Click on “Download PDF” for the PDF version or on the title for the HTML version.
If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.
Application of VNIR hyperspectral imaging for non-destructive prediction of pH, color and drip loss of chicken breast fillets
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: 2017 ASABE Annual International Meeting 1700733.(doi:10.13031/aim.201700733)
Authors: Beibei Jia, Seung-Chul Yoon, Hong Zhuang, Wei Wang, Yi Yang, Hongzhe Jiang, Xuan Chu, Xin Zhao, Daniel Kimuli
Keywords: Chicken breast fillet, Drip loss, Hyperspectral imaging, L*, Partial least square regression (PLSR), pH.
Abstract. Non-destructive and rapid prediction of quality attributes of chicken breast fillets using visible and near-infrared (VNIR) hyperspectral imaging (400-1000 nm) was carried out in this work. All hyperspectral images were acquired for bone (dorsal) side of chicken breast. A forward principal component analysis (PCA) and its reverse rotation was firstly conducted to reduce noises and multicollinearity. A band threshold method was adopted on PC1 score image to get the region of interest (ROI) of each sample, then the average reflective spectra of ROI of each image were acquired by reverse PCA rotation. Partial least square regression (PLSR) was utilized to correlate the spectra with measured pH, L* and drip loss values. Informative wavelengths were selected using competitive adaptive reweighed sampling (CARS) to build new PLSR models. Better results were acquired with determination coefficient of prediction R_p^2/RPD of 0.75/1.86, 0.85/2.52 and 0.68/1.69 for pH, L* and drip loss, respectively. Distribution maps of pH, L* and drip loss were generated based on the improved PLSR models. The results demonstrated that VNIR hyperspectral imaging technique can be used to predict quality attributes of chicken breast fillets.
(Download PDF) (Export to EndNotes)