Near-infrared reflectance spectroscopy as a method to predict chemical composition of breast meat and discriminate between different n-3 feeding sources

Abstract

The objective of this study was to evaluate near-infrared reflectance spectroscopy (NIRS) as a tool to predict the physicochemical composition of breast meat samples of laying hens fed 4 different diets, a control and 3 diets enriched with different sources of n-3 polyunsaturated fatty acids: marine origin, extruded linseed, and ground linseed. Furthermore, NIRS was used as a tool to classify meat samples according to feeding regimen. Samples were analyzed chemically for DM, ash, protein, lipids, and fatty acid profile. Absorption spectra were collected in diffuse reflectance mode between 1,100 and 2,498 nm every 2 nm. The calibration results for the 72 meat samples were accurate in predicting DM, protein, lipids, and major fatty acids. Poor results were obtained for the calibration equations for ash, pH, color, and lipid oxidation parameters. Partial least squares discriminant analysis was developed to differentiate the breast meat samples that originated from hens fed the different diets. The performance of the discriminant models showed 100% correct classification between the control and the enriched diets. It was concluded that NIRS could be used for quality control predicting chemical composition of poultry meat and possibly some dietary treatments applied to the chickens.