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

机译:近红外光谱法预测近红外光谱法

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摘要

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 (R2C) of 0.92, with coefficient of prediction (R2P) 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.
机译:北京鸭是肉类型鸭品种的最具代表性,而且它也是亚洲最受欢迎的肉类之一。报告了鸭肉质量快速评估的研究。本研究旨在通过使用近红外光谱(NIRS)方法产生快速测量鸭脂肪含量。我们测量了273只鸭胸肌肌肉脂肪(IMF)含量和光谱。部分最小二乘回归(PLSR)通过使用950和1650nm之间的波长的光谱来模拟脂肪含量预测。在第一次衍生预处理之后获得最佳预测能力,其中校准系数(R2C)为0.92,具有0.90的预测系数(R2P),比率性能与2.72的偏差(RPD)和误差范围(RER)的比率(RER) 15.45,用于30g鸭的样品。结果表明,近红外光谱是北京鸭肉脂肪含量评估的有用工具。

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