Prediction of Peking duck intramuscle fat content by near-infrared spectroscopy

利用近红外光谱法预测北京烤鸭肌内脂肪含量

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Abstract

Peking duck is the most representative of the meat-type duck breed, and it is also one of the most popular meats in Asia. Few studies were reported on the fast assessment of duck meat quality. This study aimed to develop a fast measuring of duck fat content by using the near-infrared spectroscopy (NIRS) method. We measured 273 duck breast muscle intramuscle fat (IMF) content and spectra. Partial least-squares regression (PLSR) was used to model the fat content prediction by using the spectra in the wavelengths between 950 and 1650 nm. The best predictive abilities were obtained after the first derivative pretreatment, with coefficient of calibration (R(2)(C)) of 0.92, with coefficient of prediction (R(2)(P)) of 0.90, ratio performance to deviation (RPD) of 2.72, and ratio of error range (RER) of 15.45, for samples of 30 g duck. Results demonstrated that the near-infrared spectroscopy is a useful tool for fat content assessment of Peking duck meat.

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