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

机译:使用图像分析来识别8周老肉鸡胴体的木质乳腺特征

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摘要

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 (rs) between WB scores and compression force was highly significant (rs = 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 (rs ≥ 0.70; P < 0.01) and compression force (rs ≥ 0.64; P < 0.01). The best validated model (generalized [Gen.] R2 = 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. R2 ≥ 0.56). The same predictors were significant to estimate compression force (Gen. R2 ≥ 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.
机译:木质乳房(WB)条件导致全球家禽业的重大经济损失,缺乏目标和快速的工具来识别这种肌病是一个贡献因素。本研究的目的是确定是否存在使用图像分析来识别WB特性的肉鸡胴体构象变化。在剥离之前捕获了高乳房收油株的8-WK旧雄性肉鸡(n = 544)的图像,使用imagej软件处理和分析。测量如下:M0,乳房长度; M1,颅骨区域的乳房宽度; M2,乳房尖端的乳房长度的五分之一; M3,乳房宽度在M2的末端; M4,角度形成在龙骨尖端并延伸到M3的外部点; M5,三角形的面积由M3形成和由M4产生的线; M6,乳房面积高于m3;和m7,m6减去m5。还考虑了这些测量的比率。根据触觉评估和压缩分析,对全乳腺裂片进行均得到WB严重程度,以与它们相关联。 Spearman的相关系数(RS)在Wb分数和压缩力之间非常显着(Rs = 0.83,P <0.01)。测量M4和M3以及比率M9(M3 / M2)和M11(M1 / M0)的相关性与WB得分(Rs≥0.70; P <0.01)和压缩力(Rs≥0.64; P <0.01) 。最佳验证的模型(广义[Gen.R2 = 0.60),以预测WB包括M1,M2和M3。使用该模型,84%的肉鸡屠体被正确归类为WB或正常,灵敏度为82%以检测受影响的样品。或者,M4和M6以及比率M9和M11可以被认为是不同模型(R2≥0.56)中的预测因子。相同的预测因子对于估计压缩力(R 2≥0.49)表示重要意义。这些数据支持使用图像分析来预测肉鸡屠体的WB条件。这些图像测量到商业在线视觉分级系统的潜在集成将允许处理器通过WB严重程度对肉鸡屠体进行分类。

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