Xu Wen-Li, Sun Tong, Wu Wen-Qiang, Liu Mu-Hua
Optics-Electronics Application of Biomaterials Lab, College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2012 Nov;32(11):3002-5.
The present paper studies the near-infrared spectroscopy of soluble solids content in navel orange that was influenced by different placement positions of the navel orange. According to the different angles between incident light and the straight line composed by navel orange stems and pit, the authors chose three different placement positions,vertical (90 degrees), parallel (0 degrees) and random(not including 0 degrees and 90 degrees). The authors acquired the semi-transmission spectrum of the navel orange placed in different positions in the wavelength range of 465-1 150 nm by the miniature fiber spectrometer USB4000, there were 336 navel orange samples in the experiment, 228 samples weree used as calibration set, and the rest 108 samples were used as prediction set. The authors used partial least-square regression combined with different pre-processing methods to establish the prediction model of SSC in navel orange with different placement positions. The result shows that when the angle is vertical the prediction models of SSC in navel orange are good, and the best correlation coefficient of the model is r = 0.93, RMSEC = 0.37%, r, = 0.88, and RMSEP = 0.49%.
本文研究了脐橙放置位置不同对其可溶性固形物含量近红外光谱的影响。根据入射光与脐橙果柄和果脐所构成直线之间的不同夹角，作者选择了三种不同的放置位置：垂直（90度）、平行（0度）和随机（不包括0度和90度）。作者使用微型光纤光谱仪USB4000在465 - 1150 nm波长范围内采集了放置在不同位置的脐橙的半透射光谱，实验中有336个脐橙样本，其中228个样本用作校正集，其余108个样本用作预测集。作者采用偏最小二乘回归结合不同的预处理方法，建立了不同放置位置下脐橙可溶性固形物含量的预测模型。结果表明，当角度为垂直时，脐橙可溶性固形物含量的预测模型良好，模型的最佳相关系数r = 0.93，校正均方根误差RMSEC = 0.37%，相关系数r, = 0.88，预测均方根误差RMSEP = 0.49%。
