Prediction of pork quality attributes from near infrared reflectance spectra

Near infrared spectroscopy (NIRS) is one of the most promising techniques for large-scale meat quality evaluation. We investigated the potential of NIRS-based models to predict drip loss and shear force of pork samples. Near infrared reflectance spectra (1000–2500 nm), water-holding capacity, shear force, ultimate pH, and colour (L∗, a∗, b∗-value) of 96 pork longissimus muscles were recorded at 2 days post mortem. Stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR) analyses were used to formulate models for drip loss and shear force. Prediction models for drip loss correlated moderately strong with measured drip loss (R=0.71–0.74), which is similar to the correlation obtained using a combination of ultimate pH, filter paper test, and L∗-value (R=0.74). The current results indicate that NIRS enables the classification of pork longissimus muscles with a superior or inferior water-holding capacity as having a drip loss lower than 5% or higher than 7%. No useful models could be constructed for shear force.