Development and validation of a near-infrared spectroscopy model for the prediction of muscle protein in Chinese native chickens

Abstract

This study investigated the ability of the near-infrared spectroscopy (NIRS) model to predict the protein of freeze-dried muscle samples in Chinese native chickens and to determine the accuracy of the models for other native chicken breeds. Spectral pretreatment, wavelength selection, and outlier sample elimination were used to optimize the calibration models. The results showed that the best model was obtained by using a combination of standard normal variable transformation and gap-segment first-derivative pretreatment spectra after removing 48 outliers in the wavelength range of 1,439 to 1,900 nm, with coefficient of determination for the calibration (R2C) of 0.95, standard error of cross-validation (SECV) of 1.18, coefficient of determination for the prediction (R2P) of 0.95, the ratio of the standard deviation of the validation to the standard deviation of the calibration (RPDP) of 4.62. The findings indicated that NIRS can be used to predict the protein of freeze-dried muscle in Chinese native chickens.