首页> 外文会议>International conference on simulation and modelling in the food and bio-industry >ASSESSMENT OF MUSCLE LONGISSIMUS THORACIS ET LUMBORUM INTRAMUSCULAR FAT BY ULTRASONOGRAPHY AND IMAGE ANALYSIS
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ASSESSMENT OF MUSCLE LONGISSIMUS THORACIS ET LUMBORUM INTRAMUSCULAR FAT BY ULTRASONOGRAPHY AND IMAGE ANALYSIS

机译:超声检查和图像分析评估肌肉肌肉肌肌肌肌肌肌瘤脂肪

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The intramuscular fat (IMF), recognized by the consumer as marbling, has a favorable effect on meat quality and therefore is an important trait to be assessed. The objective of this work is to predict Longissimus thoracis et lumborum muscle (LM) chemical IMF from marbling traits obtained by analysis of real time ultrasonography (RTU) images. Twenty six LM samples were collected from Charolais x Holstein heifers. The RTU images were obtained from LM samples using a RTU scanner equipped with a 7.5 MHz probe. The chemical fat of IMF was determined on LM samples. The RTU images were subjected to computer image analysis to determine the characteristics of marbling flecks. Simple and multiple regressions were established between the chemical IMF (Y) and the characteristics of marbling flecks determined by RTU (X). Stepwise procedures were used to found the best fit model to predict chemical IMF. A large variation was found for the characteristics of marbling flecks. Using regression analysis it was possible to predict chemical IMF from marbling fleck area and proportion of marbling flecks (R~2=0.66 and 0.82, respectively, P<0.0001). The best fit explains 85% of chemical IMF variation. The results observed in this work suggest that RTU associated with image analysis was a valuable tool to predict chemical IMF of LM without destroying the muscle chop.
机译:消费者作为大理石承认的肌内脂肪(IMF)对肉质有良好的影响,因此是一个重要的特征是评估。这项工作的目的是通过分析实时超声(RTU)图像来预测朗西姆斯Thoracis et Lumborum肌肉(LM)化学IMF。从Charolais X Holstein小母牛收集二十六个LM样品。使用配备有7.5MHz探针的RTU扫描仪从LM样品获得RTU图像。在LM样品上测定IMF的化学脂肪。对RTU图像进行计算机图像分析以确定大理石斑点的特征。在化学IMF(Y)之间建立简单,多元回归和RTU(X)确定的大理石斑的特性。逐步程序用于发现最佳的拟合模型以预测化学IMF。找到了大理石斑点的特征的大变异。使用回归分析可以预测从大理石斑点区域的化学IMF和大理石斑纹的比例(R〜2 = 0.66和0.82,P <0.0001)。最佳拟合解释了85%的化学IMF变化。在此工作中观察到的结果表明,与图像分析相关的RTU是一种有价值的工具,可以预测LM的化学IMF而不破坏肌肉碎片。

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