation quality of silage, and a sufficient number of lactic acid bacteria are required to lower the pH value and obtain high-quality silage [23]. previous studies have shown that higher packing density results in higher heat capacity and fermentation temperature, effectively reducing silage pH [24]. However, in this study, while the pH value decreased due to temperature, its relationship with density was not significant.Previous research has found that silage with a density of 800 g/L preserves well and has lower NH3-N content [26]. This differs somewhat from our study, where the lowest NH3-N content was observed at a density of 600 kg/m3. We believe this discrepancy might be related to the fermentation environment temperature. Higher temperatures during the fermentation process could lead to excessive protein degradation, resulting in an increase in NH3-N content.

Analysis of microbial community diversity in alfalfa silage

In this investigation, the alpha-diversity of fresh alfalfa material was found to be significantly higher, signifying elevated bacterial richness and diversity compared to silage. This observation is attributed to the prevailing fermentation activity of lactic acid bacteria in acidic and anaerobic conditions. Concurrently, aerobic microorganisms associated with alfalfa struggled to thrive in anaerobic environments, resulting in a reduction in their abundance [27]. The predominant phyla identified in alfalfa fresh material were unclassified_d_Bacteria and Proteobacteria, with Proteobacteria emerging as the largest phylum among bacteria. However, post-fermentation, a noteworthy transition in the population structure of alfalfa occurred, shifting from the dominant phylum Proteobacteria to Firmicutes. Research suggests that this transformation is linked to LAB fermentation, particularly the homofermentative type [28]. Homofermentative LAB are recognized as favorable during ensiling, producing two moles of lactic acid from each mole of fermented glucose, in contrast to heterofermentative LAB, which generate one mole of lactic acid, one mole of carbon dioxide, and one mole of ethanol or acetic acid [29]. Among Firmicutes, Lactobacillus had the largest increase. Although lactic acid bacteria produce lactic acid under anaerobic conditions, Lentilactobacillus buchneri. has shown the ability to convert lactic acid to acetic acid under aerobic conditions [30].

In the context of this study, when the stacking density reached 600 kg/m3, regardless of whether fermentation occurred at room temperature or high temperature, the lactic acid content was observed to be low, while the acetic acid content was high. Despite the decrease in lactic acid content, the generated acetic acid played a crucial role in lowering the pH in the fermentation environment, thereby inhibiting the proliferation of harmful microorganisms. Typically, ensiled forage treated with microbial inoculants exhibits higher abundance of lactic acid bacteria [31]. In this study, the lactic acid bacteria content in alfalfa fresh material was merely 0.4%, whereas the bacterial content of the Enterobacter genus was relatively high. Studies indicate that Enterobacter is a bacterium with higher content in non-inoculated microbial additive silage [32]. The primary bacteria identified in each treatment group were Lactiplantibacillus plantarum and Lentilactobacillus buchneri, a consequence of the inclusion of lactic acid bacteria additives. However, the content of Lactiplantibacillus plantarum in silage decreased with stacking density, which may be due to the high density limiting its growth and reproduction.Furthermore, when alfalfa underwent ensiling fermentation at different temperatures, the content of Lactiplantibacillus plantarum in the high-temperature treatment group was lower than that in the room temperature treatment group.Citrobacter is facultative anaerobic bacteria, and the abundance of Citrobacter in the C600 treatment group was higher than that in the C500 and C700 treatment groups, which may be due to the decline in the abundance of Lactiplantibacillus plantarum and Lentilactobacillus buchneri, so that Citrobacter can use fermentation substrate for growth and propagation.Previous studies have shown that the content of lactic acid bacteria in silage treated with high density is higher. The possible reason is that the increase in packaging density reduces the oxygen permeability of the silage surface, leading to rapid depletion of oxygen in the initial silo and inhibiting the activity of aerobic bacteria. To enable bacteria that can survive under anaerobic conditions to grow and reproduce [21]. The number of yeast in alfalfa silage fermented at high temperatures was higher than that in the ambient temperature treatment group. Previous research has found that the optimal temperature for yeast growth is around 30 °C [33]. In our study, the average fermentation temperature of the high-temperature treatment group was between 25 and 35 °C, which partly explains the higher yeast count in the high-temperature treatment group compared to the ambient temperature group.

Relationship between microbial communities and quality indicators

The factors influencing microbial communities in ensiled forage are diverse, encompassing moisture, WSC, and various chemical components. Microorganisms, generating a range of metabolic byproducts, profoundly impact the quality of ensiled forage. For instance, lactic acid bacteria assume a pivotal role in lactic acid generation, while Enterobacter can ferment lactic acid, yielding acetic acid [34]. Research findings underscore that the manipulation of bacterial communities in ensiled forage can effectively alter its nutritional, aromatic, and flavor-related chemical composition [35].Studies have shown that the silage with a density of 650 kg/m3 has good fermentation quality [36].When the silage density was higher than 600 g/L, the fermentation quality and aerobic stability of straw could be effectively improved [37]. The reason for the difference between the above results and this experiment is the characteristics of varieties, and the suitable silage density of different varieties is different.

Moreover, the relative abundance of bacteria exhibits crucial correlations with the ultimate fermentation products. In this study, a correlation analysis based on post-ensiling fermentation product content and microbial population composition unveiled a positive correlation between pH and Lactococcus. This suggests that Lactococcus encounters challenges in flourishing in low-pH environments, with Lactococcus lactis displaying low acidity tolerance and restricted growth when the pH falls below 4.8 [38]. Conversely, a negative correlation was discerned between pH and Weissella. As Weissella ferments glucose, producing acid, an elevation in Weissella abundance results in ample acid production, consequently inducing a pH decrease [16]. LA demonstrated a negative correlation with Pseudomonas and Frigoribacterium, both categorized as aerobic microorganisms [39]. Residual oxygen in the fermentation environment hampers lactic acid production by lactic acid bacteria while fostering the growth of Pseudomonas and Frigoribacterium.

Conclusion

In this investigation, the silage fermentation of alfalfa was scrutinized. When the stacking density exceeded 600 kg/m³, there was a significant decrease in the levels of DM and CP, coupled with a significant increase in the content of ADF and NDF. This indicates that high stacking density may negatively impact the nutritional quality of silage. As the density increased, there was a discernible downward trend in the abundance of Lactiplantibacillus plantarum. Concurrently, temperature exerted a notable impact on the ensiled alfalfa feed, resulting in a conspicuous reduction in the content of Lactiplantibacillus plantarum during the fermentation process under high-temperature conditions.The interaction of temperature and density had great influence on the contents of ADF, lactic acid bacteria and aerobic bacteria in silage.To sum up, from the actual production considerations, the density of alfalfa silage should be maintained at about 600 kg/m3 during silage to obtain the best results.This study covers only one year of experimental results, and we recognize that independent experiments may not capture all potential variables. Future research should explore diverse experiments, including different years, temperature conditions, fields, and varieties. In addition, it is an important direction for future research to study the influence of external temperature fluctuation on fermentation and aerobic stability. Incorporating these factors into the study design will provide a more complete understanding of silage characteristics and provide valuable insights into related research areas.

Data availability

Sequencing data for 16 S rRNA gene sequence were stored in NCBI (https://www.ncbi.nlm.nih.gov/) with BioProject accession number PRJNA1099422.

References

  1. Xu D, Ding W, Ke W, Li F, Zhang p, Guo X. Modulation of metabolome and bacterial community in whole crop corn silage by inoculating homofermentative lactiplantibacillus plantarum and heterofermentative Lactobacillus buchneri. Front Microbiol 2019;9.

  2. Liu M, Wang Y, Wang Z, Bao J, Zhao M, Ge G, Du S. Effects of isolated LAB on Chemical Composition, Fermentation Quality and Bacterial Community of Stipa grandis Silage. Microorganisms. 2022;10(12). https://doi.org/10.3390/microorganisms10122463.

  3. Wang S, Dong Z, Li J, Chen L, Shao T. Effects of storage temperature and combined microbial inoculants on fermentation end products and microbial populations of Italian ryegrass (Lolium multiflorum Lam.) Silage. J Appl Microbiol. 2018;125(6), 1682–1691.

  4. Adesogan AT. Factors affecting corn silage quality in hot and humid climates. Florida Ruminant Nutrition Symposium. 2006.

  5. Zhou Y, Drouin p, Lafrenière C. Effect of temperature (5–25°C) on epiphytic lactic acid bacteria populations and fermentation of whole-plant corn silage. J Appl Microbiol. 2016;121(3):657–71. https://doi.org/10.1111/jam.13198.

    Article  CAS  PubMed  Google Scholar 

  6. Li F, Ding Z, Ke W, Xu D, Zhang p, Bai J, Guo X. Ferulic acid esterase-producing lactic acid bacteria and cellulase pretreatments of corn stalk silage at two different temperatures: ensiling characteristics, carbohydrates composition and enzymatic saccharification. Bioresour Technol. 2019;282:211–21.

    Article  CAS  PubMed  Google Scholar 

  7. Kim SC, Adesogan AT. Influence of Ensiling temperature, simulated rainfall, and delayed sealing on fermentation characteristics and Aerobic Stability of Corn Silage. J Dairy Sci. 2006;89(8):3122–32.

    Article  CAS  PubMed  Google Scholar 

  8. Jonsson A. Role of yeasts and Clostridia in Silage Deterioration. Identification and Ecology; 1989.

  9. Driehuis F, Elferink SJWHO. The impact of the quality of silage on animal health and food safety: a review. Vet Q. 2000;22(4):212–6.

    Article  CAS  PubMed  Google Scholar 

  10. Anésio AHC, Santos MV, da Silva LD, Silveira RR, Braz TGS, pereira RC. Effects of ensiling density on chemical and microbiological characteristics of sorghum silage. J Anim Feed Sci. 2017. https://doi.org/10.22358/jafs/69270/2017.

    Article  Google Scholar 

  11. Zhang Q, Wu B, Nishino N, Wang X, Yu Z. Fermentation and microbial population dynamics during the ensiling of native grass and subsequent exposure to air. Anim Sci J. 2016;87(3):389–97. https://doi.org/10.1111/asj.12427.

    Article  CAS  PubMed  Google Scholar 

  12. Thomas TA. (1977). An Automated procedure For The Determination Of Soluble Carbohydrate In Herbage.

  13. You S, Du S, Ge G, Wan T, Jia Y. Selection of lactic acid bacteria from native grass silage and its effects as inoculant on silage fermentation. Agronomy J. 2021.

  14. Broderick GA, Kang JH. Automated simultaneous determination of ammonia and amino acids in ruminal fluids and in vitro media. J Dairy Sci. 1980;80:2964–71.

    Article  Google Scholar 

  15. Fu Z, Sun L, Hou M, Hao J, Lu Q, Liu T, Ge G. Effects of different harvest frequencies on microbial community and metabolomic properties of annual ryegrass silage. Front Microbiol. 2022;13. https://doi.org/10.3389/fmicb.2022.971449.

  16. Cai YM, Benno Y, Ogawa MOS, Kumal S, Nakase T. Influence of Lactobacillus spp. from an inoculant and of weissella and Leuconostoc spp. from forage crops on silage fermentation. App Environ Microbiol. Aug,1998;1998:2982–2987.

  17. Ruppel RA, pitt RE, Chase LE. Bunker silo management and its relationship to forage preservation on dairy farms. J Dairy Sci. 1995;78(1):141–153.

  18. Sucu E, Kalkan H, Canbolat O, Filya I. Effects of ensiling density on nutritive value of maize and sorghum silages. Revista Brasileira De Zootecnia. 2016;45(10):596–603. https://doi.org/10.1590/s1806-92902016001000003.

    Article  Google Scholar 

  19. Han KJ, Collins M, Vanzant ES, Dougherty CT. Bale density and moisture effects on alfalfa round bale silage. Crop Sci. 2004;44:914–919.

  20. Li p, Gou W, Zhang Y, Yang F, You M, Bai S, Shen Y. Fluctuant storage temperature increased the heterogeneous distributions of pH and fermentation products in large round bale silage. Grassl Sci. 2019;65(3):155–61. https://doi.org/10.1111/grs.12232.

    Article  CAS  Google Scholar 

  21. Sun L, Na N, Li X, Li Z, Wang C, Wu X, Yang F. Impact of packing density on the bacterial community, fermentation, and in vitro digestibility of whole-crop barley silage. Agriculture. 2021;11(7). https://doi.org/10.3390/agriculture11070672.

  22. Green O, Bartzanas T, Løkke MM, Bochtis DD, Sørensen CG, Jørgensen OJ, Tortajada VG. Spatial and temporal variation of temperature and oxygen concentration inside silage stacks. Biosyst Eng. 2012;111(2):155–65. https://doi.org/10.1016/j.biosystemseng.2011.11.008.

    Article  Google Scholar 

  23. Ke-Li L, Ju-Lin G, Shu-Guo LU. Studies on characteristics of silage production of different types maize. J Maize Sci. 2004.

  24. Williams AG, Lowe JF, Rees DV. (1994).The effect of oxygen concentration on changes in the microhial population, temperature and dry-matter content in grass silage.Grass and Forage Science (1994) Volume 49, 183–191.

  25. Muller CE. Fermentation patterns of small-bale silage and haylage produced as a feed for horses. Grass Forage Sci. 2005;60:109–18.

    Article  Google Scholar 

  26. Liu H, Li X, Yang F, Hu J, Jia Y, Shao T. Effects of ensiling density on the fermentation profile and aerobic stability of wilted alfalfa silage. Agronomy. 2024;14(6). https://doi.org/10.3390/agronomy14061143.

  27. Yuan X, Dong Z, Li J, Shao T. Microbial community dynamics and their contributions to organic acid production during the early stage of the ensiling of Napier grass (pennisetum purpureum). Grass Forage Sci. 2019;75(1):37–44. https://doi.org/10.1111/gfs.12455.

    Article  CAS  Google Scholar 

  28. McGarvey JA, Franco RB, palumbo JD, Hnasko R, Stanker L, Mitloehner FM. Bacterial population dynamics during the ensiling of Medicago sativa(alfalfa) and subsequent exposure to air. J Appl Microbiol. 2013;114(6):1661–70. https://doi.org/10.1111/jam.12179.

    Article  CAS  PubMed  Google Scholar 

  29. Muck RE. Silage microbiology and its control through additives. Revista Brasileira De Zootecnia. 2010;2010(supl. especial):183–191.

  30. Oude Elferink SJWH, Krooneman J, Gottschal JC, Spoelstra SF, Faber F, Driehuis F. Anaerobic conversion of lactic acid to acetic acid and 1,2-propanediol by Lactobacillus buchneri. Appl Environ Microbiol. 2001;67(1):125–32. https://doi.org/10.1128/aem.67.1.125-132.2001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pang H, Qin G, Tan Z, Li Z, Wang Y, Cai Y. Natural populations of lactic acid bacteria associated with silage fermentation as determined by phenotype, 16S ribosomal RNA and recA gene analysis. Syst Appl Microbiol. 2011;34(3):235–41. https://doi.org/10.1016/j.syapm.2010.10.003.

    Article  CAS  PubMed  Google Scholar 

  32. Du Z, Sun L, Chen C, Lin J, Yang F, Cai Y. Exploring microbial community structure and metabolic gene clusters during silage fermentation of paper mulberry, a high-protein woody plant. Anim Feed Sci Technol. 2021;275. https://doi.org/10.1016/j.anifeedsci.2020.114766.

  33. Dong Z, Yuan X, Wen A, Desta ST, Shao T. Effects of calcium propionate on the fermentation quality and aerobic stability of alfalfa silage. Asian-Australasian J Anim Sci. 2017;30(9):1278–84. https://doi.org/10.5713/ajas.16.0956.

    Article  CAS  Google Scholar 

  34. Guan H, Yan Y, Li X, Li X, Shuai Y, Feng G, Zhang X. Microbial communities and natural fermentation of corn silages prepared with farm bunker-silo in Southwest China. Bioresour Technol. 2018;265:282–90. https://doi.org/10.1016/j.biortech.2018.06.018.

    Article  CAS  PubMed  Google Scholar 

  35. He Q, Zhou W, Chen X, Zhang Q. Chemical and bacterial composition of Broussonetia papyrifera leaves ensiled at two ensiling densities with or without lactiplantibacillus plantarum. J Clean Prod. 2021;329. https://doi.org/10.1016/j.jclepro.2021.129792.

  36. Bai C, Pan G, Leng R, Ni W, Yang J, Sun J, Xue Y. Effect of ensiling density and storage temperature on fermentation quality, bacterial community, and nitrate concentration of Sorghum-Sudangrass Silage. Front Microbiol. 2022;13. https://doi.org/10.3389/fmicb.2022.828320.

  37. Liu H, Li X, Hu J, Zhao J, Xu G, Dong D, Shao T. Fermentation quality and aerobic stability evaluation of rice straw silage with different ensiling densities. Fermentation. 2023;10(1). https://doi.org/10.3390/fermentation10010020.

  38. Ávila CLS, Carvalho BF. Silage fermentation—updates focusing on the performance of micro-organisms. J Appl Microbiol. 2019;128(4):966–84. https://doi.org/10.1111/jam.14450.

    Article  PubMed  Google Scholar 

  39. Kampfer K, Rainey FA, Andersson MA, Lassila ELN, Ulrych U, Busse HJ, Weiss N, Mikkola R. Frigoribacterium faeni gen. nov., sp. nov., a novel psychrophilic genus of the family Microbacteriaceae. Int J Syst Evolutionary Microbiol. 2000;50:355–63.

    Article  CAS  Google Scholar 

  40. Ogunade IM, Jiang Y, pech Cervantes AA, Kim DH, Oliveira AS, Vyas D, Adesogan AT. Bacterial diversity and composition of alfalfa silage as analyzed by Illumina MiSeq sequencing: effects of Escherichia coli O157:H7 and silage additives. J Dairy Sci. 2018;101(3):2048–59. https://doi.org/10.3168/jds.2017-12876.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We sincerely appreciate the careful review of our manuscript by the editors and reviewers, as well as the valuable feedback they provided. Their expertise and patient guidance have been crucial in supporting our research efforts.

Funding

This work was financially supported by the Inner Mongolia Autonomous Region Science and Technology Plan (No. 2021GG0109).

Author information

Authors and Affiliations

  1. College of Grassland Resources and Environment, Inner Mongolia Agricultural University, Hohhot, 010019, China

    Jingyi Liu, Junfeng Hao, Muqier Zhao, Xingquan Yan, Yushan Jia, Zhijun Wang & Gentu Ge

  2. Key Laboratory of Forage Cultivation, Processing and High Efficient Utilization of Ministry of Agriculture and Rural Affairs, Hohhot, 010019, China

    Jingyi Liu, Junfeng Hao, Muqier Zhao, Xingquan Yan, Yushan Jia, Zhijun Wang & Gentu Ge

  3. Key Laboratory of Grassland Resources, Ministry of Education, Hohhot, 010019, China

    Jingyi Liu, Junfeng Hao, Muqier Zhao, Xingquan Yan, Yushan Jia, Zhijun Wang & Gentu Ge

Authors
  1. Jingyi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Junfeng Hao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Muqier Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xingquan Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yushan Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhijun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gentu Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J. L.: Methodology, Conceptualization, Validation, Formal analysis, Writing-Original Draft, Writing-Review & Editing. J. H.: Methodology, Validation, Formal analysis. M. Z.: Conceptualization, Investigation, Supervision, Writing-Review & Editing, Resources, Methodology. X. Y.: Methodology, Writing-Review & Editing. Y. J. and Z. W.: Methodology & Editing. G. G.: Methodology, Conceptualization, Validation, Writing-Original Draft, Writing-Review & Editing, Supervision, Project administration, Funding acquisition.

Corresponding author

Correspondence to Gentu Ge.

Ethics declarations

Ethics approval and consent to participate

The samples of this study were from the experimental planting base of Grassland and Resources and Environment College of Inner Mongolia Agricultural University. The research complied with all relevant institutional, national and international guidelines and was licensed by the College of Grassland and Resources and Environment, Inner Mongolia Agricultural University.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Hao, J., Zhao, M. et al. Effects of different temperature and density on quality and microbial population of wilted alfalfa silage. BMC Microbiol 24, 380 (2024). https://doi.org/10.1186/s12866-024-03510-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12866-024-03510-2

Keywords

BMC Microbiology

ISSN: 1471-2180

Contact us