Application of artificial intelligence techniques in meat processing: A review

被引:6
作者
Wang, Mingyu [1 ]
Li, Xinxing [1 ,2 ,3 ]
机构
[1] China Agr Univ, Coll Informat & Elect Engn, Beijing, Peoples R China
[2] Nanchang Inst Technol, Nanchang, Peoples R China
[3] China Agr Univ, Beijing 100083, Peoples R China
关键词
artificial intelligence technology; automation; carcass classification; meat; processing; quality inspection; COMPUTER VISION; NEURAL-NETWORK; QUALITY; SYSTEM; CLASSIFICATION; IDENTIFICATION; TECHNOLOGIES; CONTAMINANTS; PREDICTION;
D O I
10.1111/jfpe.14590
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The field of meat processing plays a critical role in the food industry and has seen increasing adoption of artificial intelligence (AI) technology with rapid technological advancements. AI technology has tremendous potential for enhancing production efficiency and product quality in meat processing. However, further research and exploration are necessary to tackle the challenges posed by the use of AI technology. This article details the implementation of AI technology in meat processing, focusing on carcass classification, automation and intelligent processing, and meat-quality detection. We aim to provide inspiration to researchers and industry professionals and promote the advancement of AI technology in the meat processing sector.Practical applicationsOur review article showcases the potential industrial applications of artificial intelligence (AI) techniques in the meat processing industry. AI technology can greatly improve production efficiency and product quality in meat processing. By implementing AI algorithms, meat processors can accurately classify carcasses, automate various processing tasks, and detect meat quality with higher accuracy. These advancements can lead to increased profitability and improved food safety in the industry. We hope to provide valuable insights for researchers and industry professionals, encouraging them to further explore and adopt AI technology in the meat processing sector. Our study delves into the application of AI technology in pivotal areas, including carcass categorization, automation, intelligent processing, and the detection of meat quality. Our study is expected to inspire further research on AI technology in the meat processing industry and provide a reference for researchers. image
引用
收藏
页数:11
相关论文
共 62 条
[1]  
Adesokan H K, 2014, J Prev Med Hyg, V55, P10
[2]   A Machine Learning Approach for Lamb Meat Quality Assessment Using FTIR Spectra [J].
Alaiz-Rodriguez, Rocio ;
Parnell, Andrew C. .
IEEE ACCESS, 2020, 8 (08) :52385-52394
[3]   Lean meat yield estimation using a prototype 3D imaging approach [J].
Alempijevic, Alen ;
Vidal-Calleja, Teresa ;
Falque, Raphael ;
Quin, Phillip ;
Toohey, Edwina ;
Walmsley, Brad ;
McPhee, Malcolm .
MEAT SCIENCE, 2021, 181
[4]   An intelligent decision support system for the detection of meat spoilage using multispectral images [J].
Alshejari, Abeer ;
Kodogiannis, Vassilis S. .
NEURAL COMPUTING & APPLICATIONS, 2017, 28 (12) :3903-3920
[5]   Meat Industry 4.0: A Distant Future? [J].
Barbut, S. .
ANIMAL FRONTIERS, 2020, 10 (04) :38-47
[6]   Review: Automation and meat quality-global challenges [J].
Barbut, Shai .
MEAT SCIENCE, 2014, 96 (01) :335-345
[7]   Evaluation of an Image Analysis Approach to Predicting Primal Cuts and Lean in Light Lamb Carcasses [J].
Batista, Ana Catharina ;
Santos, Virginia ;
Afonso, Joao ;
Guedes, Cristina ;
Azevedo, Jorge ;
Teixeira, Alfredo ;
Silva, Severiano .
ANIMALS, 2021, 11 (05)
[8]  
Blagoveshchenskiy I. G., 2020, Journal of Physics: Conference Series, V1705, DOI 10.1088/1742-6596/1705/1/012019
[9]  
Casey N.H., 2003, Encyclopedia of Food Sciences and Nutrition, P2937, DOI [10.1016/B0-12-227055-X/00564-2, DOI 10.1016/B0-12-227055-X/00564-2, 10.1016/B0-12-227055-X/00564-2/]
[10]   Classification of lamb carcass using machine vision: Comparison of statistical and neural network analyses [J].
Chandraratne, M. R. ;
Kulasiri, D. ;
Samarasinghe, S. .
JOURNAL OF FOOD ENGINEERING, 2007, 82 (01) :26-34