On-line prediction of fresh pork quality using visible/near-infrared reflectance spectroscopy.
Visible/near-infrared (Vis/NIR) spectroscopy was tested to predict the quality attributes of fresh pork (content of intramuscular fat, protein and water, pH and shear force value) on-line. Vis/NIR spectra (350-1100 nm) were obtained from 211 samples using a prototype. Partial least-squares regression (PLSR) models were developed by external validation with wavelet de-noising and several pre-processing methods. The 6th order Daubechies wavelet with 6 decomposition levels (db6-6) showed high de-noising ability with good information preservation. The first derivative of db6-6 de-noised spectra combined with multiplicative scatter correction yielded the prediction models with the highest coefficient of determination (R(2)) for all traits in both calibration and validation periods, which were all above 0.757 except for the prediction of shear force value. The results indicate that Vis/NIR spectroscopy is a promising technique to roughly predict the quality attributes of intact fresh pork on-line.
Liao
Yi-Tao
YT
College of Biosystems Engineering and Food Science, Zhejiang University, 268 Kaixuan Road, Hangzhou, Zhejiang 310029, PR China.
Fan
Yu-Xia
YX
Cheng
Fang
F
D000818:Animals; D005504:Food Analysis / Q000379:methods*; D005524:Food Technology; D016018:Least-Squares Analysis; D008460:Meat / Q000032:analysis* / Q000592:standards; D008954:Models, Biological; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013057:Spectrum Analysis / Q000379:methods; D013552:Swine