Skip to main content
Download PDF

Effective microorganism combinations improve the quality of compost-bedded pack products in heifer barns: exploring pack bacteria-fungi interaction mechanisms

BMC Microbiology volume 24, Article number: 302 (2024) Cite this article

Abstract

Background

Compost-bedded pack barns (CBP) are getting huge attention as an alternative housing system for dairy cows due to their beneficial impact on animal welfare. Effective microorganisms (EM) inoculums are believed to enhance compost quality, improve soil structure and benefit the environment. However, little information is available on the impact of incubation with external EM combinations on the barn environment, compost quality and microbial diversity in CBP. This experiment was carried out to investigate the effect of inoculating different combinations of EM [Lactobacillus plantarum (L), Compound Bacillus (B) and Saccharomyces cerevisiae (S)] on compost quality and microbial communities of CBP products, as well as the relationship with the heifers’ barn environment. CBP barns were subjected to the following four treatments: CON with no EM inoculum, LB/LS/LBS were Incubated with weight ratios of 1:2 (L: B), 1:2 (L: S), 1:1:1 (L: B: S), respectively.

Results

The EM inoculation (LB, LS, LBS) reduced the concentration of respirable particulate matter (PM10 and PM2.5) in the CBP, and decreased the serum total protein and total cholesterol levels in heifers. Notably, LBS achieved the highest content of high-density lipoprotein compared to other treatments. Microbiome results revealed that EM inoculation reduced the bacterial abundance (Chao1 index) and fungal diversity (Shannon & Simpson indexes), while increasing the relative abundance of various bacterial genera (Pseudomonas, Paracoccus, Aequorivita) and fungi (Pestalotiopsis), which are associated with cellulose decomposition that ultimately resulted in accelerating organic matter degradation and humification. Furthermore, high nutrient elements (TK&TP) and low mycotoxin content were obtained with EM inoculation, with LBS showing a particularly pronounced effect. Meanwhile, LBS contributed to a decline in the proportion of fungal pathogen categories but also led to an increase in fungal saprotroph categories.

Conclusion

Generally, EM inoculation positively impacted compost product quality as organic fertilizer and barn environment by modifying the abundance of cellulolytic bacteria and fungi, while inhibiting the reproduction of pathogenic microbes, especially co-supplementing with L, B and S achieved an amplifying effect.

Peer Review reports

Introduction

Growing global consumption of livestock products (especially dairy products) has led to an increased demand, resulting in the rapid development in livestock production. There were approximately 270 million dairy cows worldwide in 2020 [1] and this number is increasing gradually to meet the rising demand of livestock products. Consequently, the substantial amount of animal waste contributes to global environmental degradation [2]. Therefore, effective animal waste management and recycling have become critical challenges for sustainable livestock production systems nowadays. Proper utilization of animal waste includes composting [3], feed production [4], and biogas energy technology [5], while the implementation of an appropriate waste management system necessitates the consideration of political, economic, environmental, and other relevant factors.

In recent decades, the biological fermentation bed system has yielded positive outcomes in swine and poultry production. This system effectively integrated emission control of livestock manure, in-situ treatment of livestock pollution and animal welfare. As such, it represents an eco-friendly, clean production technology capable of achieving “near zero emission” from livestock [6, 7]. However, the application of the fermentation bed system to dairy cows is relatively different from swine and poultry and is termed compost-bedded pack barns (CBP) or “freewalk housing” [8]. Currently, the exploitation of CBP can improve animal health, growth performance, milk quality and welfare parameters in dairy cows [9, 10]. Furthermore, it can also mitigate environmental pollution caused by the disposal of manure and urine [11]. The selection of bedding material is the crucial factor affecting the comfort of dairy cows in CBP, materials commonly used include sawdust, due to its good water absorption properties, as well as rice husk and straw, which offer good air permeability [12, 13].

The key factor in CBP is the aerobic fermentation of microorganisms within the pack, as the primary goal is to promote the growth and reproduction of effective microorganisms (EM). This leads to increased microbial activity, generating heat and maintaining a dry pack [14]. Generally, EM mainly includes Lactobacillus, Bacillus, yeast, Actinomycetes and photosynthetic bacteria during the composting process which can produce cellulase, protease and several other enzymes that quickly decompose feces and urine, resulting in positive effects on composting and barn environment [15, 16]. Among them, Lactobacillus, Bacillus and yeast were widely used as microorganism supplements in livestock waste composting, benefiting the quality of compost products. For instance, Lactobacillus plantarum enhances the efficiency of sheep manure composting and the quality of final products [17]. Inoculating Lactobacillus acidophilus, Lactobacillus fermentum, and Bacillus subtilis into bovine manure supported with molasses could improve their nutritional, economic, and energetic value [18]. Co-inoculation with Trichoderma and Bacillus shortened the composting cycle and accelerated the degradation of lignocellulose [19].

Moreover, these EM can also modulate the microbial community and metabolites during composting. For example, adding 5% Bacillus megaterium to the mixed compost of pig manure and wheat straw can improve the growth of ammonia-oxidizing bacteria during the high-temperature period, which regulate nitrification and denitrification processes, leading to reduced ammonia and nitrous oxide emissions [20]. The addition of Bacillus coagulans increased the relative abundance of Firmicutes in the thermophilic and cooling stages and improved the total nitrogen content in cattle manure compost by modulating nitrification and denitrification activities [21]. Furthermore, the adjunction of compound microbial inoculums (Bacillus subtilis: Bacillus amyloliquefaciens: Bacillus licheniformis: Saccharomyces cerevisiae = 3:1:3:4) to pig and chicken manure compost increased the compost temperature, as well as the abundance of Actinobacteria and Bacteroidetes, while decreased the abundance of Firmicutes, resulting in enhanced fiber degradation and nitrogen retention [22].

Till now, studies on EM in biological fermentation bed systems have primarily focused on swine and poultry, while mainstream commercial strains were mainly purchased from Japan, e.g. EM-Bokashi, which has been widely used in agriculture and livestock production [16]. Recent research indicated the organic material generated from the compost barn confinement system could be used as an organic fertilizer and proved the positive effects on the plant growth and health [23]. However, there is limited information regarding EM application in CBP, particularly concerning the impact of inoculating different functional EM combinations to the pack on composting, because the addition of EM combinations appeared to maximize the quality of the compost product. For example, co-supplementation of Bacillus subtilis and Saccharomyces cerevisiae into swine manure was more improved on compost maturity and gas emissions than single and non-supplementation [24]. Therefore, we hypothesized that adding different EM combinations can improve the barn environment and the quality of compost-bedded pack products by modulating the microbial community within the pack.

Materials and methods

Experiment period, location and CBP facilities selection

This experiment was conducted at the dairy farm of Edweigang Modern Animal Husbandry Co., Ltd. (Sihong, Jiangsu, China) from April to November 2019. The area is situated at 33°08 ∼ 33°44 north latitude and 117°56 ∼ 118°46 east longitude with 28.6 m average altitude having an average temperature of around 14.3 °C, 893.9 mm average annual precipitation and 2356.4 h average annual sunshine hours.

Twelve CBP barns were selected from the dairy farm, with their specific location distribution shown in Fig. S1. Each barn featured a 580 m2 pack area and a 174 m2 feeding area (no bedding), having identical lighting and ventilation methods. Bedding material in the pack area consisted of 20% sawdust, 30% straw, 30% chaff and 20% dry cow dung with full cultivation at a depth of approximately 30 cm via a rototiller (WT-051575X, Shandong Weiken Technology Co., Ltd, China) during the daily morning feeding to promote the aerobic composting process.

Pack microbial inoculation and bedding management

Microbial inoculums were purchased in powder form from Haicheng Biotechnology Co., Ltd. (Yangzhou, China) that includes Compound Bacillus (B, 50% Bacillus subtilis, 30% Bacillus licheniformis and 20% Bacillus natto), Lactobacillus plantarum (L) and Saccharomyces cerevisiae (S) having live spores of 50 billion cfu/g, 6 billion cfu/g and 6 billion cfu/g respectively. The inoculums also included calcium carbonate as a carrier and polyvinyl alcohol as the supporting agent.

All CBP barns were subjected to the following four treatments (three barns each treatment) as described in Fig. S1: CON (no microbial inoculum added), LB (addition of L and B at 1:2 weight ratio), LS (addition of L and S at 1:2 weight ratio) and LBS (addition of L, B and S at 1:1:1 weight ratio). Microbial inoculums were mixed according to the specified ratios for each treatment, with 9 kg of mixed inoculums added per ton of bedding. Inoculums were configured using urea, salt, brown sugar and sterile water at a weight ratio of 10:1:1:100:1000, then fermented at a constant temperature of 37 ℃ in a fermenter for 3–5 days to activate the microbial inoculums. The activated inoculums were sprayed in different barns and turned the bedding evenly via a rototiller above-mentioned.

The initial pack cultivation occurred in early April 2019, with fresh bedding and microbial inoculants added at regular intervals of half a month based on the fermentation status of the pack throughout the experiment period. By the end of November (before winter), all the packs were cleaned out and used for fertilizer evaluation.

Management of heifers

Holstein heifers (total 168 heads) with an initial age of 16 ± 1.8 months and a body weight of 244.64 ± 28.95 kg were housed in these barns, fourteen were raised in each barn, maintaining an average density of 13.8 m2 per heifer. Heifers were given free access to the total mixed ration and clean drinking water. Total mixed ration composition included alfalfa, corn silage, corn, soybean meal, cottonseed meal and DDGS, having a 70:30 forage-to-concentrate ratio on the dry matter basis.

Sampling procedures and measurement

Barn environment assessment

The sampling date was scheduled in the middle of April, July, and November. Environmental indicators of each barn were measured over three consecutive days, then three sampling sites were selected within each barn (Fig. S1). At each site, three wet and dry bulb thermometers were placed evenly at a height of 1 m above the ground in each pen to record the temperature and relative humidity every 4 h daily (6 times a day), the average value of the above 3 sites and 6 time points were used for data analysis. The temperature-humidity index (THI) was calculated from the published formula [25]. In addition, a microcomputer laser dust meter (PC-3A(S), Qingdao Juchuang Environmental Protection Group Co., Ltd., China) was used to determine PM2.5 (particulate matter with a diameter ≤ 2.5 μm) and PM10 (particulate matter with a diameter ≤ 10 μm) of total suspended solids in the atmosphere. Ammonia was collected using a 0.01 mol/L sulfuric acid absorption liquid via atmospheric sampling machine (SY-GS-IIIB, Beijing Zhonghui Tiancheng Technology Co., Ltd., China) and measured by the Nessler’ reagent-colorimetry method.

Bedding sample collection and analysis

Simultaneously during environmental parameters monitoring, pack surface temperature and deep temperature were measured with a mercury thermometer. Depth was detected at this site and soil samplers were used to collect bedding samples from the top, middle and bottom layers at each sampling site. Finally, samples from three sites in each barn were thoroughly mixed and prepared as test samples according to the quartering method. pH was immediately measured with a pH meter (pHS-3 C, Shanghai, China) after homogenization according to the bedding and distilled water at a 1:5 ratio (W/V).

The bedding samples collected in November were used for nutrient detection, heavy metal and mycotoxins assessment and microbial sequencing. Moisture was determined by drying samples at 105 °C for 24 h. Total nitrogen (TN) was determined via a Kjeldahl analyzer (FoodALYT D4000, Bremen, Germany) and organic matter (OM) was calculated based on the ash content determined according to the protocol (method no. 923.03) [26]. Total phosphorus (TP) content was determined by ammonium molybdate spectrophotometry, while the sodium hydroxide melting-flame photometric method was used to determine total kalium (TK) content. Heavy metal ion content, including hydrargyrum (Hg), plumbum (Pb), chromium (Cr), cadmium (Cd), arsenic (As) and cuprum (Cu), was determined by Inductively Coupled Plasma Mass Spectrometers (iCAP RQ ICP-MS, Thermo Scientific, US) followed by the published protocol [27]. Furthermore, concentrations of mycotoxins (Aflatoxin B1, Deoxynivalenol, Ochratoxin and Zearalenone) were determined using the commercial manufacturer’s kits (CNW Technologies GmbH, Germany).

Bedding microbial DNA extraction and 16 S/ITS rRNA sequencing

Total genomic DNA of the bedding samples was extracted (HiPure Soil DNA Kit, D3142B, Magen, Guangzhou, China) and the quality and quantity of the extracted DNA were assessed (Nanodrop 2000, Thermo Fisher Scientific, Wilmington, DE, USA). Microbial populations in the bedding were characterized using bacterial 16 S rRNA and fungal ITS rRNA genes. The V3-V4 region of 16 S rRNA gene was amplified via GeneAmp® 9700 PCR instrument (ABI, CA, US) using primers 341 F (5′CCTACGGGNGGCWGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) while ITS2 region of ITS rRNA genes was amplified with primers ITS3F (5′-GCATCGATGAAGAACGCAGC-3′) and ITS4R (5′-TCCTCCGCTTATTGATATGC-3′). Finally, these amplified fragments were sequenced on the Illumina Novaseq PE250 sequencing platform (Genepioneer Biotechnologies Co., Ltd., Nanjing, China) as specific protocols referred to our previous publication [28].

Measurement of heifers’ blood indicators

The last day before all the pack was cleaned in late November, 7 Holstein heifers were randomly selected from each pen and 10 mL blood samples were collected from the tail vein with a disposable syringe before morning feeding. Concentrations of white blood cells, red blood cells, hemoglobin and platelets were determined by an automatic blood cell analyzer (BC-2600, Mindray, China). Serum was collected by centrifuging the blood samples at 4 °C and 3000 rpm for 10 min. Concentrations of glutaminase, aspartate aminotransferase, alkaline phosphatase, glutamyl-transferase, total bilirubin, total protein, albumin, globulin, lactate dehydrogenase, creatine kinase, urea, creatinine, glucose, cholesterol, triglycerides, high-density lipoprotein and low-density lipoprotein were measured following the protocols of manufacturer’s kits (Nanjing Jiancheng Biotechnology Research Institute, Nanjing, China).

Statistical analysis

Data related to barn environment and pack physical index were analyzed using PROC MIXED of SAS software (version 9.3, SAS Institute Inc., Cary, NC, USA) with treatment, month, treatment × month interaction as fixed effects and repeated sample as the random effect. PROC GLM procedure was employed for heifers’ blood indicators, bedding nutrient indicators, heavy metal content and mycotoxins, Tukey’s test was used for multiple comparisons, with significance declared at P < 0.05 and tendency at 0.05 ≤ P < 0.1.

Sequenced raw data were stitched and filtered followed by OTU clustering and species classification. Species richness and evenness were calculated in QIIME2. Principal coordinates analysis (PCoA) was performed based on Bray-Curtis dissimilarity matrix via “vegan” package and visualized via ggplot2 package in R program (v 3.6.1). Wilcoxon rank-sum test was utilized to analyze differences among treatments in phylum and genus levels. PICRUSt 2 package was performed to predict bacterial gene function according to the protocol detailed in our previous publication [29], while fungal functional annotation classification based on OTU abundance was carried out via FUNGuild software (Guilds_v1, https://github.com/UMNFuN/FUNGuild) [30]. Canonical correlation analysis (CCA) was applied to assess relationships between environmental factors, correlation networks were calculated and visualized by “Psych” R packages (with q-values < 0.05 or |r| >0.5 was considered a significant correlation) and Gephi software (version 0.9.2).

Results

Barn environment factors

In this study, variations in temperature, relative humidity, and THI were observed across different sampling months. Temperature and THI values were highest in July, while relative humidity peaked in April (Fig. 1A-C). Although no significant differences were found among treatments (P < 0.05), however, higher barn temperature led to an elevated THI (highest 84.3). Ammonia concentration also increased in July (month: P < 0.05; Fig. 1D). Furthermore, compared with CON, EM addition significantly reduced the content of barn environmental PM10 and PM2.5 (treatment: P < 0.05; Fig. 1E, F).

Fig. 1
figure 1

Barn environmental indicators in CBP added different combinations of microbial inoculants in different months. (A) Temperature; (B) Relative humidity; (C) Temperature-humidity index (THI); (D) Ammonia concentration; (E, F) PM2.5 and PM10 contents of total suspended solids in the atmosphere. a, b values with different superscripts differ significantly at p < 0.05. T: treatment; M: month; T*M: interaction between T and M. Treatments: CON (no microbial inoculum added), LB (addition of L and B at 1:2 weight ratio), LS (addition of L and S at 1:2 weight ratio), LBS (addition of L, B and S at 1:1:1 weight ratio). L: Lactobacillus plantarum; B: Compound Bacillus; S: Saccharomyces cerevisiae

Full size image

Bedding general characteristics and nutrient contents

Surface temperature (highest in July), deep temperature (highest in July) and depth (highest in November) of the bedding exhibited significant fluctuations with sampling month across the four treatments, though no significant differences were observed across treatments (Fig. S2A-C; month: P < 0.05; treatment: P > 0.05). The pH value of the bedding showed no significant variation across different months or treatments (Fig. S2D).

According to Table 1, moisture content did not differ significantly among treatments (P > 0.05), while OM content in LS and LBS was lower than CON (P < 0.05). Conversely, TK content increased in these two treatments (P < 0.05). Additionally, EM inoculation led to a significant increase in the TP content and a reduction in the C/N ratio (P < 0.05).

Table 1 Bedding nutrient content in CBP added different EM combinations
Full size table

Bedding heavy metal and mycotoxin contents

It can be seen from Table 2 that LS and LBS increased total Cr concentration and decreased total Cu concentration compared with CON and LB (P < 0.05), while there was no difference in concentrations of total Hg, Pb, Cd and As (P > 0.05). Moreover, the above heavy metal content was within the scope of the national standard for organic fertilizer in China (NY525-2021).

Table 2 Bedding heavy metal content in CBP added different EM combinations (mg/kg)
Full size table

Table 3 revealed EM inoculation reduced the content of aflatoxin B1 (P < 0.05), while Ochratoxin A content in LS and LBS was lower than CON (P < 0.05), and no significant difference was found in the concentrations of Deoxynivalenol and Zearalenone (P > 0.05).

Table 3 Bedding mycotoxin content in CBP added different EM combinations
Full size table

Bedding bacterial community

A total of 991,224 original readings of 16S rRNA genes were obtained from bedding samples, with an average of 82,602 valid tags following quality control. Finally, 2,790 OTUs were generated across all the samples, with an average of 1174 OTUs per sample. There were 243 shared OTUs and 120 / 192 / 245 / 147 unique OTUs in CON / LB / LS / LBS respectively (Fig. 2A). The PCoA results based on Bray-Curtis dissimilarity matrix (Fig. 2B) revealed significant differences in bacterial communities (PERMANOVA: P = 0.007), regarding bacterial alpha diversity (Table S2), EM inoculation significantly reduced the Chao1 index (P < 0.05) while Shannon and Simpson indexes had no differences among treatments (P > 0.05).

Fig. 2
figure 2

Bedding bacterial diversity and taxonomic differences. (A) Rank abundance curves and Venn diagrams based on 16S. (B) Principal coordinate analysis (PCoA) of bacteria based on Bray-Curtis dissimilarity matrix. Bacterial compositions at the phylum (C) and genus (D) levels. Bar chart based on Wilcoxon rank-sum test at the phylum (E) and genus (F) levels. Bar charts with different letters represent p < 0.05. Treatments: CON (no microbial inoculum added), LB (addition of L and B at 1:2 weight ratio), LS (addition of L and S at 1:2 weight ratio), LBS (addition of L, B and S at 1:1:1 weight ratio). L: Lactobacillus plantarum; B: Compound Bacillus; S: Saccharomyces cerevisiae

Full size image

At the phylum level (Fig. 2C), Proteobacteria (28.27-47.15%), Bacteroidetes (30.53-38.54%) and Actinobacteria (6.19-12.15%) were top 3 dominant bacteria, while the relative abundance of Chloroflexi, Planctomycetes and Acidobacteria were lower in LB and LBS compare to CON (P < 0.05, Fig. 2E). Conversely, the abundance of Actinobacteria in LS and LBS was higher compared with CON (P < 0.05, Fig. 2E). in terms of genus level, Luteimonas, Chryseolinea and Galbibacter were predominant (Fig. 2D). EM inoculation significantly increased the relative abundance of Luteimonas and Galbibacter (P < 0.05) (Fig. 2F). In addition, LS and LBS reduced the abundance of Chryseolinea but increased the abundance of Pseudomonas, Paracoccus and Aequorivita (P < 0.05).

Bedding fungal community

Totally 640,128 raw tags were derived from ITS rRNA gene sequencing with an average of 53,344 effective tags obtained from all samples after quality control. Based on the effective tags of all samples, OTUs clustering with 97% identity resulted in 1067 OTUs (494 per sample on average). Shared OTUs were 114 and 96 / 58 / 46 / 54 were unique OTUs in CON / LB / LS / LBS (Fig. 3A). The rank abundance curve for relative abundance plateaued at an OTU rank of 400 and the species distribution was uniform which can be used for the comprehensive analysis of fungal components. The PCoA results (Fig. 3B) had shown significant differences in fungal communities among treatments (PERMANOVA: P = 0.045). Fungal alpha diversity results (Table S2) indicated that EM inoculation significantly reduced Shannon and Simpson indexes (P < 0.05), while no differences were found in Chao1 index (P > 0.05).

Fig. 3
figure 3

Bedding fungal diversity and taxonomic differences. (A) Rank abundance curves and Venn diagrams based on ITS. (B) Principal coordinate analysis (PCoA) of fungi based on Bray-Curtis dissimilarity matrix. Fungal compositions at the phylum (C) and genus (D) levels. Bar chart based on Wilcoxon rank-sum test at the phylum (E) and genus (F) levels. Bar charts with different letters represent p < 0.05. Treatments: CON (no microbial inoculum added), LB (addition of L and B at 1:2 weight ratio), LS (addition of L and S at 1:2 weight ratio), LBS (addition of L, B and S at 1:1:1 weight ratio). L: Lactobacillus plantarum; B: Compound Bacillus; S: Saccharomyces cerevisiae

Full size image

Ascomycota (65.99%), Basidiomycota (1.58%) and Mortierellomycota (0.91%) were 3 most abundant fungal communities at the phylum level (Fig. 3C), with no differences were found among treatments (P > 0.05; Fig. 3E). At the genus level (Fig. 3D), Pestalotiopsis, Fusarium and Bipolaris were dominant, while EM inoculation increased the relative abundance of Pestalotiopsis (P < 0.05). Notably, EM inoculation decreased the relative abundance of Scedosporium and Triadelphia (P < 0.05; Fig. 3F). Moreover, LB and LBS increased the abundance of Cladorrhinum (P < 0.05).

Microbial functional enrichment

Functional predictions based on KEGG pathways (Fig. 4A) revealed that bacterial pathways were predominantly associated with metabolism (69.12–71.19%), gene information processing (13.65–15.15%), environmental information processing (7.60-10.21%) and cellular processes (3.42–4.02%). EM inoculation significantly increased the abundance of relevant secondary pathway-related sequences in metabolism, including amino acid metabolism and carbohydrate metabolism (Fig. 4B, C). Key pathways impacted included arginine and proline metabolism, histidine metabolism, tyrosine metabolism, phenylalanine metabolism, tryptophan metabolism, pyruvate metabolism, starch and sucrose metabolism.

Fig. 4
figure 4

Functional annotation of bacteria and fungi based on 16S/ITS gene copy number. (A) Heatmap of secondary pathway abundance of each sample based on KEGG annotation. (B) Amino acid metabolism at KEGG level 3. (C) Carbohydrate metabolism at KEGG level 3. (D) Histogram of abundance annotated by fungal functional classification for each sample, while the heatmap represents fungal categories with notable differences among the treatments. Treatments: CON (no microbial inoculum added), LB (addition of L and B at 1:2 weight ratio), LS (addition of L and S at 1:2 weight ratio), LBS (addition of L, B and S at 1:1:1 weight ratio). L: Lactobacillus plantarum; B: Compound Bacillus; S: Saccharomyces cerevisiae

Full size image

Fungal functional annotation classification (Fig. 4D) revealed that the majority of functions were categorized as saprotroph (42.02%), pathotroph-saprotroph-symbiotroph (23.89%) and pathotroph (20.78%), which were further subdivided into undefined saprotroph, plant pathogen, animal pathogen, wood saprotroph and ectomycorrhizal. Notably, inoculating LBS in the bedding reduced the proportion of plant pathogen and animal pathogen categories while increasing the proportion of wood saprotroph and soil saprotroph categories (Fig. 4D).

Heifers’ blood indicators

Table S1 indicated no differences were found in the whole blood cell indicators among treatments (P > 0.05), while EM addition significantly reduced the serum aspartate aminotransferase and total protein content in heifers (P < 0.05). Notably, LB and LBS reduced the total cholesterol content compared with CON (P < 0.05), LBS also led to an increase in high-density lipoprotein (P < 0.05).

Interaction of microbial community, barn environment factors and heifers’ blood indicators

A significant correlation was observed between environmental factors and microbial community structure (Fig. 5). Correlation scores with bacteria ranked as: Temperature > C/N ratio > TN > TK > pH value > OM > Moisture > TP (Fig. 5A). In contrast, the rankings for fungi were: TN > OM > temperature > TP > TK > C/N ratio > pH value > Moisture (Fig. 5B). Results showed both temperature and TN seem to have a high impact on the structure of bacterial and fungal communities, variance partitioning analysis (VPA) was performed to quantify the influence of these two environmental factors on community structure changes, these environmental factors contributed to explaining 59.93% of the variance in bacterial communities and 40.32% in fungal communities respectively, with highest explanatory ratio contributed by temperature (0.4391 for bacteria and 0.2330 for fungi).

Fig. 5
figure 5

Canonical correlation analysis (CCA) of bacterial community at OTU abundance (A) based on 16S rDNA sequencing and the CCA of fungal community at OTU abundance (B) based on ITS sequencing, meanwhile variance partitioning analysis (VPA) was carried out with temperature and TN as environmental factors for bacterial/fungal communities. Treatments: CON (no microbial inoculum added), LB (addition of L and B at 1:2 weight ratio), LS (addition of L and S at 1:2 weight ratio), LBS (addition of L, B and S at 1:1:1 weight ratio). L: Lactobacillus plantarum; B: Compound Bacillus; S: Saccharomyces cerevisiae

Full size image

Spearman’s rank correlation network (Fig. S3) demonstrated intricate and significant interactions among bedding microbiota (bacteria and fungi), barn environment factors and heifers’ blood indicators. Among all the interactions, linkages between bacteria and fungi communities were notably complex, and these microbial communities were also closely related to heifers’ blood indicators. In terms of barn environmental factors, PM10 and PM2.5 exhibited the most extensive connections with both bacteria/fungi communities and heifers’ blood indicators (7 connections in total), followed by ammonia (3 connections).

Discussion

Environmental monitoring of barns is crucial for optimizing dairy production, it was observed that THI in July ranged from 79 to 88, potentially leading to moderate heat stress of heifers [31]. This highlights the importance of maintaining appropriate temperature and humidity in CBP during summer. Additionally, both pack surface and deep temperatures were elevated in July, further contributing to the heat stress risk. The increase in temperature was also associated with a rise in ammonia concentration within the barns, consistent with the previous publication [32]. However, EM inoculation seemed to decrease PM10 and PM2.5 concentrations, high levels of respirable particulate matter are the primary factor leading to respiratory diseases in animals, it has been indicated that suspended solids in the air of livestock houses will be adsorbed on the surface of the pores or liquid of CBP, EM inoculation involved in the decomposition and digestion of malodorous substances in feces and urine during the adsorption process, thereby minimizing volatilization in the air [33].

It has been reported that EM inoculants had a conspicuous beneficial effect on the fixation of TN and TP contents of compost [21, 34, 35]. Additionally, the combination of EM inoculum (Bacillus sp., Actinomycetes sp., Lactobacillus sp., Saccharomyces sp., and Trichoderma sp.) maximized the content of TP (48%) and TK (38%) [36], which aligned with the findings observed for LB and LBS in this experiment, suggesting the combination of Lactobacillus and Bacillus in improving the nutrient content of compost to some extent. Furthermore, C/N ratio of LBS was higher than that of LB and LS, indicating that the combination of three EM inoculums might be more beneficial to carbon sequestration during composting [37].

High concentrations of metal elements and mycotoxins could lead to the spread chain of biological toxicity. It has been proposed that Lactobacillus and Bacillus were useful biosorbents for toxins and heavy metals to reduce their bioavailability [38, 39]. Candida utilis can reduce the mobility of composting heavy metals and mitigate the heavy metal residues in plants after subsequent fertilization [40]. Moreover, inoculation of yeast strains was beneficial to the fixation of Cr in soil and the transfer of Cu and Zn [41], which might explain higher Cr and lower Cu contents in LS and LBS. Meanwhile, Ochratoxin A was decreased in LS and LBS, as yeast can effectively degrade and adsorb Ochratoxin A [42].

Consistent with previous research that utilized cow manure and wood chips as composting materials, which identified Luteimonas, Pseudomonas and Steroidobacter as the predominant bacterial genera at the maturity stage [43], our study also observed these genera among the top ten. Furthermore, our findings corroborate previous observations that Ascomycetes and Pestalotiopsis were the dominant fungal phyla and genera during the decomposition stage when cow manure was used as the composting substrate [33]. Moreover, inoculation of EM consisting of Lactobacillus spp., yeast species, Bacillus spp., photosynthetic bacteria and Actinomycetes spp., decreased the diversity of bacteria and fungi in swine feces as well as the bioavailability of Cu and Pb [44]. Our study similarly found that EM inoculation reduced the diversity of bacteria and fungi in the bedding. Notably, EM inoculation increased the abundance of Actinobacteria, Pseudomonas and Pestalotiopsis, which are known to enhance the decomposition of OM, such as fiber, and contribute to compost maturity [45,46,47].

In addition, the introduction of 32 cellulose-degrading bacterial species, including Paracoccus denitrificans, into a mixture of chicken manure and corn straw accelerated OM decomposition, extended the high-temperature period, and improved the maturity of the compost products [48]. Aequorivita sp., known for its antibacterial and insect-repellent properties, has been employed to degrade organic pollutants [49]. Our observations revealed an upregulation of Paracoccus and Aequorivita in LS and LBS. The co-digestion of yeast and chicken manure has been shown to increase the reaction rate of OM [50], suggesting that S inoculation may play a critical role in OM degradation in our study. Cladorrhinum (belonging to the Ascomycetes phylum), which increased in LB and LBS, shows promising applications in the biological control of plant pathogens and promotion of plant growth [51], which underscored the potential role of EM, particularly Bacillus, in pathogen inhibition during composting in our study.

Previous research has demonstrated that an increase in the gene copy number associated with bacterial amino acid metabolism pathways during composting accelerates amino acid production and humus synthesis [52]. Moreover, a recent study indicated that inoculation with Bacillus licheniformis enhances carbohydrate metabolism by enriching genes involved in starch and sucrose metabolism, glycolysis/gluconeogenesis, and pyruvate metabolism [53]. Based on our study, EM combinations improved the metabolism of relevant amino acids and carbohydrates in the bedding, especially co-inoculation with L, B and S seemed to maximize the effect. It has been reported that pathogenic fungi gradually disappeared and woody saprophytes increased as composting time progressed [33]. Saprophytic fungi also held great importance during the recycling phase in our experiment. Notably, the proportion of pathogens decreased and saprotrophs increased in LBS combination, it has been reported the co-addition of L, Bacillus subtilis and S reduced the relative abundance of pathogens in cabbage waste composting [54]. Meanwhile, L, B and S all played crucial roles in inhibiting plant and soil pathogens [55,56,57], the synergistic combination of these three microorganisms appears to be a key factor in inhibiting fungal pathogens within the bedding and promoting decomposition in this experiment.

Blood physiological and biochemical indexes reflect health, metabolism and immunity. EM inoculation reduced the blood aspartate aminotransferase and total protein content in heifers, the content of aspartate aminotransferase reflects the metabolic function of liver and shows a negative correlation with immune function [58], so EM inoculation might improve the barn environment (by reducing the content of respirable particulate matter), enhance body immunity, and reduce the burden on the liver. Studies have demonstrated that L, B and S have positive effects on animal lipid metabolism [59,60,61], it was worth noting that LBS reduced the total cholesterol content but increased the content of high-density lipoprotein, whereas the content of total cholesterol (negative correlation) and high-density lipoprotein (positive correlation) were all related to the ability of lipid metabolism. Therefore, the application of combinations of L, B and S at a 1:1:1 ratio on compost package might have a positive effect on lipid metabolism of heifers in this experiment.

Recent studies indicated that composting temperature significantly affects bacterial microbiota [62], and the fungal community in compost products is positively correlated with TN, TP and TK [63]. Similarly, in our study, temperature and TN were the primary factors affecting bacterial and fungal communities, respectively, which implied that EM gradually decomposes OM and harmful substances after composting, accelerating the formation of humus precursor substances. The complex network of bacteria and fungi in the bedding indirectly affects the barn environment and the heifers’ blood indicators, the interaction between these microbial communities can impact various environmental factors, such as air quality and nutrient cycling, which in turn can affect the health status of the heifers. Overall, we can report that the combination of L, B, and S appears to be the dominant combination in this study.

Conclusions

In summary, inoculating EM into the bedding improved the barn environment by reducing PM10 and PM2.5 concentrations, it also increased high-density lipoprotein content and reduced cholesterol levels, ultimately enhancing the blood metabolism status of heifers. Moreover, EM inoculation elevated the relative abundance of cellulolytic bacteria and fungi in the bedding, such as Pseudomonas and Pestalotiopsis, thereby improving OM decomposition and accelerating composting. Additionally, EM inoculation served as a promoter by inhibiting pathogenic microbes and demonstrated good ecological recycling safety, evidenced by low mycotoxin content, along with high nutrient levels (TK & TP) (Fig. 6). Overall, inoculation with L, B and S at 1:1:1 weight ratio had the most beneficial effect on compost product quality by modifying bacterial and fungal communities, with the improvement in barn environment and blood metabolism status of heifers.

Fig. 6
figure 6

Schematic representation showing potential mechanisms of regulating the microbial community of the bedding to improve the quality of compost products as incubation of L, B and S at 1:1:1 weight ratio. P: Phosphorus; K: Kalium; Cu: Cuprum; AFB1: Aflatoxin B1; OTA: Ochratoxin A; L: Lactobacillus plantarum; B: Compound Bacillus; S: Saccharomyces cerevisiae

Full size image

Data availability

The Illumina sequencing raw data (16 S and ITS of bedding samples) were deposited to the NCBI Sequence Read Archive database under a BioProject PRJNA980083 and BioSample accessions SAMN35620207 (16S), SAMN35620208 (ITS).

References

  1. Food and Agriculture Organization of the United Nations. [https://www.fao.org/faostat/]

  2. Varma VS, Parajuli R, Scott E, Canter T, Lim TT, Popp J, Thoma G. Dairy and swine manure management – challenges and perspectives for sustainable treatment technology. Sci Total Environ. 2021;778:146319.

    Article  CAS  PubMed  Google Scholar 

  3. Bernal MP, Alburquerque JA, Moral R. Composting of animal manures and chemical criteria for compost maturity assessment. A review. Bioresour Technol. 2009;100(22):5444–53.

    Article  CAS  PubMed  Google Scholar 

  4. Green BW. Substitution of organic manure for pelleted feed in tilapia production. Aquaculture. 1992;101(3):213–22.

    Article  Google Scholar 

  5. Obaja D, Macé S, Mata-Alvarez J. Biological nutrient removal by a sequencing batch reactor (SBR) using an internal organic carbon source in digested piggery wastewater. Bioresour Technol. 2005;96(1):7–14.

    Article  CAS  PubMed  Google Scholar 

  6. Wang JM, Gan XM, Pu FJ, Wang WX, Ma M, Sun LL, Hu JW, Hu B, Zhang RP, Bai LL, et al. Effect of fermentation bed on bacterial growth in the fermentation mattress material and cecum of ducks. Arch Microbiol. 2021;203(4):1489–97.

    Article  CAS  PubMed  Google Scholar 

  7. Chen Q, Wang J, Zhang H, Shi H, Liu G, Che J, Liu B. Microbial community and function in nitrogen transformation of ectopic fermentation bed system for pig manure composting. Bioresour Technol. 2021;319:124155.

    Article  CAS  PubMed  Google Scholar 

  8. Leso L, Barbari M, Lopes MA, Damasceno FA, Galama P, Taraba JL, Kuipers A. Invited review: compost-bedded pack barns for dairy cows. J Dairy Sci. 2020;103(2):1072–99.

    Article  CAS  PubMed  Google Scholar 

  9. Guzmán-Luna P, Nag R, Lede I, Mauricio-Iglesias M, Hospido A, Cummins E. Quantifying current and future raw milk losses due to bovine mastitis on European dairy farms under climate change scenarios. Sci Total Environ. 2022;833:1–10.

    Article  Google Scholar 

  10. Bewley J, Robertson LM, Eckelkamp EA. A 100-year review: lactating dairy cattle housing management. J Dairy Sci. 2017;100:10418–31.

    Article  CAS  PubMed  Google Scholar 

  11. Giambra IJ, Jahan Y, Yin T, Engel P, Weimann C, Brügemann K, König S. Identification of thermophilic aerobic sporeformers in bedding material of compost-bedded dairy cows using microbial and molecular methods. Animals. 2021;11(10):2890.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Ferraz PFP, Ferraz GAS, Leso L, Klopčič M, Barbari M, Rossi G. Properties of conventional and alternative bedding materials for dairy cattle. J Dairy Sci. 2020;103(9):8661–74.

    Article  CAS  PubMed  Google Scholar 

  13. Bertocchi L, Fusi F, Angelucci A, Bolzoni L, Pongolini S, Strano RM, Ginestreti J, Riuzzi G, Moroni P, Lorenzi V. Characterization of hazards, welfare promoters and animal-based measures for the welfare assessment of dairy cows: elicitation of expert opinion. Prev Vet Med. 2018;150:8–18.

    Article  PubMed  Google Scholar 

  14. Eckelkamp EA, Taraba JL, Akers KA, Harmon RJ, Bewley JM. Understanding compost bedded pack barns: interactions among environmental factors, bedding characteristics, and udder health. Livest Sci. 2016;190:35–42.

    Article  Google Scholar 

  15. Harindintwali JD, Zhou J, Yu X. Lignocellulosic crop residue composting by cellulolytic nitrogen-fixing bacteria: a novel tool for environmental sustainability. Sci Total Environ. 2020;715:136912.

    Article  CAS  PubMed  Google Scholar 

  16. Yamada K, Xu H-l. Properties and applications of an organic fertilizer inoculated with effective microorganisms. J Crop Prod. 2000;3:255–68.

    Article  CAS  Google Scholar 

  17. Li W, Liu Y, Hou Q, Huang W, Zheng H, Gao X, Yu J, Kwok L-y, Zhang H, Sun Z. Lactobacillus plantarum improves the efficiency of sheep manure composting and the quality of the final product. Bioresour Technol. 2020;297:122456.

    Article  CAS  PubMed  Google Scholar 

  18. Romero-Mota DI, Estrada-García J, Sales-Pérez RE, Méndez-Contreras JM. Valorization of bovine manure and molasses by the production of lactic acid and biomass through probiotic anaerobic cofermentation with lactobacillus acidophilus, lactobacillus fermentum, and bacillus subtilis. J Environ Eng. 2024;150(2):04023100.

    Article  CAS  Google Scholar 

  19. Wang S, Long H, Hu X, Wang H, Wang Y, Guo J, Zheng X, Ye Y, Shao R, Yang Q. The co-inoculation of trichoderma viridis and bacillus subtilis improved the aerobic composting efficiency and degradation of lignocellulose. Bioresour Technol. 2024;394:130285.

    Article  CAS  PubMed  Google Scholar 

  20. Guo H, Gu J, Wang X, Nasir M, Yu J, Lei L, Wang J, Zhao W, Dai X. Beneficial effects of bacterial agent/bentonite on nitrogen transformation and microbial community dynamics during aerobic composting of pig manure. Bioresour Technol. 2020;298:122384.

    Article  CAS  PubMed  Google Scholar 

  21. Liu B, Chen W, Wang Z, Guo Z, Li Y, Xu L, Wu M, Yin H. The impact of bacillus coagulans x3 on available nitrogen content, bacterial community composition, and nitrogen functional gene levels when composting cattle manure. Agronomy. 2024;14(3):587.

    Article  CAS  Google Scholar 

  22. Cao R, Huang Y, Li R, Li K, Ren Z, Wu J. Regulation of nitrogen transformation and microbial community by inoculation during livestock manure composting. Env Microbiol Rep. 2024;16(2):e13256.

    Article  CAS  Google Scholar 

  23. Laurindo G, Ferraz G, Damasceno F, Ferraz P, Neto P, Castro R, Silva J, Barbari M, Becciolini VJAR. Use of compost from a compost barn installation as organic fertilizer. Agron Res. 2024;22:464–72.

    Google Scholar 

  24. Jeon K, Song M, Lee J, Oh H, Chang S, Song D, An J, Cho H, Park S, Kim H et al. Effects of single and complex probiotics in growing-finishing pigs and swine compost. J Anim Sci Technol. 2023.

  25. Bohmanova J, Misztal I. Temperature-humidity indices as indicators of milk production losses due to heat stress. J Dairy Sci. 2007;90:1947–56.

    Article  CAS  PubMed  Google Scholar 

  26. AOAC: Association of Official Analytical Chemists: Official Methods of Analysis. In: AOAC: official methods of analysis. vol. 1. 2005: 69–90.

  27. Srivastava SK, Tyagi R, Pant N. Adsorption of heavy metal ions on carbonaceous material developed from the waste slurry generated in local fertilizer plants. Water Res. 1989;23(9):1161–5.

    Article  CAS  Google Scholar 

  28. Zhang Z, Shahzad K, Shen S, Dai R, Lu Y, Lu Z, Li C, Chen Y, Qi R, Gao P, et al. Altering dietary soluble protein levels with decreasing crude protein may be a potential strategy to improve nitrogen efficiency in Hu Sheep based on rumen microbiome and metabolomics. Front Nutr. 2021;8:815358.

    Article  PubMed  Google Scholar 

  29. Zhang Z, Wei W, Yang S, Huang Z, Li C, Yu X, Qi R, Liu W, Loor JJ, Wang M, et al. Regulation of dietary protein solubility improves ruminal nitrogen metabolism in vitro: role of bacteria–protozoa interactions. Nutrients. 2022;14(14):2972.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Nguyen NH, Song Z, Bates ST, Branco S, Tedersoo L, Menke J, Schilling JS, Kennedy PG. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 2016;20:241–8.

    Article  Google Scholar 

  31. Armstrong DV. Heat stress interaction with shade and cooling. J Dairy Sci. 1994;77(7):2044–50.

    Article  CAS  PubMed  Google Scholar 

  32. Rhoads M, Rhoads R, VanBaale MJ, Collier R, Sanders SR, Weber WJ, Crooker BA, Baumgard L. Effects of heat stress and plane of nutrition on lactating Holstein cows: I. Production, metabolism, and aspects of circulating somatotropin. J Dairy Sci. 2009;92:1986–97.

    Article  CAS  PubMed  Google Scholar 

  33. Wang K, Yin X, Mao H, Chu C, Tian Y. Changes in structure and function of fungal community in cow manure composting. Bioresour Technol. 2018;255:123–30.

    Article  CAS  PubMed  Google Scholar 

  34. Nigussie A, Dume B, Ahmed M, Mamuye M, Ambaw G, Berhiun G, Biresaw A, Aticho A. Effect of microbial inoculation on nutrient turnover and lignocellulose degradation during composting: a meta-analysis. Waste Manag. 2021;125:220–34.

    Article  CAS  PubMed  Google Scholar 

  35. Liu N, Liu Z, Wang K, Zhao J, Fang J, Liu G, Yao H, Pan J. Comparison analysis of microbial agent and different compost material on microbial community and nitrogen transformation genes dynamic changes during pig manure compost. Bioresour Technol. 2024;395:130359.

    Article  CAS  PubMed  Google Scholar 

  36. Liu Y, Li C, Zhao B, Zhang J, Qiu R. Inoculation of prickly pear litter with microbial agents promotes the efficiency in aerobic composting. Sustainability. 2022;14(8):4824.

    Article  CAS  Google Scholar 

  37. Duan M, Zhang Y, Zhou B, Qin Z, Wu J, Wang Q, Yin Y. Effects of bacillus subtilis on carbon components and microbial functional metabolism during cow manure–straw composting. Bioresour Technol. 2020;303:122868.

    Article  CAS  PubMed  Google Scholar 

  38. Zoghi A, Massoud R, Todorov SD, Chikindas ML, Popov I, Smith S, Khosravi-Darani K. Role of the lactobacilli in food bio-decontamination: friends with benefits. Enzyme Microb Technol. 2021;150:109861.

    Article  CAS  PubMed  Google Scholar 

  39. Alotaibi BS, Khan M, Shamim S. Unraveling the underlying heavy metal detoxification mechanisms of bacillus species. Microorganisms. 2021;9(8):1628.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Li X, Wei Y, Liu C, Wang P, Wang L, Jin S, et al. Effects of the combined candida utilis and physical passivator on heavy metal passivation, compost quality and plant growth. SSRN Electron J. 2024.

  41. Aziza K, Naïma EG, Naoual R, Khalid D, Mustapha I, Wifak B. Leaching of heavy metals and enzymatic activities in un-inoculated and inoculated soils with yeast strains. Soil Sediment Contam. 2020;29(8):860–79.

    Article  CAS  Google Scholar 

  42. Pfliegler WP, Pusztahelyi T, Pócsi I. Mycotoxins – prevention and decontamination by yeasts. J Basic Microbiol. 2015;55(7):805–18.

    Article  CAS  PubMed  Google Scholar 

  43. Zhong X-Z, Ma S-C, Wang S-P, Wang T-T, Sun Z-Y, Tang Y-Q, Deng Y, Kida K. A comparative study of composting the solid fraction of dairy manure with or without bulking material: performance and microbial community dynamics. Bioresour Technol. 2018;247:443–52.

    Article  CAS  PubMed  Google Scholar 

  44. Zhou H, Shen Y, Li R, Meng H, Zhang X, Wang J, Cheng H, Dong S, Song L, Ding J, et al. Heavy metals and community structure of microorganism changes during livestock manure composting with inoculation of effective microorganisms. Int J Agr Biol Eng. 2020;13(6):125–32.

    Google Scholar 

  45. Guo Y, Rene ER, Wang J, Ma W. Biodegradation of polyaromatic hydrocarbons and the influence of environmental factors during the co-composting of sewage sludge and green forest waste. Bioresour Technol. 2020;297:122434.

    Article  CAS  PubMed  Google Scholar 

  46. Zhao Y, Lu Q, Wei Y, Cui H, Zhang X, Wang X, Shan S, Wei Z. Effect of actinobacteria agent inoculation methods on cellulose degradation during composting based on redundancy analysis. Bioresour Technol. 2016;219:196–203.

    Article  CAS  PubMed  Google Scholar 

  47. Osono T, Takeda H. Fungal decomposition of abies needle and betula leaf litter. Mycologia. 2006;98(2):172–9.

    Article  CAS  PubMed  Google Scholar 

  48. Wan L, Wang X, Cong C, Li J, Xu Y, Li X, Hou F, Wu Y, Wang L. Effect of inoculating microorganisms in chicken manure composting with maize straw. Bioresour Technol. 2020;301:122730.

    Article  CAS  PubMed  Google Scholar 

  49. Palma Esposito F, Ingham CJ, Hurtado-Ortiz R, Bizet C, Tasdemir D, de Pascale D. Isolation by miniaturized culture chip of an Antarctic bacterium aequorivita sp. with antimicrobial and anthelmintic activity. Biotechnol Rep. 2018;20:e00281.

    Article  Google Scholar 

  50. Fang H, Shi Y, Li D, Song L, Li Y-Y, Liu R, Yuan D, Niu Q. Synergistic co-digestion of waste commercial yeast and chicken manure: kinetic simulation, DOM variation and microbial community assessment. Renew Energ. 2020;162:2272–84.

    Article  CAS  Google Scholar 

  51. Barrera VA, Martin ME, Aulicino M, Martínez S, Chiessa G, Saparrat MCN, Gasoni AL. Carbon-substrate utilization profiles by Cladorrhinum (Ascomycota). Rev Argent Microbiol. 2019;51(4):302–6.

    PubMed  Google Scholar 

  52. Wu J, Zhao Y, Qi H, Zhao X, Yang T, Du Y, Zhang H, Wei Z. Identifying the key factors that affect the formation of humic substance during different materials composting. Bioresour Technol. 2017;244:1193–6.

    Article  CAS  PubMed  Google Scholar 

  53. Su J, Zhou K, Chen W, Xu S, Feng Z, Chang Y, Ding X, Zheng Y, Tao X, Zhang A, et al. Enhanced organic degradation and microbial community cooperation by inoculating bacillus licheniformis in low temperature composting. J Environ Sci. 2024;143:189–200.

    Article  Google Scholar 

  54. Du G, Shi J, Zhang J, Ma Z, Liu X, Yuan C, et al. Exogenous probiotics improve fermentation quality, microflora phenotypes, and trophic modes of fermented vegetable waste for animal feed. Microorganisms. 2021;9(3):644.

  55. Durairaj K, Velmurugan P, Park JH, Chang WS, Park YJ, Senthilkumar P, Choi KM, Lee JH, Oh BT. An investigation of biocontrol activity pseudomonas and bacillus strains against panax ginseng root rot fungal phytopathogens. Biol Control. 2018;125:138–46.

    Article  CAS  Google Scholar 

  56. Nakasaki K, Hirai H. Temperature control strategy to enhance the activity of yeast inoculated into compost raw material for accelerated composting. Waste Manag. 2017;65:29–36.

    Article  CAS  PubMed  Google Scholar 

  57. Gerez CL, Carbajo MS, Rollan G, Torres Leal G, Font de Valdez G. Inhibition of citrus fungal pathogens by using lactic acid bacteria. J Food Sci. 2010;75(6):M354–359.

    Article  CAS  PubMed  Google Scholar 

  58. Zou Y, Zhong L, Hu C, Sheng G. Association between the alanine aminotransferase/aspartate aminotransferase ratio and new-onset non-alcoholic fatty liver disease in a nonobese Chinese population: a population-based longitudinal study. Lipids Health Dis. 2020;19(1):245.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Yuan K, Liang T, Muckey MB, Mendonca LG, Hulbert LE, Elrod CC, Bradford BJ. Yeast product supplementation modulated feeding behavior and metabolism in transition dairy cows. J Dairy Sci. 2015;98(1):532–40.

    Article  CAS  PubMed  Google Scholar 

  60. Cui C, Shen C, Jia G, Wang K. Effect of dietary bacillus subtilis on proportion of bacteroidetes and firmicutes in swine intestine and lipid metabolism. Genet Mol Res. 2013;12:1766–76.

    Article  CAS  PubMed  Google Scholar 

  61. Jeun J, Kim S, Cho SY, Jun HJ, Park HJ, Seo JG, Chung MJ, Lee SJ. Hypocholesterolemic effects of lactobacillus plantarum KCTC3928 by increased bile acid excretion in C57BL/6 mice. Nutrition. 2010;26(3):321–30.

    Article  CAS  PubMed  Google Scholar 

  62. Sun S, Guo C, Wang J, Ren L, Qu J, Guan Q, Dou N, Zhang J, Chen Q, Wang Q, et al. Effect of initial moisture content, resulting from different ratios of vegetable waste to maize straw, on compost was mediated by composting temperatures and microbial communities at low temperatures. Chemosphere. 2024;357:141808.

    Article  CAS  PubMed  Google Scholar 

  63. Lin N, Zha X, Cai J, Li Y, Wei L, Wu B. Investigating fungal community characteristics in co-composted cotton stalk and various livestock manure products. Environ Sci Pollut R. 2024;31(17):26141–52.

    Article  CAS  Google Scholar 

Download references

Funding

This work was supported by Bintuan Science and Technology Program (2023AB078); Bintuan Agricultural Innovation Project (NCG202232); China Scholarship Council (NO. 202208320271); Jiangxi Key Research and Development Program (20201BBF61008); National 13th Five-Year Plan Key Research and Development Program (2017YFD0800200) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), China. The authors declare no competing financial interests.

Author information

Author notes

  1. Zhenbin Zhang and Yalan Gu contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Metabolic Manipulation of Herbivorous Animal Nutrition, College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, Jiangsu, China

    Zhenbin Zhang, Yalan Gu, Shan Wang, Yongkang Zhen, Yifei Chen, Yongjiang Mao & Mengzhi Wang

  2. State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural Reclamation Sciences, Shihezi, 832000, Xinjiang, China

    Zhenbin Zhang, Jimeng Meng & Zhenyu Duan

  3. Shanghai Frontan Animal Health Co., Ltd, Shanghai, 201502, China

    Yalan Gu

  4. Edweigang Modern Animal Husbandry Co., Ltd, Suqian, 223999, Jiangsu, China

    Yongkuan Wang

  5. Institute for Quality and Safety and Standards of Agricultural Products Research, Jiangxi Academy of Agricultural Sciences, Nanchang, 330299, Jiangxi, China

    Jun Xu

Authors
  1. Zhenbin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yalan Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yongkang Zhen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yifei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yongkuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yongjiang Mao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jimeng Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Zhenyu Duan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jun Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Mengzhi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MW, ZZ, and YG: conceived and designed the study. ZZ, YG, SW, YZ, YC, YW, YM and JM: conducted the experiment. ZZ, YG, and SW: analyzed the animal data. ZZ and YG wrote the first draft of the manuscript. ZZ, MW, ZD and JX revised sections and grammar of the manuscript. All authors contributed to the manuscript revision, read, and approved the submitted version.

Corresponding authors

Correspondence to Zhenyu Duan, Jun Xu or Mengzhi Wang.

Ethics declarations

Ethical approval

The study performed in heifers was reviewed and approved by Animal Welfare Committee of Yangzhou Veterinarians of the Agriculture Ministry of China (Yangzhou, China, license No. Syxk (Su) 2019-0029).

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.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

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

Zhang, Z., Gu, Y., Wang, S. et al. Effective microorganism combinations improve the quality of compost-bedded pack products in heifer barns: exploring pack bacteria-fungi interaction mechanisms. BMC Microbiol 24, 302 (2024). https://doi.org/10.1186/s12866-024-03447-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12866-024-03447-6

Keywords

BMC Microbiology

ISSN: 1471-2180

Contact us