1. Introduction
In recent years, under the policy of switching from grain crops to feed crops by the Ministry of Agriculture and Rural Affairs of China, the area of alfalfa fields in Inner Mongolia has been growing year by year. There are two common approaches to utilizing alfalfa in animal husbandry production: hay preparation and ensiling. However, hay preparation is susceptible to nutrient loss caused by rainfall, leaf shedding, and mold contamination. Ensiling is a method of preserving the nutritional properties of green fodder for a long time by using the fermentation of lactic acid bacteria to produce large amounts of lactic acid, which makes the fodder acidic, thus inhibiting the growth of harmful bacteria under sealed conditions. Silage not only retains the maximum amount of nutrients in the raw material, but also has good palatability. The fermentation process relies on lactic acid bacteria (LAB) to produce organic acids from water-soluble carbohydrates (WSCs), lowering the pH and thus achieving long-term preservation.
Most current research on silage has focused on low-moisture (wilted) silage. However, the wilting process is often subject to interference by factors such as rainfall, which causes difficulties in storage and transportation [1]. In contrast, ensiling saves a lot of time and reduces economic costs and labor because the silage can be stored without drying. However, harmful bacteria such as Clostridium spp. proliferate when silage is prepared at high moisture levels, and these bacteria not only compete with LAB for the fermentation substrate, but also decompose and utilize protein, metabolizing it to ammonia and biogenic amines [1]. If the proliferation of Clostridium spp. cannot be inhibited at the early stage of fermentation, the silage will be highly susceptible to anaerobic spoilage [2]. Since Clostridium spp. are intolerant of even low pH, their fermentation can be minimized by adding LAB to the raw material to increase the amount of LAB at the beginning of fermentation and induce the rapid production of LA [3].
It is difficult to ensile alfalfa due to its high buffering capacity and low WSC content [4], and thus it requires supplementation with exogenous WSC. Corn flour has a high maize content and is an ideal fermentation enhancer [5]. The addition of corn flour not only increases the WSC content of silage, but also reduces the water content and thus improves the silage quality. Although corn meal can make up for the deficiencies caused by ensiling alfalfa alone, excess corn meal can lead to a decrease in the nutritional value of the mixed silage due to its low crude protein (CP) content, so the selection of an appropriate ratio is critical. Since the silage fermentation process is highly dependent on interactions among multiple bacteria and the bacterial community is closely related to the fermentation quality, it is necessary to analyze the changes in fermentation characteristics and microbial composition during the silage process in order to understand the process and improve the quality [6].
Therefore, in this experiment, a composite additive containing LAB and corn flour or sucrose was added to alfalfa silage to compare its fermentation quality, nutritional value, and microbial diversity, and to initially investigate the microbial change pattern in high-moisture alfalfa silage. In addition, with the help of LAB and corn flour or sucrose, the high-moisture alfalfa ensilage process was optimized to provide a theoretical basis for an efficient silage processing system.
2. Materials and Methods
2.1. Experimental Materials
The alfalfa (cultivar Biaoba) used in this experiment was mowed on 2 September 2019, at the first flowering of the third crop. The alfalfa field was located at the research base of the Bayannur Institute of Agriculture and Animal Husbandry Science, Inner Mongolia Autonomous Region (107°29’ E, 40°80’ N), with an average annual temperature of 3.7–7.6 °C, 3100–3300 h of sunshine, a frost-free period of 126 d, and an average precipitation of 188 mm. The basic conditions of soil nutrients at 0–20 cm depth in the base were: pH 8.50, organic matter 18.00 g/kg, total nitrogen 0.92 g/kg, alkaline nitrogen 102.00 mg/kg, available potassium 140.00 mg/kg, and available phosphorus 32.80 mg/kg. Zonglamet silage inoculant was used as the LAB source; its ingredients are Lactobacillus plantarum ≥ 1.3 × 1010 CFU/g and Lactobacillus brucei ≥ 7 × 109 CFU/g. The corn flour was purchased from the Rongqin Agricultural Store in Hohhot.
2.2. Silage Preparation
Freshly mown alfalfa grass was chopped to about 2 cm using a hand straw cutter. The nutrient composition and bacterial community of the alfalfa and corn meal before silage are shown in Table 1 and Figure 1. There were four groups in the experiment: CK, S (0.01 g/kg LAB + 2% sucrose), C5 (0.01 g/kg LAB + 5% corn flour), and C10 (0.01 g/kg LAB + 10% corn flour). In groups C5 and C10, 190 and 180 g of alfalfa were taken in trays and sprayed with Lactobacillus spp., and 10 and 20 g of corn flour was then added, respectively. These were mixed well by hand and placed in 200 g polyethylene vacuum packing bags (size 20 × 25 cm), vacuum sealed, and stored at room temperature, and there were five replicates for each treatment. After 60 d of silage, three bags were randomly taken and opened to test their nutrient content, fermentation quality, and microbial diversity.
2.3. Silage Chemical Composition Analysis
2.3.1. pH, Organic Acids, and Ammonia-N
For this analysis, 20 g of silage was placed into a beaker with 180 mL of water and sealed using sealing film. The extracts were placed in a refrigerator at 4 °C for 24 h and then removed and filtered through 4 layers of gauze and qualitative filter paper to obtain the extracts. The pH of the resulting extracts was determined using a portable pH meter (LAQUAtwin, HORIBA, Kyoto, Japan). Ammoniacal nitrogen (NH3-N) content was determined by the phenol hypochlorite colorimetric method [7], and the LA, acetic acid (AA), propionic acid (PA), and butyric acid (BA) contents were determined using high-performance liquid chromatography (flow rate 1 mL/min, temperature 30 °C; Waters 2695, Waters, Milford, MA, USA) according to the method of Wang et al. [8].
2.3.2. Conventional Silage Quality Detection
The remaining silage was dried to a constant weight at 65 °C, and the dry matter (DM) content was determined [9], after which the samples were ground and passed through a 1 mm mesh sieve for chemical composition analysis. The WSC and CP contents were determined according to the official Association of Analytical Chemists method [10]. Neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined by the method described by Van Soest et al. [11].
2.4. Silage Bacterial Community Analysis
A 10 g sample was removed from each silage bag, 40 mL of sterile saline (0.9% NaCl) was added, and the sample was mixed thoroughly by vortexing. The filtrate was centrifuged at 10,000 r/min for 10 min and the supernatant was discarded. The remaining precipitate was then suspended in 3 mL of sterile saline. Total DNA extraction from microbial communities was performed according to the instructions of the E.Z.N.A.® Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA). PCR amplification of the V3-V4 variable region of the 16S rRNA gene was performed using 799F_1193R (5′-ACGTCATCCCCACCTTCC-3′), and DNA extraction and PCR amplification were performed according to the method of NIE et al. [12]. Sequencing was performed using the Illumina MiSeq PE300/NovaSeq PE250 platform (Shanghai Meiji Biomedical Technology Co. Ltd., Shanghai, China). PCR products from the same sample were mixed and recovered using a 2% agarose gel, purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), detected by 2% agarose gel electrophoresis, and quantified by a Quantus™ Fluorometer (Promega, Madison, WI, USA). Library construction was performed using a NEXTflexTM Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA).
Quality control of the raw sequences was carried out using fastp software, version 0.20.0 (
2.5. Statistical Analysis
The experimental data were subjected to one-way ANOVA using SPSS 20.0 (IBM, Armonk, NY, USA) to compare the effects of additives on silage quality and differences in microbial diversity indices. Duncan’s HSD test was employed to determine the differences between treatment means, with significance at p < 0.05. The microbial diversity indices (Shannon, Simpson, Ace, Chao1, and Coverage) for silage quality data (DM, WSC, CP, NDF, ADF, pH, LA, AA, BA, and NH3-N parameters) are expressed as the mean ± standard error of three measurements.
3. Results
3.1. Chemical Composition and Bacterial Community of Fresh Alfalfa and Corn Flour
Table 1 and Figure 1 show the nutrient and microbial composition of alfalfa and corn meal before silage. The CP content of alfalfa was 19.94%, but the NDF and ADF contents were higher, and the WSC content was low at 4.96%; the NDF and ADF contents of corn meal were lower and the WSC content was higher, at 27.89%. The dominant pre-silage flora of alfalfa were Pantoea (75.60%), Pseudomonas (6.98%), unclassified_o_Enterobacterales (5.24%), Morganella (4.25%), and Escherichia shigella (1.23%), with almost no LAB.
3.2. Effect of Compound Additives on Nutrient Composition of High-Moisture Alfalfa Silage
As seen in Table 2, compared with the control group, ADF content was significantly lower in all test groups (p < 0.05); DM content was significantly higher in C5 and C10 (p < 0.05), and NDF content was significantly lower (p < 0.05); CP content was significantly higher in S (p < 0.05) and significantly lower in C10 (p < 0.05); and NDF was significantly lower in C5 and C10 (p < 0.05).
3.3. Effect of Compound Additives on the Nutrient Composition of High-Moisture Alfalfa Silage
As seen in Table 3, compared with the control group, the pH was significantly lower in groups C5 and C10 (p < 0.05), the LA content was significantly higher in all treatment groups (p < 0.05), and the AA and NH3-N/TN contents were significantly lower (p < 0.05); PA was not detected in any group, and BA was not detected in C5 or C10.
3.4. Effect of Compound Additives on Microbial Diversity of High-Moisture Alfalfa Silage
As can be seen from Table 4, the coverage index was greater than 0.99 for all groups, indicating that the results can reflect the species information of the vast majority of microbes in the samples. Compared to CK, the Shannon index was significantly lower (p < 0.05), and the Simpson index was significantly higher (p < 0.05) for groups S and C10, indicating that their silage microbial diversity was significantly lower (p < 0.05). The Ace and Chao indices were significantly lower (p < 0.05) for C10 compared to the control, indicating that silage microbial richness was significantly lower (p < 0.05) under this treatment.
From Figure 2, the differences between groups of silage samples were shown using principal coordinate analysis (PCoA) based on the distance matrix of β-diversity. The results are shown in Figure 3, where each experimental group was significantly separated from the control group, and the C5 group was also more significantly separated from the S and C10 groups. However, the separation of group S and group C10 was not obvious.
From Figure 3A, it can be seen that the dominant phylum in all groups was Firmicutes, followed by Proteobacteria. As shown in Figure 3B, the highest relative abundance of Lactobacillus spp. in each treatment was 53.38, 82.67, 75.73, and 88.53% in groups CK, S, C5, and C10, respectively. Weissella was dominant in each group, with a relative abundance of 24.62, 9.29, 10.00, and 3.15%, respectively. The relative abundance of Pantoea in CK, S, C5, and C10 was 14.97, 4.07, 6.12, and 4.46%, respectively; that of Escherichia-Shigella was 1.69, 1.19, 2.79, and 1.18%, respectively; and that of Enterobacter was 0.96, 0.79, 1.31, and 0.69%, respectively. In addition, CK had 1.47% Clostridium sensu stricto 12, while there was no significant evidence of its presence in S, C5, and C10.
The 17 biomarkers listed above can be found in Figure 4. At the genus level, CK was differentially enriched with Pantoea, Clostridium sensu stricto 12, and Weissella; C5 was enriched with Escherichia-Shigella; and C10 was enriched with Lactobacillus spp. We also observed that the Firmicutes phylum was enriched in group S.
As shown in Figure 5, Lactobacillus spp. were positively correlated with LA and negatively correlated with NH3-N/TN, pH, and ADF. Unclassified_o_Enterobacterales was positively correlated with LA and WSC and negatively correlated with NH3-N/TN, pH, ADF, and NDF. Rhodococcus was positively correlated with WSC and negatively correlated with NH3-N/TN, pH, CP, ADF, and NDF. Weissiella was negatively correlated with LA and WSC and positively correlated with NH3-N/TN, pH, ADF, and NDF. Clostridium sensu stricto 12 was negatively correlated with LA and WSC, and positively correlated with NH3-N/TN, pH, and ADF.
4. Discussion
4.1. Effect of Compound Additives on Nutrient Composition and Fermentation Quality of High-Moisture Alfalfa Silage
Silage fermentation relies on the rapid degradation of WSCs by LAB into organic acids, which decreases the pH and thus inhibits the activity of aerobic microorganisms [18]. Thus, both the LAB and fermentation substrate are indispensable parts of silage; it has been confirmed in previous studies that fermentation is not ideal for silage with low sugar content and with LAB used as the only additive [19], and a lack of fermentation substrate has a more restrictive effect on silage fermentation quality than a lack of LAB [20]. At the beginning of silage fermentation, proteases and facultative aerobes such as yeasts and Enterobacteriaceae remain alive in the plant. Thus, the rate and extent of pH decrease determine the extent of nutrient loss in silage [21]. The low WSC content of alfalfa is not enough to provide substrate for LAB fermentation, so in addition to adding LAB to silage, exogenous WSC should be added, which not only provides substrate for fermentation, but also synthesizes bacterial proteins to increase the CP content in the silage [22]. At the same time, the rapid decrease in pH can inhibit the activity of plant proteases and some microbes, thus reducing the degradation of proteins in silage to non-protein nitrogen such as amino acids and ammonia to a greater extent. Liu et al. [23] reported that adding a mixture of Lactobacillus plantarum and Lactobacillus casei as well as sucrose to alfalfa silage could reduce protein loss, which is in agreement with the results of Wang et al. [24]. In this experiment, CP content was significantly higher in group S, which was consistent with the above results. The lower water, CP, and crude fiber content of corn flour resulted in higher DM content and lower CP, ADF, and NDF content in groups C5 and C10.
In Van Soest’s approximate nutrient analysis scheme, NDF includes cellulose, hemicellulose, and lignin, and ADF includes cellulose and lignin; it is difficult for lignin to be degraded by the rumen of ruminants. During fermentation, both homo- and heterofermentative LAB partially hydrolyze hemicellulose and produce pentoses, such as xylose and arabinose, which are fermented to organic acids via the phosphoketolase pathway [25]. In addition, several Bacillus and Penicillium species have enzymes capable of degrading starch or hemicellulose. Cellulose, as a macromolecular polysaccharide, cannot be directly utilized by LAB [26], but it can be acidolyzed by certain metabolites of LAB, such as formic acid [27]. In silage, certain Lactobacillus spp. are capable of producing ferulic acid esterase, which can also effectively degrade cellulose [28]. Li et al. [29] and Jing [30] successfully screened out ferulic acid esterase, producing LAB from silage. In our experiment, ADF was significantly reduced in group S. This may be related to the partial breakdown of hemicellulose and cellulose, and the significant decrease of NDF and ADF in C5 and C10 was caused by the different raw materials.
After the aerobic respiration stage, silage is depleted of oxygen and enters the LA fermentation stage. During this stage, the activity of aerobic microorganisms ceases and LAB multiply and produce LA, thus reducing the pH of the silage. However, the epiphytic LAB on the raw plant material are usually heterofermentative and found in very low numbers [31]. The compound additive in this experiment contains Lactobacillus plantarum, which can carry out homofermentation to produce large amounts of LA. According to Zhang et al. [32], pH is mainly influenced by moisture. Excessive moisture causes a decrease in the concentration of soluble sugars in silage, which inhibits LAB reproduction, and in turn leads to lower LA yield and higher pH [33].
In this experiment, the water content of CK and S was around 80%, which might be the reason for the higher pH in these groups. NH3-N/TN is an indicator of protein degradation, and the production of ammoniacal nitrogen in silage is usually caused by microbial and plant protease activity. Both Clostridium spp. and plant protein hydrolases are active when the pH is between 5 and 6.26. The LA produced by LAB (pKa 3.86) is usually the most concentrated acid in silage, up to 10 to 12 times more intense than any other major acid (e.g., AA (pKa 4.75) and PA (pKa 4.87)), thus it is a major contributor to the decreased pH during fermentation [34]. AA is the second most concentrated acid in silage, and it may be beneficial to have appropriate concentrations of AA due to its ability to inhibit yeasts and improve the stability of silage when exposed to air. In silage treated with Lactobacillus brucei, AA concentrations were often higher than normal due to the conversion of LA to AA [35]. The LA-to-AA ratio is often used as a qualitative indicator of fermentation, with the value for well-fermented silage usually ranging from 2.5 to 3.0. This indicator should not be too high, and silage with a very high ratio can be more unstable than silage with a normal ratio, because low concentrations of AA may not be sufficient to inhibit yeast, which assimilates LA. The mean value of LA/AA in the control group in this experiment was 1.63, indicating that LA produced by fermentation of high-moisture alfalfa without treatment was insufficient, while the alfalfa in C5 and C10 was well fermented. In addition, the high AA content in this experiment may have been caused by the metabolism of some LA to AA by Lactobacillus brucei in the additive. Kung et al. [34] concluded that this phenomenon should not be considered as an indicator of poor fermentation. BA should not be detected in well-fermented silage, and the presence of this acid indicates the metabolic activity of Clostridium, which can metabolize sugars and LA to BA and considerably hydrolyze proteins, leading to a significant loss of DM [34,36].
4.2. Effect of Compound Additives on Microbial Diversity of High-Moisture Alfalfa Silage
The silage fermentation process involves complex changes and a variety of microorganisms [37]. The composition, species, and number of microorganisms affect the fermentation of silage, and decreased pH during fermentation can inhibit the activity of microorganisms, which leads to decreased microbial diversity [38]. Allen et al. [39] noted that the greater the abundance of dominant flora, the smaller the microbial diversity, and more diverse microbial species in silage can cause silage failure [40].
In this experiment, compared to the control group, the Shannon index decreased and the Simpson index increased in all experimental groups, and the difference between groups S and C10 reached a significant level, indicating good fermentation in all treatment groups. Moisture can greatly affect microbial colonization [41], and Wang et al. [42] concluded that the effect of LAB addition is reduced in high-moisture silage. However, it has also been shown that under high-moisture conditions, LAB decreases silage pH more rapidly due to easier access to metabolic water [34]. However, no significant difference was found in the number of Lactobacillus spp. between groups S and C10 in this experiment, perhaps indicating that water is not the main factor limiting Lactobacillus spp. reproduction within a certain range when the sugar source and LAB are sufficient.
Before silage, Pantoea is the main dominant flora, which is a harmful microorganism to suppress, because it will use sugar and amino acids to produce AA during the fermentation process. LAB is the main microorganism that ensures good silage fermentation, and is also the main dominant flora during the silage stabilization period [43]. Inoculation with Lactobacillus plantarum was shown to have a positive effect on silage by promoting the LA accumulation and lower pH. The low-pH environment and anaerobic conditions favor the growth of Firmicutes, which are important acid hydrolytic microorganisms that produce large amounts of extracellular enzymes under anaerobic conditions. The phylum includes the genera Lactobacillus, Lactococcus, Weissella, and Leucontos, which are the main microorganisms involved in LA fermentation [36,44], and also play a role in cellulose degradation [45]. Among them, Lactococcus usually grows vigorously and initiates LA fermentation early in silage, thus stimulating the dominance of Lactobacillus spp., while Lactobacillus spp. become progressively more active and grow vigorously as the pH decreases [46].
Harmful microorganisms (Enterobacteriaceae, Clostridium) in silage are inactivated or gradually disappear as the acidic environment in the fermentation system rapidly develops [44]. The dominant flora in all groups in this experiment were Firmicutes and Proteobacteria, which is consistent with the findings of Ogunade et al. [47] and Zhang et al. [48]. The dominant groups at the genus level were Lactobacillus and Weissella, which is in agreement with the findings of Sun [49]. McDonald et al. [50] reported high-moisture silage characterized by poor (but natural) fermentation dominated by Enterobacteriaceae, Clostridium, or heterofermentative lactic acid bacteria.
In our experiment, Proteobacteria were present in relatively high abundance (19.71%) in the CK group. Proteobacteria are Gram-negative and are members of the phylum that also includes Enterobacteriaceae, Aumonas, etc. [47], among which are pathogenic bacteria such as E. coli and Salmonella that need to be inhibited [51]. In addition, some bacterial genera slow down the pH reduction, compete with LAB for fermentation substrates, and hinder the decomposition of ADF [52]. In this experiment, LEfSe analysis revealed that the characteristic microorganisms in the control group were mainly in Weissella, Pantoea, and Clostridium sensu stricto 12. Weissella is a heterofermentative lactic acid bacteria [53], and its fermentation products include substances such as AA, carbon dioxide, and ethanol in addition to LA [54]. Thus, heterofermentative lactic acid bacteria can cause some loss of silage nutrients. However, they are not without benefits; the AA they produce during fermentation can inhibit fungi and thus improve aerobic stability [55,56]. Cai et al. [57] showed that Weissella was unable to grow at a pH lower than 4.5. Thus, it was replaced by acid-tolerant Lactobacillus spp. in the later stages of fermentation [47]. Graf et al. [58] concluded that Weissella abundance was negatively correlated with the degree of pH decrease.
LEfSe analysis in this experiment showed that one of the characteristic microorganisms detected in the CK group was Pantoea, a member of Enterobacterales. AA is mainly produced by Enterobacterales during fermentation [59]. Pantoea competes with LAB for sugars, and its presence in silage is considered undesirable [60]. However, the survival rate of Pantoea in an acidic environment is low [61,62], and thus its survival rate was significantly lower in all experimental groups because of the more acidic environment. Since Clostridium spp. can grow under high moisture conditions (DM < 30–35%), can convert LA to PA, and causes excessive protein degradation and DM loss, it is generally believed that high concentrations of BA and NH3-N in poorly fermented high-moisture silage are usually associated with Clostridium spp. activity [36,63]. Clostridium sensu stricto 12 is generally considered to be the main producer of hexanoic acid [64]; in addition, it can also produce AA and ethanol via the Wood–Ljungdahl pathway [65]. Clostridium sensu stricto 12 was positively correlated with AA and ammonia nitrogen in this experiment, which may explain the higher ammonia nitrogen and AA in the CK group. Furthermore, Weissella and Clostridium sensu stricto 12 were significantly and positively correlated with pH, which might be due to the replacement of these two genera by Lactobacillus spp. as the pH decreased, leading to the lower relative abundance of Weissella and Clostridium sensu stricto 12 observed in silage with lower pH. In conclusion, bacterial communities were found to affect silage fermentation quality by influencing pH and organic acid concentration. Adding a compound consisting of LAB and sugar sources to high-moisture alfalfa silage significantly increased Lactobacillus spp. abundance and decreased Weissella, Clostridium sensu stricto 12, and Pantoea abundance, which greatly improved silage quality.
5. Conclusions
This study shows that the addition of a compound consisting of LAB and sugar sources was effective at improving the fermentation quality, nutrient composition, and microbial diversity of high-moisture alfalfa silage. Compared with the control group, the addition of the compound was able to reduce the NDF and ADF levels as well as pH and NH3-N/TN, while it was able to increase the LA content. In the microbial community, the complex additive increased the relative abundance of Lactobacillus spp. and decreased the relative abundance of undesirable bacteria (Weissella, Clostridium sensu stricto 12, Pantoea, etc.). Among the three added compounds, group C10 had the lowest pH, NH3-N/TN, NDF, and ADF had the highest LA concentration, and the highest relative abundance of Lactobacillus spp. Therefore, adding a compound consisting of LAB + 10% corn flour in the preparation of high-moisture alfalfa silage can achieve good fermentation with high nutritional quality.
Conceptualization, H.J. and F.G.; methodology, H.J.; software, B.B.; validation, J.W.; formal analysis, L.S.; investigation, H.Q.; resources, F.G.; data curation, H.W.; writing—original draft preparation, H.J.; writing—review and editing, B.L.; visualization, H.J.; supervision, B.L.; project administration, F.G.; funding acquisition, F.G. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
Not applicable.
The authors declare that they have no conflicts of interest.
Footnotes
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Enlarge this image.Figure 3. Histograms of bacterial communities at (A) phylum and (B) genus levels.
Enlarge this image.Figure 4. Linear discriminant analysis (LDA) effect size (LEfSe) showing microbial differences among treatments at different taxonomic levels. (A) Different colored nodes indicate significantly enriched microbial taxa in corresponding groups with a significant effect on differences between groups; light yellow nodes indicate taxa that are not significantly different in any groups or have no significant effect on differences between groups. (B) LDA discriminant bar chart statistics of microbial taxa with significant effects in multiple groups, scores obtained by LDA; a larger LDA score indicates the greater effect of species abundance on differential effects. The threshold for the LDA score of discriminative features was set at 4.0. The Kruskal–Wallis and Wilcoxon test filter threshold was 0.05.
Enlarge this image.Figure 5. Heatmap showing the correlation between silage fermentation quality and the relative abundance of bacterial genera. WSC, water-soluble carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; NH3-N, ammonia nitrogen as a percentage of total nitrogen; LA, lactic acid; AA, acetic acid. * p < 0.05; ** p < 0.01; *** p < 0.001.
Nutritional composition of raw alfalfa and corn flour.
| Nutritional |
DM |
CP |
NDF |
ADF |
WSC |
Crude Ash |
|---|---|---|---|---|---|---|
| Alfalfa | 22.04 | 19.94 | 43.81 | 31.66 | 4.96 | 9.75 |
| Corn flour | 90.2 | 9.08 | 21.60 | 6.17 | 27.89 | 1.06 |
Effect of compound additives on the nutrient composition of high-moisture alfalfa silage.
| Item | CK | S | C5 | C10 | SEM | p-Value |
|---|---|---|---|---|---|---|
| DM | 21.30 ± 0.50 c | 21.69 ± 0.14 c | 26.92 ± 0.40 b | 30.79 ± 1.76 a | 1.21 | <0.01 |
| CP (DM%) | 16.17 ± 0.23 b | 16.80 ± 0.31 a | 15.78 ± 0.27 bc | 15.26 ± 0.38 c | 0.19 | <0.01 |
| WSC (DM%) | 1.46 ± 0.08 c | 4.37 ± 0.04 b | 4.28 ± 0.25 b | 4.74 ± 0.18 a | 0.40 | <0.01 |
| NDF (DM%) | 41.39 ± 3.00 a | 40.12 ± 1.30 a | 35.85 ± 1.28 b | 33.31 ± 2.32 b | 1.11 | <0.01 |
| ADF (DM%) | 34.15 ± 1.13 a | 30.68 ± 1.42 b | 26.05 ± 1.25 c | 23.22 ± 0.87 d | 1.30 | <0.01 |
Note: DM, dry matter; CP, crude protein; WSC, water-soluble carbohydrate; NDF, neutral detergent fiber; ADF, acid detergent fiber; SEM, standard error of the mean. Different superscript lowercase letters indicate significant differences between treatments (p < 0.05).
Effect of additives on fermentation quality of high-moisture alfalfa.
| Item | CK | S | C5 | C10 | SEM | p-Value |
|---|---|---|---|---|---|---|
| pH | 5.63 ± 0.12 a | 5.27 ± 0.30 a | 4.83 ± 0.20 b | 4.48 ± 0.11 b | 0.14 | <0.01 |
| LA (DM%) | 2.44 ± 0.05 c | 3.29 ± 0.03 b | 3.41 ± 0.23 ab | 3.68 ± 0.24 a | 0.15 | <0.01 |
| AA (DM%) | 1.48 ± 0.04 a | 1.16 ± 0.00 b | 1.23 ± 0.08 b | 1.22 ± 0.02 b | 0.04 | 0.15 |
| PA (DM%) | ND | ND | ND | ND | - | - |
| BA (DM%) | 0.49 ± 0.02 a | 0.32 ± 0.01 b | ND | ND | - | - |
| NH3-N/TN (%) | 4.89 ± 0.25 a | 3.69 ± 0.15 b | 3.02 ± 0.11 c | 2.57 ± 0.06 d | 0.27 | <0.01 |
| LA/AA | 1.63 ± 0.08 b | 2.83 ± 0.03 a | 2.79 ± 0.29 a | 3.02 ± 0.25 a | 0.17 | <0.01 |
Note: LA, lactic acid; AA, acetic acid; PA, propionic acid; BA, butyric acid; NH3-N, ammonia nitrogen, TN, total nitrogen; SEM, standard error of the mean. Different superscript lowercase letters indicate significant differences between treatments (p < 0.05).
Effect of compound additives on abundance and diversity indices of microbial communities in high-moisture alfalfa.
| Item | CK | S | C5 | C10 | SEM | p-Value |
|---|---|---|---|---|---|---|
| Shannon index | 2.81 ± 0.05 a | 1.65 ± 0.59 b | 2.42 ± 0.19 a | 1.74 ± 0.09 b | 0.16 | 0.12 |
| Simpson index | 0.09 ± 0.01 b | 0.40 ± 0.22 a | 0.19 ± 0.04 ab | 0.33 ± 0.03 a | 0.05 | 0.05 |
| Ace index | 61.62 ± 1.67 b | 59.71 ± 1.08 b | 65.37 ± 1.32 a | 56.70 ± 0.86 c | 1.00 | 0.61 |
| Chao index | 60.63 ± 2.29 b | 58.76 ± 1.80 bc | 64.62 ± 1.28 a | 56.45 ± 0.64 c | 0.99 | 0.19 |
| Good’s coverage | 0.9997 ± 0.0001 a | 0.9993 ± 0.0002 a | 0.9996 ± 0.0003 a | 0.9994 ± 0.0002 a | 0.0001 | 0.38 |
Note: Different superscript lowercase letters indicate significant differences between treatments (p < 0.05). SEM, standard error of the mean.
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