Detection of Needles in Meat using X-Ray Images and Convolution Neural Networks

Ahn, Jin-Ho; Jang, Won-Jae; Lee, Wonhee; Kim, Jeong-Do

doi:10.46670/jsst.2020.29.6.427

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Cited by 3 publications

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Toward Meat Industry 4.0: opportunities and challenges for digitalized red meat processing

Hamill,

Ferragina,

Mishra

et al. 2024

Food Industry 4.0

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Toward Meat Industry 4.0: opportunities and challenges for digitalized red meat processing

Hamill,

Ferragina,

Mishra

et al. 2024

Food Industry 4.0

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Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review

Liang

Wang

et al. 2022

Foods

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With the continuous development of economy and the change in consumption concept, the demand for meat, a nutritious food, has been dramatically increasing. Meat quality is tightly related to human life and health, and it is commonly measured by sensory attribute, chemical composition, physical and chemical property, nutritional value, and safety quality. This paper surveys four types of emerging non-destructive detection techniques for meat quality estimation, including spectroscopic technique, imaging technique, machine vision, and electronic nose. The theoretical basis and applications of each technique are summarized, and their characteristics and specific application scope are compared horizontally, and the possible development direction is discussed. This review clearly shows that non-destructive detection has the advantages of fast, accurate, and non-invasive, and it is the current research hotspot on meat quality evaluation. In the future, how to integrate a variety of non-destructive detection techniques to achieve comprehensive analysis and assessment of meat quality and safety will be a mainstream trend.

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