Optimization of solid-state fermentation process of diets and its effects on growth performance and intestinal function in growing pigs

Optimization of solid-state fermentation process of diets and its effects on growth performance and intestinal function in growing pigs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimization of solid-state fermentation process of diets and its effects on growth performance and intestinal function in growing pigs Mengting Ji, Jingchao Liu, Qinglin Wang, Tianye Gong, Jiaqi Zhang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7242996/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Biological fermentation can improve animal growth performance and meat quality by optimizing feed nutritional properties. However, the complex fermentation parameters require further systematic optimization. This study aimed to establish and optimize a solid-state fermentation (SSF) process, evaluate changes in the feed microbial community and flavor metabolites, and investigate their effects on muscle development and intestinal barrier function in growing pigs. Here, we developed a synergistic solid-state fermentation (SSF) strategy for pig feed using combinations of 4 probiotics and 11 enzymatic preparations, 16S rDNA-seq and flavoromics-seq were employed to investigate the dynamic changes in microbial communities and flavor compounds post-fermentation. Subsequently, 32 Duroc × Jinfen White pigs were fed diets containing 10% SSF to assess growth performance, intestinal health and muscle development. Results The optimal fermentation ratio of Bacillus subtilis, Lactobacillus plantarum, Saccharomyces cerevisiae and Aspergillus niger is 1:2:3:3, with a temperature of 36°C, an inoculation rate of 93%, a moisture content of 72%, and a time of 4.1 days. SSF significantly enhanced the nutritional value of feed by increasing the ash, organic matter (OM), crude protein (CP), and ether extract (EE) content, while simultaneously reducing the concentration of anti-nutritional factors. Sequencing identified 17 differential microbes and 116 flavor compounds, with the relative abundance of Lactobacillus and the Firmicutes significantly increased, 2-octenal and vanillin imparting sweet, fruity, and grassy notes to the feed. Meanwhile, RNA-seq revealed 320 DEGs in muscle tissue following fermented feed supplementation, which are mainly enriched in pathways related to cytochrome P450 drug metabolism and arginine biosynthesis. Additionally, H&E staining results indicated that fermentation significantly increased the villus height, crypt depth, and villus-to-crypt ratio in the small intestine of growing pigs, and the levels of tight junction proteins Claudin-1 and ZO-1 in the jejunum were significantly higher than those in the ctrl group. Subsequent correlation analysis indicated that Firmicutes may influence pig growth performance and IL-6, TNF-α levels by affecting their metabolites. Conclusion Our findings establish and optimize an SSF process that markedly elevates feed nutritional value, enriches beneficial microbes, and fosters the production of unique flavor metabolites. When fed to growing pigs, it effectively enhances growth performance and antioxidant capacity while improving small-intestinal morphology and barrier function. Microbial-enzyme synergy Feed microbiota Feed flavoromics Muscle development Intestinal barrier Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Corn and soybean meal, as high-quality nutritional sources in pig diets, provide essential energy, protein[ 1 ]. However, it is limited by anti-nutritional factors such as soybean antigenic proteins, trypsin inhibitors (TI), and non-starch polysaccharides (NSP), which negatively affect feed utilization, nutrient release and absorption in pigs, and may lead to intestinal allergies and diarrhea in pigs[ 1 , 2 ]. Microbial fermentation can effectively eliminate anti-nutritional factors and certain macromolecular substances in feed. Previous studies have predominantly focused on liquid-state fermented feed[ 3 ], while solid-state fermentation (SSF) has gradually emerged as the preferred process in modern feed industry, owing to its comprehensive advantages in enhanced nutritional bioavailability, improved product stability, and reduced environmental footprint[ 4 – 6 ]. SSF is a type of feed produced through microbial fermentation on a solid substrate, has been demonstrated to reduce energy consumption in feed production through multiple mechanisms, such as eliminating the need for substantial water inputs during fermentation and minimizing energy requirements for raw material processing[ 7 ]. Nonetheless, the fermentation process involves multiple conditions, and the substances that play a key role in enhancing feed quality remain unclear. Therefore, establishing and optimizing SSF processes is of great significance. Compared with microbial SSF alone, microbial-enzyme co-fermentation can more degrade and utilize substrates, significantly reducing the ANFs in feed and enhancing the value of feed or raw materials[ 8 , 9 ]. For instance, during the fermentation process, the addition of cellulase and lactic acid bacteria can effectively reduce ANFs in soybean meal and enhance its nutritional value[ 10 ]. Concurrently, the addition of non-starch polysaccharide enzymes to fermented feed can increase the diversity of the pig gut microbiota, particularly enhancing the relative abundance of beneficial bacteria such as Bifidobacterium[ 11 ]. Moreover, the addition of enzymes can compensate for the insufficiency of enzyme production by the microorganisms, accelerating substrate degradation. Research has found that enzymes can influence the fermentation efficiency of microorganisms by affecting the production of lactic acid and changes in pH levels, and the co-fermented feed is rich in probiotics and enzymatic metabolic products, which are beneficial for maintaining animal gut health[ 12 ]. It has also been reported that microbial-enzyme co-fermentation can break down high-molecular-weight proteins into various peptides[ 13 ]. Research indicates that fermentation is a dynamic process during which the composition of the microbial community undergoes significant changes. For instance, Tang et al. effectively reduced the relative abundance of pathogenic bacteria such as Escherichia-Shigella in the intestines of finishing pigs using SSF, while increasing the relative abundance of beneficial bacteria like Firmicutes and Clostridium [ 3 ]. There have also been experimental findings that SSF feed can increase the abundance of beneficial bacteria, such as Lactobacillus , thereby enhancing the balance of the intestinal microbiota and immune function[ 14 ]. Simultaneously, fermentation can also significantly improve the volatile flavor compounds in feed[ 15 ]. It has been reported that during the solid-state fermentation process, enzymes produced by microorganisms can break down complex organic matter in feed, such as cellulose, hemicellulose, and pectin, releasing a greater amount of flavor compounds and nutrients, thereby enhancing the nutritional value of the feed[ 16 ]. However, research on the microbial community structure and changes in flavor compounds within fermented feed is still relatively scarce. Therefore, this study aims to optimize the strain ratios and fermentation conditions in SSF using a four-strain mixture, analyze changes in microbial community structure and flavor metabolites in fermented feed, and investigate their effects on growth performance and intestinal function. This research will provide a scientific basis for the optimization of SSF processes and a comprehensive evaluation of its nutritional value. Materials and methods Establishment of solid-state fermented (SSF) feed process The Lactobacillus plantarum ( L. Plantarum , BNCC336421) and Bacillus subtilis ( B. Subtilis , BNCC109047) used in the experiment were purchased from Bena Culture Collection, while Saccharomyces cerevisiae ( S. Cerevisiae , CICC1355) and Aspergillus niger ( A. niger , CICC40273) were obtained from the China Center of Industrial Culture Collection. After each microbial strain was activated, optimization and screening were carried out based on the orthogonal experiment (Table 1 ), with trichloroacetic acid-soluble protein (TCA-SP), CF, and the anti-nutritional factor β-conglycinin as the evaluation indicators. Subsequently, through single-factor and response surface optimization experiments (Table 2 ), the optimal microbial ratios were conducted to investigate the effects of different fermentation times (1 day, 2 days, 3 days, 4 days, 5 days, and 6 days), fermentation temperatures (24°C, 28°C, 32°C, 36°C, and 40°C), water content (60%, 80%, 100%, 120%, and 140%), and microbial inoculation levels (6%, 9%, 12%, 15%, and 18%) on the TCA-SP and CF content in fermented feed. Thoroughly dissolve the compound enzyme preparation and mix it uniformly into the feed. Then, subject the mixture to bacteria-enzyme synergistic fermentation under optimized conditions using the refined mixed-strain ratio to produce SSF feed. The characteristics of the compound enzyme preparation are presented in Table 3 , and the nutritional composition and levels of the basal diet are shown in Table 4 . All experiments were conducted with three biological replicates. Table 1 Orthogonal test factors and levels design table of L9 (3 4 ) for strains proportion Level Factors (A) B. subtilis (B)L. plantarum (C) S. cerevisiae (D) A. niger 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 Table 2 Design of RSM experimental factors and levels Factor Levels -1 0 1 A Inoculum quantity(%) 6 9 12 B Moisture content(%) 60 80 100 C Time(d) 3 4 5 Table 3 Characteristics of forage enzyme preparation Enzyme Temperature range (℃) Amount added (g/kg) Enzyme activity β-glucanase 30–40 0.02 ≥ 50000 Alkaline protease 40–50 0.01 ≥ 200000 Acid protease 30–40 0.025 ≥ 60000 Neutral protease 30–40 0.015 60000 α-Amylase 30–40 0.03 ≥ 3000 Pectinase 30–40 0.001 30000 Lipase 40–55 0.2 ≥ 10000 α-Galactosidase 30–40 0.03 ≥ 500 Cellulase 30–40 0.01 ≥ 10000 Xylanase 40–55 0.003 ≥ 1000000 Glucose oxidase 30–40 0.005 ≥ 10000 Table 4 Nutrient composition and nutrient level of basal diet. Ingradient Contents (%) Nutrient levels 1) Contents (%) Corn 67.45 DM 92.30 Whey powder 3.00 Water 7.70 Soybean oil 1.23 CP 18.36 Soybean 20.61 EE 4.10 Fish meal 2.00 Ash 6.87 Lysine hydrochloride 0.55 ADF 15.88 Met(98%) 0.23 NDF 7.38 Thr(98%) 0.23 Ca 0.69 Trp(98%) 0.08 Total Phosphorus 0.65 Limestone 0.48 Lys 1.20 CaHPO4 1.57 Met + Cys 0.71 NaCl 0.56 Thr 0.76 Premix 2) 2.00 Trp 0.24 Total 100.00 Met = Methionine; Thr = Threonine; Trp = Tryptophan; DM = Dry Matter; CP = Crude Protein; EE = Ether extract; ADF = Acid detergent fiber; NDF = Neutral detergent fiber; CA = Crude Ash; Lys = Lysine; Cys = Cystine. 1) Water, CP, EE, Ash, NDF and ADF were measured values, the others were calculated values. 2) Premix provided per kilogram of diet: Vitamin A 10000 IU; Vitamin D 3500 IU; Vitamin E 70 IU; Vitamin K3 3 mg; Vitamin B1 3 mg; Vitamin B2 10 mg; Vitamin B6 6 mg; biotin 0.4 mg; pantothenate acid 30 mg; niacin 30 mg; Cu 110 mg (as copper sulfate); Mn 10 mg (as manganese sulfate); Fe 140 mg (as ferrous sulfate); I 0.5 mg (as potassium iodide); Se 0.3 mg (as sodium selenite). Determination of feed nutritional value The SSF feed was taken out from the incubator, ground into fine powder after being dried in an oven at 65°C for over 48 hours, and then stored sealed at 4°C for later use. Following the methods of previous studies[ 17 , 18 ], the feed was analyzed for crude protein (CP), ether extract (EE), ash, and neutral detergent fiber (NDF), while also determining the content of acid detergent fiber (ADF) and trichloroacetic acid-soluble protein (TCA-SP). The contents of soybean globulin (YJ820239), trypsin inhibitor (TI, YJ820238), β-conglycinin (YJ831129), phytohemagglutinin (PHA, YJ854229), deoxynivalenol (DON, ml103502), zearalenone (ZEN, ml036116), aflatoxin B1 (AFB1, ml036115), and T-2 toxin (TS, ml036120) were determined according to the manufacturer's instructions (Shanghai Enzyme-Linked Biotechnology Co., Ltd., China). Determination of small peptides and analysis by electron microscopy Gently pick up feed sample particles with tweezers and lay them flat on the operating plate for observation of different fields of view of the feed morphology under a scanning electron microscope. Additionally, add the denatured feed to a protein gel for electrophoresis, followed by staining and destaining with Coomassie brilliant blue dye. 16S rDNA sequencing 16S rDNA sequencing was performed on the basal feed and SSF feed. After DNA extraction from the samples, a library was constructed and sequenced on the Illumina PE250 platform. The DADA2 software was used for data assembly, read filtering, redundancy removal, denoising, and chimera elimination. After generating ASVs (Amplicon Sequence Variants), species annotation was conducted based on sequence information. The annotation results were visualized using KRONA, and sequence counts at the phylum and genus levels were tallied. Alpha diversity indices, including observed_species (Sob), Chao1, Shannon, and Pielou, were analyzed using QIIME software. Beta diversity was assessed using the weighted UniFrac algorithm to analyze differences among microbial communities in different groups, with results displayed in a Principal Coordinates Analysis (PCoA) plot. Venn diagram analysis was conducted using the vegan package in R, followed by intergroup difference analysis using the LEfSe software. Functional annotation and community function prediction were performed using the Tax4Fun software. The OTU abundance table was combined with the “species-gene” network to output the relative functional abundance for each sample (NCBI: PRJNA1275368). Flavor metabolomics analysis The 1 g sample was mixed with 10 µL of internal standard solution and incubated at 60°C for 30 minutes. The Solid-Phase Microextraction (SPME) fiber was aged at 270°C for 10 minutes, then placed in the incubation chamber. After adsorption at 60°C for 30 minutes, the SPME fiber was inserted into the injection port (desorbed at 250°C for 5 minutes) and then aged again at 270°C for 10 minutes. The injection volume was 10 µL, with an injection temperature set at 250°C and a constant helium flow rate of 1.0 mL/min. Detection was performed using the GC × GC-TOFMS chromatography system (LECO, St. Joseph, MI, USA). The scan range was set at m/z 35–550, with the transfer line and ion source temperature maintained at 250°C, an acquisition rate of 200 spectra/second, an electron impact energy of 70 eV, and a detector voltage of 2019 V. Continuous scan MS data were collected to generate total ion current (TIC) chromatograms. The data were processed using ChromaTOF software, which is specifically designed for advanced chromatography and mass spectrometry data analysis, providing features such as NonTarget Deconvolution and library searches. Flavor compounds were annotated using the ChromaTOF search software, and the numbers and relative abundances of various flavor compounds were analyzed. The flavor profiles of the samples were evaluated using relative odor activity values (ROAV), and sensory flavor analysis was performed using the FlavorDB database. Principal component analysis (PCA) was conducted on the metabolites, and volcano plots were used to visually display the distribution of differential metabolites between the two sample groups. A network relationship among flavor compounds was constructed using the igraph package based on the FlavorDB database (NGDC: OMIX011743). RNA-seq In this study, total RNA was extracted from the rapidly frozen longissimus dorsi muscle using the Trizol method and assessed for purity with the NanoDrop ND-2000 (Thermo Fisher Scientific, Wilmington, DE) and validated for integrity with the Agilent 2100 Bioanalyzer. Stranded mRNA libraries were constructed using the Illumina TruSeq Stranded mRNA LT Kit and sequenced on the NovaSeq 6000 platform with 150 bp paired-end reads. Raw data underwent quality control with fastp to filter out low-quality data, yielding clean reads. These reads were then aligned to the reference genome using HISAT 2. Gene expression levels were quantified using Stringtie to reconstruct transcripts and RSEM to calculate expression levels across all genes in each sample. Differentially expressed genes (DEGs) were identified based on criteria of FDR < 0.05 and |log2FoldChange| ≥ 1. Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted using the online platform I-Sanger (NCBI: PRJNA1282860). Experimental animal management This study selected 48 Duroc × Jinfen White pigs with a body weight of 17.87 ± 2.83 kg at 60 ± 3 days of age. The pigs were randomly divided into two groups, each with 4 replicates per group and 6 pigs per replicate (an equal number of males and females): the control (Ctrl) group and the SSF group. The Ctrl group was fed a basal feed, while the SSF group was fed a diet supplemented with 10% SSF feed. After a 5-day adaptation period, the feeding trial lasted for 28 days. During the trial, the temperature and relative humidity inside the pig house were regularly monitored and recorded. The remaining feed and the amount of feed added were cleared and recorded every morning at 8:00, with free access to water throughout the period. Measurement of growth performance and sample collection Individuals participating in the experiment were weighed at the beginning and end of the trial, and daily feed intake per pen was recorded. These data were used to calculate average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR). Blood samples were collected from each pig via jugular vein before the end of the trial, and serum was separated. The longissimus dorsi muscle was collected from the left side of the carcass, between the 13th and 16th lumbar vertebrae, after slaughter, for the measurement of meat color, shear force, drip loss, and pH value. Sections of the duodenum, jejunum, ileum, and mid-colon were gently washed in pre-cooled sterile saline or PBS and then placed in 4% paraformaldehyde fixative. The remaining tissue samples were immediately frozen in liquid nitrogen and stored at -80°C. Immune biochemistry and enzyme-linked immunosorbent assay (ELISA) Conventional nutritional indicators such as total protein, albumin, globulin, blood glucose, and urea nitrogen were measured using an automatic biochemical analyzer (IDEXX, USA). ELISA kits for detecting interleukin-4 (IL-4, YJ31752), interleukin-6 (IL-6, YJ35656), interleukin-10 (IL-10, YJ31974), and tumor necrosis factor-α (TNF-α, YJ31476) in serum were purchased from Shanghai Enzyme-Linked. Malondialdehyde (MDA, A003-1-2), catalase (CAT, A007-1-1), total antioxidant capacity (T-AOC, A015-2-1), superoxide dismutase (SOD, A001-3-2), and glutathione peroxidase (GSH-PX, A005-1-2) were measured using biochemical assay kits from Nanjing Jiancheng. Histological evaluation The fixed intestinal tissues were dehydrated using an ASP-200 (Leica, Germany). Tissue sections with a thickness of 5 µm were obtained using a rotary microtome (Leica, Germany), following a previously reported protocol [ 19 ]. The tissue sections were stained with hematoxylin-eosin, and images were captured using the EVOSFL Auto Cell Imaging System software. Chorion length, crypt depth, and chorion height/crypt depth ratios were calculated using Image-Pro Plus 6.0 software. Statistical analysis In this experiment, data were processed using SPSS20.0. An independent samples T-test was used to analyze the data, and the results were expressed as "mean ± SEM". Statistical significance was indicated by a p-value of less than 0.05. Results The effect of strain ratios on solid-state fermentation The optimal mixing ratios of the four strains were determined through orthogonal experiments. The results showed that the best combination for increasing the TCA-SP value was A 1 B 2 C 3 D 3 (Table 5 ), with significant effects from B. subtilis ( P < 0.01) and S. cerevisiae ( P < 0.05) on TCA-SP (Table 6 ). Meanwhile, the best combination for CF degradation was A 1 B 3 C 3 D 3 (Table 7 ), with significant effects from S. cerevisiae ( P < 0.01) and B. subtilis ( P < 0.05) on CF (Table 8 ). Additionally, the two mixed strains significantly reduced the levels of soybean globulin, TI, and β-conglycinin in the feed ( P < 0.001), with the degradation effects of the A 1 B 2 C 3 D 3 group being significantly higher than that of the A 1 B 3 C 3 D 3 group (Fig. 1 ). Therefore, the A 1 B 2 C 3 D 3 combination was selected as the optimal mixed strain ratio for further screening. Table 5 Effect of 4 bacteria mixed fermentation on TCA-SP Level Factors TCA-SP (%) B. Subtilis (A) L. Plantarum (B) S. Cerevisiae (C) A. Niger (D) y1 y2 y3 y 1 1 1 1 1 3.352 3.467 3.434 3.418 2 1 2 2 2 3.566 3.648 3.691 3.635 3 1 3 3 3 3.615 3.702 3.609 3.642 4 2 1 2 3 3.533 3.407 3.516 3.485 5 2 2 3 1 3.380 3.981 3.363 3.575 6 2 3 1 2 3.101 3.270 3.095 3.155 7 3 1 3 2 3.210 3.232 3.451 3.298 8 3 2 1 3 3.374 3.495 3.024 3.298 9 3 3 2 1 3.254 3.320 3.298 3.290 K1 32.085 30.603 29.613 30.849 K2 30.647 31.522 31.232 30.264 K3 29.657 30.264 31.544 31.276 k1 3.565 3.400 3.290 3.428 k2 3.405 3.502 3.470 3.363 k3 3.295 3.363 3.505 3.475 R 0.270 0.140 0.214 0.112 Optimal combination A 1 B 2 C 3 D 3 B. Subtilis: Bacillus subtilis; L. Plantarum: Lactobacillus plantarum; S. Cerevisiae: Saccharomyces cerevisiae; A. Niger: Aspergillus niger. Table 6 Table of variance analysis of orthogonal test Variation source SS df MS F P -value Significance TCA-SP B. Subtilis 0.331 2 0.166 6.556 0.007 ** L. Plantarum 0.094 2 0.047 1.863 0.184 ns S. Cerevisiae 0.239 2 0.119 4.723 0.022 * A. Niger 0.057 2 0.029 1.135 0.344 ns SSe2 0.455 18 0.025 Total 1.176 26 0.045 To compare the statistical significance between two groups: ns (not significant) indicates P > 0.05, * P < 0.05 indicates a significant difference, and ** P < 0.01 indicates a highly significant difference. Table 7 Effect of 4 bacteria mixed fermentation on CF Level Factors CF(%) B. Subtilis (A) L. Plantarum (B) S. Cerevisiae (C) A. Niger (D) y1 y2 y3 y 1 1 1 1 1 3.691 3.835 3.564 3.697 2 1 2 2 2 3.746 3.802 3.866 3.805 3 1 3 3 3 3.458 3.265 3.301 3.341 4 2 1 2 3 3.871 4.062 3.821 3.918 5 2 2 3 1 3.826 3.741 3.659 3.742 6 2 3 1 2 3.905 3.982 3.785 3.891 7 3 1 3 2 3.848 3.513 3.582 3.648 8 3 2 1 3 3.854 3.611 3.837 3.767 9 3 3 2 1 3.980 3.785 3.931 3.899 K1 32.529 33.788 34.066 34.014 K2 34.654 33.943 34.866 34.030 K3 33.942 33.394 32.193 33.081 k1 3.614 3.754 3.785 3.779 k2 3.850 3.771 3.874 3.781 k3 3.771 3.710 3.577 3.676 R 0.236 0.061 0.297 0.105 Optimal combination A1 B3 C3 D3 B. Subtilis: Bacillus subtilis; L. Plantarum: Lactobacillus plantarum; S. Cerevisiae: Saccharomyces cerevisiae; A. Niger: Aspergillus niger. Table 8 Table of variance analysis of orthogonal test Variation source SS df MS F P -value Significance CF A-B. Subtilis 0.260 2.000 0.130 9.319 0.0017 * B-L. Plantarum 0.018 2.000 0.009 0.638 0.5396 ns C-S. Cerevisiae 0.418 2.000 0.209 14.993 0.0001 ** D-A. Niger 0.066 2.000 0.033 2.354 0.1236 ns SSe2 0.251 18.000 0.014 Total 1.013 26.000 0.039 To compare the statistical significance between two groups: ns (not significant) indicates P > 0.05, * P < 0.05 indicates a significant difference, and ** P < 0.01 indicates a highly significant difference. The effects of different fermentation conditions on solid-state fermented feed Single-factor and response surface optimization experiments were further conducted to verify the effects of moisture content, inoculation amount, fermentation time, and temperature on SSF feed. As shown in Fig. 2 A-D, the highest levels of TCA-SP were observed at a moisture content of 80%, while CF levels were at their lowest, indicating that 80% is the optimal moisture content. Similarly, comparative analysis of TCA-SP and CF responses across experimental conditions determined the optimum inoculum size at 9%, fermentation time at 4 days, and fermentation temperature at 36°C. The response surface optimization experiment indicated that the established second-order regression model was highly significant ( P < 0.01, Table 9 ). The analysis of variance showed that the model had an R² value of 0.96 and an adjusted R² of 0.92 (Table 10 ). By using response surface optimization software to fit the data, the resulting equation was obtained as Y = 4.15–0.0592A − 0.088B + 0.0563C + 0.0162AB − 0.0237AC − 0.1008BC − 0.1561A 2 − 0.1881B 2 − 0.2686C 2 . Furthermore, based on the interactions among moisture content, fermentation time, and inoculation amount, the optimal TCA-SP value was predicted. The predicted conditions were an inoculation amount of 9.283%, moisture content of 71.539%, and fermentation time of 4.112 days. Under these conditions, the TCA-SP value in the solid-state mixed-strain fermented feed was 4.112% (Fig. 2 E-G). Table 9 Results of response surface variance analysis Source Sum of Squares df Mean Square F-value P -value Significance Model 0.7758 9 0.0862 21.29 0.003 ** A-Inoculation amount 0.0281 1 0.0281 6.94 0.0337 * B-Moisture content 0.062 1 0.062 15.3 0.0058 ** C-Fermentation time 0.0253 1 0.0253 6.25 0.041 * AB 0.0011 1 0.0011 0.2609 0.6252 AC 0.003 1 0.003 0.7337 0.4201 BC 0.0406 1 0.0406 10.03 0.0158 * A² 0.1026 1 0.1026 25.33 0.0015 ** B² 0.1489 1 0.1489 36.79 0.0005 ** C² 0.3037 1 0.3037 75.02 < 0.0001 ** Residual 0.0283 7 0.004 Lack of Fit 0.0037 3 0.0012 0.1979 0.8929 ns Pure Error 0.0247 4 0.0062 Total 0.8041 16 To compare the statistical significance between two groups: ns (not significant) indicates P > 0.05, * P < 0.05 indicates a significant difference, and ** P < 0.01 indicates a highly significant difference. Table 10 Variance analysis of quadratic regression equation Parameter Value Std. Dev. 0.0636 Mean 3.87 C.V. % 1.65 R² 0.9648 Adjusted R² 0.9194 Predicted R² 0.8792 The impact of solid-state fermented feed with strain-enzyme on feed To address the issue of insufficient enzyme production during mixed-strain fermentation, microbial-enzyme synergistic fermentation was employed for optimization. The results showed that, compared with the A 1 B 2 C 3 D 3 group, the A 1 B 2 C 3 D 3 + complex enzyme group had significantly lower crude fiber content ( P < 0.05) and significantly higher acid-soluble protein content ( P < 0.05), indicating better performance of microbial-enzyme synergistic fermentation (Fig. 3 A). Meanwhile, after SSF, the boundaries of the feed cell walls became indistinct (Fig. 3 B), and the proteins were degraded from large molecules to below 25 kDa after 4 days of fermentation (Fig. 3 C). Furthermore, the nutritional components in the feed were analyzed. The results showed that the SSF group had significantly higher contents of CP, CF, and ash compared to the ctrl group ( P < 0.01), while the contents of NDF and ADF were significantly lower than those in the ctrl group ( P < 0.01) (Table 11 ). Additionally, compared to the ctrl group, the contents of ANF and DON and ZEN were significantly reduced ( P < 0.01) (Tables 12 – 13 ), indicating that feed fermentation more effectively reduced the risk of vomiting and poisoning by toxins. Table 11 Quality of SSF feed (as air-dry basis) Items Ctrl SSF Water, % 7.70 ± 0.01 6.10 ± 0.13** Ash, % 6.83 ± 0.04 7.35 ± 0.12** OM, % 85.47 ± 0.04 86.54 ± 0.17** CP, % 18.36 ± 0.07 22.86 ± 0.18** EE, % 4.10 ± 0.04 4.89 ± 0.34** NDF, % 15.88 ± 0.91 11.42 ± 0.63** ADF, % 7.38 ± 0.39 4.86 ± 0.10** OM: Organic matter; CP: Crude protein; EE: Ether extract; NDF: Neutral detergent fiber; ADF: Acid detergent fiber. For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). Table 12 Effects of SSF feed on content of anti-nutritional factors Anti-nutritional factor Ctrl SSF ɑ-conglycinin (µg/g) 24.94 ± 1.20 14.80 ± 0.58** β-conglycinin (µg/g) 48.79 ± 1.94 32.85 ± 0.53** Globulin (µg/g) 331.05 ± 14.10 212.99 ± 9.98** Soybean trypsin inhibitor (µmol/L) 69.43 ± 5.05 46.56 ± 4.45** PHA 599.59 ± 34.87 203.03 ± 12.05** For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). Table 13 Effects of SSF on content of toxin in feed Toxin(µg/kg) Safety standards(µg/kg) Ctrl SSF DON < 1000 375.67 ± 22.19 287 ± 10.54** ZEN < 500 140.33 ± 6.66 91.33 ± 7.23** AFB1 < 10 1.6 ± 0.1 < 1.5 TS < 500 < 50 < 50 DON: Deoxynivalenol; ZEN: Zearalenone; AFB1: Aflatoxin B1; TS: T-2 Toxin. For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). The impact of solid-state fermentation on the microbial community structure of feed The impact of microbial-enzyme synergistic fermentation on feed microbial composition was investigated using 16S rDNA sequencing. The results showed that the alpha diversity in the SSF group was significantly higher (Fig. 4 A), and the microbial community structures between the two groups were distinctly separated (Fig. 4 B). Meanwhile, the Venn diagram indicated that the ctrl group had 2,574 ASVs, while the SSF group had 4,117 ASVs (Fig. 4 C). At the phylum level, the proportions of Cyanobacteria and Proteobacteria were significantly reduced in the SSF group ( P < 0.01), while the proportions of Firmicutes , Acidobacteriota , and Gemmatimonadota were significantly increased ( P < 0.01) (Fig. 4 D). At the genus level, the core genera in the ctrl group were Pseudomonas and Lactobacillus , while the core genus in the SSF group was Lactobacillus ( P < 0.01). The SSF group also significantly increased the proportions of Lactobacillus , Pediococcus , and Acidobacterium RB41 , while significantly reducing the proportion of Streptococcus (Fig. 4 E). LEfSe analysis of intergroup differences revealed that the ctrl group had 10 specific microbial genera, while the SSF group had 17 differentially abundant bacterial communities, with Lactobacillus and Pediococcus being the main specific genera (Fig. 4 F). KEGG functional prediction showed that the main enrichments were in pathways such as amino acids and nucleotide sugars (Fig. 4 G-H). The impact of solid-state fermentation on feed flavor metabolites The three-dimensional chromatograms of the fermented feed samples identified by GC × GC-TOFMS are shown in Fig. 5 A. PLS-DA analysis revealed that the volatile compounds in each group of feed clustered together, while the two groups were distinctly separated, indicating reliable data (Fig. 5 B). The Venn diagram showed that 404 specific compounds were identified in the Ctrl group and 513 in the SSF group (Fig. 5 C). The relative contents of aldehyde, acid, ester, and phenolic flavor compounds in the feed increased after fermentation (Fig. 5 D). ROAV analysis indicated that the relative contents of 2-octenal and vanillin in the SSF group significantly increased (Fig. 5 E), which also enhanced sweet, fruity, and fatty flavors (Fig. 5 F). The volcano plot results showed that the SSF group significantly downregulated several flavor compounds, including ethyl dodecanoate, methionine, ethyl hexanoate, ethyl octanoate, and 3-(methylthio) propanal (Fig. 5 G). Finally, to explore the relationship between differential flavor compounds and sensory flavor characteristics, a network was constructed based on the top 10 important sensory characteristics. It was found that flavor metabolites associated with more than five sensory characteristics included ethyl octanoate, 3-nonanone, benzaldehyde, and acetic acid (Fig. 5 H). Effect of solid-state fermented on apparent digestibility and meat quality Compared to the ctrl group, the SSF group significantly enhanced the ADG in pigs ( P < 0.05) and reduced the FCR ( P < 0.01) (Table 14 ). Concurrently, the relative abundance of Firmicutes increased significantly in the SSF group, which was positively correlated with the relative abundance of SCFAs and related metabolic products such as 2,3-Butanediol and 2-Nonenal, while the relative abundance of Cyanobacteria was lower in the SSF groups with higher final weight (Fig. 6 A-B). Serum analysis revealed that ALB and blood GLU levels in the SSF group were highly significantly elevated compared to the ctrl group ( P < 0.01), while GLOB and Crea were significantly reduced ( P < 0.05, Table. 15). Immune markers showed that IgA ( P < 0.01) and IgG ( P < 0.05) levels in the serum of pigs fed SSF were significantly higher than those in the ctrl group, with highly significant reductions in inflammatory cytokines IL-4 and IL-6 ( P < 0.01). In terms of antioxidant indicators, SOD and GSH-PX were significantly higher in the SSF group ( P < 0.05), while MDA was significantly lower ( P < 0.05, Table. 16). Meat quality analysis indicated that the shear force of the longissimus dorsi muscle in the SSF group was highly significantly lower than that in the ctrl group ( P < 0.01, Table. 17). Table 14 Effects of SSF feed on growth performance of growing pigs Items Ctrl SSF First weight (kg) 17.27 ± 1.40 18.25 ± 0.40 Final weight (kg) 36.08 ± 1.56 38.65 ± 0.56* ADG (g) 672.02 ± 41.36 728.50 ± 9.72* ADGI (g) 1370.70 ± 110.03 1239.28 ± 51.73 FCR 2.01 ± 0.09 1.70 ± 0.06** ADG: Average daily gain; ADGI: Average daily gain intake; FCR: Feed conversion ratio. For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). Table 15 Effects of SSF feed on serum biochemical indices of growing pigs Item Ctrl SSF TP(g/L) 62.47 ± 3.32 63.95 ± 0.33 ALB(g/L) 33.85 ± 3.54 39.2 ± 0.51 ** GLOB(g/L) 28.62 ± 3.05 24.73 ± 1.55 * GGT(U/L) 28.33 ± 19.66 23.00 ± 8.6 ALT(U/L) 75.25 ± 0.96 69.25 ± 7.63 Crea(µmol/L) 123.22 ± 16.43 109.55 ± 7.42 * UN(µmol/L) 4.98 ± 0.75 4.31 ± 0.82 GLU(µmol/L) 7.33 ± 0.52 8.10 ± 0.21 ** INS(mIU/L) 66.55 ± 2.58 68.83 ± 6.81 GH(µg/L) 27.68 ± 0.87 26.89 ± 2.78 TP: Total protein; ALB: Albumin; GLOB: globulin; GGT: glutamyl transferase; ALT: alanine aminotransferase; Crea: creatinine; UN: urea; GLU: glucose; INS: insulin; GH: growth hormone. For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). Table 16 Effects of SSF feed on serum immune and antioxidant indexes of growing pigs Item Ctrl SSF IL-4(ng/L) 105.45 ± 2.64 96.16 ± 5.96 ** IL-6(ng/L) 1381.84 ± 43.72 1283.54 ± 19.27 ** IL-10(ng/L) 225.80 ± 16.16 210.14 ± 7.13 TNF-α(pg/mL) 484.76 ± 19.13 483.08 ± 16.03 IgA(µg/mL) 42.66 ± 1.78 46.34 ± 1.55 ** IgG(µg/mL) 463.63 ± 43.23 516.65 ± 38.94 * CAT(U/mL) 15.59 ± 1.46 15.82 ± 1.71 SOD(U/mL) 21.66 ± 0.31 30.99 ± 5.55 * T-AOC(µmol Trolox/mL) 0.94 ± 0.13 0.96 ± 0.20 GSH-PX(nmol/min/mL) 4.11 ± 0.82 5.54 ± 0.31 * MDA(nmoL/L) 1.88 ± 0.55 0.75 ± 0.33 * IL-4: Interleukin-4; IL-6: Interleukin-6; IL-10: Interleukin-10; TNF-α: Tumor necrosis-α; IgA: Immunoglobulin A; IgG: Immunoglobulin G; CAT: Catalase; SOD: Superoxide dismutase; T-AOC: Total antioxidant capacity; GSH-PX: Glutathione peroxidase; MDA: Malondialdehyde. For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). Table 17 Effects of probiotic fermented liquid feed on meat quality Items Ctrl SSF Drip force (%) 39.67 ± 8.48 31.76 ± 8.89** Drip loss (%) 8.65 ± 1.99 8.56 ± 1.24 PH pH 45min 6.38 ± 0.24 6.44 ± 0.15 pH 24h 5.48 ± 0.22 5.41 ± 0.11 Meat color lightness (L*) 1h 43.49 ± 1.58 43.07 ± 1.99 24h 50.45 ± 1.65 49.56 ± 3.27 Meat color redness (a*) 1h 4.92 ± 0.41 5.05 ± 0.37 24h 6.80 ± 0.96 7.13 ± 1.41 Meat color yellowness (b*) 1h 11.55 ± 0.88 12.04 ± 0.83 24h 13.73 ± 0.80 14.12 ± 0.58 For the same row, statistically significant differences between Ctrl and SSF groups were considered: * P < 0.05 and ** P < 0.01. Data are expressed as means ± SEM (n = 4). Effect of solid-state fermented feed on pig intestine HE staining revealed that the villi in the small intestine of the SSF group were more neatly arranged, with jejunal villi exhibiting more leaf-like shapes compared to the finger-like shapes in the ctrl group (Fig. 7 A). This change in villus morphology increased the surface area for nutrient absorption. Additionally, the villus height and crypt depth in all intestinal segments of the SSF group were significantly higher than those in the Ctrl group ( P < 0.01). The villus-to-crypt ratio in the jejunum and duodenum of the SSF group was also significantly higher than that of the Ctrl group ( P < 0.01), indicating that feeding SSF helped maintain the integrity of the small intestinal tissue structure in growing pigs (Table. 18). Moreover, the expression levels of tight junction proteins Claudin-1, Occludin, and ZO-1 in the jejunal tissue of the SSF group were significantly higher than those in the ctrl group (P < 0.05), suggesting that feeding solid-state fermented feed positively impacted the intestinal barrier function in growing pigs (Fig. 7 B). Table 18 Effects of SSF feed on small intestinal histomorphology of growing pigs Small intestine Item Ctrl SSF Duodenum VH(µm) 535.87 ± 30.66 843.51 ± 59.76 ** CD(µm) 362.08 ± 11.17 246.26 ± 12.65 ** VH / CD 1.48 ± 0.10 3.429 ± 0.25 ** Jejunum VH(µm) 323.38 ± 25.82 620.23 ± 35.03 ** CD(µm) 418.05 ± 21.51 248.05 ± 8.33 ** VH / CD 0.78 ± 0.09 2.50 ± 0.20 ** VH: Villus height; CD: Crypt depth. For the same row, statistically significant differences between Ctrl and SSF groups were considered: *p < 0.05 and **p < 0.01. Data are expressed as means ± SEM (n = 4). Discussion SSF is widely used in bio-feed technology due to its broad range of applicable microbial strains, large fermentation substrate volume, and simple operating procedures. However, the SSF process is influenced by microbial types, substrates, and various fermentation conditions, leading to unstable microbial performance and low enzyme production[ 15 , 20 , 21 ]. Some studies have shown that the addition of extra enzymes in combination with microbial fermentation can overcome this challenge and help reduce feed quality losses caused by fermentation[ 22 – 24 ]. Therefore, this study aims to optimize the fermentation ratios and conditions of B. subtilis , L. plantarum , S.cerevisiae , and A. niger by using TCA-SP and CF as key indicators[ 25 ] during the SSF process, and to conduct a combined microbial and enzymatic fermentation with 11 enzyme preparations. The results showed that the optimal ratio of B. subtilis : L. plantarum : S. cerevisiae : A. niger was 1:2:3:3, with a fermentation temperature of 36℃, inoculation amount of 9.3%, moisture content of 72%, and fermentation time of 4.1 days. Meanwhile, the SSF group exhibited significant increases in CP, EE, CF, and NDF content, and high-molecular-weight proteins into smaller peptide molecules. It has been reported that the increase in CP may be associated with the conversion of large molecular substances into more TCA-SP, while the reduction in NDF is beneficial for the absorption of nutrients[ 26 , 27 ]. Furthermore, ANFs and toxins contained in feed ingredients such as corn and soybean meal can pose risks to animal health[ 28 ]. Among these, TI in ANFs can hinder digestion[ 29 ], and PHA can damage pig intestinal tissue[ 30 ]. Consistent with previous research findings[ 31 ], this study discovered that after fermentation, α-conglycinin, β-conglycinin, SPAg, TI, and PHA were significantly reduced, and the contents of toxins DON and ZEN were extremely significantly decreased compared to the ctrl group. These results indicate that SSF can effectively degrade ANFs in feed, has a positive effect on feed quality improvement, and can more effectively reduce the risk of vomiting and poisoning in growing pigs caused by toxins. During the fermentation process of feed, the involvement of microorganisms promotes changes in certain metabolites within the feed. This experiment further employed 16S rDNA sequencing and flavoromics sequencing to investigate the microbial community composition and flavor metabolite in feed. The results showed that, as the fermentation progressed, the phyla Acidobacteria and Firmicutes significantly increased, and the core bacterial genera shifted from Pseudomonas to Lactobacillus . This shift may be associated with the acid-producing activity of Lactobacillus plantarum[ 32 ] and the strong proteolytic and cellulolytic capabilities of Bacillus during fermentation[ 33 ]. Meanwhile, as feed fermentation progressed, the abundance of genes related to carbohydrate and amino acid metabolism significantly increased, indicating that these metabolic functions may be associated with the production of carbohydrates and membrane transport. Given that current research primarily focuses on the impact of fermented feed on pork flavor[ 34 , 35 ], while studies on characteristic flavor metabolites of fermented feed are relatively rare. It has been reported that the fermentation of corn flour with Lactobacillus plantarum and Saccharomyces cerevisiae significantly increases aromatic compounds and alcohol flavor substances, resulting in a strong fruity aroma[ 36 ]. In this experiment, the increase in phenolic and heterocyclic compounds can also release a special aromatic odor. However, the trend of changes in alcohol metabolites is opposite, which may be due to the combination of alcohols with some acidic substances in the substrate to produce more ester compounds, thereby reducing their relative content. Interestingly, the key flavor compounds such as 2,3-butanediol, 2-nonanone, Benzyl alcohol, γ-decalactone, and γ-octalactone identified in this study have also yielded the same results in other studies[ 37 ]. Growth performance is the most direct indicator reflecting the feeding effectiveness of fermented feed and assessing economic benefits[ 38 ]. It has been reported that fermented feed can significantly increase ADG and decrease FCR, but has no significant effect on ADFI[ 39 ], which is consistent with the results of this experiment. Further analysis through interaction plots revealed that the significant increase in Firmicutes was positively correlated with the production of SCFA-related metabolites such as 2,3-butanediol and 2-nonenal, which in turn promoted pig growth and improved feed conversion efficiency. Conversely, the reduction in Cyanobacteria may be associated with enhanced growth performance in pigs. It was found that in the early developmental stage of growing pigs, SSF significantly improved muscle tenderness, but had no significant effect on meat color and pH value, which this may be related to the early improvement of the myofibrillar protein network structure[ 40 ]. Currently, Serum physiological, immune, and antioxidant indicators have been proven to comprehensively reflect the animal's basic nutritional metabolism and immune status[ 41 ]. In this study, SSF significantly increased serum IgA and IgG levels, indicating its positive role in enhancing animal immune function. The study also observed that in the SSF group, the levels of the pro-inflammatory factor IL-6 and the oxidative factor MDA in serum were significantly reduced, while the levels of the antioxidant indicators GSH-PX and SOD were significantly increased, indicating that fermentation effectively enhanced the immune stress resistance of growing pigs. The small intestine is the primary site for nutrient digestion and absorption in pigs and is closely related to growth performance[ 42 ]. Studies have shown that the key to nutrient absorption in the small intestine lies in the integrity and morphology of intestinal villi. The higher the villus-crypt ratio, the greater the absorptive surface area and the stronger the absorption capacity of the villi[ 43 ]. Moreover, tight junction proteins Claudin-1, ZO-1, and Occludin are important components of the intestinal barrier, selectively permeating nutrients and water between intestinal wall cells and preventing pathogens from entering the body through the intestinal lumen[ 44 , 45 ]. These results showed that the addition of SSF feed significantly improved the structural morphology of the small intestine and increased the relative expression of Occludin, Claudin-1, and ZO-1 proteins in the jejunum and ileum of growing pigs. Conclusion This study successfully established and optimized a SSF process based on a combination of B. subtilis , L. plantarum , S. cerevisiae , and A. niger . This process significantly enhances the nutritional value of feed through the synergistic action of microbes and enzymes, increases the abundance of beneficial bacterial populations, and improves flavor characteristics. After feeding growing pigs a diet containing 10% fermented feed, it effectively improved muscle development and tenderness of the meat, increased serum antioxidant and immune capabilities, significantly improved the morphology of the small intestine tissue, and enhanced the intestinal barrier function, which is beneficial for the nutritional absorption and healthy growth of growing pigs. Abbreviations Met Methionine Thr Threonine Trp Tryptophan DM Dry matter OM Organic matter CP Crude protein EE Ether extract ADF Acid detergent fiber NDF Neutral detergent fiber CA Crude ash Lys Lysine Cys Cystine B. Subtilis Bacillus subtilis L. Plantarum Lactobacillus plantarum S. Cerevisiae Saccharomy cescerevisiae A. Niger Aspergillus niger DON Deoxynivalenol ZEN Zearalenone AFB1 Aflatoxin B1 TS T-2 toxin ADG Average daily gain ADGI Average daily gain intake FCR Feed conversion ratio TP Total protein ALB Albumin GLOB globulin GGT Glutamyl transferase ALT Alanine aminotransferase Crea Creatinine UN Urea GLU Glucose INS Insulin GH Growth hormone IL-4 Interleukin-4 IL-6 Interleukin-6 IL-10 Interleukin-10 TNF-α Tumornecrosis-α IgA Immunoglobulin A IgG Immunoglobulin G CAT Catalase SOD Superoxide dismutase T-AOC Total antioxidant capacity GSH-PX Glutathione peroxidase MDA Malondialdehyde VH Villus height CD Crypt depth Declarations Acknowledgements This work was supported by the Shanxi Province Basic Research Program (202403021211043); the Shanxi Province Graduate Research Innovation Project (2024KY308); the National Key Research and Development Program of China (2023YFD130040203); National Natural Science Foundation of China (NSFC 32272846); the funding from the Jinzhong National Agricultural High-tech Zone Doctoral Workstation (JZNGQBSGZZ005); and the earmarked fund for Modern Agro-industry Technology Research System. Author contributions Mengting Ji: Validation, Formal analysis, Funding acquisition, Writing - Original Draft and Writing - Review & Editing. Jingchao Liu: Validation and Formal analysis. Qinglin Wang: Conceptualization and Formal analysis. Tianye Gong: Data curation, Conceptualization and Methodology. Jiaqi Zhang: Formal analysis, Investigation. Meng Li: Data Curation. Xiaohong Guo: Supervision and Resources. Yang Yang: Supervision, Project administration, Funding acquisition and Writing - Review & Editing. Bugao Li: Project administration, Funding acquisition and Writing - Review & Editing. Funding This work was supported by the Shanxi Province Basic Research Program (202403021211043); the Shanxi Province Graduate Research Innovation Project (2024KY308); the National Key Research and Development Program of China (2023YFD130040203); National Natural Science Foundation of China (NSFC 32272846); the funding from the Jinzhong National Agricultural High-tech Zone Doctoral Workstation (JZNGQBSGZZ005); and the earmarked fund for Modern Agro-industry Technology Research System. Availability of data and material The 16S dataset used and analyzed during this study can be found at NCBI SRA under accession number PRJNA1275368, the RNA-seq dataset is also available at NCBI SRA under the same accession number PRJNA1282860, and the metabolomics datasets are available under NGDC OMIX accession OMIX011743. The above data that support the study findings are publicly available. Information can be made available from the authors upon request. Ethics approval and consent to participate All experimental procedures were approved by the Animal Ethics Committee of Shanxi Agricultural University (approval number. SXAU-EAW-2021MS.P.052801). The experimental protocols complied with the requirements for farm animal welfare and were approved by the College of Animal Science and Technology at Shanxi Agricultural University. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details College of Animal Science, Shanxi Agricultural University, Taigu 030801, China. Shanxi Provincial Key Laboratory of Poultry and Livestock Genetic Resources Exploration and Precision Breeding, Shanxi Agricultural University, Taigu 030801, China. References Xie K, Dai Y, Zhang A, Yu B, Luo Y, Li H, He J. Effects of fermented soybean meal on growth performance, meat quality, and antioxidant capacity in finishing pigs. J Funct Foods. 2022;94:105128. Ram S, Narwal S, Gupta OP, Pandey V, Singh GP. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7242996","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":518695335,"identity":"786ebe3a-b691-4f0e-99fd-6bdc4342eecf","order_by":0,"name":"Mengting Ji","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Mengting","middleName":"","lastName":"Ji","suffix":""},{"id":518695336,"identity":"ebdd2b7e-b6e5-4f28-b324-37608503c5aa","order_by":1,"name":"Jingchao Liu","email":"","orcid":"","institution":"Shanxi Agricultural 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18:59:33","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":239626,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/2f2f81dd9158cd28d8b7d661.html"},{"id":92113762,"identity":"913ca56f-09b4-42b6-82b6-099d2012609d","added_by":"auto","created_at":"2025-09-24 18:59:33","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":33760,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of different mixed-strain combinations and fermentation conditions on solid-state fermented feed and anti-nutritional factors. Statistically significant differences between two groups were considered: *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01 and ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Data are expressed as means ± SEM (n = 4).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/5d53c10bc76e612a54196771.jpeg"},{"id":92113763,"identity":"f1644fea-fefc-493e-b82f-6e45d950500b","added_by":"auto","created_at":"2025-09-24 18:59:33","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":443552,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different fermentation conditions on solid-state fermented feed and response surface optimization experiments. The effect of \u003cstrong\u003eA \u003c/strong\u003emoisture content, \u003cstrong\u003eB\u003c/strong\u003e inoculation amount, \u003cstrong\u003eC\u003c/strong\u003e fermentation time, \u003cstrong\u003eD\u003c/strong\u003e temperature on solid-state fermented feed. \u003cstrong\u003eE\u003c/strong\u003e Response surface plots and contour plots of inoculum quantity and moisture content. \u003cstrong\u003eF\u003c/strong\u003e Response surface plots and contour plots of moisture content and fermentation time. \u003cstrong\u003eG\u003c/strong\u003e Response surface plots and contour plots of inoculum quantity and fermentation time.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea, b, c\u003c/sup\u003e Different superscripts in each row for each factor differ significantly (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/8561c7b32808f903a6884de4.jpeg"},{"id":92113769,"identity":"330b7a35-0252-4b9a-be83-17b411478404","added_by":"auto","created_at":"2025-09-24 18:59:33","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":706196,"visible":true,"origin":"","legend":"\u003cp\u003eSurface structure of solid-state fermented feed and changes in protein molecular weight by SDS-PAGE. \u003cstrong\u003eA \u003c/strong\u003eThe synergistic fermentation effect of strains and enzymes. \u003cstrong\u003eB\u003c/strong\u003e Effect of SSF on feed surface structure (40×, 500×, 1500×). \u003cstrong\u003eC\u003c/strong\u003e SDS-PAGE of SSF feed at fermentation times of 4 d.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea, b, c\u003c/sup\u003e Different superscripts in each row for each factor differ significantly (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/aaf44202d7213a689dc0cba6.jpeg"},{"id":92114059,"identity":"b6a9f669-e23b-4cc3-b088-f56ada07d51f","added_by":"auto","created_at":"2025-09-24 19:07:33","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":207089,"visible":true,"origin":"","legend":"\u003cp\u003eThe diversity of feed microbiota community structure and the relative abundance at the phylum and genus levels. \u003cstrong\u003eA\u003c/strong\u003e chao index, pd_whole index, shannon index, simpson index. \u003cstrong\u003eB\u003c/strong\u003e The analysis of principal coordinates analysis (PCoA). \u003cstrong\u003eC\u003c/strong\u003eVenn diagram. Composition of SSF feed at phylum \u003cstrong\u003eD\u003c/strong\u003e and genus \u003cstrong\u003eE\u003c/strong\u003elevel. \u003cstrong\u003eF \u003c/strong\u003eThe result of LDA discriminant (LDA\u0026gt;3.5). \u003cstrong\u003eG\u003c/strong\u003e is the KEGG 1-level pathway. \u003cstrong\u003eH\u003c/strong\u003e is the 3-level pathway.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/8eb6d7aa594e9b9b655a17d6.jpeg"},{"id":92113773,"identity":"443d61ca-7d3f-4345-8f16-2568c8539611","added_by":"auto","created_at":"2025-09-24 18:59:33","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":258696,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in Feed Flavor Metabolites. \u003cstrong\u003eA\u003c/strong\u003e Chromatographic 3D plots. \u003cstrong\u003eB\u003c/strong\u003e PLS-DA. \u003cstrong\u003eC\u003c/strong\u003e Venn. \u003cstrong\u003eD\u003c/strong\u003e Radar map of relative content of flavor substances. \u003cstrong\u003eE\u003c/strong\u003e ROVA and \u003cstrong\u003eF\u003c/strong\u003e Sensory Flavor radar map. \u003cstrong\u003eG\u003c/strong\u003e Volcano Plot of the flavor metabolite. \u003cstrong\u003eH\u003c/strong\u003e Graph of the association network between sensory flavor features and flavor substances.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/618c58d2ebdcc7d2107540d4.jpeg"},{"id":92113771,"identity":"1e14b942-c377-484d-b081-6fcdf3486900","added_by":"auto","created_at":"2025-09-24 18:59:33","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":175547,"visible":true,"origin":"","legend":"\u003cp\u003eConstruct interaction network diagrams between environmental factors, microorganisms, and metabolites. \u003cstrong\u003eA\u003c/strong\u003e An interaction network diagram between environmental factors and microorganisms. \u003cstrong\u003eB\u003c/strong\u003e An interaction network diagram between microorganisms and metabolites.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/cdb6022ded525212d9123885.jpeg"},{"id":92114063,"identity":"e9be31bf-2ecc-4f7c-abfc-607881994a04","added_by":"auto","created_at":"2025-09-24 19:07:33","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":266559,"visible":true,"origin":"","legend":"\u003cp\u003eThe impact of strain-enzyme solid-state fermented feed on the intestinal barrier function of growing pigs. \u003cstrong\u003eA\u003c/strong\u003e Hematoxylin and eosin (H\u0026amp;E) staining of the duodenum and jejunum (100×). \u003cstrong\u003eB\u003c/strong\u003e Expression of tight junction factors and proteins in the jejunum of growing pigs in the SSF group. For the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 and **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01. Data are expressed as means ± SEM (n = 4).\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/44e91a229dcb1f1e1f1e3b5b.jpeg"},{"id":92188852,"identity":"ac9300bd-d737-4432-bdcc-eda26b0eac5f","added_by":"auto","created_at":"2025-09-25 14:54:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4085035,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/f9daad57-98cd-4fce-a41b-c9c7f8e3712f.pdf"},{"id":92113765,"identity":"f166614f-975f-4f02-9ff1-0e385d7ca946","added_by":"auto","created_at":"2025-09-24 18:59:33","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2072463,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7242996/v1/9eb9f59abe7724d7a837eff0.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimization of solid-state fermentation process of diets and its effects on growth performance and intestinal function in growing pigs","fulltext":[{"header":"Background","content":"\u003cp\u003eCorn and soybean meal, as high-quality nutritional sources in pig diets, provide essential energy, protein[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, it is limited by anti-nutritional factors such as soybean antigenic proteins, trypsin inhibitors (TI), and non-starch polysaccharides (NSP), which negatively affect feed utilization, nutrient release and absorption in pigs, and may lead to intestinal allergies and diarrhea in pigs[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Microbial fermentation can effectively eliminate anti-nutritional factors and certain macromolecular substances in feed. Previous studies have predominantly focused on liquid-state fermented feed[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], while solid-state fermentation (SSF) has gradually emerged as the preferred process in modern feed industry, owing to its comprehensive advantages in enhanced nutritional bioavailability, improved product stability, and reduced environmental footprint[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. SSF is a type of feed produced through microbial fermentation on a solid substrate, has been demonstrated to reduce energy consumption in feed production through multiple mechanisms, such as eliminating the need for substantial water inputs during fermentation and minimizing energy requirements for raw material processing[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nonetheless, the fermentation process involves multiple conditions, and the substances that play a key role in enhancing feed quality remain unclear. Therefore, establishing and optimizing SSF processes is of great significance.\u003c/p\u003e\u003cp\u003eCompared with microbial SSF alone, microbial-enzyme co-fermentation can more degrade and utilize substrates, significantly reducing the ANFs in feed and enhancing the value of feed or raw materials[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. For instance, during the fermentation process, the addition of cellulase and lactic acid bacteria can effectively reduce ANFs in soybean meal and enhance its nutritional value[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Concurrently, the addition of non-starch polysaccharide enzymes to fermented feed can increase the diversity of the pig gut microbiota, particularly enhancing the relative abundance of beneficial bacteria such as Bifidobacterium[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, the addition of enzymes can compensate for the insufficiency of enzyme production by the microorganisms, accelerating substrate degradation. Research has found that enzymes can influence the fermentation efficiency of microorganisms by affecting the production of lactic acid and changes in pH levels, and the co-fermented feed is rich in probiotics and enzymatic metabolic products, which are beneficial for maintaining animal gut health[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It has also been reported that microbial-enzyme co-fermentation can break down high-molecular-weight proteins into various peptides[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eResearch indicates that fermentation is a dynamic process during which the composition of the microbial community undergoes significant changes. For instance, Tang et al. effectively reduced the relative abundance of pathogenic bacteria such as \u003cem\u003eEscherichia-Shigella\u003c/em\u003e in the intestines of finishing pigs using SSF, while increasing the relative abundance of beneficial bacteria like \u003cem\u003eFirmicutes\u003c/em\u003e and \u003cem\u003eClostridium\u003c/em\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. There have also been experimental findings that SSF feed can increase the abundance of beneficial bacteria, such as \u003cem\u003eLactobacillus\u003c/em\u003e, thereby enhancing the balance of the intestinal microbiota and immune function[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Simultaneously, fermentation can also significantly improve the volatile flavor compounds in feed[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. It has been reported that during the solid-state fermentation process, enzymes produced by microorganisms can break down complex organic matter in feed, such as cellulose, hemicellulose, and pectin, releasing a greater amount of flavor compounds and nutrients, thereby enhancing the nutritional value of the feed[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, research on the microbial community structure and changes in flavor compounds within fermented feed is still relatively scarce. Therefore, this study aims to optimize the strain ratios and fermentation conditions in SSF using a four-strain mixture, analyze changes in microbial community structure and flavor metabolites in fermented feed, and investigate their effects on growth performance and intestinal function. This research will provide a scientific basis for the optimization of SSF processes and a comprehensive evaluation of its nutritional value.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEstablishment of solid-state fermented (SSF) feed process\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003eLactobacillus plantarum\u003c/em\u003e (\u003cem\u003eL. Plantarum\u003c/em\u003e, BNCC336421) and \u003cem\u003eBacillus subtilis\u003c/em\u003e (\u003cem\u003eB. Subtilis\u003c/em\u003e, BNCC109047) used in the experiment were purchased from Bena Culture Collection, while \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e (\u003cem\u003eS. Cerevisiae\u003c/em\u003e, CICC1355) and \u003cem\u003eAspergillus niger\u003c/em\u003e (\u003cem\u003eA. niger\u003c/em\u003e, CICC40273) were obtained from the China Center of Industrial Culture Collection. After each microbial strain was activated, optimization and screening were carried out based on the orthogonal experiment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with trichloroacetic acid-soluble protein (TCA-SP), CF, and the anti-nutritional factor β-conglycinin as the evaluation indicators. Subsequently, through single-factor and response surface optimization experiments (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), the optimal microbial ratios were conducted to investigate the effects of different fermentation times (1 day, 2 days, 3 days, 4 days, 5 days, and 6 days), fermentation temperatures (24\u0026deg;C, 28\u0026deg;C, 32\u0026deg;C, 36\u0026deg;C, and 40\u0026deg;C), water content (60%, 80%, 100%, 120%, and 140%), and microbial inoculation levels (6%, 9%, 12%, 15%, and 18%) on the TCA-SP and CF content in fermented feed. Thoroughly dissolve the compound enzyme preparation and mix it uniformly into the feed. Then, subject the mixture to bacteria-enzyme synergistic fermentation under optimized conditions using the refined mixed-strain ratio to produce SSF feed. The characteristics of the compound enzyme preparation are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and the nutritional composition and levels of the basal diet are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. All experiments were conducted with three biological replicates.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOrthogonal test factors and levels design table of L9 (3\u003csup\u003e4\u003c/sup\u003e) for strains proportion\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(A) B. subtilis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(B)L. plantarum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(C) S. cerevisiae\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(D) A. niger\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDesign of RSM experimental factors and levels\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFactor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eLevels\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA Inoculum quantity(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB Moisture content(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC Time(d)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of forage enzyme preparation\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnzyme\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTemperature range (℃)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAmount added (g/kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnzyme activity\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-glucanase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;50000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlkaline protease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;200000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcid protease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;60000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutral protease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eα-Amylase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePectinase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLipase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u0026ndash;55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;10000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eα-Galactosidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCellulase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;10000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXylanase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u0026ndash;55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;1000000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlucose oxidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;10000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNutrient composition and nutrient level of basal diet.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIngradient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eContents (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNutrient levels \u003csup\u003e1)\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eContents (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCorn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e67.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e92.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhey powder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWater\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoybean oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoybean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFish meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAsh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLysine hydrochloride\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eADF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMet(98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNDF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThr(98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrp(98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal Phosphorus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLimestone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaHPO4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMet\u0026thinsp;+\u0026thinsp;Cys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNaCl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePremix \u003csup\u003e2)\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTrp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eMet\u0026thinsp;=\u0026thinsp;Methionine; Thr\u0026thinsp;=\u0026thinsp;Threonine; Trp\u0026thinsp;=\u0026thinsp;Tryptophan; DM\u0026thinsp;=\u0026thinsp;Dry Matter; CP\u0026thinsp;=\u0026thinsp;Crude Protein; EE\u0026thinsp;=\u0026thinsp;Ether extract; ADF\u0026thinsp;=\u0026thinsp;Acid detergent fiber; NDF\u0026thinsp;=\u0026thinsp;Neutral detergent fiber; CA\u0026thinsp;=\u0026thinsp;Crude Ash; Lys\u0026thinsp;=\u0026thinsp;Lysine; Cys\u0026thinsp;=\u0026thinsp;Cystine.\u003c/p\u003e\u003cp\u003e\u003csup\u003e1)\u003c/sup\u003e Water, CP, EE, Ash, NDF and ADF were measured values, the others were calculated values.\u003c/p\u003e\u003cp\u003e\u003csup\u003e2)\u003c/sup\u003e Premix provided per kilogram of diet: Vitamin A 10000 IU; Vitamin D 3500 IU; Vitamin E 70 IU; Vitamin K3 3 mg; Vitamin B1 3 mg; Vitamin B2 10 mg; Vitamin B6 6 mg; biotin 0.4 mg; pantothenate acid 30 mg; niacin 30 mg; Cu 110 mg (as copper sulfate); Mn 10 mg (as manganese sulfate); Fe 140 mg (as ferrous sulfate); I 0.5 mg (as potassium iodide); Se 0.3 mg (as sodium selenite).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDetermination of feed nutritional value\u003c/h3\u003e\n\u003cp\u003eThe SSF feed was taken out from the incubator, ground into fine powder after being dried in an oven at 65\u0026deg;C for over 48 hours, and then stored sealed at 4\u0026deg;C for later use. Following the methods of previous studies[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], the feed was analyzed for crude protein (CP), ether extract (EE), ash, and neutral detergent fiber (NDF), while also determining the content of acid detergent fiber (ADF) and trichloroacetic acid-soluble protein (TCA-SP). The contents of soybean globulin (YJ820239), trypsin inhibitor (TI, YJ820238), β-conglycinin (YJ831129), phytohemagglutinin (PHA, YJ854229), deoxynivalenol (DON, ml103502), zearalenone (ZEN, ml036116), aflatoxin B1 (AFB1, ml036115), and T-2 toxin (TS, ml036120) were determined according to the manufacturer's instructions (Shanghai Enzyme-Linked Biotechnology Co., Ltd., China).\u003c/p\u003e\n\u003ch3\u003eDetermination of small peptides and analysis by electron microscopy\u003c/h3\u003e\n\u003cp\u003eGently pick up feed sample particles with tweezers and lay them flat on the operating plate for observation of different fields of view of the feed morphology under a scanning electron microscope. Additionally, add the denatured feed to a protein gel for electrophoresis, followed by staining and destaining with Coomassie brilliant blue dye.\u003c/p\u003e\u003cp\u003e\u003cb\u003e16S rDNA sequencing\u003c/b\u003e\u003c/p\u003e\u003cp\u003e16S rDNA sequencing was performed on the basal feed and SSF feed. After DNA extraction from the samples, a library was constructed and sequenced on the Illumina PE250 platform. The DADA2 software was used for data assembly, read filtering, redundancy removal, denoising, and chimera elimination. After generating ASVs (Amplicon Sequence Variants), species annotation was conducted based on sequence information. The annotation results were visualized using KRONA, and sequence counts at the phylum and genus levels were tallied. Alpha diversity indices, including observed_species (Sob), Chao1, Shannon, and Pielou, were analyzed using QIIME software. Beta diversity was assessed using the weighted UniFrac algorithm to analyze differences among microbial communities in different groups, with results displayed in a Principal Coordinates Analysis (PCoA) plot. Venn diagram analysis was conducted using the vegan package in R, followed by intergroup difference analysis using the LEfSe software. Functional annotation and community function prediction were performed using the Tax4Fun software. The OTU abundance table was combined with the \u0026ldquo;species-gene\u0026rdquo; network to output the relative functional abundance for each sample (NCBI: PRJNA1275368).\u003c/p\u003e\n\u003ch3\u003eFlavor metabolomics analysis\u003c/h3\u003e\n\u003cp\u003eThe 1 g sample was mixed with 10 \u0026micro;L of internal standard solution and incubated at 60\u0026deg;C for 30 minutes. The Solid-Phase Microextraction (SPME) fiber was aged at 270\u0026deg;C for 10 minutes, then placed in the incubation chamber. After adsorption at 60\u0026deg;C for 30 minutes, the SPME fiber was inserted into the injection port (desorbed at 250\u0026deg;C for 5 minutes) and then aged again at 270\u0026deg;C for 10 minutes. The injection volume was 10 \u0026micro;L, with an injection temperature set at 250\u0026deg;C and a constant helium flow rate of 1.0 mL/min. Detection was performed using the GC \u0026times; GC-TOFMS chromatography system (LECO, St. Joseph, MI, USA). The scan range was set at m/z 35\u0026ndash;550, with the transfer line and ion source temperature maintained at 250\u0026deg;C, an acquisition rate of 200 spectra/second, an electron impact energy of 70 eV, and a detector voltage of 2019 V. Continuous scan MS data were collected to generate total ion current (TIC) chromatograms. The data were processed using ChromaTOF software, which is specifically designed for advanced chromatography and mass spectrometry data analysis, providing features such as NonTarget Deconvolution and library searches. Flavor compounds were annotated using the ChromaTOF search software, and the numbers and relative abundances of various flavor compounds were analyzed. The flavor profiles of the samples were evaluated using relative odor activity values (ROAV), and sensory flavor analysis was performed using the FlavorDB database. Principal component analysis (PCA) was conducted on the metabolites, and volcano plots were used to visually display the distribution of differential metabolites between the two sample groups. A network relationship among flavor compounds was constructed using the igraph package based on the FlavorDB database (NGDC: OMIX011743).\u003c/p\u003e\n\u003ch3\u003eRNA-seq\u003c/h3\u003e\n\u003cp\u003eIn this study, total RNA was extracted from the rapidly frozen longissimus dorsi muscle using the Trizol method and assessed for purity with the NanoDrop ND-2000 (Thermo Fisher Scientific, Wilmington, DE) and validated for integrity with the Agilent 2100 Bioanalyzer. Stranded mRNA libraries were constructed using the Illumina TruSeq Stranded mRNA LT Kit and sequenced on the NovaSeq 6000 platform with 150 bp paired-end reads. Raw data underwent quality control with fastp to filter out low-quality data, yielding clean reads. These reads were then aligned to the reference genome using HISAT 2. Gene expression levels were quantified using Stringtie to reconstruct transcripts and RSEM to calculate expression levels across all genes in each sample. Differentially expressed genes (DEGs) were identified based on criteria of FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2FoldChange| \u0026ge; 1. Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted using the online platform I-Sanger (NCBI: PRJNA1282860).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eExperimental animal management\u003c/h2\u003e\u003cp\u003eThis study selected 48 Duroc \u0026times; Jinfen White pigs with a body weight of 17.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83 kg at 60\u0026thinsp;\u0026plusmn;\u0026thinsp;3 days of age. The pigs were randomly divided into two groups, each with 4 replicates per group and 6 pigs per replicate (an equal number of males and females): the control (Ctrl) group and the SSF group. The Ctrl group was fed a basal feed, while the SSF group was fed a diet supplemented with 10% SSF feed. After a 5-day adaptation period, the feeding trial lasted for 28 days. During the trial, the temperature and relative humidity inside the pig house were regularly monitored and recorded. The remaining feed and the amount of feed added were cleared and recorded every morning at 8:00, with free access to water throughout the period.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasurement of growth performance and sample collection\u003c/h3\u003e\n\u003cp\u003eIndividuals participating in the experiment were weighed at the beginning and end of the trial, and daily feed intake per pen was recorded. These data were used to calculate average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR). Blood samples were collected from each pig via jugular vein before the end of the trial, and serum was separated. The longissimus dorsi muscle was collected from the left side of the carcass, between the 13th and 16th lumbar vertebrae, after slaughter, for the measurement of meat color, shear force, drip loss, and pH value. Sections of the duodenum, jejunum, ileum, and mid-colon were gently washed in pre-cooled sterile saline or PBS and then placed in 4% paraformaldehyde fixative. The remaining tissue samples were immediately frozen in liquid nitrogen and stored at -80\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eImmune biochemistry and enzyme-linked immunosorbent assay (ELISA)\u003c/h3\u003e\n\u003cp\u003eConventional nutritional indicators such as total protein, albumin, globulin, blood glucose, and urea nitrogen were measured using an automatic biochemical analyzer (IDEXX, USA). ELISA kits for detecting interleukin-4 (IL-4, YJ31752), interleukin-6 (IL-6, YJ35656), interleukin-10 (IL-10, YJ31974), and tumor necrosis factor-α (TNF-α, YJ31476) in serum were purchased from Shanghai Enzyme-Linked. Malondialdehyde (MDA, A003-1-2), catalase (CAT, A007-1-1), total antioxidant capacity (T-AOC, A015-2-1), superoxide dismutase (SOD, A001-3-2), and glutathione peroxidase (GSH-PX, A005-1-2) were measured using biochemical assay kits from Nanjing Jiancheng.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eHistological evaluation\u003c/h2\u003e\u003cp\u003eThe fixed intestinal tissues were dehydrated using an ASP-200 (Leica, Germany). Tissue sections with a thickness of 5 \u0026micro;m were obtained using a rotary microtome (Leica, Germany), following a previously reported protocol [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The tissue sections were stained with hematoxylin-eosin, and images were captured using the EVOSFL Auto Cell Imaging System software. Chorion length, crypt depth, and chorion height/crypt depth ratios were calculated using Image-Pro Plus 6.0 software.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eIn this experiment, data were processed using SPSS20.0. An independent samples T-test was used to analyze the data, and the results were expressed as \"mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\". Statistical significance was indicated by a p-value of less than 0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eThe effect of strain ratios on solid-state fermentation\u003c/h2\u003e\u003cp\u003eThe optimal mixing ratios of the four strains were determined through orthogonal experiments. The results showed that the best combination for increasing the TCA-SP value was A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e2\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), with significant effects from \u003cem\u003eB. subtilis\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and \u003cem\u003eS. cerevisiae\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on TCA-SP (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Meanwhile, the best combination for CF degradation was A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), with significant effects from \u003cem\u003eS. cerevisiae\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and \u003cem\u003eB. subtilis\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on CF (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Additionally, the two mixed strains significantly reduced the levels of soybean globulin, TI, and β-conglycinin in the feed (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with the degradation effects of the A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e2\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e group being significantly higher than that of the A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Therefore, the A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e2\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e combination was selected as the optimal mixed strain ratio for further screening.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffect of 4 bacteria mixed fermentation on TCA-SP\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u003cp\u003eTCA-SP (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB. Subtilis\u003c/p\u003e\u003cp\u003e(A)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eL. Plantarum\u003c/p\u003e\u003cp\u003e(B)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eS. Cerevisiae\u003c/p\u003e\u003cp\u003e(C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eA. Niger (D)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ey1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ey2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003ey3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003ey\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.418\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.566\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.635\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.642\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.485\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.575\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.155\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.298\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.298\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.320\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.290\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e32.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.603\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e29.613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30.849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e30.647\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e31.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e29.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e31.544\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ek1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.565\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.290\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ek2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.470\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ek3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.505\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.475\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimal combination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003eA\u003csub\u003e1\u003c/sub\u003e B\u003csub\u003e2\u003c/sub\u003e C\u003csub\u003e3\u003c/sub\u003e D\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eB. Subtilis: Bacillus subtilis; L. Plantarum: Lactobacillus plantarum; S. Cerevisiae: Saccharomyces cerevisiae; A. Niger: Aspergillus niger.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTable of variance analysis of orthogonal test\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariation source\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSignificance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eTCA-SP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB. Subtilis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eL. Plantarum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eS. Cerevisiae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.723\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA. Niger\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSSe2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo compare the statistical significance between two groups: ns (not significant) indicates \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a significant difference, and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 indicates a highly significant difference.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffect of 4 bacteria mixed fermentation on CF\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u003cp\u003eCF(%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB. Subtilis\u003c/p\u003e\u003cp\u003e(A)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eL. Plantarum\u003c/p\u003e\u003cp\u003e(B)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eS. Cerevisiae\u003c/p\u003e\u003cp\u003e(C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eA. Niger (D)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ey1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ey2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003ey3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003ey\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.697\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.746\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.802\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.805\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.341\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.821\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.918\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.742\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.891\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.848\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.513\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.648\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.611\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.837\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.767\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3.899\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e32.529\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e34.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e34.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e34.654\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.943\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e34.866\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e34.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e33.942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e32.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33.081\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ek1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.779\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ek2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.850\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.874\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ek3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.676\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.297\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimal combination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e\u003cp\u003eA1 B3 C3 D3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eB. Subtilis: Bacillus subtilis; L. Plantarum: Lactobacillus plantarum; S. Cerevisiae: Saccharomyces cerevisiae; A. Niger: Aspergillus niger.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTable of variance analysis of orthogonal test\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariation source\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSignificance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eCF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA-B. Subtilis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB-L. Plantarum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.638\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.5396\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC-S. Cerevisiae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.209\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD-A. Niger\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSSe2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo compare the statistical significance between two groups: ns (not significant) indicates \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a significant difference, and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 indicates a highly significant difference.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eThe effects of different fermentation conditions on solid-state fermented feed\u003c/h2\u003e\u003cp\u003eSingle-factor and response surface optimization experiments were further conducted to verify the effects of moisture content, inoculation amount, fermentation time, and temperature on SSF feed. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-D, the highest levels of TCA-SP were observed at a moisture content of 80%, while CF levels were at their lowest, indicating that 80% is the optimal moisture content. Similarly, comparative analysis of TCA-SP and CF responses across experimental conditions determined the optimum inoculum size at 9%, fermentation time at 4 days, and fermentation temperature at 36\u0026deg;C. The response surface optimization experiment indicated that the established second-order regression model was highly significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The analysis of variance showed that the model had an R\u0026sup2; value of 0.96 and an adjusted R\u0026sup2; of 0.92 (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). By using response surface optimization software to fit the data, the resulting equation was obtained as Y\u0026thinsp;=\u0026thinsp;4.15\u0026ndash;0.0592A \u0026minus;\u0026thinsp;0.088B\u0026thinsp;+\u0026thinsp;0.0563C\u0026thinsp;+\u0026thinsp;0.0162AB \u0026minus;\u0026thinsp;0.0237AC \u0026minus;\u0026thinsp;0.1008BC \u0026minus;\u0026thinsp;0.1561A\u003csup\u003e2\u003c/sup\u003e \u0026minus;\u0026thinsp;0.1881B\u003csup\u003e2\u003c/sup\u003e \u0026minus;\u0026thinsp;0.2686C\u003csup\u003e2\u003c/sup\u003e. Furthermore, based on the interactions among moisture content, fermentation time, and inoculation amount, the optimal TCA-SP value was predicted. The predicted conditions were an inoculation amount of 9.283%, moisture content of 71.539%, and fermentation time of 4.112 days. Under these conditions, the TCA-SP value in the solid-state mixed-strain fermented feed was 4.112% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-G).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of response surface variance analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSum of Squares\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSignificance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.7758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA-Inoculation amount\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB-Moisture content\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC-Fermentation time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.6252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.4201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLack of Fit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.8929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePure Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo compare the statistical significance between two groups: ns (not significant) indicates \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a significant difference, and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 indicates a highly significant difference.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariance analysis of quadratic regression equation\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStd. Dev.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0636\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC.V. %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9648\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9194\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredicted R\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8792\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eThe impact of solid-state fermented feed with strain-enzyme on feed\u003c/h2\u003e\u003cp\u003eTo address the issue of insufficient enzyme production during mixed-strain fermentation, microbial-enzyme synergistic fermentation was employed for optimization. The results showed that, compared with the A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e2\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e group, the A\u003csub\u003e1\u003c/sub\u003eB\u003csub\u003e2\u003c/sub\u003eC\u003csub\u003e3\u003c/sub\u003eD\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;complex enzyme group had significantly lower crude fiber content (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and significantly higher acid-soluble protein content (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating better performance of microbial-enzyme synergistic fermentation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Meanwhile, after SSF, the boundaries of the feed cell walls became indistinct (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), and the proteins were degraded from large molecules to below 25 kDa after 4 days of fermentation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Furthermore, the nutritional components in the feed were analyzed. The results showed that the SSF group had significantly higher contents of CP, CF, and ash compared to the ctrl group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while the contents of NDF and ADF were significantly lower than those in the ctrl group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Additionally, compared to the ctrl group, the contents of ANF and DON and ZEN were significantly reduced (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Tables\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e), indicating that feed fermentation more effectively reduced the risk of vomiting and poisoning by toxins.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eQuality of SSF feed (as air-dry basis)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsh, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOM, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCP, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEE, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNDF, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eADF, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOM: Organic matter; CP: Crude protein; EE: Ether extract; NDF: Neutral detergent fiber; ADF: Acid detergent fiber.\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of SSF feed on content of anti-nutritional factors\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-nutritional factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eɑ-conglycinin (\u0026micro;g/g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-conglycinin (\u0026micro;g/g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobulin (\u0026micro;g/g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e331.05\u0026thinsp;\u0026plusmn;\u0026thinsp;14.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e212.99\u0026thinsp;\u0026plusmn;\u0026thinsp;9.98**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoybean trypsin inhibitor (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69.43\u0026thinsp;\u0026plusmn;\u0026thinsp;5.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.56\u0026thinsp;\u0026plusmn;\u0026thinsp;4.45**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePHA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e599.59\u0026thinsp;\u0026plusmn;\u0026thinsp;34.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e203.03\u0026thinsp;\u0026plusmn;\u0026thinsp;12.05**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of SSF on content of toxin in feed\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eToxin(\u0026micro;g/kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSafety standards(\u0026micro;g/kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDON\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e375.67\u0026thinsp;\u0026plusmn;\u0026thinsp;22.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e287\u0026thinsp;\u0026plusmn;\u0026thinsp;10.54**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e140.33\u0026thinsp;\u0026plusmn;\u0026thinsp;6.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91.33\u0026thinsp;\u0026plusmn;\u0026thinsp;7.23**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAFB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eDON: Deoxynivalenol; ZEN: Zearalenone; AFB1: Aflatoxin B1; TS: T-2 Toxin.\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eThe impact of solid-state fermentation on the microbial community structure of feed\u003c/h2\u003e\u003cp\u003eThe impact of microbial-enzyme synergistic fermentation on feed microbial composition was investigated using 16S rDNA sequencing. The results showed that the alpha diversity in the SSF group was significantly higher (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), and the microbial community structures between the two groups were distinctly separated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Meanwhile, the Venn diagram indicated that the ctrl group had 2,574 ASVs, while the SSF group had 4,117 ASVs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). At the phylum level, the proportions of \u003cem\u003eCyanobacteria\u003c/em\u003e and \u003cem\u003eProteobacteria\u003c/em\u003e were significantly reduced in the SSF group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while the proportions of \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eAcidobacteriota\u003c/em\u003e, and \u003cem\u003eGemmatimonadota\u003c/em\u003e were significantly increased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). At the genus level, the core genera in the ctrl group were \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eLactobacillus\u003c/em\u003e, while the core genus in the SSF group was \u003cem\u003eLactobacillus\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The SSF group also significantly increased the proportions of \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003ePediococcus\u003c/em\u003e, and \u003cem\u003eAcidobacterium RB41\u003c/em\u003e, while significantly reducing the proportion of \u003cem\u003eStreptococcus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eLEfSe analysis of intergroup differences revealed that the ctrl group had 10 specific microbial genera, while the SSF group had 17 differentially abundant bacterial communities, with \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003ePediococcus\u003c/em\u003e being the main specific genera (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). KEGG functional prediction showed that the main enrichments were in pathways such as amino acids and nucleotide sugars (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG-H).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eThe impact of solid-state fermentation on feed flavor metabolites\u003c/h2\u003e\u003cp\u003eThe three-dimensional chromatograms of the fermented feed samples identified by GC \u0026times; GC-TOFMS are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. PLS-DA analysis revealed that the volatile compounds in each group of feed clustered together, while the two groups were distinctly separated, indicating reliable data (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The Venn diagram showed that 404 specific compounds were identified in the Ctrl group and 513 in the SSF group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). The relative contents of aldehyde, acid, ester, and phenolic flavor compounds in the feed increased after fermentation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eROAV analysis indicated that the relative contents of 2-octenal and vanillin in the SSF group significantly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), which also enhanced sweet, fruity, and fatty flavors (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The volcano plot results showed that the SSF group significantly downregulated several flavor compounds, including ethyl dodecanoate, methionine, ethyl hexanoate, ethyl octanoate, and 3-(methylthio) propanal (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Finally, to explore the relationship between differential flavor compounds and sensory flavor characteristics, a network was constructed based on the top 10 important sensory characteristics. It was found that flavor metabolites associated with more than five sensory characteristics included ethyl octanoate, 3-nonanone, benzaldehyde, and acetic acid (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eEffect of solid-state fermented on apparent digestibility and meat quality\u003c/h2\u003e\u003cp\u003eCompared to the ctrl group, the SSF group significantly enhanced the ADG in pigs (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and reduced the FCR (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab14\" class=\"InternalRef\"\u003e14\u003c/span\u003e). Concurrently, the relative abundance of \u003cem\u003eFirmicutes\u003c/em\u003e increased significantly in the SSF group, which was positively correlated with the relative abundance of SCFAs and related metabolic products such as 2,3-Butanediol and 2-Nonenal, while the relative abundance of \u003cem\u003eCyanobacteria\u003c/em\u003e was lower in the SSF groups with higher final weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-B). Serum analysis revealed that ALB and blood GLU levels in the SSF group were highly significantly elevated compared to the ctrl group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while GLOB and Crea were significantly reduced (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table. 15). Immune markers showed that IgA (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and IgG (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) levels in the serum of pigs fed SSF were significantly higher than those in the ctrl group, with highly significant reductions in inflammatory cytokines IL-4 and IL-6 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In terms of antioxidant indicators, SOD and GSH-PX were significantly higher in the SSF group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while MDA was significantly lower (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table. 16). Meat quality analysis indicated that the shear force of the longissimus dorsi muscle in the SSF group was highly significantly lower than that in the ctrl group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Table. 17).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab14\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 14\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of SSF feed on growth performance of growing pigs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst weight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinal weight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eADG (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e672.02\u0026thinsp;\u0026plusmn;\u0026thinsp;41.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e728.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.72*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eADGI (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1370.70\u0026thinsp;\u0026plusmn;\u0026thinsp;110.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1239.28\u0026thinsp;\u0026plusmn;\u0026thinsp;51.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFCR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eADG: Average daily gain; ADGI: Average daily gain intake; FCR: Feed conversion ratio.\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab15\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 15\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of SSF feed on serum biochemical indices of growing pigs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTP(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALB(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.85\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLOB(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.62\u0026thinsp;\u0026plusmn;\u0026thinsp;3.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGGT(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.33\u0026thinsp;\u0026plusmn;\u0026thinsp;19.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALT(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69.25\u0026thinsp;\u0026plusmn;\u0026thinsp;7.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrea(\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e123.22\u0026thinsp;\u0026plusmn;\u0026thinsp;16.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e109.55\u0026thinsp;\u0026plusmn;\u0026thinsp;7.42\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUN(\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLU(\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINS(mIU/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.83\u0026thinsp;\u0026plusmn;\u0026thinsp;6.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGH(\u0026micro;g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.89\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTP: Total protein; ALB: Albumin; GLOB: globulin; GGT: glutamyl transferase; ALT: alanine aminotransferase; Crea: creatinine; UN: urea; GLU: glucose; INS: insulin; GH: growth hormone.\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab16\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 16\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of SSF feed on serum immune and antioxidant indexes of growing pigs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-4(ng/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e105.45\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.16\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6(ng/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1381.84\u0026thinsp;\u0026plusmn;\u0026thinsp;43.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1283.54\u0026thinsp;\u0026plusmn;\u0026thinsp;19.27\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-10(ng/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e225.80\u0026thinsp;\u0026plusmn;\u0026thinsp;16.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e210.14\u0026thinsp;\u0026plusmn;\u0026thinsp;7.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF-α(pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e484.76\u0026thinsp;\u0026plusmn;\u0026thinsp;19.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e483.08\u0026thinsp;\u0026plusmn;\u0026thinsp;16.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgA(\u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIgG(\u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e463.63\u0026thinsp;\u0026plusmn;\u0026thinsp;43.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e516.65\u0026thinsp;\u0026plusmn;\u0026thinsp;38.94\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAT(U/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOD(U/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.99\u0026thinsp;\u0026plusmn;\u0026thinsp;5.55\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT-AOC(\u0026micro;mol Trolox/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSH-PX(nmol/min/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMDA(nmoL/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIL-4: Interleukin-4; IL-6: Interleukin-6; IL-10: Interleukin-10; TNF-α: Tumor necrosis-α; IgA: Immunoglobulin A; IgG: Immunoglobulin G; CAT: Catalase; SOD: Superoxide dismutase; T-AOC: Total antioxidant capacity; GSH-PX: Glutathione peroxidase; MDA: Malondialdehyde.\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab17\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 17\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of probiotic fermented liquid feed on meat quality\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDrip force (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.67\u0026thinsp;\u0026plusmn;\u0026thinsp;8.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.76\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDrip loss (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003epH\u003csub\u003e45min\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003epH\u003csub\u003e24h\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMeat color lightness (L*)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMeat color redness (a*)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMeat color yellowness (b*)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eEffect of solid-state fermented feed on pig intestine\u003c/h2\u003e\u003cp\u003eHE staining revealed that the villi in the small intestine of the SSF group were more neatly arranged, with jejunal villi exhibiting more leaf-like shapes compared to the finger-like shapes in the ctrl group (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). This change in villus morphology increased the surface area for nutrient absorption. Additionally, the villus height and crypt depth in all intestinal segments of the SSF group were significantly higher than those in the Ctrl group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The villus-to-crypt ratio in the jejunum and duodenum of the SSF group was also significantly higher than that of the Ctrl group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that feeding SSF helped maintain the integrity of the small intestinal tissue structure in growing pigs (Table. 18). Moreover, the expression levels of tight junction proteins Claudin-1, Occludin, and ZO-1 in the jejunal tissue of the SSF group were significantly higher than those in the ctrl group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that feeding solid-state fermented feed positively impacted the intestinal barrier function in growing pigs (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab18\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 18\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of SSF feed on small intestinal histomorphology of growing pigs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSmall intestine\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCtrl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSSF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eDuodenum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVH(\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e535.87\u0026thinsp;\u0026plusmn;\u0026thinsp;30.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e843.51\u0026thinsp;\u0026plusmn;\u0026thinsp;59.76\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCD(\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e362.08\u0026thinsp;\u0026plusmn;\u0026thinsp;11.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e246.26\u0026thinsp;\u0026plusmn;\u0026thinsp;12.65\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVH / CD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.429\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eJejunum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVH(\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e323.38\u0026thinsp;\u0026plusmn;\u0026thinsp;25.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e620.23\u0026thinsp;\u0026plusmn;\u0026thinsp;35.03\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCD(\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e418.05\u0026thinsp;\u0026plusmn;\u0026thinsp;21.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e248.05\u0026thinsp;\u0026plusmn;\u0026thinsp;8.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVH / CD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eVH: Villus height; CD: Crypt depth.\u003c/p\u003e\u003cp\u003eFor the same row, statistically significant differences between Ctrl and SSF groups were considered: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSSF is widely used in bio-feed technology due to its broad range of applicable microbial strains, large fermentation substrate volume, and simple operating procedures. However, the SSF process is influenced by microbial types, substrates, and various fermentation conditions, leading to unstable microbial performance and low enzyme production[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Some studies have shown that the addition of extra enzymes in combination with microbial fermentation can overcome this challenge and help reduce feed quality losses caused by fermentation[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, this study aims to optimize the fermentation ratios and conditions of \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eL. plantarum\u003c/em\u003e, \u003cem\u003eS.cerevisiae\u003c/em\u003e, and \u003cem\u003eA. niger\u003c/em\u003e by using TCA-SP and CF as key indicators[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] during the SSF process, and to conduct a combined microbial and enzymatic fermentation with 11 enzyme preparations. The results showed that the optimal ratio of \u003cem\u003eB. subtilis\u003c/em\u003e: \u003cem\u003eL. plantarum\u003c/em\u003e: \u003cem\u003eS. cerevisiae\u003c/em\u003e: \u003cem\u003eA. niger\u003c/em\u003e was 1:2:3:3, with a fermentation temperature of 36℃, inoculation amount of 9.3%, moisture content of 72%, and fermentation time of 4.1 days. Meanwhile, the SSF group exhibited significant increases in CP, EE, CF, and NDF content, and high-molecular-weight proteins into smaller peptide molecules. It has been reported that the increase in CP may be associated with the conversion of large molecular substances into more TCA-SP, while the reduction in NDF is beneficial for the absorption of nutrients[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, ANFs and toxins contained in feed ingredients such as corn and soybean meal can pose risks to animal health[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Among these, TI in ANFs can hinder digestion[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and PHA can damage pig intestinal tissue[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Consistent with previous research findings[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], this study discovered that after fermentation, α-conglycinin, β-conglycinin, SPAg, TI, and PHA were significantly reduced, and the contents of toxins DON and ZEN were extremely significantly decreased compared to the ctrl group. These results indicate that SSF can effectively degrade ANFs in feed, has a positive effect on feed quality improvement, and can more effectively reduce the risk of vomiting and poisoning in growing pigs caused by toxins.\u003c/p\u003e\u003cp\u003eDuring the fermentation process of feed, the involvement of microorganisms promotes changes in certain metabolites within the feed. This experiment further employed 16S rDNA sequencing and flavoromics sequencing to investigate the microbial community composition and flavor metabolite in feed. The results showed that, as the fermentation progressed, the phyla \u003cem\u003eAcidobacteria\u003c/em\u003e and \u003cem\u003eFirmicutes\u003c/em\u003e significantly increased, and the core bacterial genera shifted from \u003cem\u003ePseudomonas\u003c/em\u003e to \u003cem\u003eLactobacillus\u003c/em\u003e. This shift may be associated with the acid-producing activity of \u003cem\u003eLactobacillus\u003c/em\u003e plantarum[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and the strong proteolytic and cellulolytic capabilities of \u003cem\u003eBacillus\u003c/em\u003e during fermentation[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Meanwhile, as feed fermentation progressed, the abundance of genes related to carbohydrate and amino acid metabolism significantly increased, indicating that these metabolic functions may be associated with the production of carbohydrates and membrane transport. Given that current research primarily focuses on the impact of fermented feed on pork flavor[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], while studies on characteristic flavor metabolites of fermented feed are relatively rare. It has been reported that the fermentation of corn flour with \u003cem\u003eLactobacillus plantarum\u003c/em\u003e and \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e significantly increases aromatic compounds and alcohol flavor substances, resulting in a strong fruity aroma[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In this experiment, the increase in phenolic and heterocyclic compounds can also release a special aromatic odor. However, the trend of changes in alcohol metabolites is opposite, which may be due to the combination of alcohols with some acidic substances in the substrate to produce more ester compounds, thereby reducing their relative content. Interestingly, the key flavor compounds such as 2,3-butanediol, 2-nonanone, Benzyl alcohol, γ-decalactone, and γ-octalactone identified in this study have also yielded the same results in other studies[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGrowth performance is the most direct indicator reflecting the feeding effectiveness of fermented feed and assessing economic benefits[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. It has been reported that fermented feed can significantly increase ADG and decrease FCR, but has no significant effect on ADFI[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which is consistent with the results of this experiment. Further analysis through interaction plots revealed that the significant increase in \u003cem\u003eFirmicutes\u003c/em\u003e was positively correlated with the production of SCFA-related metabolites such as 2,3-butanediol and 2-nonenal, which in turn promoted pig growth and improved feed conversion efficiency. Conversely, the reduction in \u003cem\u003eCyanobacteria\u003c/em\u003e may be associated with enhanced growth performance in pigs. It was found that in the early developmental stage of growing pigs, SSF significantly improved muscle tenderness, but had no significant effect on meat color and pH value, which this may be related to the early improvement of the myofibrillar protein network structure[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Currently, Serum physiological, immune, and antioxidant indicators have been proven to comprehensively reflect the animal's basic nutritional metabolism and immune status[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In this study, SSF significantly increased serum IgA and IgG levels, indicating its positive role in enhancing animal immune function. The study also observed that in the SSF group, the levels of the pro-inflammatory factor IL-6 and the oxidative factor MDA in serum were significantly reduced, while the levels of the antioxidant indicators GSH-PX and SOD were significantly increased, indicating that fermentation effectively enhanced the immune stress resistance of growing pigs. The small intestine is the primary site for nutrient digestion and absorption in pigs and is closely related to growth performance[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Studies have shown that the key to nutrient absorption in the small intestine lies in the integrity and morphology of intestinal villi. The higher the villus-crypt ratio, the greater the absorptive surface area and the stronger the absorption capacity of the villi[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Moreover, tight junction proteins Claudin-1, ZO-1, and Occludin are important components of the intestinal barrier, selectively permeating nutrients and water between intestinal wall cells and preventing pathogens from entering the body through the intestinal lumen[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. These results showed that the addition of SSF feed significantly improved the structural morphology of the small intestine and increased the relative expression of Occludin, Claudin-1, and ZO-1 proteins in the jejunum and ileum of growing pigs.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study successfully established and optimized a SSF process based on a combination of \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eL. plantarum\u003c/em\u003e, \u003cem\u003eS. cerevisiae\u003c/em\u003e, and \u003cem\u003eA. niger\u003c/em\u003e. This process significantly enhances the nutritional value of feed through the synergistic action of microbes and enzymes, increases the abundance of beneficial bacterial populations, and improves flavor characteristics. After feeding growing pigs a diet containing 10% fermented feed, it effectively improved muscle development and tenderness of the meat, increased serum antioxidant and immune capabilities, significantly improved the morphology of the small intestine tissue, and enhanced the intestinal barrier function, which is beneficial for the nutritional absorption and healthy growth of growing pigs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eMet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eMethionine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eThr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eThreonine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eTrp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eTryptophan\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eDry matter\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eOrganic matter\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eCP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCrude protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eEE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eEther extract\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eADF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAcid detergent fiber\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eNDF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eNeutral detergent fiber\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCrude ash\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eLys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eLysine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eCys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCystine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eB. Subtilis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eBacillus subtilis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eL. Plantarum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eLactobacillus plantarum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eS. Cerevisiae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eSaccharomy cescerevisiae\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eA. Niger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAspergillus niger\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eDON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eDeoxynivalenol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eZEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eZearalenone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eAFB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAflatoxin B1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eT-2 toxin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eADG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAverage daily gain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eADGI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAverage daily gain intake\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eFCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eFeed conversion ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eTotal protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eALB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eGLOB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGlutamyl transferase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eALT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eAlanine aminotransferase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eCrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCreatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eUN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eUrea\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eGLU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGlucose\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eINS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eInsulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eGH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGrowth hormone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eIL-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eInterleukin-4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eInterleukin-6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eIL-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eInterleukin-10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eTNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eTumornecrosis-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eIgA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eImmunoglobulin A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eIgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eImmunoglobulin G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCatalase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eSOD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eSuperoxide dismutase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eT-AOC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eTotal antioxidant capacity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eGSH-PX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGlutathione peroxidase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eMDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eMalondialdehyde\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eVH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eVillus height\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eCD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCrypt depth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Shanxi Province Basic Research Program (202403021211043); the Shanxi Province Graduate Research Innovation Project (2024KY308); the National Key Research and Development Program of China (2023YFD130040203); National Natural Science Foundation of China (NSFC 32272846); the funding from the Jinzhong National Agricultural High-tech Zone Doctoral Workstation (JZNGQBSGZZ005); and the earmarked fund for Modern Agro-industry Technology Research System.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMengting Ji: Validation, Formal analysis, Funding acquisition, Writing - Original Draft and Writing - Review \u0026amp; Editing. Jingchao Liu: Validation and Formal analysis. Qinglin Wang: Conceptualization and Formal analysis. Tianye Gong: Data curation, Conceptualization and Methodology. Jiaqi Zhang: Formal analysis, Investigation. Meng Li: Data Curation. Xiaohong Guo: Supervision and Resources. Yang Yang: Supervision, Project administration, Funding acquisition and Writing - Review \u0026amp; Editing. Bugao Li: Project administration, Funding acquisition and Writing - Review \u0026amp; Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Shanxi Province Basic Research Program (202403021211043); the Shanxi Province Graduate Research Innovation Project (2024KY308); the National Key Research and Development Program of China (2023YFD130040203); National Natural Science Foundation of China (NSFC 32272846); the funding from the Jinzhong National Agricultural High-tech Zone Doctoral Workstation (JZNGQBSGZZ005); and the earmarked fund for Modern Agro-industry Technology Research System.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 16S dataset used and analyzed during this study can be found at NCBI SRA under accession number PRJNA1275368, the RNA-seq dataset is also available at NCBI SRA under the same accession number PRJNA1282860, and the metabolomics datasets are available under NGDC OMIX accession OMIX011743. The above data that support the study findings are publicly available. Information can be made available from the authors upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental procedures were approved by the Animal Ethics Committee of Shanxi Agricultural University (approval number. SXAU-EAW-2021MS.P.052801). The experimental protocols complied with the requirements for farm animal welfare and were approved by the College of Animal Science and Technology at Shanxi Agricultural University.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCollege of Animal Science, Shanxi Agricultural University, Taigu 030801, China.\u003c/p\u003e\n\u003cp\u003eShanxi Provincial Key Laboratory of Poultry and Livestock Genetic Resources Exploration and Precision Breeding, Shanxi Agricultural University, Taigu 030801, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eXie K, Dai Y, Zhang A, Yu B, Luo Y, Li H, He J. 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Systematic review and meta-analysis of the effect of feed enzymes on growth and nutrient digestibility in grow-finisher pigs: Effect of enzyme type and cereal source. Anim Feed Sci Technol. 2019;251:153\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu H, Hu J, Mahfuz S, Piao X. Effects of hydrolysable tannins as zinc oxide substitutes on antioxidant status, immune function, intestinal morphology, and digestive enzyme activities in weaned piglets. Animals. 2020;10:757.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eModina SC, Polito U, Rossi R, Corino C, Di Giancamillo A. Nutritional Regulation of Gut Barrier Integrity in Weaning Piglets. Anim (Basel), 2019; 9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRuckman LA, Petry AL, Gould SA, Kerr BJ, Patience JF. The effects of enzymatically treated soybean meal on growth performance and intestinal structure, barrier integrity, inflammation, oxidative status, and volatile fatty acid production of nursery pigs. Transl Anim Sci. 2020;4:txaa170.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"animal-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"amic","sideBox":"Learn more about [Animal Microbiome](http://animalmicrobiome.biomedcentral.com)","snPcode":"42523","submissionUrl":"https://submission.nature.com/new-submission/42523/3","title":"Animal Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Microbial-enzyme synergy, Feed microbiota, Feed flavoromics, Muscle development, Intestinal barrier","lastPublishedDoi":"10.21203/rs.3.rs-7242996/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7242996/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBiological fermentation can improve animal growth performance and meat quality by optimizing feed nutritional properties. However, the complex fermentation parameters require further systematic optimization. This study aimed to establish and optimize a solid-state fermentation (SSF) process, evaluate changes in the feed microbial community and flavor metabolites, and investigate their effects on muscle development and intestinal barrier function in growing pigs. Here, we developed a synergistic solid-state fermentation (SSF) strategy for pig feed using combinations of 4 probiotics and 11 enzymatic preparations, 16S rDNA-seq and flavoromics-seq were employed to investigate the dynamic changes in microbial communities and flavor compounds post-fermentation. Subsequently, 32 Duroc \u0026times; Jinfen White pigs were fed diets containing 10% SSF to assess growth performance, intestinal health and muscle development.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe optimal fermentation ratio of Bacillus subtilis, Lactobacillus plantarum, \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e and \u003cem\u003eAspergillus niger\u003c/em\u003e is 1:2:3:3, with a temperature of 36\u0026deg;C, an inoculation rate of 93%, a moisture content of 72%, and a time of 4.1 days. SSF significantly enhanced the nutritional value of feed by increasing the ash, organic matter (OM), crude protein (CP), and ether extract (EE) content, while simultaneously reducing the concentration of anti-nutritional factors. Sequencing identified 17 differential microbes and 116 flavor compounds, with the relative abundance of \u003cem\u003eLactobacillus\u003c/em\u003e and the \u003cem\u003eFirmicutes\u003c/em\u003e significantly increased, 2-octenal and vanillin imparting sweet, fruity, and grassy notes to the feed. Meanwhile, RNA-seq revealed 320 DEGs in muscle tissue following fermented feed supplementation, which are mainly enriched in pathways related to cytochrome P450 drug metabolism and arginine biosynthesis. Additionally, H\u0026amp;E staining results indicated that fermentation significantly increased the villus height, crypt depth, and villus-to-crypt ratio in the small intestine of growing pigs, and the levels of tight junction proteins Claudin-1 and ZO-1 in the jejunum were significantly higher than those in the ctrl group. Subsequent correlation analysis indicated that \u003cem\u003eFirmicutes\u003c/em\u003e may influence pig growth performance and IL-6, TNF-α levels by affecting their metabolites.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur findings establish and optimize an SSF process that markedly elevates feed nutritional value, enriches beneficial microbes, and fosters the production of unique flavor metabolites. When fed to growing pigs, it effectively enhances growth performance and antioxidant capacity while improving small-intestinal morphology and barrier function.\u003c/p\u003e","manuscriptTitle":"Optimization of solid-state fermentation process of diets and its effects on growth performance and intestinal function in growing pigs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-24 18:59:28","doi":"10.21203/rs.3.rs-7242996/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-12T10:36:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-10T16:10:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-02T01:53:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308888307699208045139043396401677189799","date":"2025-10-17T14:36:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184922165875152432776071371043037384296","date":"2025-09-24T16:00:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-16T10:18:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-08T15:16:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T16:02:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Animal Microbiome","date":"2025-09-04T07:16:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"animal-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"amic","sideBox":"Learn more about [Animal Microbiome](http://animalmicrobiome.biomedcentral.com)","snPcode":"42523","submissionUrl":"https://submission.nature.com/new-submission/42523/3","title":"Animal Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e4747b74-268c-4649-a78a-bdbb12914727","owner":[],"postedDate":"September 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T11:38:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-24 18:59:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7242996","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7242996","identity":"rs-7242996","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}