Title
An application based on the decision tree to classify the marbling of beef by hyperspectral imaging
Date Issued
01 November 2017
Access level
metadata only access
Resource Type
journal article
Publisher(s)
Elsevier Ltd
Abstract
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 528 nm was selected to segment the sample and the background, and 440 nm 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.
Start page
43
End page
50
Volume
133
Language
English
OCDE Knowledge area
Agricultura, Silvicultura, Pesquería
Alimentos y bebidas
Subjects
Scopus EID
2-s2.0-85020243772
PubMed ID
Source
Meat Science
ISSN of the container
03091740
Sponsor(s)
Raúl Siche thanks the Universidad Nacional de Trujillo for the funding received through “Canon Minero” funds (PIC2-2013/UNT). The authors thank Prof. Wilson Castro Silupú of the Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas for their support in the digitization of BMS Japanese standard and programming of analysis of marbling in Matlab.
Sources of information:
Directorio de Producción Científica
Scopus