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 (3501100 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. (C) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.