Chen Xiumei, Yu Xiuzhu, Wang Yage, Yang Yandie, Zhang Jingya
College of Food Science and Engineering, Northwest A&F University.
J Oleo Sci. 2015;64(3):255-61. doi: 10.5650/jos.ess14227. Epub 2015 Feb 9.
A rapid and convenient method was developed to determine the polar components (PC) of frying oil by Fourier-transform near-infrared (FTNIR) spectroscopy. One hundred twenty six oil samples were used to PC determination by column chromatography and FTNIR spectroscopy combined with partial least-square (PLS) calibration. The optimal PLS calibration was obtained after the Savitzky-Golay smoothing and first derivative treatment performed in the wavelength ranges of 4963 cm(-1) to 4616 cm(-1), 5222 cm(-1) to 5037 cm(-1), and 5688 cm(-1) to 5499 cm(-1). The obtained correlation coefficient (R) was 0.998 and the root mean square error of calibration was 1.0%. The PLS calibration was validated, and the results showed that the highest correlation (R) was 0.997 between reference value and the FTNIR predicted value and the root mean square error of prediction was 1.3%. Therefore, the FTNIR technique can be effectively applied to quantify PC with the advantages of simple operation and no pollution.
开发了一种快速便捷的方法,通过傅里叶变换近红外(FTNIR)光谱法测定煎炸油的极性成分(PC)。采用柱色谱法和FTNIR光谱法结合偏最小二乘(PLS)校准,对126个油样进行PC测定。在4963 cm(-1)至4616 cm(-1)、5222 cm(-1)至5037 cm(-1)以及5688 cm(-1)至5499 cm(-1)波长范围内进行Savitzky-Golay平滑和一阶导数处理后,获得了最佳的PLS校准。得到的相关系数(R)为0.998,校准均方根误差为1.0%。对PLS校准进行了验证,结果表明参考值与FTNIR预测值之间的最高相关性(R)为0.997,预测均方根误差为1.3%。因此,FTNIR技术可有效应用于PC的定量分析,具有操作简单、无污染的优点。