供应链
高光谱成像
质量(理念)
工厂(面向对象编程)
肉类包装业
范围(计算机科学)
产品(数学)
食品安全
计算机科学
生产(经济)
比例(比率)
风险分析(工程)
生化工程
环境科学
业务
工程类
人工智能
食品科学
营销
数学
哲学
化学
物理
几何学
认识论
量子力学
经济
宏观经济学
程序设计语言
作者
Wenyang Jia,Saskia M. van Ruth,Nigel Scollan,Anastasios Koidis
标识
DOI:10.1016/j.crfs.2022.05.016
摘要
Meat products are particularly plagued by safety problems because of their complicated structure, various production processes and complex supply chains. Rapid and non-invasive analytical methods to evaluate meat quality have become a priority for the industry over the conventional chemical methods. To achieve rapid analysis of safety and quality parameters of meat products, hyperspectral imaging (HSI) is now widely applied in research studies for detecting the various components of different meat products, but its application in meat production and supply chain integrity as a quality control (QC) solution is still ambiguous. This review presents the fresh look at the current states of HSI research as both the scope and the applicability of the HSI in the meat quality evaluation expanded. The future application scenarios of HSI in the supply chain and the future development of HSI hardware and software are also discussed, by which HSI technology has the potential to enable large scale meat product testing. With a fully adapted for factory setting HSI, the inspection coverage can reliably identify the chemical properties of meat products. With the introduction of Food Industry 4.0, HSI advances can change the meat industry to become from reactive to predictive when facing meat safety issues.
科研通智能强力驱动
Strongly Powered by AbleSci AI