期刊
TRENDS IN FOOD SCIENCE & TECHNOLOGY
卷 111, 期 -, 页码 771-782出版社
ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tifs.2020.12.016
关键词
Grading; Classification; Meat prediction; Automation; DEXA; VIA
资金
- Meat Technology Ireland (MTI)
- industry/Enterprise Ireland Project [TC 2016 002]
Carcass evaluation is crucial for determining the value and quality of animals at slaughter, with recent advancements in non-invasive techniques showing potential to improve classification and grading systems in the meat industry. Challenges exist in implementing these technologies in meat processing plants, and further research and development are needed in certain areas.
Background: Carcass evaluation is a key process to ascertain the value and the quality characteristics of the animal at slaughter. In addition to being the base for monetary transactions between livestock producers and meat processors, in some countries, this evaluation also helps to determine the market allocation of cuts. Recent advances in non-invasive techniques are being tested for their potential to improve classification and grading systems in the meat industry. Scope and approach: In this review, global grading and classification practices for pig, sheep and beef carcasses are discussed along with the latest technological developments in objective carcass measurement. We discuss a number of studies predicting marketable attributes such as yield (lean and saleable meat yield), eating quality attributes (inter- and intra-muscular fat, meat and fat colour) and carcass dimensions (skeletal structure, ribeye area). Technologies based on x-ray, nuclear magnetic resonance, video image analysis, ultrasound, bioelectric impedance and spectroscopy are discussed, along with recent developments and their possible future adoption. Key findings and conclusions: Dual-energy x-ray absorptiometry and magnetic induction technologies have been commercialised for the sheep and pig industries, respectively. X-ray technologies and updates in video image analysis could go beyond grading to improve yield and cut dimension predictions. Some technologies could improve process efficiencies through cut sorting and enabling robotic cutting, while also enabling improved value-based payment systems. However, there are challenges associated with their implementation in meat processing plants and further research and development is required in some areas.
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