title: Potential of hyperspectral imaging for rapid prediction of hydroxyproline content in chicken meat.
abstract: In this study, the potential of hyperspectral imaging (HSI) for predicting hydroxyproline content in chicken meat was investigated. Spectral data contained in the hyperspectral images (400-1000 nm) of chicken meat was extracted, and a partial least square regression (PLSR) model was then developed for predicting hydroxyproline content. The model yielded acceptable results with regression coefficient in prediction (Rp) of 0.874 and root mean error squares in prediction (RMESP) of 0.046. Based on the eight optimal wavelengths selected by regression coefficients (RC) from the PLSR model, a new RC-PLSR model was built and good results were shown with high Rp of 0.854 and low RMSEP of 0.049. Finally, distribution maps of hydroxyproline were created by transferring the RC-PLSR model to each pixel in the hyperspectral images. The results demonstrated that HSI has the capability for rapid and non-destructive determination of hydroxyproline content in chicken meat.
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, PR China.
authors.forename: Zhenjie
authors.initials: Z
authors.lastname: Xiong
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, PR China; Food Refrigeration and Computerised Food Technology, Agriculture and Food Science Centre, University College Dublin, National University of Ireland, Belfield, Dublin 4, Ireland. Electronic address: dawen.sun@ucd.ie.
authors.forename: Da-Wen
authors.initials: DW
authors.lastname: Sun
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, PR China.
authors.forename: Anguo
authors.initials: A
authors.lastname: Xie
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, PR China.
authors.forename: Zhong
authors.initials: Z
authors.lastname: Han
authors.affiliation: College of Light Industry and Food Sciences, South China University of Technology, Guangzhou 510641, PR China.
authors.forename: Lu
authors.initials: L
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D002645:Chickens; D006909:Hydroxyproline / Q000032:analysis*; D008460:Meat / Q000032:analysis*; D008956:Models, Chemical; D064847:Multimodal Imaging; D019265:Spectroscopy, Near-Infrared / Q000379:methods*
chemical_list: D006909:Hydroxyproline
keywords: Chicken meat; Hydroxyproline; Hyperspectral imaging; Multivariate analysis; Non-destructive