Effect of the dietary ingredient composition and type of muscle on the classification of intact chicken muscles evaluated by near infrared spectroscopy

Abstract

The objective of this study was to evaluate the ability of a portable NIR instrument to classify 3 samples (breast, drumstick or leg, and thigh) from chickens fed with isocaloric and isonitrogenous diets containing different feed ingredients. The NIR spectra of the muscle samples were collected using a portable NIR instrument (950 to 1600 nm). Principal component analysis (PCA), linear discriminant analysis and partial least squares (PLS) discriminant analysis (DA) regression were used to evaluate the ability of the NIR spectra to classify samples according to the type of muscle and/or dietary composition. The LDA correct classification rate of 79% was obtained when all muscle samples were used (breast, thigh and drumstick) while 95% correct classification rate was achieved using the intact breast muscle samples. However, the origin of the muscles according to diet was poorly predicted using the combination of PLS-DA and NIR spectroscopy. This study demonstrated the potential of NIR spectroscopy combined with PCA to recognise between the three intact muscles (breast, drumstick or leg, thigh). However, the PLS-DA regression models indicated that NIR was not able to classify muscles according to the different ingredients used to feed the birds.