title: Classification of organic beef freshness using VNIR hyperspectral imaging.
abstract: Consumer trust in the food industry is heavily reliant upon accurate labelling of meat products. As such, methods, which can verify whether meat is correctly labelled are of great value to producers, retailers, and consumers. This paper illustrates two approaches to classify between, fresh and frozen thawed, and in a novel manner matured and matured frozen-thawed, as well as fresh and matured beef using the 500-1010nm waveband, captured using hyperspectral imaging, and CIELAB measurements. The results show successful classification based upon CIELAB between 1) fresh and frozen-thawed (CCR=0.93), and 2) fresh and matured (CCR=0.92). With successful classification between matured and matured frozen-thawed beef using the entire spectral range (CCR=1.00). The performance of reduced spectral models is also investigated. Overall it was found that CIELAB co-ordinates can be used for successful classification for all comparisons except between matured and matured frozen-thawed. Biochemical and physical changes of the meat are thoroughly discussed for each condition.
authors.affiliation: Postharvest Technologies and Processing Group, Department of Agricultural Engineering, University of Kassel, Witzenhausen, Germany.
authors.forename: Stuart O J
authors.initials: SOJ
authors.lastname: Crichton
authors.affiliation: Postharvest Technologies and Processing Group, Department of Agricultural Engineering, University of Kassel, Witzenhausen, Germany.
authors.forename: Sascha M
authors.initials: SM
authors.lastname: Kirchner
authors.affiliation: School of Chemistry, University of St Andrews, St Andrews, UK; School of Physics, University of St Andrews, St Andrews, UK.
authors.forename: Victoria
authors.initials: V
authors.lastname: Porley
authors.affiliation: Postharvest Technologies and Processing Group, Department of Agricultural Engineering, University of Kassel, Witzenhausen, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Retz
authors.affiliation: Postharvest Technologies and Processing Group, Department of Agricultural Engineering, University of Kassel, Witzenhausen, Germany.
authors.forename: Gardis
authors.initials: G
authors.lastname: von Gersdorff
authors.affiliation: Postharvest Technologies and Processing Group, Department of Agricultural Engineering, University of Kassel, Witzenhausen, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Hensel
authors.affiliation: Cluster of Excellence NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Weygandt
authors.affiliation: Postharvest Technologies and Processing Group, Department of Agricultural Engineering, University of Kassel, Witzenhausen, Germany; School of Agriculture, Food and Rural Development, Newcastle University, Newcastle upon Tyne, UK. Electronic address: barbarasturm@daad-alumni.de.
authors.forename: Barbara
authors.initials: B
authors.lastname: Sturm
mesh_terms: D000818:Animals; D002417:Cattle; D005524:Food Technology / Q000379:methods; D005615:Freezing; D000069466:Red Meat / Q000032:analysis* / Q000145:classification; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013057:Spectrum Analysis
keywords: Beef; Chromaticity; Classification; Freezing; Hyperspectral; Maturation; Quality; SVM; Storage; Support vector machines; VNIR