Liu Ling-Ling, Zhao Bo, Zhang Yin-Qiao, Zhang Xiao-Chao
National Key Laboratory of Soil-Plant-Machine System, Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Jan;33(1):92-7.
In order to detect wheat quality rapidly and nondestructively, NIR wheat quality quick detection system was developed on the base of grating technology. To test accuracy, repeatability and stability of this self-made system, Bruker MPA spectroscopy was selected as target analyzer and 56 wheat samples were analyzed by building and validating PLS calibration models. In the 4 models of the self-made system, the coefficient of determination R2 is 92.38%, 93.48%, 93.16% and 94.44%; root mean square error of cross validation RMSECV = 0.405, 0.374, 0.383, 0.346; ratio of performance to standard deviate RPD = 3.62, 3.39, 3.82, 4.24, respectively. And evaluating indicators of validating results in the 4 models are as follows: R2 = 96.97%, 94.22%, 96.62% and 96.34%; Root mean square error of prediction RMSEP = 0.221, 0.305, 0.233 and 0.243 respectively. The model of MPA spectroscopy gave an R2 of 95.99%, a RMSECV of 0.293, RPD of 5 and validation results are R2 of 98.31%, RMSEP of 0.165, respectively. The results show that the models of self-made instrument have good prediction performance, stability and repeatability, and wavelength and absorbance of the obtained spectra have a good repeatability. The prediction effect of single spectrum is not ideal, but it can be improved by using average spectrum of repeated acquisition. NIR wheat quality quick detection system can detect wheat quality with good performance.
为了快速、无损地检测小麦品质，基于光栅技术开发了近红外小麦品质快速检测系统。为测试该自制系统的准确性、重复性和稳定性，选择布鲁克MPA光谱仪作为目标分析仪，并通过建立和验证偏最小二乘（PLS）校准模型对56个小麦样品进行分析。在自制系统的4个模型中，决定系数R2分别为92.38%、93.48%、93.16%和94.44%；交叉验证均方根误差RMSECV = 0.405、0.374、0.383、0.346；性能与标准差之比RPD分别为3.62、3.39、3.82、4.24。4个模型验证结果的评价指标如下：R2分别为96.97%、94.22%、96.62%和96.34%；预测均方根误差RMSEP分别为0.221、0.305、0.233和0.243。MPA光谱仪模型的R2为95.99%，RMSECV为0.293，RPD为5，验证结果的R2为98.31%，RMSEP为0.165。结果表明，自制仪器模型具有良好的预测性能、稳定性和重复性，所获得光谱的波长和吸光度具有良好的重复性。单光谱的预测效果不理想，但通过多次采集的平均光谱可提高预测效果。近红外小麦品质快速检测系统能够很好地检测小麦品质。
