Objective determination of pork marbling scores using the wide line detector

被引:24
作者
Liu, L. [1 ]
Ngadi, M. O. [1 ]
Prasher, S. O. [1 ]
Gariepy, C. [2 ]
机构
[1] McGill Univ, Dept Bioresource Engn, Ste Anne De Bellevue, PQ H9X 3V9, Canada
[2] Agr & Agri Food Canada, St Hyacinthe, PQ J2S 8E3, Canada
关键词
Pork; Marbling; Wide line detector; Linear regression; Stepwise procedure; MEAT QUALITY; SYSTEM;
D O I
10.1016/j.jfoodeng.2011.11.008
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Marbling is an important factor in evaluating pork quality and can be estimated by marbling scores based on the official marbling standards. The marbling score is normally assessed by experienced graders by comparing pork chops with the standardized chart system. In this paper, the potentials of automatic objective prediction of marbling scores were studied. The region of interest (ROI) of the marbling standards and the pork samples was automatically determined for marbling extraction. Marblings were regarded as kind of line patterns and thereby extracted by the wide line detector. Proportion of marblings (PM) was used for determinating the marbling score. The stepwise procedure was employed to select prediction models. A multiple linear regression equation was used as the initial model of the procedure and the PM of marbling standards at all three channels as potential variables. Three models were developed by the stepwise procedure with different first entry variable of the initial model. The multiple linear model obtained by the PM of marbling standards at all three RGB channels outperformed the two simple linear models respectively developed at the green and blue channels. The adjusted coefficient of determination (R-2) of the multiple linear model was 0.9992 and the root mean square error of leave-one-out cross-validation (RMSECV) was 0.0938. Forty pork loin samples were used to predict marbling scores. The prediction results of the three models showed that the prediction ability of the simple linear model developed at the blue channel was comparable with the multiple linear model. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:497 / 504
页数:8
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