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Potential use of NIR spectroscopy for the estimation of milled rice yield.

机译:NIR光谱在估计碾米产量中的潜在用途。

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摘要

Milled rice yield is one of the important indicators used to define the quality of milled rice. Near-infrared reflectance (NIR) spectroscopy was evaluated as a tool to estimate milled rice yield. Rough rice was dehusked and then milled to various milled rice yields. A total of 198 samples with milled rice yields of 85.72% to 96.91% were scanned over the NIR spectral wavelength ranging from 833 to 2500 nm with a Fourier transform near-infrared reflectance spectroscopy (FT-NIR) system. After finding the optimal spectral region (1638.8 to 2354.9 nm) according to the coefficients of determination, eleven mathematical pretreatments were performed on the selected spectra. The optimal calibration and prediction were obtained in the selected optimal spectral region using partial least square regression (PLS) on the spectra pretreated by a combination of first-derivation and multiplicative scattering correction. The best calibration model yielded a coefficient of determination (r2) of 0.994, a root mean square error of prediction (RMSEP) of 0.174%, and a bias of -0.021%, showing good predictability. Thus, the NIR spectroscopy technology has potential for predicting milled rice yield.
机译:精米的产量是用来定义精米质量的重要指标之一。评价了近红外反射(NIR)光谱,作为估计碾米的产量的工具。将糙米去壳,然后磨成不同的碾米产量。使用傅立叶变换近红外反射光谱(FT-NIR)系统在833至2500 nm的NIR光谱波长范围内扫描了198份米粉收率为85.72%至96.91%的样品。根据确定系数找到最佳光谱区域(1638.8至2354.9 nm)后,对所选光谱进行了11次数学预处理。使用偏最小二乘回归(PLS)在通过一阶导数和乘法散射校正组合进行预处理的光谱上,在选定的最佳光谱区域中获得最佳校准和预测。最佳校准模型得出的确定系数(r 2 )为0.994,预测的均方根误差(RMSEP)为0.174%,偏差为-0.021%,显示出良好的可预测性。因此,NIR光谱技术具有预测碾米的产量的潜力。

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