Sheep and goat meats are increasingly popular worldwide due to their superior nutritional properties and distinctive flavor profiles. In recent decades, substantial progress in meat science has facilitated in-depth examinations of ovine and caprine muscle development during the antemortem phase, as well as post-mortem changes influencing meat attributes. To elucidate the intrinsic molecular mechanisms and identify potential biomarkers associated with meat quality, the methodologies employed have evolved from traditional physicochemical parameters (such as color, tenderness, water holding capacity, flavor, and pH) to some cutting-edge omics technologies, including transcriptomics, proteomics, and metabolomics approaches. This review provides a comprehensive analysis of multi-omics techniques and their applications in unraveling sheep and goat meat quality attributes. In addition, the challenges and future perspectives associated with implementing multi-omics technologies in this area of study are discussed. Multi-omics tools can contribute to deciphering the molecular mechanism responsible for the altered the meat quality of sheep and goats across transcriptomic, proteomic, and metabolomic dimensions. The application of multi-omics technologies holds great potential in exploring and identifying biomarkers for meat quality and quality control, thereby promoting the optimization of production processes in the sheep and goat meat industry.

Sheep and goat meat products are becoming increasingly popular among consumers due to their unique flavor derived from intramuscular fat (IMF), which contributes to formation of the distinctive odor. However, there is currently a dearth of reviews on the impact of IMF on the flavor of sheep and goat meat. The present review aims to discuss the relationships between IMF and flavor through lipid composition and fatty acid (FA) distribution, provide an overview of characteristic flavor compounds affecting the flavor of sheep and goat meat, and shed light on the impacts of pre-mortem and post-mortem factors on meat flavor attributed to changes in FAs and flavor compounds. Controlling pre-mortem practices and adjusting post-mortem harvesting methods are key factors in shaping and/or driving the flavor of sheep and goat meat products. This review enhances the comprehensive understanding of the impact of IMF on the flavor of sheep and goat meat.

Dietary protein supplementation has emerged as a promising strategy in combating sarcopenia. Furthermore, searching for alternatives of animal proteins has been a hot topic. The present study aimed to investigate the effects of zein peptides on C₂C₁₂ myoblasts and explore their potential molecular mechanisms. The proliferative, cell cycle, and anti-apoptotic activities of zein peptides were evaluated. Peptidomics analysis and transcriptome sequencing were employed to explore the structure-activity relationship and underlying molecular mechanisms. The results indicated that zein peptides (0.05–0.2 mg/mL) exerted a significant proliferation-promoting impact on C₂C₁₂ cells, via increasing cell viability by 33.37 to 42.39%. Furthermore, zein peptides significantly increased S phase proportion and decreased the apoptosis rate from 34.08% (model group) to 28.96% in C₂C₁₂ cells. In addition, zein peptides exhibited a pronounced anti-apoptotic effect on C₂C₁₂ cells. Zein peptides are abundant in branch-chain amino acids, especially leucine. Transcriptomics analysis revealed that zein peptides can promote proliferation, accelerate cell cycle, and improve protein synthesis of muscle cells through mTORC1 and mTORC2 signaling pathways.

Collagen peptides derived from fish skin may be limited in food applications due to undesirable flavors. To investigate the effects of Maillard reaction modification on their physicochemical and flavor properties, collagen peptides from tilapia skin were prepared via enzymatic hydrolysis, followed by the Maillard reaction with four reducing sugars (xylose, ribose, glucose and glucosamine) through a combined procedure involving simultaneous enzyme inactivation and Maillard reaction at 100 °C. The resultant Maillard reaction products (MRPs) were characterized by analyzing free amino groups, peptide size distribution and color difference, while the reaction progression was monitored using UV absorption and fluorescence spectroscopy. The flavor profile of MRPs was analyzed through quantitative descriptive sensory evaluation and GC-MS coupled with principal component analysis. Among the four reducing sugars tested, glucosamine-induced Maillard reaction products exhibited the most pronounced physicochemical and sensory improvements. Specifically, glucosamine-MRPs showed the greatest reduction in free amino groups (0.69 μmol/L) and a notable decrease in high-molecular-weight peptides (3.31%), accompanied by an increase in low-molecular-weight fractions. Colorimetric analysis revealed a marked color change (ΔE = 31.78), and spectral analysis further confirmed intensified UV absorbance and fluorescence intensity in the glucosamine group, indicating advanced reaction progression. Sensory evaluation demonstrated a significant reduction in bitterness and enhancement of umami and saltiness. Moreover, GC-MS analysis revealed that the glucosamine-treated group exhibited the most favorable volatile profile, characterized by an increase in aromatic compounds and a substantial decrease in undesirable odorants. This study provides a theoretical basis for controlling the undesirable flavor of collagen peptides through low-extent Maillard reactions by different reducing sugars.

To enhance the screening efficiency of bioactive peptides, an AI-driven approach was employed to screen DPP-IV inhibitory peptides from goat blood proteins by an integrated in silico, in vitro, and machine learning strategy. Furthermore, the inhibitory mechanism of DPP-IV inhibitory peptides was elucidated by kinetics, molecular docking and simulation. Additionally, their in vitro digestive stability was assessed. In silico results revealed that goat blood proteins were promising precursors of DPP-IV inhibitory peptides, while bromelain was the optimal protease. Their peptide sequences were further identified by peptidomics and predicted by self-developed machine learning models (LightGBM) to identify the potent DPP-IV inhibitory peptides. Two novel DPP-IV inhibitory peptides were identified (FPL and FPHFDL). Enzyme kinetics, molecular docking and molecular simulation data indicated that FPL served as a competitive inhibitor, whereas FPHFDL was a non-competitive inhibitor. Overall, the integrative in silico and in vitro strategy is feasible for rapid screening of DPP-IV inhibitory peptides from goat blood proteins.