Warsaw University of Life Sciences-SGGW, Faculty of Food Sciences, Department of Food Technology, Division of Meat Technology, Nowoursynowska Street 159c, 02–787 Warsaw, Poland.
Meat Sci. 2011 Jul;88(3):566-70. doi: 10.1016/j.meatsci.2011.02.014. Epub 2011 Feb 25.
The aim of this study was an attempt to use computer image analysis (CIA) to detect PSE (pale, soft, exudative) defect in pork meat. Material for the study was 50 slices obtained from pork longissimus muscles (m. longissimus) from 50 different animals. Based on measurements of pH, electrical conductivity, color lightness (L*), sixteen of the slices were classified as PSE meat. Another sixteen slices showed features of a normal meat. Photos of tested meat slices were taken and analyzed with computer image analysis. The article presents the data in three color models: RGB, HSV/HSB and HSL. Obtained results demonstrate the possibility of using V/B values (HSV/HSB model), L (HSL model) and the R, G, B values with the RGB model to detect PSE defect in pork meat.
本研究旨在尝试使用计算机图像分析(CIA)检测猪肉中的 PSE(苍白、柔软、渗出)缺陷。研究材料为来自 50 个不同动物的 50 个猪背最长肌(m. longissimus)切片。根据 pH 值、电导率、颜色亮度(L*)的测量,其中 16 个切片被归类为 PSE 肉。另外 16 个切片显示出正常肉的特征。对测试的肉切片进行拍照并使用计算机图像分析进行分析。本文以三种颜色模型(RGB、HSV/HSB 和 HSL)呈现数据。得出的结果表明,使用 V/B 值(HSV/HSB 模型)、L 值(HSL 模型)以及 R、G、B 值(RGB 模型)检测猪肉 PSE 缺陷是可行的。