Application of VNIR hyperspectral imaging for nondestructive prediction of pH, color and drip loss of chickenbreast fillets

摘要

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 acquiredfor bone (dorsal) sideof 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 PCi 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 measuredpH, 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 Rp/RPD ofO. 75/1.86, 0.85/2.52 and 0.68/1.69for 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.