Perspective of NIRS measurements early post mortem for prediction of pork quality.

The potential of near-infrared spectroscopy (NIRS) measurements early post mortem was investigated to predict ultimate drip loss, colour, tenderness and intra-muscular fat of pork. Three locations (M. longissimus thoracis, M. longissimus lumborum and M. semimembranosus) in 102 pig carcasses were tested at the end of the slaughter line. A priori variation in pork quality was introduced using an experimental design covering: genotype, lairage time, pre-slaughter handling and day of slaughter. At 1 h post mortem a diode array VIS/NIR instrument (Zeiss MCS 511/522, 380-1700 nm) equipped with a surface fibre optic probe was used and at 1 day post mortem ultimate pH, drip loss, colour and shear force was measured on similar locations. Results indicated that it was possible to predict intra-muscular fat content (correlation (R(2) of 0.35 with multiple linear regression), standard error of prediction (SEP)=3.6 g/kg), but the configuration has to be refined for on-line application (bigger aperture). For drip loss no correlation was achieved with the PLS method. Even extremes (low drip loss (<2.5%) or high drip loss (>4.5%)) in drip loss were not discriminated. Predicting drip loss with NIRS early post mortem is not successful, although NIRS in the slaughter line has potential as a fast predictor of intra-muscular fat. Possibilities for using the NIRS technique to get to know more about muscle metabolism and post mortem changes are promising.

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.