Effects of Rice Straw Variety on Rumen Fermentation, Bacterial Community, and Metabolite Profile

Abstract

The objective of this study was to investigate the effects of different rice varieties on in vitro rumen fermentation characteristics, microbial community, and metabolite profile of rice straw. The inbred variety Zhongjiazao 17 (Z17) and the hybrid variety Ruiliangyou 1053 (R1053) were selected as the two test varieties. Each variety was subjected to in vitro rumen fermentation for 72 h, with five replicates conducted for each. The results showed that R1053 had higher values in total gas production, in vitro dry matter digestibility, total volatile fatty acids (VFA), and individual VFA compared to Z17. Additionally, R1053 exhibited higher values in rumen microbial diversity indices, including Chao1, observed species, PD whole tree, and Shannon index, compared to Z17. The Z17 group had higher relative abundances of Verrucomicrobiota, Chloroflexi, Saccharofermentans, Probable genus 10, and Lachnospiraceae AC2044 group. In contrast, the R1053 group had higher relative abundance of Patescibacteria. Analysis of similarities (ANOSIM) confirmed a significant difference between the Z17 and R1053 groups (R = 0.8160, p = 0.005). Metabolomic analysis identified a total of nine differential metabolites, with four upregulated in the Z17 group and five upregulated in the R1053 group. This study demonstrates that the hybrid variety R1053 has a higher utilization value than the inbred variety Z17, which is closely associated with rumen microbes and metabolites. This study provides new insights into the efficient utilization of rice straw in ruminants from microbiological and metabolomic perspectives.

1. Introduction

Roughage is indispensable in the diet of ruminants, offering vital benefits that enhance their overall health and productivity [1]. It serves as a primary source of fiber, which is essential for maintaining rumen health. This fiber promotes the growth of beneficial microbes that facilitate the digestion of complex carbohydrates [2]. Moreover, it stimulates saliva production, helping to buffer the rumen pH and prevent acidosis, a common digestive disorder in ruminants [3]. Furthermore, roughage enhances the structural integrity of the diet, facilitating proper rumination and cud chewing. These processes are crucial for the mechanical breakdown of feed and also intervene in the fermentation process to generate volatile fatty acids (VFA), which serve as the main energy supply for ruminants, supporting their growth and production performance [4]. Therefore, understanding the role of roughage in ruminant diets is essential for optimizing nutrient utilization and feed formulations. This understanding ensures sustainable livestock production.

Rice straw is a widely available and cost-effective feed resource for ruminants, particularly in regions where rice is a major crop. It serves as a valuable roughage component, providing essential fiber that supports rumen health and function. Although rice straw is low in protein and has limited digestibility due to its high silica and lignin content, its nutritional value can be significantly enhanced through various pre-treatment methods. These methods include physical, chemical, and biological approaches [5,6,7]. Physical methods, such as grinding and chopping, increase the surface area of rice straw. This makes it more accessible to digestive enzymes and microbes [5]. Chemical treatments, including alkali and acid treatments, are effective in breaking down lignin and hemicellulose, thereby improving the straw’s degradability and nutrient availability [7]. Additionally, biological treatments using fungi and enzymes can further degrade fibrous components, enhancing the straw’s digestibility and overall nutritional quality [6]. These approaches not only improve feed quality but also contribute to sustainable agricultural waste management by reducing the environmental impact of rice straw disposal. Furthermore, they help reduce feed costs and improve the productivity of ruminant livestock.

In addition to the aforementioned pre-treatment methods for rice straw, the variety of rice can also influence the nutritional value of the resulting straw. Different rice varieties can exhibit variations in straw composition, such as differences in lignin, cellulose, and silica content, which directly impact their nutritional value and digestibility [8]. For instance, some varieties may have higher proportions of digestible components like cellulose. Others may contain more indigestible components like silica, which can reduce the overall feed value [9]. Additionally, the morphological structure of the straw, including the ratio of leaf blades to stems, can vary among varieties, affecting its digestibility and nutritional quality. Vadiveloo [10] reported that shorter varieties of rice tend to have a higher proportion of leaf blades, which are generally more digestible than stems, thus influencing the overall feed value of the straw. A preceding investigation revealed that the straw from Brittle Culm 15 mutation rice exhibited superior nutritional value and notable rumen fermentation characteristics compared to that from wild-type rice [11]. Specifically, the mutant straw contained less cellulose and more water-soluble carbohydrate, leading to enhanced degradation and a shift in fermentation patterns during in vitro rumen fermentation. Notably, the mutant straw exhibited a more rapid increase in both total gas and methane production during the early stages of fermentation and resulted in a higher relative abundance of Fibrobacter succinogenes and lower fungal abundance after 48 h. Understanding these variations is crucial for selecting or breeding rice varieties that not only yield high-quality grain but also produce straw with enhanced nutritional value for livestock. However, there is limited information on comprehensive evaluations between certain varieties such as hybrid rice and inbred rice.

Therefore, two commonly found hybrid and inbred rice varieties from southern China were selected as experimental materials. This study employed in vitro rumen fermentation techniques, as well as 16S rRNA high-throughput sequencing and metabolomics methods, to comprehensively evaluate the feed value of hybrid and inbred rice straw. These findings help to optimize the roughage feeding strategy for ruminants and enrich the pathways for producing high-quality straw. The evaluation focused on the conventional nutritional value, fiber structure, microbial composition, and metabolite profile of straw. This study hypothesized that hybrid rice straw has a higher feed value, primarily due to its superior nutritional content, which is expected to modify the structure of the microbial community and the composition of metabolites.

2. Materials and Methods

2.1. Rice Straw Origin, Chemical Composition Analysis, and Fiber Structure Scanning

The rice straw samples were sourced from two distinct varieties cultivated in a shared experimental field in 2022: the hybrid variety Ruiliangyou 1053 (R1053) and the inbred variety Zhongjiazao 17 (Z17), each variety with three plots. The soil fertility of these plots is characterized by a pH level of 5.4, an organic matter content of 3.8%, alkali-hydrolyzable nitrogen at 0.14 g/kg, readily available phosphorus at 15.4 mg/kg, and readily available potassium at 92.6 mg/kg. Upon reaching maturity, the rice was harvested, and the fresh straw was collected. The straw was then dried at 65 °C, ground to achieve a uniform particle size, and sieved through a 1 mm mesh to refine it. This preparation was conducted to produce a suitable substrate for use in subsequent in vitro fermentation studies.

The analysis of rice straw composition was conducted with precision, employing Association of Official Analytical Chemists (AOAC) methodologies to quantify the levels of organic matter (942.05), crude protein (920.39), and ether extract (990.03). For a more nuanced assessment of fiber content, the procedures outlined by Van Soest et al. [12] were rigorously followed to evaluate both neutral detergent fiber (NDF) and acid detergent fiber (ADF). Additionally, the anthrone-sulfuric acid colorimetric method was utilized to ascertain the content of water-soluble carbohydrates (WSC) [13].

The examination of rice straw fiber structure, both before and after in vitro incubation, was performed using a scanning electron microscope (FESEM, Zeiss Sigma 300, Carl Zeiss AG, Oberkochen, Germany). The sample preparation entailed the precise selection of a consistent section from each rice variety. Each section was then delicately coated with an ultra-thin layer of gold to improve the clarity and resolution of the microscopic images. Subsequently, images that encapsulated the characteristic features of each group were chosen. These images were magnified 200 times, providing a detailed and thorough visualization of the structural changes induced by the incubation process.

2.2. Experimental Design, Treatments, and In Vitro Incubation

Rumen fluid for the preparation of the in vitro incubation inoculum was sourced from five healthy Holstein dairy cows (34.32 ± 0.28 months old, 607.40 ± 11.28 kg body weight, 3.30 ± 0.11 body condition score) during their dry period. All cows had been consuming a diet with a concentrate-to-forage ratio of 55:45 for one month. The diet was composed of the following ingredients and proportions: corn silage at 23.87%, alfalfa hay at 18.56%, oat hay at 2.64%, corn at 25.69%, soybean meal at 3.01%, wheat at 7.65%, wheat bran at 2.67%, beet pulp at 1.81%, molasses at 2.54%, cottonseed at 8.53%, fat-energy powder at 1.29%, dicalcium phosphate at 0.62%, salt at 0.57%, and a premix at 0.55%. The formulated diet comprised 16.9% crude protein, 1.75 Mcal/kg of net energy for lactation, 31.01% NDF, and 23.10% ADF. The donor cows were fed the specified diet twice daily, at 7:00 AM and 3:00 PM, with ad libitum access to feed and clean water provided throughout the day. The rumen contents were collected via an oral intubation method, as described in Paz et al. [14], with the aid of a specialized sampling tube (KeliBo Animal Husbandry Technology Co., Ltd., Wuhan, China) before morning feeding, and subsequently filtered through four layers of cheesecloth. The rumen fluids, collected from each of the five cows, were then pooled and thoroughly mixed to form the final rumen fluid. The inoculum was crafted by blending the rumen fluid with an artificial culture medium at a precise volume ratio of 1:2. The composition of the artificial culture medium was prepared according to the specifications detailed in Wei et al. [15], which consisted of the following components: 47.57% distilled water, 0.01% trace element solution, 23.78% artificial saliva, 23.78% constant element solution, 0.1% resazurin solution, and 4.76% reducing agent solution.

The inbred variety Z17 and the hybrid variety R1053 were selected as the two test varieties, and each variety was subjected to in vitro rumen fermentation for 72 h. The in vitro incubation was performed in three runs, with five replicates for each rice variety in each run. The in vitro incubation procedure was performed based on Qiu et al. [16], with the following specific modifications: the substrate mass was set to 300 mg and the inoculum volume was correspondingly adjusted to 45 mL. Briefly, 300 mg of the substrate was transferred into a 125 mL culture bottle. Subsequently, 45 mL of inoculum was added to the bottle. The bottle was purged with carbon dioxide to remove oxygen, and then incubated in a constant-temperature water bath (SHA-B, Changzhou Guohua Electric Appliance Co., Ltd., Changzhou, China) for 72 h. The water bath was set to maintain a steady temperature of 39 °C and a shaking rate of 50 r/min [17]. During the 72 h incubation period, gas production was recorded every 3 h with a graduated glass syringe. The fermentation was terminated using an ice bath. Following the collection of the fermentation liquid, the pH value was immediately measured with a portable pH meter (testo 206, testo AG, Schwarzwald, Germany). The samples were then aliquoted into cryovials and stored at −80 °C for further detection and analysis. The in vitro dry matter digestibility was assessed by filtering the residue through a pre-weighed filter crucible and calculating the weight difference between the original sample and the residue, normalized to the original sample weight. Rumen fermentation characteristics included pH value, ammonia nitrogen, microbial protein, and VFA. The levels of ammonia nitrogen were assessed via the phenol-hypochlorite reaction method, as described by Broderick and Kang [18]. The concentration of MCP was measured using Lowry’s assay method [19]. In this study, the detected VFA comprised acetate, propionate, isobutyrate, butyrate, isovalerate, and valerate. The branched-chain volatile fatty acids (BCVFA) were determined by summing the concentrations of isobutyrate, isovalerate, and valerate. The individual VFA was quantified using a gas chromatograph (GC-2014, Shimadzu Corporation, Kyoto, Japan), employing the same analytical procedures outlined by Wei et al. [15].

2.3. DNA Extraction, Sequencing, and Data Analysis

Genomic DNA was extracted from the fermentation liquid using a bacterial DNA kit (OMEGA, Omega Bio-tek, Inc., Norcross, GA, USA), adhering to the manufacturer’s protocol. The Nanodrop 2000 spectrophotometer (ThermoFisher Scientific, Inc., Waltham, MA, USA) was used to assess DNA quality and concentration. Only samples that met the quality criteria proceeded to PCR amplification. The V3-V4 region of the bacterial 16S rRNA gene was targeted using universal primers on the ABI 9700 PCR system (Applied Biosystems, Inc., Foster City, CA, USA). Amplification and reaction conditions were derived from a previous study [20]. Briefly, a 25 μL reaction mixture was carefully prepared, consisting of 12.5 μL of 2x Taq Plus Master Mix, 2 μL each of forward and reverse primers (at a concentration of 5 μM), 2 μL of DNA, 3 μL of BSA, and 5.5 μL of sterile double-distilled water. The thoroughly mixed reaction mixture was subjected to amplification using the following thermal cycling program: an initial denaturation at 95 °C for 5 min, followed by 28 cycles of denaturation at 95 °C for 45 s, annealing at 55 °C for 50 s, and extension at 72 °C for 45 s, concluding with a final extension at 72 °C for 10 min. The sizes of the PCR products were confirmed by 1% agarose gel electrophoresis, and the products were subsequently purified with the Agencourt AMPure XP kit (Beckman Coulter, Inc., Brea, CA, USA) for nucleic acid cleanup. The purified PCR products were utilized to construct sequencing libraries using the NEB Next Ultra II DNA Library Prep Kit (New England Biolabs, Inc., Ipswich, MA, USA). These libraries, once quality-controlled, were sequenced on the Nextseq 2000 platforms (Illumina, Inc., San Diego, CA, USA), and the raw sequencing data were submitted to the NCBI Sequence Read Archive (SRA) with the accession number PRJNA1181277.

The raw sequencing data were processed using the QIIME 2 platform. Paired-end reads were filtered and assembled with PEAR (version 0.9.6), removing sequences with ambiguous nucleotides ’N’ and those below a quality score of 20, with a minimum overlap of 10 bp set for assembly. Following assembly, sequences outside the range of 250 to 500 bp were filtered out using Vsearch (version 2.7.1), and chimeras were identified and removed by alignment against the Gold Database with the Uchime algorithm. The unnoise3 algorithm was then used to denoise the cleaned tags, generating amplicon sequence variants (ASV), with species classification information for each ASV derived from alignment with the SILVA 138 database. Alpha diversity indices, including Chao1, observed species, PD whole tree, Shannon index, and Simpson index, were calculated from the ASV and their relative abundances using QIIME 2. To discern differences between the Z17 and R1053 groups, analysis of similarities (ANOSIM) was conducted with the vegan and mixOmics packages in R. The LDA effect size analysis, using Python (version 3.8), was employed to elucidate the differential species between the Z17 and R1053 groups across various taxonomic levels, with an LDA score threshold of 3. The phylogenetic investigation of communities by reconstruction of unobserved states tool (PICRUSt, version 2.4.1) was employed to predict the metagenomic functions of the identified microbial communities, thereby elucidating the intrinsic ruminal roles of the bacterial microbiota from the Z17 and R1053 groups.

2.4. Rumen Metabolomics Analysis

The fermentation liquid was mixed with an extraction solvent—composed of methanol and acetonitrile in a 1:1 volume ratio—at a 1:4 volume ratio, followed by vortexing. After ultrasonication, a period of standing, and centrifugation, the supernatant was collected for further analysis. The instrumental analysis was performed using a liquid chromatography–mass spectrometry (LC-MS) system, which included a Vanquish UPLC system and an Orbitrap Exploris 120 mass spectrometer, both from Thermo Fisher Scientific (Waltham, MA, USA). The chromatographic separation was achieved using an ACQUITY UPLC BEH Amide column (1.7 μm particle size, 2.1 mm × 100 mm dimensions). The injection volume was 2 μL, with the temperature of the automatic sampler controlled at 4 °C. ProteoWizard software (version 3.0.21229) was utilized to convert raw mass spectrometry data into the mzXML format. XCMS was applied for retention time alignment, peak detection, extraction, integration, and alignment, as well as for the identification of metabolites. The criteria for selecting differential metabolites were a Student’s t-test p-value less than 0.05, a fold change greater than 1.5 or less than 0.67, and a variable importance in the projection (VIP) value greater than 1.

2.5. Statistical Analysis

The normality of data distribution was assessed using the Shapiro–Wilk test. As these data, except for the microbial data, were normally distributed, an independent samples t-test was performed using SPSS software (version 20, IBM Corporation, Armonk, NY, USA) to evaluate the differences between the Z17 and R1053 groups. The independent samples Mann–Whitney U test was applied to analyze the microbial data using the same software. The threshold for statistical significance was established at p < 0.05.

3. Results

3.1. Chemical Composition and Fiber Structure

The chemical compositions of rice straw from two varieties are detailed in

Table 1. Chemical component (%) of Zhongjiazao 17 (Z17) and Ruiliangyou 1053 (R1053).

Item	Z17	R1053
Organic matter	86.85	88.21
Crude protein	5.40	6.61
Neutral detergent fiber	62.74	59.91
Acid detergent fiber	35.81	33.57
Ether extract	2.21	2.36
Crude ash	13.15	11.79
Water-soluble carbohydrates	2.10	2.73

. The R1053 group exhibited numerically higher contents of organic matter, crude protein, ether extract, and WSC. In contrast, the Z17 group was distinguished by its elevated content of NDF and ADF. Initial assessments using scanning electron microscopy (SEM) showed no significant differences in the fiber structure between the two varieties before incubation, as illustrated in Figure 1A,B. After a 72 h in vitro rumen fermentation period, SEM imaging (Figure 1D) of the R1053 group’s fiber structure revealed an increased number of pores than that in the Z17 group (Figure 1C), indicating a more complete fiber digestion.

3.2. Gas Production and Rumen Fermentation Characteristics

As depicted in Figure S1, the total gas production fluctuated dynamically with the progression of incubation time. Notably, the in vitro gas production plateaued after 66 h, suggesting that the 72 h incubation period employed in this study was justified. Furthermore, the R1053 group demonstrated superior performance with higher total gas yield and in vitro dry matter digestibility compared to the Z17group (

Table 2. Effects of rice straw variety on gas production and rumen fermentation characteristics.

Item	Z17	R1053	SEM	p-Value
Total gas production, mL/g	136.67	173.27	5.395	0.002
In vitro dry matter digestibility, %	52.57	59.90	0.960	0.001
pH value	6.75	6.79	0.035	0.531
Microbial protein, mg/L	45.48	54.91	9.324	0.506
Ammonia nitrogen, mg/dL	16.28	19.30	1.009	0.188
Total volatile fatty acids, mmol/L	62.90	77.69	1.174	0.001
Concentration, mmol/L
Acetate	40.03	48.75	0.750	0.002
Propionate	13.09	15.66	0.095	<0.001
Isobutyrate	0.41	0.57	0.028	0.041
Butyrate	7.71	10.28	0.221	0.002
Isovalerate	0.81	1.28	0.071	0.024
Valerate	0.85	1.15	0.030	0.003
Branched chain volatile fatty acids	2.06	3.00	0.127	0.016
Proportion, %
Acetate	63.65	62.74	0.070	<0.001
Propionate	20.82	20.19	0.231	0.203
Acetate/propionate	3.06	3.11	0.038	0.469
Isobutyrate	0.65	0.72	0.026	0.177
Butyrate	12.26	13.22	0.104	0.005
Isovalerate	1.29	1.64	0.069	0.052
Valerate	1.35	1.48	0.016	0.009
Branched chain volatile fatty acids	3.28	3.85	0.107	0.051

Z17, Zhongjiazao 17; R1053, Ruiliangyou 1053; SEM, standard error of the mean.

).

The R1053 group was demonstrated to increase the concentration of total VFA and BCVFA, with a significant enhancement observed in the levels of individual VFA such as acetate, propionate, isobutyrate, butyrate, isovalerate, and valerate. Moreover, the Z17 group exhibited a higher proportion of acetate compared to the R1053 group, whereas butyrate and valerate showed a converse trend (Table 2).

3.3. Rumen Bacterial Diversity and Community Composition

The R1053 group showed higher Chao1, observed species, PD whole tree, and Shannon index values when compared to the Z17 group (p < 0.05,

Table 3. Effect of rice straw variety on alpha-diversity indices of rumen bacterial community.

Item	Z17	R1053	SEM	p-Value
Chao1	507.42	865.07	49.04	0.016
Observed species	505.60	853.78	48.13	0.016
PD whole tree	44.13	56.97	2.27	0.016
Shannon index	8.02	8.61	0.08	0.008
Simpson index	0.993	0.994	0.0005	0.056

Z17, Zhongjiazao 17; R1053, Ruiliangyou 1053; SEM, standard error of the mean.

). The relative abundances of Verrucomicrobiota and Chloroflexi in the Z17 group were higher than those in the R1053 group, while the Patescibacteria abundance showed the opposite relationship (p < 0.05,

Table 4. Effect of rice straw variety on rumen bacterial community composition at the levels of phylum and genus.

Item	Z17	R1053	SEM	p-Value
Phylum
Bacteroidota	52.35	56.79	1.698	0.095
Firmicutes	36.30	33.53	1.149	0.222
Proteobacteria	4.66	3.97	1.201	0.690
Desulfobacterota	2.49	2.01	0.292	0.310
Verrucomicrobiota	2.45	1.68	0.101	0.008
Spirochaetota	0.61	0.83	0.092	0.222
Elusimicrobiota	0.53	0.42	0.094	0.841
Patescibacteria	0.22	0.38	0.040	0.032
Euryarchaeota	0.17	0.21	0.026	0.690
Synergistota	0.05	0.07	0.011	0.310
Actinobacteriota	0.06	0.04	0.027	0.690
Chloroflexi	0.06	0.03	0.010	0.032
Fibrobacterota	0.02	0.02	0.010	0.841
Cyanobacteria	0.02	0.01	0.013	0.310
Genus
Prevotella	11.23	14.60	1.634	0.310
Rikenellaceae RC9 gut group	13.16	12.20	0.629	0.310
Bacteroidales UCG-001	12.02	10.69	0.923	0.421
F082	10.02	11.93	0.699	0.095
Succiniclasticum	4.85	6.00	0.959	0.222
Saccharofermentans	5.55	4.63	0.192	0.008
Pseudomonas	3.28	2.16	1.070	0.690
Probable genus 10	3.14	1.67	0.193	0.008
Desulfovibrio	2.48	1.98	0.290	0.310
Lachnospiraceae AC2044 group	2.70	1.66	0.123	0.008
Bacteroidales BS11 gut group	2.13	2.19	0.103	0.841
Lachnospiraceae XPB1014 group	2.07	1.79	0.098	0.095
Christensenellaceae R-7 group	1.50	1.59	0.184	1.000
NK4A214 group	1.15	1.46	0.111	0.151

Z17, Zhongjiazao 17; R1053, Ruiliangyou 1053; SEM, standard error of the mean.

). At the level of genus, the relative abundances of Saccharofermentans, Probable genus 10, and Lachnospiraceae AC2044 group were higher in the Z17 group when compared to the R1053 group (p < 0.05, Table 4). No significant differences were observed in the predicted metabolic pathway between the Z17 and R1053 groups (p > 0.05,

Table 5. Effect of rice straw variety on the relative abundance of the predicted metabolic pathways in the rumen bacterial community.

Item	Z17	R1053	SEM	p-Value
Carbohydrate metabolism	13.89	13.71	0.071	0.151
Metabolism of cofactors and vitamins	13.31	13.40	0.108	0.548
Amino acid metabolism	13.23	13.07	0.049	0.095
Metabolism of terpenoids and polyketides	9.31	9.23	0.091	0.690
Metabolism of other amino acids	7.04	7.35	0.144	0.222
Replication and repair	6.23	6.28	0.052	0.690
Energy metabolism	5.51	5.85	0.098	0.056
Glycan biosynthesis and metabolism	5.17	5.37	0.101	0.151
Lipid metabolism	4.49	4.39	0.127	0.841
Translation	3.45	3.48	0.041	0.690
Folding, sorting and degradation	3.10	3.07	0.020	0.690
Xenobiotics biodegradation and metabolism	3.04	2.86	0.133	0.841
Biosynthesis of other secondary metabolites	2.43	2.43	0.030	1.000
Nucleotide metabolism	2.11	2.13	0.019	0.690
Cell motility	1.70	1.52	0.065	0.151
Cell growth and death	1.60	1.61	0.014	0.421
Membrane transport	1.56	1.49	0.037	0.310
Transcription	1.12	1.12	0.013	1.000

Z17, Zhongjiazao 17; R1053, Ruiliangyou 1053; SEM, standard error of the mean.

). ANOSIM further confirmed significant differences between the R1053 and Z17 groups (R = 0.8160, p = 0.005).

In addition to the previously highlighted differential bacteria and their affiliated species, the LEfSe analysis (Figure 2) uncovered an additional 35 distinct microbial taxa that exhibited significant differences in abundance. These are detailed as follows: o_Oligosphaerales, f_Oligosphaeraceae, o_Monoglobales, f_Monoglobaiceae, g_Monoglobus, o_Burkholderiales, f_Oxalobacteraceae, g_Noviherbaspirillum, g_Ruminococcus_flavefaciens, c_Kiritimatiellae, f_WCHB1_41, o_Victivallales, c_Lentisphaeria, g_VadinBE97, f_vadinBE97, o_Clostridia, f_Hungateiclostridiaceae, and c_Clostridia in the Z17 group; and o_Aeromonadales, f_Succinivibrionaceae, g_Selenomonas, s_Selenomonas_ruminantium, s_Bacteroides_uniformis, g_Succinivibrionaceae_UCG_002, g_UCG_004, f_Erysipelatoclostridiaceae, g_Ruminobacter, g_Eubacterium_nodatum_group, g_Pyramidobacter, f_Butyricicoccaceae, g_UCG_009, f_p_251_o5, g_p_251_o5, g_Sediminispirochaeta, and g_Moryella in the R1053 group.

3.4. Rumen Metabolic Profile

A comprehensive metabolome analysis identified nine distinct metabolites with differential expressions between the R1053 and Z17 groups, as detailed in

Table 6. Differential rumen metabolites between Ruiliangyou 1053 (R1053) and Zhongjiazao 17 (Z17).

Metabolites	Metabolic Pathway	Mass	Formula	VIP	p-Value	FC	Trend
Estradiol	Endocrine resistance	272.18	C18H24O2	2.28	0.0002	0.42	down
Fipronil-desulfinyl	Amino acid metabolism	389.08	C12H4Cl2F6N4	2.24	0.0004	0.46	down
Eicosapentaenoic acid	Lipid metabolism	302.22	C20H30O2	2.31	0.0002	0.60	down
Abietic acid	Metabolism of terpenoids and polyketides	302.22	C20H30O2	2.28	0.0004	0.65	down
Aerobactin	Microbial metabolism in diverse environments	564.23	C22H36N4O13	2.30	0.0003	1.59	up
Stanozolol	Lipid metabolism	328.25	C21H32N2O	2.33	0.0000	1.71	up
Manumycin A	Metabolism of terpenoids and polyketides	550.27	C31H38N2O7	2.23	0.0006	2.62	up
Saccharocin	Glycan biosynthesis and metabolism	540.56	C21H40N4O12	2.39	0.0000	4.31	up
Canthiumine	Biosynthesis of other secondary metabolites	552.66	C33H36N4O4	2.26	0.0003	4.45	up

VIP, variable importance in the projection; FC, fold change.

. The R1053 group exhibited five significant upregulated metabolites, namely aerobactin, stanozolol, manumycin A, saccharocin, and canthiumine. In contrast, the Z17 group demonstrated increased levels of estradiol, fipronil-desulfinyl, eicosapentaenoic acid, and abietic acid.

4. Discussion

4.1. Effects of Rice Straw Variety on Gas Production and Rumen Fermentation Characteristics

The nutritional value of rice straw significantly influences its in vitro gas production and digestibility. Traditionally regarded as a low-quality feed because of its high fiber and low protein content, the nutritional value of rice straw can vary considerably depending on the rice variety and cultivation practices. In this study, the two tested rice varieties were cultivated under identical conditions, thus isolating the variety as the sole influencing factor. A previous study found that varieties with lower NDF and ADF content typically exhibited higher in vitro gas production and digestibility [21]. This is because these fibers primarily restrict the accessibility of cellulolytic microbes, thereby affecting the rate and extent of fermentation. Additionally, the crude protein content of rice straw positively correlates with gas production, as it provides essential nitrogen for microbial growth and activity, which in turn enhances the breakdown of fibrous components [10]. Furthermore, the presence of silica and lignin can hinder the digestion process, resulting in lower gas production and digestibility rates [22]. In this study, the R1053 group showed higher in vitro gas production and digestibility. This could be because of its numerically higher content of organic matter, crude protein, and WSC, as well as its lower levels of NDF and ADF.

VFA, including acetate, propionate, and butyrate, are indispensable to ruminant animals, supplying over 70% of their energy needs [23]. The production of VFA within the rumen is influenced by the feed’s composition, the microbial community, and ambient conditions [23]. An elevated total VFA production, as well as increased concentrations of individual VFA, was observed in the R1053 group. This can be attributed to the numerically higher levels of WSC and crude protein in R1053, which are more susceptible to fermentation. Theoretical insights suggest that these components are crucial for enhancing the fermentation process [23]. As a result, the numerically higher contents of these fermentable substrates in the R1053 group likely contributes to its superior VFA production. Fermenting structural carbohydrates generally results in higher acetate proportion than fermenting starch [23]. This difference in fermentation outcomes may account for the elevated proportion of acetate observed in the Z17 group, which could be because of its numerically higher contents of NDF and ADF.

4.2. Effects of Rice Straw Variety on Rumen Bacterial Diversity and Community Composition

Rumen microbial alpha diversity is vital for the health and productivity of ruminants. Jia et al. [24] reported that a high alpha diversity signified a complex microbial community, which boosted the host’s resilience to environmental stress and enhanced nutrient utilization efficiency. This study found that the R1053 group exhibited greater richness and evenness than the Z17 group, suggesting that it is more conducive to the stability and resilience of the rumen microbial community. This increased diversity, in turn, promotes nutrient digestion, as indicated by higher gas production and in vitro dry matter digestibility. Verrucomicrobiota and Chloroflexi possess the ability to break down complex carbohydrates, including cellulose, hemicellulose, and polysaccharides, thereby generating short-chain fatty acids that serve as a crucial energy source for ruminants [25]. In the context of this study, it was observed that the relative abundances of these two phyla were higher in the Z17 group than in the R1053 group. This difference is likely attributed to the higher fiber content in the Z17 group. Similarly, the genera Saccharofermentans, Probable genus 10, and Lachnospiraceae AC2044 group also play significant roles in the process of fiber degradation [26]. Therefore, it is not surprising to observe their higher relative abundances in the Z17 group. Patescibacteria are a group of uncultured bacteria that have lost the genes necessary for key metabolic pathways, including the synthesis of amino acids, nucleotides, fatty acids, and cofactors. Despite these losses, they have evolved pilus-like structures that enable them to adhere to other microorganisms. These structures are hypothesized to function as tunnels, facilitating the exchange of metabolites [27]. The higher relative abundance of Patescibacteria in the R1053 group suggests a potentially greater metabolic activity and an enhanced capacity for microbial cooperation to maintain the stability and functional diversity of the rumen community, which could be indirectly inferred from the higher alpha diversity in this group.

LEfSe analysis provides a more comprehensive perspective on the differential microbes at different taxonomic levels between the Z17 and R1053 groups. Ruminococcus flavefaciens is a significant cellulose-degrading bacterium identified within the rumen of ruminants, possessing the capability to break down cellulose via a sophisticated enzyme system [28]. This bacterium also collaborates with other rumen microorganisms, such as Clostridia and Hungateiclostridiaceae, in the process of cellulose degradation. Together, these microorganisms employ distinct enzyme systems and metabolic pathways to effectively degrade and ferment cellulose. This study revealed that the relative abundances of these microorganisms were notably higher in the Z17 group, thereby further substantiating their role in cellulose degradation. Members of the order Monoglobales are equipped with pectin-specific glycoside hydrolase domains and cell wall-anchored S-layer homology motifs. These features empower them to efficiently degrade a wide range of pectins, rhamnogalacturonan-I, and galactans, thereby producing polysaccharide degradation products [29]. Members of the Oligosphaeraceae and Burkholderiales, as well as its affiliated Oxalobacteraceae and Noviherbaspirillum, are primarily involved in the fermentation of glucose, fructose, and sucrose, a process that results in the production of acetate, which serves as a crucial energy source for ruminant animals [30]. Kiritimatiellae, WCHB1_41, and VadinBE97 exhibit strict anaerobic and fermentative metabolic pathways, utilizing carbohydrates as their primary substrate. These bacteria derive energy through fermentation in oxygen-deprived environments, thereby playing a crucial role in intricate energy networks. For instance, during cold seasons when feed is scarce, they can modulate their nutritional requirements to acclimate to harsh conditions [31]. Lentisphaera and Victivallis are capable of utilizing a diverse array of carbohydrates as carbon sources, generating acetate via fermentation. In the present study, the elevated relative abundances of the aforementioned microorganisms in the Z17 group are mirrored by a correspondingly higher proportion of acetate within the same group.

Aeromonadales, including Succinivibrionaceae and Succinivibrionaceae UCG 002, exhibit a diverse array of enzymatic activities, including those of proteases, amylases, and lipases [32]. Their primary metabolic products consist of short-chain fatty acids, including acetic acid, propionic acid, butyric acid, and succinic acid. Given the elevated levels of crude protein, ether extract, and WSC in the R1053 group, it is expected that these bacteria would have a higher relative abundance in this group. Selenomonas and Selenomonas ruminantium are crucial for gluconeogenesis and the production of propionate in ruminants, being particularly abundant in the rumen of high-performing animals [33]. This study observed higher relative abundances of these bacteria in the R1053 group, which correlates with increased in vitro dry matter digestibility and elevated propionate levels. Ruminobacter is extensively prevalent in the rumen of cattle and sheep, playing a pivotal role in the breakdown of dietary starch. Research has indicated that Ruminobacter, Selenomonas, and Succinivibrio not only synergistically interact but also exhibit a significant positive correlation with feed efficiency [30]. During the degradation of β-glucan, Bacteroides uniformis generates metabolites like glucose and nicotinamide. These metabolites serve as substrates for other beneficial bacteria, such as Lactobacillus johnsonii, thereby fostering their growth [34]. This synergistic interaction contributes to the maintenance of the rumen microbial community’s equilibrium and augments overall digestive efficiency. Erysipelatoclostridiaceae exhibits a positive correlation with the concentration of ammonia nitrogen in the rumen. Meanwhile, Pyramidobacter aids in the digestion of cellulose by leveraging enzymes indirectly [35]. These two bacterial groups significantly enhance the efficiency of nitrogen utilization and protein degradation in the rumen, which was verified by the numerically higher abundance of the metabolic pathway of metabolism of other amino acids. Butyricicoccaceae and Eubacterium nodatum group supply an energy source for rumen epithelial cells through the production of butyrate, while also strengthening the tight junctions of the intestinal epithelium and reducing inflammatory states [36]. This, in turn, improves hindgut function and boosts the immune capabilities of animals. This study observed that the relative abundance of Butyricicoccaceae was notably higher in the R1053 group, aligning with the elevated levels and proportions of butyrate in this group. Furthermore, Sediminispirochaeta, UCG 004, and Moryella were identified as being positively correlated with feed efficiency [37]. These findings from rumen microbiota abundance imply that hybrid rice straw may have a higher feed value.

4.3. Effect of Rice Straw Variety on Rumen Metabolites

Estradiol and fipronil-desulfinyl interact with specific receptors on rumen microbial cells, thereby disrupting endocrine and amino acid metabolic pathways. Consequently, this interaction results in cellular macromolecule damage, impairs neural signal transmission, and induces disordered energy metabolism, ultimately leading to a suppression of rumen metabolic activity [38]. Previous research demonstrated that eicosapentaenoic acid markedly diminishes the levels of acetate and ammonia nitrogen in the rumen, simultaneously reducing the diversity of the rumen microbiota [39]. Additionally, abietic acid shows a synergistic interaction with eicosapentaenoic acid within the rumen, which is involved in terpenoid metabolism. The metabolites previously mentioned are notably elevated in the Z17 group, suggesting that Z17 is unfavorable for the fermentative metabolic processes of rumen microorganisms. This unfavorable condition is reflected in a decline in the production of VFA and a decrease in microbial diversity.

Aerobactin is an iron chelator that forms iron–aerobactin complexes, thereby facilitating more efficient iron acquisition by bacteria from the rumen environment, as seen from its metabolic pathway of microbial metabolism in diverse environments. This process not only promotes bacterial growth and reproduction but also helps maintain the stability of the microbial community [40]. Stanozolol, a steroid hormone, significantly enhances protein synthesis and is utilized to improve feed utilization efficiency and growth in ruminants [41]. Manumycin A, known for its anti-tumor, anti-inflammatory, and immune-regulatory activities, shares similarities with saccharocin and canthiumine in its ability to inhibit the growth of harmful bacteria [42]. By increasing the populations of cellulolytic and lactic acid bacteria in the rumen, it boosts the degradation efficiency of cellulose and starch, thereby promoting rumen fermentation and increasing the production of VFA. In the R1053 group, these metabolites were found to be significantly upregulated. When considering the rumen fermentation characteristics and microbial diversity within this group, it becomes evident that the straw of hybrid rice can enhance rumen fermentation, implying that feeding this type of straw could lead to a greater energy input in the rumen.

It is crucial to note that the current findings are based solely on rumen fluid collected from dairy cows during their dry period. To enhance the applicability of hybrid rice straw as a feedstock for ruminants, future studies might consider including a broader spectrum of animal species, such as beef cattle, buffaloes, sheep, and goats. Additionally, incorporating rumen fluid samples from a greater number of donors across various physiological stages would be beneficial for the precision feeding of different varieties of rice straw.

5. Conclusions

In conclusion, the hybrid rice straw R1053 demonstrated a superior utilization value over the inbred variety Z17. This is evident through its higher in vitro gas production, enhanced dry matter digestibility, increased VFA production, and greater microbial diversity. These enhancements are intricately linked to the structure of the microbial community and rumen metabolites. It is recommended to feed ruminants with the straw of hybrid rice and to cultivate hybrid rice to enhance the feed value of crop by-products.

It should be pointed out that this conclusion was drawn under in vitro conditions. Therefore, it is essential to conduct in vivo feeding trials in ruminants to examine how hybrid and inbred rice straw impacts animal growth and digestive characteristics. These trials are crucial for verifying the practical relevance of the current in vitro findings. Furthermore, potential trade-offs such as cost, availability, and sustainability should be considered when adopting hybrid rice straw as a valuable feed resource.