A simple but quantitative method for non-destructive monitoring of myoglobin redox forms inside the meat

Rapid identification of counterfeited beef using deep learning-aided spectroscopy: Detecting colourant and curing agent adulteration

The adulteration of meat products using colourants and curing agents has heightened concerns over food safety, thereby necessitating the development of advanced detection methods. This study introduces a deep-learning-based spectroscopic method for swiftly identifying counterfeit beef altered to appear fresh. The experiment involved 60 beef samples, half of which were artificially adulterated using a colouring solution. Despite meticulous analysis of the beef's colour attributes, no significant differences were observed between the fresh and adulterated samples. However, our method, utilising a 344-1040 nm spectral range, achieved a classification accuracy of 98.84%. To enhance practicality, we employed gradient-weighted class activation mapping and identified the 580-600 nm range as particularly influential for classification. Remarkably, even when we narrowed the input to the model to this spectral range, a high level of classification accuracy was maintained. To further validate the model's robustness and generalisability, we allocated 70 beef samples to an external validation set. Comparative performance analysis revealed that our model outperformed traditional machine learning algorithms, such as SVM and logistic regression, by 9.3% and 28.4%, respectively. Overall, this study offers invaluable insights for detecting counterfeited beef, thereby contributing to the preservation of meat product quality and integrity within the food industry.

Dietary α-lipoic acid supplementation improves postmortem color stability of the lamb muscles through changing muscle fiber types and antioxidative status

This study investigated the effect of dietary α-lipoic acid (600 mg/kg) supplementation on the postmortem color stability of the biceps femoris from lambs. The results showed that dietary α-lipoic acid supplementation increased a* and decreased b* and metmyoglobin (MMb) percentage of the biceps femoris with the time of storage (P < 0.05). The content of malondialdehyde (MDA) reduced with the time of storage after treatment with α-lipoic acid (P < 0.05). α-lipoic acid increased the myoglobin (Mb) content, and myosin heavy chain I (MyHC I) gene expression but decreased glycogen content, lactate dehydrogenase (LDH) activity, and MyHC IIb gene expression (P < 0.05). The T-AOC value, catalase (CAT) activity, and expression of SOD and CAT gene expression increased after α-lipoic acid treatment (P < 0.05). Therefore, dietary α-lipoic acid supplementation improved the meat color by regulating muscle fiber types and inhibited glycolysis. Moreover, α-lipoic acid maintained meat color stability by effectively inhibiting muscle oxidation via enhancing the antioxidant capacity.

Rapid and non-destructive spectroscopic method for classifying beef freshness using a deep spectral network fused with myoglobin information

A simple, novel, rapid, and non-destructive spectroscopic method that employs the deep spectral network for beef-freshness classification was developed. The deep-learning-based model classified beef freshness by learning myoglobin information and reflectance spectra over different freshness states. The reflectance spectra (480-920 nm) were measured from 78 beef samples for 17 days, and the datasets were sorted into three freshness classes based on their pH values. Myoglobin information showed statistically significant differences depending on the freshness; consequently, it was utilized as a crucial parameter for classification. The model exhibited improved performance when the reflectance spectra were combined with the myoglobin information. The accuracy of the proposed model improved to 91.9%, whereas that of the single-spectra model was 83.6%. Further, a high value for the area under the receiver operating characteristic curve (0.958) was recorded. This study provides a basis for future studies on the investigation of myoglobin information associated with meat freshness.