Food Science of Animal Resources (Food Sci. Anim. Resour.) is an international, peer-reviewed bimonthly journal publishing original research and reviews on basic and applied aspects of the use of animal resources including the meat, egg, dairy, and edible insect/worm products. Food Sci. Anim. Resour. is published and distributed by the Korean Society for Food Science of Animal Resources.

Active packaging (AP) has been developed to improve the safety, quality and integrity of food, and minimise food waste, while its application in meat is scarce. This review aims to describe meat production and consumption culture in China and New Zealand to provide the context for packaging innovation requirements, focusing on the emerging opportunities for AP to be used for the improvement of the shelf-life of pre-rigor, aged, and frozen-thawed meat products. Sustainable polymers utilised in the manufacturing of AP, manufacturing techniques, the release mechanisms of actives, and legal and regulatory constraints are also discussed. Diverse market compositions and consumption cultures in China and New Zealand require different packaging solutions to extend the shelf-life of meat. AP containing antimicrobials, moisture regulating agents, and antioxidants may be used for pre-rigor, dry- and wet-aged products and in improving the quality and shelf-life of frozen-thawed meat. Further innovations using sustainably produced polymers for AP, along with incorporating active compounds of multiple functions for effectively improving meat quality and shelf-life are necessary. Challenges remain to resolve issues with scaling the technology to commercially relevant volumes as well as complying with the rigorous legal and regulatory constraints in various countries.

The potential of four dimension reduction methods for near-infrared spectroscopy was investigated, in terms of predicting the protein, fat, and moisture contents in lamb meat. With visible/near-infrared spectroscopy at 400–1050 nm and 900–1700 nm, respectively, calibration models using partial least squares regression (PLSR) or multiple linear regression (MLR) between spectra and quality parameters were established and compared. The MLR prediction models for all three quality parameters based on the wavelengths selected by stepwise regression achieved the best results in the spectral region of 400–1050 nm. As for the spectral region of 900–1700 nm, the PLSR prediction model based on the raw spectra or high-correlation spectra achieved better results. The results of this study indicate that sampling interval shortening and of peak-to-trough jump features are worthy of further study, due to their great potential in explaining the quality parameters.

A nondestructive method was developed for assessing total viable count (TVC) in pork during refrigerated storage by using hyperspectral imaging technique in this study. The hyperspectral images in the visible/near-infrared (VIS/NIR) region of 400–1100 nm were acquired for fifty pork samples, and their VIS/NIR diffuse reflectance spectra were extracted from the images. The reference values of TVC in pork samples were determined by classical microbiological plating method. Both partial least square regression (PLSR) model and support vector machine regression model (SVR) of TVC were built for comparative analysis to achieve better results. Different transformation methods and filtering methods were applied to improve the models. The results show that both the optimized PLSR model and SVR model can predict the TVC very well, while the SVR model based on second derivation was better, which achieved with R_P (correlation coefficient of prediction set) = 0.94 and SEP (standard error of prediction set) = 0.4570 log CFU/g in the prediction set. An image processing algorithm was then developed to transfer the prediction model to every pixel of the image of the entire sample; the visualizing map of TVC would be displayed in real-time during the detection process due to the simplicity of the model. The results demonstrated that hyperspectral imaging is a potential reliable approach for non-destructive and real-time prediction of TVC in pork.

Food Science of Animal Resources (Food Sci. Anim. Resour.) is an international, peer-reviewed bimonthly journal publishing original research and reviews on basic and applied aspects of the use of animal resources including the meat, egg, and dairy product. Food Sci. Anim. Resour. is published and distributed by the Korean Society for Food Science of Animal Resources.