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Article

Ensiling Characteristics, Bacterial Community Structure, Co-Occurrence Networks, and Their Predicted Functionality in Alfalfa Haylage Silage with or Without Foliar Selenium Application

by
Kexin Wang
†,
Fengdan Wang
†,
Shengnan Sun
,
Yilin Zou
,
Zifeng Gao
,
Yi Hua
,
Ligang Qin
* and
Guofu Hu
*
Department of Grassland Science, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2024, 14(11), 2709; https://doi.org/10.3390/agronomy14112709
Submission received: 10 October 2024 / Revised: 10 November 2024 / Accepted: 15 November 2024 / Published: 17 November 2024
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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Abstract

:
Selenium (Se) is an essential trace element in living systems. In this study, we applied a spray of 50 mg/kg sodium selenite to alfalfa (Medicago sativa L.) at different stages of development (bud, initial bloom, and full bloom stages). After 0, 1, 3, 7, and 45 days of ensiling, we assessed the fermentation quality, chemical composition, and bacterial community of the alfalfa. Our findings indicated that the addition of Se led to an increase in the Se content and a decrease in the pH, acid detergent fiber (ADF), and neutral detergent fiber (NDF) contents. As ensiling fermentation progressed, the Se treatments increased the relative abundance of Lactobacillus, which was significantly greater than that in the control group (42.44% vs. 3.76%). In conclusion, the addition of sodium selenate to silage additive ensures the quality of the silage and reduces bacterial community diversity. This study provides valuable insights for the investigation of Se enrichment in alfalfa haylage silage.

1. Introduction

Selenium (Se) is a useful micronutrient and an essential component of all living systems [1]. Immune system deficiencies, reproductive problems, and Keshan disease can result from a Se shortage [2]. However, geologist research has indicated that almost 72% of China’s regions are Se-deficient and that there is a low-Se zone from Northeast China and North China to Northwest China. There are generally two ways to improve the Se status of livestock [3]. One method involves offering Se-rich mineral supplements, injecting Se, or both. However, this method often does not provide the consistent blood Se concentrations required for optimal health and productivity [4]. The other method, referred to as agronomic Se biofortification, involves the fertilization of feed sources to increase their Se concentration [5]. Many studies have been conducted recently on increasing the amount of Se produced through agronomic Se biofortification [6]. Interestingly, Se can increase the biomass and antibacterial ability of Lactobacillus [7].
Alfalfa (Medicago sativa L.) is known for its high protein, vitamin, and mineral contents and palatability, so it is also known as the “queen of forage” [8]. Alfalfa is usually fed to ruminants in the form of silage, a complex microbial system [9]. Haylage silage is made by reducing the water content of the raw materials for silage to 40–60%. This reduction inhibits the biochemical activities of microorganisms, hinders microbial cell activity, and prevents aerobic microorganisms from breaking down and metabolizing an excessive amount of nutrients in the raw materials under anaerobic conditions [10]. Compared with hay and alfalfa silage, alfalfa haylage silage has a lower moisture content and weaker fermentation during production, making it more nutrient dense and more like fresh alfalfa. Se-rich alfalfa is expected to increase Se levels in livestock through feeding [4]. Under Se application, the total Se, Fe, and Mn contents and the forage yield of alfalfa increase [11]. Our previous study revealed that the foliar spraying of Na2SeO3 significantly increased the growth rate, dry weight, total Se content, the amount of pollen per flower, pollen viability, pod spirals, and the number of seeds per pod of alfalfa plants [12]. In addition, soil Se applications significantly increased Se uptake in rice, and low rates of Se application increased plant growth and rice yield [13]. The microbial makeup of alfalfa silage influences fermentation quality, and numerous Se species can change during fermentation. These processes include reduction, oxidation, methylation, and demethylation [14]. To date, several specific taxonomic groups of Se-tolerant and/or Se-transforming microorganisms, such as Enterobacter, Bacillus, and Delftia tsuruhatensis have been identified [15]. Se increased the abundance of aerobes and decreased the amount of anaerobic microbes [16]. Furthermore, in fermented pickles, Se inhibits the growth of Enterobacter, a foodborne disease, while promoting the growth of advantageous microbes, including Lactococcus, Lactobacillus, and Leuconostoc [2]. Sun et al. [17] reported that Se enrichment significantly increased the crude protein and soluble carbohydrate contents of alfalfa silage. Silage additives are evenly sprayed into the grass material prior to ensiling, and adding Se to the silage additive might be a practical solution to ensure that the required dose of Se is applied safely and evenly into the silage [18].
As a result, it is important to investigate the modifications to the microbial population in sodium selenite-treated alfalfa haylage silage. Although Se plays an important role in ensiling, few studies have investigated the problems related to Se-rich alfalfa haylage silage or the effect of the mowing period on alfalfa haylage silage. Therefore, an ensiling experiment was conducted to explore differences in the Se content, the fermentation quality, the chemical composition, and the bacterial community structure of alfalfa haylage silage cut at different stages and to clarify the significance of Se-enriched alfalfa haylage silage.

2. Materials and Methods

2.1. Raw Materials and Silage Preparation

The experimental material was three-year-old alfalfa, which was planted in an experimental field at Northeast Agricultural University (Heilongjiang, China) (126°73′ E, 45°75′ N) in 2020. In this experiment, conventional field management, including field observation and weeding, was used; however, no fertilization or irrigation was used, and the plot area was 25 m2 (5 m × 5 m) with three replications. A foliar application of sodium selenite was carried out on the alfalfa 20 d after emergence. Sodium selenite (Na2SeO3) was sprayed with a hand-held sprayer at a concentration of 50 mg/kg and a dose of 6 L once every 6 days, three times in total. Equal volumes of water instead of sodium selenite solution were sprayed as the control group.
The samples of alfalfa were collected at three periods (bud, initial bloom, and full bloom stages), leaving 5 cm of stubble. After mowing, the alfalfa plants were brought to the laboratory and left to dry in the shade for approximately 24 h until they reached the haylage state. The alfalfa haylage was mixed and chopped with a paper cutter into 2–3 cm pieces. The samples were placed in polythene bags (20 cm × 30 cm) of approximately 150 g each, vacuum-sealed and stored at room temperature (25–32 °C) (each treatment had 3 replicates). Each silage sample was stored for 0 (no silage), 1, 3, 7 and 45 days for the determination of fermentation quality, the chemical composition, and the bacterial community.
These alfalfa haylage silage bags were then assigned to the following treatments: (1) mowed at the bud stage without selenite application; (2) mowed at the bud stage with selenite application; (3) mowed at the initial bloom stage without selenite application; (4) mowed at the initial bloom stage with selenite application; (5) mowed at the full bloom stage without selenite application; and (6) mowed at the full bloom stage with selenite application. After 1, 3, 7 and 45 days of silage, each of the three treated bags was opened separately. Alfalfa haylage without silage was used as the control at 0 d.

2.2. Determination of Nutrient Indices and Fermentation Indices

Six treated samples were taken at 0, 1, 3, 7 and 45 days and dried in an oven at 65 °C for 48 h to determine the dry matter (DM) content. The raw material was subsequently pulverized and sieved through 40 mesh. Using a Kjeltec 8600 nitrogen analyzer (FOSS Analytical AB, Hoganas, Sweden), crude protein (CP) was examined in accordance with the Association of Official Analytical Chemists’ procedures [19]. The method of Van Soest et al. [20] was used to quantify the amounts of acid detergent fiber (ADF) and neutral detergent fiber (NDF). Ether extract (EE) was determined via an ANKOM automatic analysis (ANKOM extractor XT15i, ANKOM Technology, Macedon, NY, USA). Crude ash (Ash) content was determined by the high temperature burning method. A microwave digestion and extraction system were used to determine the Se content before determination, and the concentration was determined via inductively coupled plasma–mass spectrometry according to the method of Fernández et al. [21].
For the above samples, 10 g of each material was mixed with 90 mL of sterile water, sealed with plastic wrap, placed in a refrigerator at 4 °C for 24 h, and then filtered through four layers of cheesecloth. The pH value of the filtrate was determined via a pH meter. After the other portion was centrifuged for 15 min at 4 °C (4500× g), the supernatant was saved for the analysis of ammonia-N and organic acid. The method used to measure ammonia-N was phenol–sodium hypochlorite colorimetry [22]. High-performance liquid chromatography (HPLC) was used to measure the concentrations of lactic acid, acetic acid, propionic acid, and butyric acid (Waters600, Waters Technology (Shanghai) Co., LTD, Shanghai, China) under the following conditions described by He et al. [23]: oven temperature, 50 °C; mobile phase, 3 mmol/L HClO4; flow rate, 1.0 mL/min; injection volume, 5 μL; and the detector [23].

2.3. Microbial Diversity Measurement

A DNA Kit (D4015, Omega, Inc., Norwalk, CT, USA) was used to extract total DNA from a variety of samples in accordance with the manufacturer’s instructions. After being eluted in 50 μL of elution buffer, the whole DNA was kept cold at −80 °C. The primers 341F (CCTACGGGNGCWGCAG) and 805R (GACTACHVGGGTATCTAATCC) were used to amplify the 16S rDNA V3-V4 regions. The PCR amplification was carried out in a mixture with a total volume of 25 μL, which included 12.5 μL of PCR premix, 25 ng of template DNA, 2.5 μL of each primer, and PCR level water regulation. The products were purified via PCR AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA) and quantified via qubits (Invitrogen, Carlsbad, CA, USA). The samples were then subjected to Illumina NovaSeq platform sequencing.
The quality filter of the raw materials was read under specific filter conditions to comply with FQTRIM (V0.94) for high-quality clean labels. Chimeras were filtered via Vsearch software (V2.3.4). After deduplication with DADA2, the feature table and feature sequence were obtained, and the effective data were allocated to multiple operational taxonomic units (OTUs) with a threshold of 97%. Comparisons were made against the SILVA (Release132) bacterial database, and the characteristic abundance was normalized to the relative abundance of each sample. Alpha and beta diversities were analyzed via QIIME2 (V3.6.7). BLAST was used for sequence alignment, and each character sequence representing a sequence was annotated via the SILVA database.
The raw sequencing data were deposited in the National Microbiology Data Center (NMDC: https://nmdc.cn/, accessed on 30 June 2023) under the accession number NMDCX0000215.

2.4. Data Processing and Statistical Analyses

The experiment had a completely randomized design with 3 growth stages, 5 ensiling times, and 3 replicates per treatment. Data on fermentation quality and the Se content of the silages were tested via a one-way analysis of variance (ANOVA) and analyzed via SPSS (v26.0) software. The effects of the mowing period, fertilization treatment, and their interaction on the above indices were analyzed via a two-way ANOVA. The mowing period, silage time, fertilization, and their interaction were used to analyze the nutritional and fermentation indices of alfalfa haylage silage via a three-factor ANOVA. Duncan’s test was used for multiple comparisons. Values of p < 0.05 were considered significant. The diagrams were implemented on a free online platform of OmicStudio (https://www.omicstudio.cn/, accessed on 22 April 2024).

3. Results

3.1. Chemical Composition of Alfalfa Haylage Silage

The chemical composition of the alfalfa haylage silage is presented in Table 1. The DM and CP contents gradually increased with increasing alfalfa growth. At 45 days of ensiling, the CP content of the alfalfa haylage silage mowed at the initial and full bloom stages treated with sodium selenite was significantly greater than that at the bud stage (both the control and treatment groups) (p < 0.05). Among all the groups, the alfalfa haylage silage treated with sodium selenite and mowed at the full bloom stage presented the highest CP content (51.06 g/kg DM). The contents of NDF and ADF in the Se treatment group were lower than those in the control group during each mowing period. The contents of NDF and ADF gradually increased with the extension of the growth period. The contents of Ash and EE also increased gradually with increasing alfalfa growth. The Se content under the sodium selenite treatment during each mowing period was greater than that under the control treatment (p < 0.05). The highest Se content was 9.68 mg/kg in alfalfa haylage silage treated with sodium selenite mowed at the bud stage.

3.2. Fermentation Quality of Alfalfa Haylage Silage

In the present study, the proportion of ammonia-N increased with increasing fermentation time, as shown in Table 2, and it increased significantly at 45 days. However, the ammonia-N content was lower in the Se treatment groups than in the control groups at the initial bloom stage and at the 45-day, full bloom stage. The ammonia-N content was significantly lower in the full bloom stage than in the other periods and was less than 3.5% TN at all time points.
The lactic acid (LA) content increased with increasing fermentation time and significantly increased in the group at the full bloom stage (p < 0.05) (Table 2). Compared with that of presilage (0 d), the acetic acid (AA) content of haylage silage was greater at all stages. However, the content of AA decreased as the alfalfa growth period increased. Among all the groups, the lowest content of AA (0.04% DM) occurred in the sodium selenite treatment group at the full bloom stage. The propionic acid (PA) content in the alfalfa haylage silage tended to increase in all the groups, but the difference was not significant. In the present study, the butyric acid (BA) content in each group was extremely low, with a maximum value of only 0.12% DM. In this study, the PA and BA contents always remained low.
The pH of the alfalfa haylage silage in the Se application group and the control group first increased but then decreased with the extension of silage time (Table 2). In the present study, the bud period silage in the control group was weakly preserved, as demonstrated by the high pH value (5.04–5.86). After sodium selenite treatment, the pH of the alfalfa haylage silage mowed at the three stages was lower than that of the control group. The pH of all the groups ranged from 4.86 to 5.86, indicating that the alfalfa haylage silage was acidic.

3.3. Comprehensive Evaluation of Haylage Silage

Twelve indices (DM, CP, Ash, NDF, ADF, EE, pH, LA, AA, PA, ammonia-N, and Se) were measured for different haylage silage combinations and were taken as the gray system. The alfalfa groups were mowed at different periods, and, to determine whether Se treatment was carried out according to the total fermentation score, the standard control was set according to the nutrient content and the optimal value, the resolution was 0.5, the data initiative was calculated, the correlation between each process was calculated, and the magnitude of the value was sorted. The higher the combination is, the better the evaluation. The TF-45 combination correlation coefficient was the highest at 0.726 (Table 3), and the CKI-45 combination correlation coefficient was the lowest at 0.614. These findings indicated that alfalfa haylage silage treated with sodium selenite mowed at the full-bloom stage was the best plan for silage.

3.4. Bacterial Community Analysis of Alfalfa Silage

These sequences were divided into 27 phyla, 64 classes, 133 orders, 253 families, and 629 genera. Figure 1a,b shows the Venn diagram of the sample feature distribution, which can reflect the number of common and unique operational taxonomic units (OTUs) of all groups. The total number of OTUs in the alfalfa haylage silage treated with sodium selenite was 123, and there were 115 OTUs in the control group. The unique OTU numbers of the two treatments decreased with prolonged ensiling, and both treatments presented minimum values at 45 d of ensiling, with 171 in the sodium selenite group and 170 in the control group.
Figure 1c shows the dilution curve of the alfalfa haylage silage. In this experiment, the longer the fermentation time was, the gentler the dilution curve was, which means that the species in fermentation gradually became uniform and were sequenced in sufficient quantities. The results of the principal component analysis (PCA) are shown in Figure 1d, which clearly reflected the variance in the bacterial community. A clear separation of the bacterial communities of the alfalfa haylage silage between day 0 of ensiling and day 45 of ensiling was observed. This finding indicates that the distance between the two groups at 0 d was far from that in the other periods.
The bacterial colony composition and heatmap analysis at the phylum level during haylage ensiling are shown in Figure 2a,b. The advantageous groups associated with these two processes were Proteobacteria and Firmicutes. After 45 days of ensiling, in the treatment group, the abundance of the Proteobacteria phylum was greatly reduced, and Firmicutes increased, becoming the dominant phylum. Moreover, the treatment group presented a greater abundance of Firmicutes than did the control group.
The relative abundances of bacteria in the silage samples were determined via a heatmap analysis at the genus level, as shown in Figure 2c,d, and the dominant bacteria were Enterobacter, Pantoea, Klebsiella, Lactococcus, and Lactobacillus. Many genera of bacteria found in silage, including Lactobacillus, Pediococcus, Lactococcus, Enterococcus, Streptococcus, and Leuconostoc, are collectively referred to as lactic acid bacteria. In the sodium selenite treatment group, as the duration of silage increased, Lactobacillus and Lactococcus gradually increased and eventually became the dominant bacteria, whereas Enterococcus was the dominant bacterium in the control group. Compared with the control group, the Se group presented increased Pantoea abundance (p < 0.05), increased Enterobacter and Lactococcus abundances compared with those of the control group from 1 to 7 days of ensiling, and significantly increased Lactobacillus abundance compared with that of the control group at 45 days of ensiling (p < 0.05). Klebsiella and Enterobacter levels were significantly lower in the Se treatment group than in the control group at 45 days of ensiling (p < 0.05).
The alpha diversity is reflected mainly by the Chao1, observed species, Shannon, and Simpson indices (Table 4). The Chao1 index, the observed species index, and the Shannon index in the two groups decreased significantly with increasing haylage duration, indicating that the number of bacteria decreased gradually. The Simpson index was between 0 and 1, and the closer it was to 1, the greater the species diversity. In this study, the Simpson index of the sodium selenite treatment group was lower than that of the control group.
As shown in Figure 3a, the changes in the presumptive biological function of the haylage alfalfa silage microflora in the prefermentation group and the postfermentation group under Se treatment were verified via PICRUSt 2. Most metabolic pathways improved after 45 days of ensiling, and the treatment group presented increased activities in the metabolism of cofactors and vitamins, carbohydrate metabolism, and nucleotide metabolism and decreased activities in energy metabolism and amino acid metabolism. Compared with those in the CK group (Figure 3b), the metabolism of energy, carbohydrates, starches, sucrose, nucleotides, amino acids, and glycan biosynthesis was increased.
To investigate the impacts of Se on the relationships between bacterial species, separate bacterial networks were created for alfalfa haylage silage during ensiling via Pearson’s rank correlation (Figure 4). The abundance of Lactobacillus and Pantoea gradually showed a negative correlation with ensiling. After 45 d of ensiling, there was a negative correlation between Lactobacillus and Enterobacter in the Se treatment group. However, the control group showed the opposite result. The negative/positive ratio was greater in the Se treatment groups than in the CK group during ensiling, suggesting that Se increased the structural stability of the bacterial microbiota in the silage.
A redundancy analysis (RDA) revealed the relationships between the major bacterial community and the fermentation properties of alfalfa haylage silage (Figure 5). As shown in Figure 5a, 98.73% of the total variance in the bacterial communities at the phylum level could be explained by the first and second axes. Axis 1 (horizontal) was positively correlated with EE content and the pH. The primary determinant of the Proteobacteria abundance structure at various fermentation times was the pH. Axis 2 (vertical) was strongly correlated with the ADF, Ash, PA, and BA contents. There was a strong positive correlation between Se and Firmicutes. Additionally, at the genus level, the combined contribution of the first and second axes to the variance in the bacterial communities was greater than 76.36%. (Figure 5b). Axis 1 (horizontal) was positively correlated with the Ash content, pH and EE ratio, whereas axis 2 (vertical) was correlated with the CP, EE, BA, and Se contents. Among them, ammonia-N, CP, BA, PA, and Se had positive relationships with Lactobacillus and Lactococcus, whereas the pH was negatively correlated with the abundance of Lactobacillus.

4. Discussion

4.1. Effects of Se on the Chemical Composition of Alfalfa Haylage Silage

The content of DM in this experiment gradually increased with the extension of alfalfa growth; however, because alfalfa is harvested during the rainy season, the water content of alfalfa increases, which may lead to effluent loss during ensiling [24]. In addition, the high moisture content of the raw material promoted the growth and fermentation of Clostridium, which led to a pH higher than 4.8 [25]. In the present study, the content of CP in mowed alfalfa haylage silage in the sodium selenite treatment group was greater than that in the control group, indicating that the addition of Se to alfalfa silage inhibited proteolysis. A relatively high fiber content is not conducive to ensiling fermentation and leads to relatively low feed intake and digestibility in animals [26]. The contents of NDF and ADF in the Se treatment group in the present study were lower than those in the control group during each mowing period. The EE content also directly affects the energy content and quality of silage; the higher the EE content is, the higher the energy content of the silage, the higher the nutritional value, and the better the quality of the silage. The EE content gradually increased with the extension of alfalfa growth time. The Se content of the treatment group in each mowing period was greater than that of the control group, indicating that spraying with Se fertilizer can significantly increase the Se content of alfalfa. This finding was the same as that of Lintschinger [6], who reported that the application of Se to wheat and alfalfa could increase Se accumulation in the crops. Both SeO42− and SeO32− can be reduced to Se0 by bacteria under anaerobic conditions. Some bacteria reduce SeO42− and can incorporate it into organic compounds, i.e., selenoproteins [14]. Microorganisms can convert inorganic selenium into organic selenium with low toxicity, stable properties, and high biological activity [27]. In conclusion, foliar sodium selenite can effectively reduce the fiber content of alfalfa silage, increase the Se content of alfalfa silage, and has no negative effect on the nutritional quality of alfalfa.

4.2. Effects of Se on the Fermentation Quality of Alfalfa Haylage Silage

Nonprotein nitrogen in silage, including ammonia-N, mainly results from proteolysis during ensiling, which originates from the activities of plant proteases and undesirable microbes [28]. In the present study, the addition of sodium selenite effectively reduced the content of ammonia-N for alfalfa collected in the initial and full bloom stages. Ammonia-N was positively correlated with the content of CP. The reason may be that nitrate/nitrite reductase is also responsible for Se(VI)/Se(IV) reduction [14].
The main organic acids that affect silage fermentation include LA, AA, PA, and BA. The lactic acid (LA) content is an important indicator reflecting the degree of fermentation. Lactic acid bacteria can ferment a variety of substrates and rapidly produce large amounts of lactic acid for pH decline and microorganism inhibition [29]. As expected, as fermentation progressed, the content of LA increased gradually. Interestingly, compared with the CK groups, the Se treatment groups presented a lower content of LA; the reason for this phenomenon may be the lower pH at the late stage of ensiling, and many strains of LAB are less tolerant to lower pH values [30]. As the duration of silage increased, the AA content gradually increased in both the treatment and the control groups. AA originates from sugar decomposition and fermentation by heterofermentative Lactobacilli, Enterobacteriaceae, and Clostridia [31]. In this study, beneficial acids such as LA steadily increased during the ensiling process, with the BA and PA contents remaining at low levels in all the treatment groups (PA < 0.2% DM and BA < 0.1% DM). BA is generally produced by Clostridium [32]; therefore, the low concentration of butyric acid may be due to the poor growth of Clostridium, and the decrease in pH during fermentation prevents Clostridium from converting lactic acid to butyric acid [33]. When fermentation indicators of silage are evaluated, both ammonia-N and organic acids are closely associated with the pH [34]. A lower pH often ensures a more stable fermentation environment and protects the forage from undesirable fermentation [35]. An acidic environment has an inhibitory effect on harmful microorganisms in silage fermentation. Selenium helps create a relatively highly acidic environment [36]. Finally, through a gray system analysis, we found that alfalfa haylage silage treated with sodium selenite mowed at the full bloom stage presented the highest quality.

4.3. Effects of Se on the Bacterial Community of Alfalfa Haylage Silage

The main microbial population in silage forage is bacteria, and their fluctuations cause a series of physicochemical changes in the raw material; thus, the quality of silage is affected. The PCA plot revealed changes in the bacterial composition of alfalfa in both groups during ensiling. Fermentation is a process driven by microorganisms, and the fermentation quality of silage relies strongly on the activities and types of microorganisms involved in the fermentation process [37].
In our study, an overall trend toward a decrease in the relative abundance of Proteobacteria was observed in the treatment group, and Firmicutes increased to become the dominant phylum because the anaerobic conditions and acidic environment formed during ensiling favored the growth of the Firmicutes phylum [38]. However, Proteobacteria was still the dominant phylum in the control group at 45 days. Lactic acid bacteria are known to be regularly involved in silage fermentation and belong to the phylum Firmicutes and to the genera Enterococcus, Lactobacillus, Lactococcus, Leuconostoc, Pedicoccus, Streptococcus, and Weissella [36]. Bacteria in the phylum Firmicutes produce acid and rapidly decrease the pH of silage, inhibiting the growth of undesirable microorganisms [39].
In the sodium selenite treatment group, Lactobacillus and Lactococcus gradually increased, whereas Enterobacter decreased. This finding is similar to the results of Yang et al. [7], who reported that selenium can increase the biomass and bacteriostatic capacity of lactic acid bacteria. The appearance of the Enterobacter species in silage is undesirable since they compete with lactic acid bacteria for substrates during ensiling because of their facultative anaerobic nature [40]. Lactococcus starts lactic acid fermentation at the beginning of ensiling, but these species are sensitive to low pH and cannot survive in acidic environments [41]. Therefore, Lactobacillus plays a crucial role in lowering the pH in the late silage stage [42]. We hypothesized that the addition of Se affects the quality of alfalfa silage at the end of ensiling by altering the bacterial community structure. Lactobacilli are important for the accumulation of LA and a decline in pH [43], and a higher abundance of Lactobacilli often results in better fermentation quality. As expected, in the present study, Lactobacilli was negatively correlated with the pH and positively correlated with CP content, which demonstrates the important role of LAB in rapidly acidizing silage and inhibiting protein breakdown. This finding meant that, compared with the control group, the sodium selenite group had a greater percentage of bacteria conducive to fermentation.
The Chao1 index, the observed species index, and the Shannon index in the two groups decreased significantly with the extension of haylage silage duration, indicating that a decrease in bacterial diversity occurred in the alfalfa haylage silage after 45 days of fermentation. As fermentation proceeded, the pH of the silage environment decreased, and the oxygen content gradually decreased to an anaerobic environment [42]. This environment leads to a decrease in anaerobic microorganisms and acid-intolerant epiphytic microorganisms [44], resulting in a decrease in the diversity of the bacterial community of alfalfa haylage silage [42]. Microorganisms that compete with LAB do not survive, and the result is anaerobically stable silage [45].
Many previously published studies have shown that Se(IV) is converted to SeNPs, which also reduce the richness of bacterial families and genera [14]. That is, the higher the Se content in the soil is, the fewer bacterial species reduce Se(IV) [46], which may be a reason for the decrease in microbial diversity in silage treated with sodium selenite. Importantly, Se does not exist in a single form in plants, with 25 selenoproteins known to be detected in humans [47]. Among the 25 selenoproteins, organic Se-rich foods, represented by selenium methionine (SeMet), can promote the absorption and utilization of selenium in livestock and humans [48]. For example, in ruminants such as cattle, when selenium is present in the diet in the form of SeMet, SeMet replaces methionine for protein synthesis [49]. This phenomenon is why selenium accumulates in the muscle of cattle. Therefore, we suggest that future research should focus on the transformation of selenium by microorganisms in selenium-rich plant silage.

5. Conclusions

This study confirmed that the foliar spraying of sodium selenite increased the selenium content without affecting the fermentation quality or nutritional value of alfalfa haylage silage; improved the nutrition and fermentation quality of alfalfa haylage silage; promoted the growth of beneficial microorganisms, such as Lactococcus and Lactobacillus; and inhibited the growth of unfavorable bacteria, such as Enterobacter. This action improved the bacterial community structure and function. Further in-depth studies on the relationships between Se and other silage additives could improve the efficiency of Se and bacteria in alfalfa haylage silage.

Author Contributions

Methodology, K.W., S.S., L.Q. and G.H.; Validation, F.W., S.S. and Y.Z.; Investigation, Y.Z., Z.G. and Y.H.; Data curation, K.W., Z.G. and Y.H.; Writing—original draft, K.W., Writing—review and editing, K.W., F.W., L.Q. and G.H.; Funding acquisition, L.Q. and G.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (32271770).

Data Availability Statement

Date have been stored in the National Microbiology Data Center (NMDC). The URL is https://nmdc.cn/, accessed on 30 June 2023. The periodical attachment number: NMDCX0000215.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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Figure 1. (a) OTU Venn diagram of haylage silage in the sodium selenite treatment group. (b) OTU Venn diagram of haylage silage in the control group. (c) Dilution curve. (d) The 2D schematic diagram of PCA.
Figure 1. (a) OTU Venn diagram of haylage silage in the sodium selenite treatment group. (b) OTU Venn diagram of haylage silage in the control group. (c) Dilution curve. (d) The 2D schematic diagram of PCA.
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Figure 2. (a) Bacterial colony composition at the phylum level during haylage ensiling. (b) Heatmap analysis at the bacterial phylum level in haylage silage. (c) Heatmap analysis at the bacterial genus level in haylage silage. (d) Bacterial colony composition at the genus level during haylage ensiling.
Figure 2. (a) Bacterial colony composition at the phylum level during haylage ensiling. (b) Heatmap analysis at the bacterial phylum level in haylage silage. (c) Heatmap analysis at the bacterial genus level in haylage silage. (d) Bacterial colony composition at the genus level during haylage ensiling.
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Figure 3. Using PICRUSt2 to predict pathway function based on the EC pathway database: before and after fermentation (a), applied selenium or not (b). CK: not treated with sodium selenium; Se: sodium selenium treatment.
Figure 3. Using PICRUSt2 to predict pathway function based on the EC pathway database: before and after fermentation (a), applied selenium or not (b). CK: not treated with sodium selenium; Se: sodium selenium treatment.
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Figure 4. Bacterial correlation network of alfalfa haylage silage influenced by different silage times and additions of selenium (a–f). The node represents bacterial species, and the line thickness represents the strength of the correlation. The red line represents a positive correlation, and the green dashed line represents a negative correlation. CK: not treated with sodium selenium; Se: sodium selenium treatment.
Figure 4. Bacterial correlation network of alfalfa haylage silage influenced by different silage times and additions of selenium (a–f). The node represents bacterial species, and the line thickness represents the strength of the correlation. The red line represents a positive correlation, and the green dashed line represents a negative correlation. CK: not treated with sodium selenium; Se: sodium selenium treatment.
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Figure 5. Redundancy analysis (RDA) was used to predict the correlation between silage quality and the major microbial community: (a) RDA at the phylum level during haylage ensiling. (b) RDA at the genus level during haylage ensiling.
Figure 5. Redundancy analysis (RDA) was used to predict the correlation between silage quality and the major microbial community: (a) RDA at the phylum level during haylage ensiling. (b) RDA at the genus level during haylage ensiling.
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Table 1. Effects of sodium Se on the chemical composition of alfalfa haylage silage.
Table 1. Effects of sodium Se on the chemical composition of alfalfa haylage silage.
ItemsMowing PeriodCK ± SEMT ± SEMp Value
DM, g/kg FMBud302.90 ± 0.46292.28 ± 0.640.93
Initial bloom388.10 ± 1.45370.88 ± 0.620.62
Full bloom427.90 ± 0.62427.82 ± 0.680.89
CP, %DMBud20.42 ± 0.8020.76 ± 0.580.42
Initial bloom20.63 ± 0.2121.26 ± 0.62<0.05
Full bloom22.21 ± 0.2323.87 ± 0.59<0.05
NDF, %DMBud41.54 ± 2.1238.78 ± 1.610.24
Initial bloom40.80 ± 1.0838.67 ± 1.750.14
Full bloom37.52 ± 0.6936.31 ± 1.58<0.05
ADF, %DMBud33.31 ± 1.6631.14 ± 1.230.64
Initial bloom31.42 ± 1.4629.83 ± 1.800.29
Full bloom26.86 ± 1.4026.24 ± 1.530.27
Ash, %DMBud11.75 ± 0.3812.29 ± 0.21<0.05
Initial bloom10.99 ± 0.1210.95 ± 0.090.24
Full bloom10.11 ± 0.1010.00 ± 0.310.17
EE, %DMBud2.84 ± 0.133.04 ± 0.17<0.05
Initial bloom2.54 ± 0.142.67 ± 0.130.49
Full bloom2.60 ± 0.102.48 ± 0.190.78
Se, mg/kgBud1.33 ± 0.189.68 ± 0.81<0.05
Initial bloom0.85 ± 0.185.57 ± 0.08<0.05
Full bloom0.51 ± 0.092.80 ± 0.56<0.05
Note: Samples at 45 d after the start of ensiling; DM: dry matter; ADF: acid detergent fiber; Ash: crude ash; CP: crude protein; NDF: neutral detergent fiber; Se: total selenium content; CK: not treated with sodium selenium; T: sodium selenium treatment; and SEM: standard error of the mean.
Table 2. Effects of sodium selenium on the fermentation quality of alfalfa haylage silage.
Table 2. Effects of sodium selenium on the fermentation quality of alfalfa haylage silage.
ItemsMowing PeriodTreatment0 d1 d3 d7 d45 d
Ammonia-N,%TNBudCK0.53 Ac3.22 Ac6.27 Abc10.85 Aab13.16 ABab
T0.35 ABc1.23 Bc4.05 Bbc9.62 Aab13.70 Aa
Initial bloomCK0.31 ABd0.99 Bd1.73 Cd3.83 Bc10.28 ABa
T0.11 Bc0.83 Bbc3.04 BCbc3.05 Bbc7.68 BCa
Full bloomCK0.23 ABc0.22 Bc0.90 Cbc1.85 Bab3.29 Dab
T0.28 ABe0.75 Bd1.21 Cc1.56 Bc3.24 CDa
Lacticacid, %DMBudCK1.81 Ca2.47 Ba1.97 Aa2.91 Aa2.66 Aa
T1.71 Ca2.78 ABa2.60 Aa2.25 Aa2.76 Aa
Initial bloomCK1.23 Aa3.02 ABa2.67 Aa2.47 Aa3.11 ABCa
T1.45 Aa1.07 Ca2.72 Aa2.27 Aa2.69 BCa
Full bloomCK2.12 Acd3.89 Aab1.89 Ad3.23 Abc4.47 Aa
T2.63 Aa2.12 BCa2.62 Aa3.23 Aa3.63 ABa
Acetic acid, %DMBudCK0.16 Ab0.20 Ab0.40 ABb0.52 Aab0.78 Aa
T0.08 Ad0.20 Acd0.49 Aabc0.35 ABbcd0.66 Aab
Initial bloomCK0.11 Ac0.10 Ac0.07 Cc0.21 BCbc0.60 Aa
T0.09 Ab0.10 Ab0.18 BCb0.20 BCb0.54 Aa
Full bloomCK0.07 Aa0.07 Aa0.08 Ca0.14 BCa0.10 Aa
T0.04 Aa0.11 Aa0.12 Ca0.06 Ca0.06 Aa
Propionic acid, %DMBudCK0.08 Aa0.08 Aa0.11 BA0.08 Aa0.14 Aa
T0.08 Aa0.13 Aa0.21 Aa0.09 Aa0.16 Aa
Initial bloomCK0.08 Aa0.12 Aa0.07 Ba0.11 Aa0.15 Aa
T0.09 Aa0.06 Aa0.12 Ba0.10 Aa0.11 Aa
Full bloomCK0.10 Aa0.18 Aa0.11 Ba0.10 Aa0.18 Aa
T0.12 Aa0.14 Aa0.14 Ba0.14 Aa0.14 Aa
Butyric acid, %DMBudCK0.00 Bb0.00 Bb0.04 Aab0.01 BCab0.06 Aa
T0.04 ABa0.05 Aa0.04 Aa0.00 Ca0.05 Aa
Initial bloomCK0.08 Aab0.00 Bc0.04 Abc0.09 Aab0.08 Aab
T0.06 Bab0.01 Bb0.02 Ab0.05 Aab0.05 Aab
Full bloomCK0.07 ABa0.00 Bb0.02 Aab0.02 BCab0.05 Aab
T0.07 ABb0.01 Bb0.02 Aab0.05 ABab0.05 Aab
pHBudCK5.16 Ad5.52 Ac5.75 Aab5.86 Aa5.04 Ad
T5.00 ABb5.50 Aa5.74 Aa5.79 Aa4.95 Ab
Initial bloomCK4.99 ABd4.99 Bbc5.26 Bb5.50 Ba5.10 Acd
T4.97 ABbc5.16 Babc5.33 Ba5.38 BCa4.86 Ac
Full bloomCK5.19 Aa5.15 Ba5.19 Ba5.12 Da5.08 Aa
T5.20 Bb5.20 Ba5.24 Ba5.19 CDa5.01 Cb
Note: CK: not treated with sodium selenium; T: sodium selenium treatment; TN: total nitrogen; 0 d: no silage control; 1 d: samples were opened at 1 d; 3 d: samples were opened at 3 d; 7 d: samples were opened at 7 d; 45 d: samples were opened at 45 d; different small letters (a–e) represent significant differences on different days during the same period and in the same treatment; and the different capital letters (A–D) represent significant differences on the same silage days.
Table 3. Comprehensive analysis of the different mowing periods and different silage treatments.
Table 3. Comprehensive analysis of the different mowing periods and different silage treatments.
TreatmentCorrelation CoefficientAssociation Order
TB-450.6863
CKB-450.6185
TI-450.6724
CKI-450.6146
TF-450.7261
CKF-450.7252
Note: B, bud stage; I, initial bloom stage; F, full bloom stage; and 45, 45th date of silage.
Table 4. Alpha diversity indices of the haylage silage samples.
Table 4. Alpha diversity indices of the haylage silage samples.
TreatmentSilage TimeChao1Observed SpeciesShannonSimpson
CK0 d879.35 A863.67 A7.90 A0.98 A
1 d451.89 B445.67 BC6.60 B0.97 AB
3 d354.01 B333.67 C5.56 BCD0.95 ABC
7 d243.59 B234.00 C5.27 CD0.95 BC
45 d278.59 B267.00 C5.14 CD0.93 CD
T0 d763.79 A722.67 AB6.58 B0.95 BC
1 d321.69 B318.33 C6.03 BC0.96 ABC
3 d332.30 B313.33 C5.48 CD0.95 ABC
7 d350.02 B327.67 C5.03 CD0.93 CD
45 d244.27 B235.33 C4.76 D0.90 D
Note: CK: not treated with sodium selenium; T: sodium selenium treatment; and the same row (A–D) represents the significant difference in samples at the same silage time.
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Wang, K.; Wang, F.; Sun, S.; Zou, Y.; Gao, Z.; Hua, Y.; Qin, L.; Hu, G. Ensiling Characteristics, Bacterial Community Structure, Co-Occurrence Networks, and Their Predicted Functionality in Alfalfa Haylage Silage with or Without Foliar Selenium Application. Agronomy 2024, 14, 2709. https://doi.org/10.3390/agronomy14112709

AMA Style

Wang K, Wang F, Sun S, Zou Y, Gao Z, Hua Y, Qin L, Hu G. Ensiling Characteristics, Bacterial Community Structure, Co-Occurrence Networks, and Their Predicted Functionality in Alfalfa Haylage Silage with or Without Foliar Selenium Application. Agronomy. 2024; 14(11):2709. https://doi.org/10.3390/agronomy14112709

Chicago/Turabian Style

Wang, Kexin, Fengdan Wang, Shengnan Sun, Yilin Zou, Zifeng Gao, Yi Hua, Ligang Qin, and Guofu Hu. 2024. "Ensiling Characteristics, Bacterial Community Structure, Co-Occurrence Networks, and Their Predicted Functionality in Alfalfa Haylage Silage with or Without Foliar Selenium Application" Agronomy 14, no. 11: 2709. https://doi.org/10.3390/agronomy14112709

APA Style

Wang, K., Wang, F., Sun, S., Zou, Y., Gao, Z., Hua, Y., Qin, L., & Hu, G. (2024). Ensiling Characteristics, Bacterial Community Structure, Co-Occurrence Networks, and Their Predicted Functionality in Alfalfa Haylage Silage with or Without Foliar Selenium Application. Agronomy, 14(11), 2709. https://doi.org/10.3390/agronomy14112709

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