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The deterioration of wooden breast myofibrillar protein (WBMP) increases with the increase in wooden breast grades. In order to quickly and conveniently classify wooden breast to prevent waste of raw materials and unsuitable processing. Different grades of wooden breasts that exhibited mild, moderate, and severe degrees were collected, and correlation analysis was employed for the quality and WBMP functional characteristic indicators. The indicators were further classified into two components according to the principal component analysis method. Based on the correlation and variation coefficients, two main indicators were selected to represent the quality level of wooden breasts (redness (a*) and pH value (P)). The weights of the two indicators were 0.353 and 0.219 for a* and P, respectively, using the weighted coefficient method. Therefore, a formula for calculating the comprehensive evaluation score (y) of different grades of wooden breast meat was obtained: y = 0.353a* + 0.219P. Based on regression analysis, the fitting equation y = 2.407 1x + 0.0343 (R2 = 0.9883) was obtained, for the comprehensive quality score (y) and sensory evaluation score (x) through regression analysis, with a fitting coefficient ˃ 0.8. This equation can accurately predict sensory evaluation scores, effectively reflect the quality differences of different grades of wooden breasts, and accurately and rapidly grade wooden breasts.


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Construction of a grading model based on the quality characteristics of different grades of chicken wooden breast

Show Author's information Ke Wang1Huan Liu1Jingxin Sun1,2( )
College of Food Science and Engineering, Qingdao Agricultural University, Qingdao 266109, China
Shandong Research Center for Meat Food Quality Control, Qingdao Agricultural University, Qingdao 266109, China

Abstract

The deterioration of wooden breast myofibrillar protein (WBMP) increases with the increase in wooden breast grades. In order to quickly and conveniently classify wooden breast to prevent waste of raw materials and unsuitable processing. Different grades of wooden breasts that exhibited mild, moderate, and severe degrees were collected, and correlation analysis was employed for the quality and WBMP functional characteristic indicators. The indicators were further classified into two components according to the principal component analysis method. Based on the correlation and variation coefficients, two main indicators were selected to represent the quality level of wooden breasts (redness (a*) and pH value (P)). The weights of the two indicators were 0.353 and 0.219 for a* and P, respectively, using the weighted coefficient method. Therefore, a formula for calculating the comprehensive evaluation score (y) of different grades of wooden breast meat was obtained: y = 0.353a* + 0.219P. Based on regression analysis, the fitting equation y = 2.407 1x + 0.0343 (R2 = 0.9883) was obtained, for the comprehensive quality score (y) and sensory evaluation score (x) through regression analysis, with a fitting coefficient ˃ 0.8. This equation can accurately predict sensory evaluation scores, effectively reflect the quality differences of different grades of wooden breasts, and accurately and rapidly grade wooden breasts.

Keywords: principal component analysis, sensory evaluation, myofibrillar protein, wooden breast, grading model

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Publication history

Received: 29 August 2023
Revised: 14 September 2023
Accepted: 18 September 2023
Published: 20 November 2023
Issue date: October 2023

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© Beijing Academy of Food Sciences 2023.

Acknowledgements

This work was financially supported by the Natural Science Foundation of Shandong Province (ZR2022MC087), Shandong Modern Agricultural Technology and Industry System (SDAIT-11-11).

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Food Science of Animal Products published by Tsinghua University Press. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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