The use of near-infrared reflectance spectroscopy in the prediction of the chemical composition of goose fatty liver

The use of near-infrared reflectance spectroscopy (NIRS) on a meat product is described in this report. The aim of the study was to develop calibration equations to predict the chemical composition of goose fatty liver (foie gras) with lipid contents greater than 40% of the fresh pate. Spectra of 52 foie gras samples were collected in the visible and NIR region (400 to 2,498 nm). Calibration equations were computed for DM, CP, lipids and fatty acids using modified partial least-squares regression. R(2) values were high for the total lipid content (0.805) and DM (0.908) but were low for ash (0.151) and relatively low for protein content (0.255). For the major fatty acids, R(2) ranged from 0.886 for palmitic acid to 0.988 for oleic acid. Oleic acid, the main fatty acid of the liver, and the stearic acid had higher R(2) values than the less represented fatty acids. This study suggests that the NIRS technique can be used to predict lipid content and the fatty acid composition of goose fatty livers, but calibration must be built on a larger number of samples to generate accurate predictions.