title: Rapid and non-destructive identification of water-injected beef samples using multispectral imaging analysis.
abstract: Water-injected beef has aroused public concern as a major food-safety issue in meat products. In the study, the potential of multispectral imaging analysis in the visible and near-infrared (405-970 nm) regions was evaluated for identifying water-injected beef. A multispectral vision system was used to acquire images of beef injected with up to 21% content of water, and partial least squares regression (PLSR) algorithm was employed to establish prediction model, leading to quantitative estimations of actual water increase with a correlation coefficient (r) of 0.923. Subsequently, an optimized model was achieved by integrating spectral data with feature information extracted from ordinary RGB data, yielding better predictions (r = 0.946). Moreover, the prediction equation was transferred to each pixel within the images for visualizing the distribution of actual water increase. These results demonstrate the capability of multispectral imaging technology as a rapid and non-destructive tool for the identification of water-injected beef.
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Jinxia
authors.initials: J
authors.lastname: Liu
authors.affiliation: School of Medical Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Cao
authors.affiliation: Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, China.
authors.forename: Qiu
authors.initials: Q
authors.lastname: Wang
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Wenjuan
authors.initials: W
authors.lastname: Pan
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Ma
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Changhong
authors.initials: C
authors.lastname: Liu
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
authors.affiliation: Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, China.
authors.forename: Jianbo
authors.initials: J
authors.lastname: Yang
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China; School of Medical Engineering, Hefei University of Technology, Hefei 230009, China. Electronic address: lzheng@hfut.edu.cn.
authors.forename: Lei
authors.initials: L
authors.lastname: Zheng
mesh_terms: D000818:Animals; D002417:Cattle; D064088:Hazard Analysis and Critical Control Points; D016018:Least-Squares Analysis; D000069466:Red Meat / Q000032:analysis*; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D014867:Water / Q000032:analysis*
chemical_list: D014867:Water
keywords: Feature information; Multispectral imaging; Non-destructive analysis; Partial least squares regression; Water-injected beef