Meat traceability is important for linking process and quality parameters from the individual meat cuts back to the production data from the farmer that produced the animal. Current tracking systems rely on physical tagging, which is too intrusive for individual meat cuts in a slaughterhouse environment. In this article, we demonstrate a computer vision system for recognizing meat cuts at different points along a slaughterhouse production line. More specifically, we show that 211 pig loins can be identified correctly between two photo sessions. The pig loins undergo various perturbation scenarios (hanging, rough treatment and incorrect trimming) and our method is able to handle these perturbations gracefully. This study shows that the suggested vision-based approach to tracking is a promising alternative to the more intrusive methods currently available.
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http://dx.doi.org/10.1016/j.meatsci.2013.07.023 | DOI Listing |
PLoS One
January 2025
Insilicogen, Inc., Yongin, Republic of Korea.
With the development of the Korean economy, demand for high-quality beef, specifically Hanwoo beef, is escalating, with marbling traits-measured by the widely used marbling score-being a key contributor to meat palatability. The differences between the high-quality and the lower-quality meat, according to the satisfaction of the customers, are not the result from only the degree of marbling but also from the delicacy of the marbling flecks distribution. Using the computer marbling analysis technique, an index for quantifying marbling fineness of 256 sirloin cuts at 12th- 13th thoracic vertebra named F7 index was developed in this study.
View Article and Find Full Text PDFBiomater Adv
January 2025
Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo 162-8666, Japan.
Alternative meat production technologies offer the potential to alleviate many of the ethical, environmental, and public health concerns associated with conventional meat production. Cultured meat produced using cell culture technology promises to become a viable alternative to animal-raised meat for the future of the food industry. The process of cultured meat production relies on cell sources harvested from livestock such as bovine, swine, and chicken.
View Article and Find Full Text PDFVet Med Sci
January 2025
Department of Animal Breeding and Husbandry, Istanbul University-Cerrahpasa, Istanbul, Türkiye.
Background: Obtaining information about the growth rates of animals' organs and tissues can help understand their meat production potential and determine the ideal slaughter weight (SW).
Objectives: This study aimed to determine the effects of production system and SW on the allometric growth of the non-carcass components, carcass cuts, and hind limb tissues of Kivircik lambs.
Methods: A total of 54 single-born male lambs were randomly allocated into production systems (concentrate- and pasture-based) and SW groups: 25-26 kg (LOW), 30-31 kg (MEDIUM), and 35-36 kg (HIGH).
Meat Sci
December 2024
Scotland's Rural College, West Mains Road, UK.
Three-dimensional (3D) measurements extracted from beef carcass images were used to predict the weight of four saleable meat yield (SMY) traits (total SMY and the SMY of the forequarter, flank, and hindquarter) and four primal cuts (sirloin, ribeye, topside and rump). Data were collected at two UK abattoirs using time-of-flight cameras and manual bone out methods. Predictions were made for 484 carcasses, using multiple linear regression (MLR) or machine learning (ML) techniques.
View Article and Find Full Text PDFFoods
December 2024
College of Agricultural Engineering, Shanxi Agricultural University, Jinzhong 030801, China.
With the increasing importance of meat quality inspection, traditional manual evaluation methods face challenges in terms of efficiency and accuracy. To improve the precision and efficiency of pork quality assessment, an automated detection method based on computer vision technology is proposed for evaluating different parts and freshness of pork. First, high-resolution cameras were used to capture image data of Jinfen white pigs, covering three pork cuts-hind leg, loin, and belly-across three different collection times.
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