title: Prediction of pork color attributes using computer vision system.
abstract: Color image processing and regression methods were utilized to evaluate color score of pork center cut loin samples. One hundred loin samples of subjective color scores 1 to 5 (NPB, 2011; n=20 for each color score) were selected to determine correlation values between Minolta colorimeter measurements and image processing features. Eighteen image color features were extracted from three different RGB (red, green, blue) model, HSI (hue, saturation, intensity) and L*a*b* color spaces. When comparing Minolta colorimeter values with those obtained from image processing, correlations were significant (P<0.0001) for L* (0.91), a* (0.80), and b* (0.66). Two comparable regression models (linear and stepwise) were used to evaluate prediction results of pork color attributes. The proposed linear regression model had a coefficient of determination (R(2)) of 0.83 compared to the stepwise regression results (R(2)=0.70). These results indicate that computer vision methods have potential to be used as a tool in predicting pork color attributes.
authors.affiliation: Department of Animal Sciences, North Dakota State University, Fargo, ND 58102, USA; Department of Engineering, Nanjing Agricultural University, Nanjing 210031, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Sun
authors.affiliation: Department of Animal Sciences, North Dakota State University, Fargo, ND 58102, USA.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Young
authors.affiliation: Department of Animal Sciences, North Dakota State University, Fargo, ND 58102, USA.
authors.forename: Jeng Hung
authors.initials: JH
authors.lastname: Liu
authors.affiliation: Department of Animal Sciences, North Dakota State University, Fargo, ND 58102, USA.
authors.forename: Laura
authors.initials: L
authors.lastname: Bachmeier
authors.affiliation: Department of Animal Sciences, North Dakota State University, Fargo, ND 58102, USA.
authors.forename: Rose Marie
authors.initials: RM
authors.lastname: Somers
authors.affiliation: Department of Engineering, Nanjing Agricultural University, Nanjing 210031, China.
authors.forename: Kun Jie
authors.initials: KJ
authors.lastname: Chen
authors.affiliation: Department of Animal Sciences, North Dakota State University, Fargo, ND 58102, USA.
authors.forename: David
authors.initials: D
authors.lastname: Newman
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D008460:Meat / Q000032:analysis*; D010860:Pigments, Biological / Q000032:analysis*; D013552:Swine
chemical_list: D010860:Pigments, Biological
keywords: Color feature; Image processing; Pork color; Regression model