Konarska Małgorzata, Kuchida Keigo, Tarr Garth, Polkinghorne Rodney J
Warsaw University of Life Sciences, Department of Technique and Food Development, Faculty of Human Nutrition and Consumer Sciences, (WULS-SGGW), 159C Nowoursynowska Str., 02-776 Warsaw, Poland.
Obihiro University of Agriculture and Veterinary Medicine, Obihiro 080-8555, Japan.
Meat Sci. 2017 Jan;123:67-78. doi: 10.1016/j.meatsci.2016.09.005. Epub 2016 Sep 10.
As marbling is a principal input into many grading systems it is important to have an accurate and reliable measurement procedure. This paper compares three approaches to measuring marbling: trained personnel, near infrared spectroscopy (NIR) and image analysis. One 25mm slice of meat was utilised from up to 12 cuts from 48 carcasses processed in Poland and France. Each slice was frozen to enable a consistent post-slaughter period then thawed for image analysis. The images were appraised by experienced beef graders and the sample used to determine fat content by NIR. We find that image analysis based marbling measures are capturing something different to trained personnel and that there is a strong relationship between near infrared spectroscopy and trained personnel. Finally, we demonstrate that marbling measures taken on one muscle can be predictive of marbling in other muscles in the same carcase. This is particularly important for cut based models such as the Meat Standards Australia system.
由于大理石花纹是许多分级系统的主要考量因素，因此拥有准确可靠的测量方法至关重要。本文比较了三种测量大理石花纹的方法：专业人员评估、近红外光谱法（NIR）和图像分析法。从在波兰和法国加工的48头牛的胴体上最多选取12个部位，各取一片25毫米厚的肉样。每片肉样均冷冻保存，以确保宰后时间一致，然后解冻用于图像分析。图像由经验丰富的牛肉分级员评估，样本用于通过近红外光谱法测定脂肪含量。我们发现，基于图像分析的大理石花纹测量结果与专业人员的评估有所不同，并且近红外光谱法与专业人员的评估之间存在密切关系。最后，我们证明，对一块肌肉的大理石花纹测量结果可以预测同一胴体其他肌肉的大理石花纹情况。这对于基于切块的模型（如澳大利亚肉类标准系统）尤为重要。
