Facultad de Ciencias Agropecuarias, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n, Ciudad Universitaria, Trujillo, Peru.
Facultad de Ciencias Agropecuarias, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n, Ciudad Universitaria, Trujillo, Peru.
Meat Sci. 2017 Nov;133:43-50. doi: 10.1016/j.meatsci.2017.06.002. Epub 2017 Jun 6.
The aim of this study was to develop a system to classify the marbling of beef using the hyperspectral imaging technology. The Japanese standard classification of the degree of marbling of beef was used as reference and twelve standards were digitized to obtain the parameters of shape and spatial distribution of marbling of each class. A total of 35 samples M. longissmus dorsi muscle were scanned by the hyperspectral imaging system of 400-1000 nm in reflectance mode. The wavelength of 528nm was selected to segment the sample and the background, and 440nm was used for classified the samples. Processing algorithms on image, based on decision tree method, were used in the region of interest obtaining a classification error of 0.08% in the building stage. The results showed that the proposed technique has a great potential, as a non-destructive and fast technique, that can be used to classify beef with respect to the degree of marbling.
本研究旨在开发一种使用高光谱成像技术对牛肉大理石花纹进行分类的系统。参考日本牛肉大理石花纹分级标准，将 12 个等级进行数字化，以获得每个等级大理石花纹的形状和空间分布参数。使用反射模式的 400-1000nm 高光谱成像系统对 35 个 M. longissmus dorsi 肌肉样本进行扫描。选择 528nm 波长对样本和背景进行分割，440nm 用于对样本进行分类。在感兴趣区域的图像上使用基于决策树方法的处理算法，在构建阶段的分类错误率为 0.08%。结果表明，该技术具有很大的潜力，作为一种非破坏性和快速的技术，可以用于对牛肉大理石花纹的分级进行分类。
