Food Science and Technology Research
Online ISSN : 1881-3984
Print ISSN : 1344-6606
ISSN-L : 1344-6606
Original papers
Correlation of the Attributes Measured by Computer Vision with Moisture and Fat Content of Meat Batters
Monika MODZELEWSKA-KAPITUŁAMarek CIERACH
著者情報
ジャーナル オープンアクセス

2012 年 18 巻 6 号 p. 769-779

詳細
抄録
The aim of this study was to determine if there is any correlation between moisture and fat content and such attributes estimated by the computer vision system (CVS) as white and red areas (%), values of colour coordinates in RGB and CIELAB colour systems, in the batters composed of porcine meat and fat (Experiment 1) or meat, fat and water (Experiment 2). The fat content (the Soxhlet method) was most highly correlated with the white fields’ area (r = 0.98, 0.85 and 0.85 for data obtained from Exp. 1, Exp. 2, and both, respectively). Also, the moisture content (the oven drying method) showed the strongest correlation with the area of white fields (r = −0.97, −0.85, −0.83, for Exp. 1, Exp. 2, and both, respectively). Thus, for estimation of fat and moisture content in meat batters the most useful CVS attribute is area of white fields.
著者関連情報
© 2012 by Japanese Society for Food Science and Technology

This article is licensed under a Creative Commons [Attribution-NonCommercial-ShareAlike 4.0 International] license.
https://creativecommons.org/licenses/by-nc-sa/4.0/
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