Wang B, Yang H, Lu F, Yu F, Wang X, Zou Y, Liu D, Zhang J, Xia W. Establish intelligent detection system to evaluate the sugar smoking of chicken thighs.
Poult Sci 2021;
100:101447. [PMID:
34601440 PMCID:
PMC8496180 DOI:
10.1016/j.psj.2021.101447]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 08/04/2021] [Accepted: 08/23/2021] [Indexed: 12/03/2022] Open
Abstract
The objective of this study was to establish a standardized color detection method to achieve low-cost, rapid, nonintrusive and accurate characterization of the color change of smoked chicken thighs during the smoking process. This study was based on machine vision technology using the Mean algorithm, K-means algorithm and K-means algorithm + image noise reduction algorithm to establish 3 colorimetric cards for the color of sugar-smoked chicken thighs. The accuracy of the 3 colorimetric cards was verified by the K-medoids algorithm and sensory analysis, respectively. Results showed that all 3 colorimetric cards had significant color gradient changes. From the K-medoids algorithm, the accuracy of the colorimetric card produced by the Mean algorithm, K-means algorithm and K-means algorithm + image noise reduction algorithm was 87.2, 95.1, and 96.7%, respectively. Meanwhile, the verification results of the sensory analysis showed that the accuracy of the Mean algorithm, K-means algorithm and K-means algorithm + image noise reduction algorithm colorimetric card was 69.4, 80.9, and 79.2%, respectively. A comparative analysis found that the colorimetric cards produced by the K-means algorithm and K-means algorithm + image noise reduction have excellent accuracy. These 2 colorimetric cards could become a suitable method for rapid, low-cost, and accurate online color monitoring of smoked chicken.
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