This study aimed to address the growing prevalence of wooden breast (WB) in fast-growing broilers and the limitations of conventional detection methods, which are often subjective and lack precision in grading. Normal breast (NB), mild wooden breast (LWB), moderate wooden breast (MWB), and severe wooden breast (SWB) from Cobb broilers were evaluated for quality parameters including pH, color, water-holding capacity, textural properties, and shear force; additionally, volatile compounds were analyzed to develop a comprehensive, multidimensional grading system for wooden breast meat. Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) identified a total of 45 volatile compounds, among which 16 were determined as key differential substances. The contents of aldehydes and esters exhibited a significant decreasing trend with increasing WB severity. Principal component analysis (PCA) indicated that texture parameters and water-holding capacity were critical indicators for differentiating WB grades. Based on these findings, a backpropagation artificial neural network (BP-ANN) model was developed, demonstrating high classification accuracy with training and testing set accuracies of 98.81% and 94.44%, respectively. SHapley Additive exPlanations (SHAP) analysis further identified resilience, chewiness, pH, drip loss, and L^* value as key discriminant indicators. Mantel tests showed a significant positive correlation between resilience and 1-propanol, between chewiness and 1-octenal, and between L^* value and 1-octenal. These findings suggest that structural damage of muscle fibers and enhanced lipid oxidation during WB development may influence the formation of volatile flavor compounds. This study contributes to the theoretical understanding of the multidimensional mechanisms underlying meat quality deterioration.

This study explored the impact of adding sesbania gum on the quality of salami using backpropagation-artificial neural network (BP-ANN) analysis. Four treatment groups were designed: blank control (CK), inoculation of a mixed culture (CG), addition of sesbania gum (SE), and sesbania gum addition combined with mixed culture inoculation (SE-CG). The quality of salami was evaluated in terms of its pH, water activity (a_w), color difference, texture, sensory evaluation, and electronic nose analysis. It was demonstrated that the combined treatment rapidly decreased the pH and a_w of the product, thereby contributing to the formation of the final quality of salami. Compared with the CK and CG groups, the SE-CG group exhibited significantly improved a* value (4.64 ± 0.38) and hardness ((60.95 ± 1.48) N). Furthermore, the electronic nose analysis revealed that the SE-CG treatment significantly increased the contents of sulfur-containing compounds, alcohols, and aromatic compounds in the product. The developed BP-ANN model had good classification accuracy and predictive ability with a 96% accuracy. Additionally, the Shapley additive explanations (SHAP) method was employed to interpret the BP-ANN model, highlighting the significance of various quality indicators in the prediction. Notably, the signal of electronic nose sensor S12, hardness, and chewiness were identified as the most important features for the model prediction.

As the economy rapidly develops and residents’ consumption patterns change, consumers’ demand for meat and meat products is growing increasingly and consumers raise higher requirements for the quality and safety of meat and meat products. The major meat quality characteristics are color, tenderness, flavor and taste. Meat quality evaluation was initially completed by the mouth, nose, tongue and other organs of humans. With the development of food processing science and technology, meat quality evaluation techniques gradually tend to be specialized, and more sensitive and objective methods are now available to evaluate meat quality. This paper summarizes the main techniques for meat quality detection including hyperspectral imaging, computer vision, chromatography-mass spectrometry, electronic tongue and electronic nose as well as the latest progress in their research and application, so as to provide a theoretical basis for the objective evaluation of meat quality.