Objective carcass measurement technologies: Latest developments and future trends
| Autor: | Paul Allen, Gonzalo Delgado-Pando, Declan J. Troy, Ciara K. McDonnell |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0303 health sciences
Meat packing industry 030309 nutrition & dietetics business.industry Computer science media_common.quotation_subject 0402 animal and dairy science food and beverages 04 agricultural and veterinary sciences Agricultural engineering Payment 040201 dairy & animal science Video image 03 medical and health sciences business Bioelectric Impedance Grading (education) Quality characteristics Food Science Biotechnology media_common |
| Zdroj: | Trends in Food Science & Technology. 111:771-782 |
| ISSN: | 0924-2244 |
| DOI: | 10.1016/j.tifs.2020.12.016 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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