This study systematically investigated the effects of tea polyphenols on methane (CH₄) production and the rumen epithelial cell transport capability in cattle using both in vitro and animal experiments, employing multi-omics techniques. The in vitro results demonstrated that, compared to the control group, tea polyphenols significantly reduced CH₄ production and the acetate/propionate ratio (p < 0.05). Tea polyphenols reduced CH₄ production by inhibiting the relative abundance of unclassified_d_Archaea methanogens and the protozoa Pseudoentodinium and g__Balantioides. The animal experiments showed that tea polyphenols significantly increased the concentrations of T-AOC and GSH-PX in bovine blood (p < 0.05). In addition, microbial groups such as Rikenellaceae_RC9_gut_group, Ruminococcaceae_NK4A214_group, and Butyrivibrio_2 were significantly enriched in the ruminal fluid of the tea polyphenol group (p < 0.05). The proteomic results indicated significant upregulation of proteins such as COIII, S100A8, FABP1, SLC2A8, and SLC29A1 (p < 0.05) and downregulation of proteins including HBB, RAB4A, RBP4, LOC107131172, HBA, and ZFYVE19 (p < 0.05), with FABP1 showing a positive correlation with propionate concentration, and RAB4A had a negative correlation (p < 0.05). Overall, tea polyphenols modulate the microbial composition within the rumen, inhibiting CH₄ production and enhancing the host’s rumen epithelial cell transport capacity for volatile fatty acids.

The aim of this study was to improve the utilization of peanut vines as forage material for ruminants by investigating the degradation pattern of peanut vines in the dairy cow rumen. Samples of peanut vine incubated in cow rumens were collected at various time points. Bacterial diversity was investigated by scanning electron microscopy (SEM) and 16S rRNA gene sequencing. Carbohydrate-active enzymes (CAZymes) were analyzed by metagenomics. The peanut vines degraded rapidly from 2 to 24 h, before slowing from 24 to 72 h. SEM images confirmed dynamic peanut vine colonization. Firmicutes and Bacteroidetes were the two most dominant bacterial phyla throughout. Principal coordinates analysis indicated significant microbial composition changes at 6 and 24 h. This may be because, in the early stage, soluble carbohydrates that are easily degradable were degraded, while in the later stage, fibrous substances that are difficult to degrade were mainly degraded. Glycoside hydrolases (GHs) were the most abundant CAZymes, with peak relative abundance at 6 h (56.7 trans per million, TPM), and reducing at 24 (55.9 TPM) and 72 h (55.3 TPM). Spearman correlation analysis showed that Alistipes_sp._CAG:435, Alistipes_sp._CAG:514, Bacteroides_sp._CAG:1060, Bacteroides_sp._CAG:545, Bacteroides_sp._CAG:709, Bacteroides_sp._CAG:770, bacterium_F082, bacterium_F083, GH29, GH78, and GH92 were important for plant fiber degradation. These findings provide fundamental knowledge about forage degradation in the cow rumen, and will be important for the targeted improvement of ruminant plant biomass utilization efficiency.

To fill the gap in systematic data on mineral contents and their dietary contributions in four mainstream dairy products (sterilized, pasteurized, fermented, modified milk) from Henan Province, China, this study aimed to characterize the mineral profiles [magnesium (Mg), iron (Fe), zinc (Zn), selenium (Se), copper (Cu)] and clarify the mineral nutritional disparities between domestic and imported sterilized milk. A total of 150 samples were analysed via inductively coupled plasma mass spectrometry (ICP-MS). Results revealed significant mineral content differences across dairy types: fermented milk had significantly lower Mg and Zn than sterilized and pasteurized milk (p < 0.05). Imported sterilized milk exhibited higher Mg (160.10 ± 31.88 mg/kg) than domestic counterparts (147.41 ± 32.47 mg/kg, p < 0.05). In terms of mineral intake contribution rates (defined as the percentage of mineral intake from dairy products relative to the Recommended Nutrient Intake (RNI), unit: %), the rates are ranked in descending order as follows: Se (11.68–25.32%) > Mg (11.11–20.76%) > Zn (5.88–16.33%) > Cu (0.62–1.81%) > Fe (0.25–1.00%). This study elucidates the mineral profiles of Henan’s dairy products, supporting residents’ dairy choices and optimisation of dairy processing technologies.

Background: National dietary guidelines have largely overlooked the environmental sustainability of food systems. A multi-objective optimization framework to evaluate trade-offs among nutritional requirements, greenhouse-gas emissions, and economic costs across four countries at different development stages—the United States, China, Australia, and New Zealand. Methods: Using epidemiologically informed nutrient constraints and life-cycle environmental data, we systematically evaluate dietary scenarios that optimize animal-product consumption while ensuring essential nutrient adequacy. Results: Our analysis shows that strategic reductions in beef consumption can lower diet-related greenhouse-gas emissions by 28–62%, while chicken and eggs are reallocated to maintain nutritional integrity. Economic impacts vary markedly: vitamin-optimized scenarios reduce costs by 23% in China but increase costs by 19% in Australia. Conclusion: The results reveal distinct optimization pathways that necessitate tailored policy measures. This framework enables policymakers to revise food-based dietary guidelines to align with climate commitments while safeguarding nutritional security and economic viability across diverse national contexts.

Alpha lipoic acid (α-LA) is a powerful antioxidant, which can reduce oxidative damage and inflammation in the host. In previous research, we found that 600 mg/kg α-LA supplemented in the diet could improve the activity of antioxidant enzymes and regulate the secretion of inflammatory factors in rumen of sheep. However, the mechanism of α-LA driving the antioxidant capacity in rumen of sheep remains unknown. The aim of this current research was to investigate the role of α-LA in antioxidant and inflammatory processes in the rumen of sheep. Transcriptomic and metabolomic analyses were performed to assess the variation of genes and metabolites of rumen epithelial tissue in sheep induced in the LA (600 mg/kg α-LA) group compared with the CTL (0 mg/kg α-LA) group. The results showed that some discovered core genes in the rumen epithelial tissue were negatively correlated with antioxidant activity. G6PD and HK2, the downregulated and upregulated core genes in the comparison of LA/CTL, were enriched in the pentose phosphate pathway (PPP) and the pathways of mannose and oligosaccharide metabolism, respectively. The PPP is a metabolic pathway within cells, primarily functioning to produce nicotinamide adenine dinucleotide phosphate (NADPH) and ribose-5-phosphate. The differential metabolites were enriched in the pathway of 2-oxocarboxylic acid metabolism, which improves the antioxidant capacity of the rumen epithelium by increasing enzymatic activities of SOD. In conclusion, the present study demonstrated that α-LA improved antioxidant activity by regulating PPP and 2-oxocarboxylic acid metabolism. This study will provide a theoretical basis for the application of α-LA in the raising of sheep.

In intensive farming, contactless individual pig identification is crucial for precision feeding and health monitoring. However, real-world barn conditions—such as fluctuating illumination, severe occlusions, non-rigid poses, and high inter-individual similarity—pose significant challenges. Existing models struggle to balance high accuracy with lightweight deployment. To address this, we propose YOLO-ESO, an optimized detection framework based on YOLOv10n. YOLO-ESO introduces three core innovations: (1) integrating the C2f_ODConv module into the backbone to strengthen feature learning under complex poses via dynamic convolution; (2) redesigning the neck with a Semantics and Detail Infusion (SDI) module to improve multi-scale fusion while suppressing background noise; and (3) embedding an Efficient Multi-Scale Attention (EMA) mechanism before the detection head to capture fine-grained identity cues like texture and contours. Evaluated on a real-world pig dataset, YOLO-ESO achieves an mAP@0.5 of 96.6%, an mAP@0.5:0.95 of 71.1%, and an F1 of 92.0%. YOLO-ESO surpasses state-of-the-art detectors including YOLOv8, YOLOv11, and RT-DETR, while introducing only 8.7 GFLOPs and 3.48 million parameters. Overall, the proposed YOLO-ESO provides an accurate and lightweight solution for robust individual pig identification in complex farming environments, showing strong potential for practical deployment in precision livestock farming.