Determination of Maximum Viscosity of Milled Rice Flours Using Near-Infrared Transmittance Spectroscopy
Determination of Maximum Viscosity of Milled Rice Flours Using Near-Infrared Transmittance Spectroscopy
复制标题
近红外透射光谱法测定碾米粉的最大粘度
DOI：
10.3136/fstr.7.104
复制
发表时间：
2001
影响因子：
0.6
通讯作者：
K. Ohtsubo
中科院分区：
文献类型：
--
作者：
N. Shimizu;T. Yanagisawa;H. Okadome;H. Toyoshima;H. Andrén;Toshinori Kimura;K. Ohtsubo
本研究的目的是开发一种偏最小二乘回归（PLS）校准方法的最大粘度测定日本精米粉使用近红外透射（NIT）光谱。水稻各亚科的光谱和最大粘度的多样性远大于粳稻。光谱和最大粘度的变化被发现影响PLS加载重量。在粳稻PLS模型的第8次加载中，ROH和H_2O的C-H和O-H值均达到显著水平。该PLS校正模型（11个组分）用于快速粘度分析仪（RVA）的最大粘度的性能为预测标准误差（SEP）为17.7，回归系数平方（R2）为0.75，SEP与原始数据标准偏差（RPD）的比值为1.9。该方法可用于粳稻最大粘度的测定。
The objective of this study was to develop a partial least squares regression (PLS) calibration method of maximum viscosity determination of Japanese milled rice flours using near-infrared transmittance (NIT) spectroscopy. The diversity of spectra and maximum viscosity of wide ranging of rice subfamilies were much more than those of japonica type rices. The variations of spectra and maximum viscosity were found to influence PLS loading weights. C-H and O-H in ROH and H2O absorbances presented by the loading weights were significant in the 8th loading of the PLS model for japonica type rices. The performance of this PLS calibration model (11 components) for maximum viscosity of a rapid visco analyser (RVA) was the standard error of prediction (SEP) of 17.7, square of regression coefficient (R2) of 0.75 and the ratio of the SEP to the standard deviation of the original data (RPD) of 1.9. This method can be applied to the determination of maximum viscosity of japonica type rices.