4.7 Article

Use of image analysis to identify woody breast characteristics in 8-week-old broiler carcasses

期刊

POULTRY SCIENCE
卷 100, 期 4, 页码 -

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ELSEVIER
DOI: 10.1016/j.psj.2020.12.003

关键词

woody breast; image analysis; processing; carcass grading; meat quality

资金

  1. U.S. Poultry & Egg Association [F072]
  2. University of Arkansas Division of Agriculture

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This study investigated the use of image analysis to identify Woody Breast (WB) condition in broiler carcasses. The measurements of M4 and M3, as well as the ratios M9 and M11, showed high correlation with WB severity and compression force. The best model for predicting WB included M1, M2, and M3, with an 84% accuracy rate for classification of affected samples.
Woody breast (WB) condition causes significant economic losses to the global poultry industry, and the lack of an objective and fast tool to identify this myopathy is a contributing factor. The aim of this study was to determine if there are broiler carcass conformation changes that can be used to identify WB characteristics using image analysis. Images of 8-wk-old male broiler carcasses (n = 544) of high breast-yielding strains were captured before evisceration, which were processed and analyzed using ImageJ software. Measurements were as follows: M0, breast length; M1, breast width in the cranial region; M2, one-fifth of the breast length starting at the tip of keel; M3, breast width at the end of M2; M4, angle formed at the tip of keel and extending to outer points of M3; M5, area of the triangle formed by M3 and lines generated by M4; M6, area of the breast above M3; and M7, M6 minus M5. Ratios of these measurements were also considered. Whole breast fillets were scored for WB severity based on tactile assessment and compression analysis to correlate them. Spearman's correlation coefficient (r(s)) between WB scores and compression force was highly significant (r(s) = 0.83, P < 0.01). Measurements M4 and M3 as well as ratios M9 (M3/M2) and M11 (M1/M0) had the highest correlation to the WB score (r(s) >= 0.70; P < 0.01) and compression force (r(s) >= 0.64; P < 0.01). The best validated model (generalized [Gen.] R-2 = 0.60) to predict WB included M1, M2, and M3. Using this model, 84% of broiler carcasses were correctly classified as WB or normal with a sensitivity of 82% to detect affected samples. Alternatively, M4 and M6 as well as ratios M9 and M11 could be considered as predictors in different models (Gen. R-2 >= 0.56). The same predictors were significant to estimate compression force (Gen. R-2 >= 0.49). These data support the use of image analysis to predict WB condition in broiler carcasses. The potential integration of these image measurements into commercial in-line vision grading systems would allow processors to sort broiler carcasses by WB severity.

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