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Proceedings Paper

Machine vision application to analyze the quality of meat products by color characteristics
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Paper Abstract

To the traditional criteria that determine consumer demand, another factor is added: health and healthy lifestyle, which affects the safety and usefulness of the product consumed. There search focuses on the development of formulations and technologies for the production of cooked sausage using whole sesame seeds containing antioxidant sesamin, and the assessment of its quality. The studies were carried out on a control sample and several samples with different options for adding white and black sesame seeds; organoleptic, physico-chemical and microbiological evaluation of the samples, as well as a qualitative response to sesamin content in sausages were evaluated. The best sample of sausage containing whole white sesame seeds in the amount of 5% was determined. Studies have shown that a natural additive in the form of sesame seeds can significantly enrich the organoleptic properties of sausages. The use of vegetable raw materials is a future direction that will ensure the emergence of sausage products with improved and new unique properties on the market. Products enriched with sesamin should be present in the daily diet of man, as this antioxidant is an oncoprotector and hepatoprotector. Because of its ability to retain vitamin E in cells, it has an indirect antioxidant effect. However, precise control over the formulation and technology of cooked sausage production is not an easy task. In the case of whole sesame seeds, which can be white and black, i.e. with very different colour characteristics, the task is greatly facilitated by the use of optical inspection methods.

Paper Details

Date Published: 21 June 2019
PDF: 7 pages
Proc. SPIE 11061, Automated Visual Inspection and Machine Vision III, 110610J (21 June 2019);
Show Author Affiliations
S. V. Murashev, ITMO Univ. (Russian Federation)
E. A. Gorlach, ITMO Univ. (Russian Federation)
I. V. Baranov, ITMO Univ. (Russian Federation)
D. E. Troshkin, ITMO Univ. (Russian Federation)
A. N. Chertov, ITMO Univ. (Russian Federation)
D. Yu. Mironova, ITMO Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 11061:
Automated Visual Inspection and Machine Vision III
Jürgen Beyerer; Fernando Puente León, Editor(s)

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