应用GA-DOSC算法消除果皮影响近红外漫反射光谱分析苹果硬度的研究

Using GA-DOSC Method to Eliminate Interference of Peel with Prediction of Apple Firmness Based on Near Infrared Diffuse Reflection Spectra

通过偏最小二乘法(PLS)分别建立去皮前后苹果硬度的近红外回归模型。采用光谱附加散射校正(MSC)、微分处理(Derivative)、直接正交信号校正(DOSC)等预处理方法和基于遗传算法(GA)的有效波段选择方法来消除果皮对模型精度的影响。结果表明,苹果果皮对近红外光谱分析模型的预测能力有很大影响,但仅通过常规的光谱预处理方法(MSC、Derivative)很难有效消除。文章提出的遗传算法结合直接正交信号校正(GA-DOSC)方法能有效消除果皮的影响,不但使所建模型的波长点和最佳主因子数分别由1 480和5降到36和1;其相关系数r由0.753提高到0.805,更重要的是模型的预测相对误差RSDp从16.71%显著下降到12.89%,并接近采用苹果果肉建模的预测性能(12.36%),达到了对苹果硬度的近红外无损检测要求。

In the present work, ＂Fuji＂ apples from Shandong Yantai were used to take the diffuse reflection spectra by FT-NIP PLS components （i. e. , factors） were computed by nonlinear iterative partial least squares （NIPALS） and the number of latent factors （LV） was optimized by a leave-one-out cross-validation procedure on the calibration set. On the basis of partial least square （PLS） regression, the models for apples＇ firmness before and after peeling were compared. In order to eliminate the effect of apple peel on prediction, spectral pretreatments such as muhiplicative scatter correction （MSC）, derivative, direct orthogonal signal correction （DOSC） and wavelengths selection based on genetic algorithms （GA） were used. Finally, the results of different spectral treatments were compared. In conclusion, the RSDp of models for apples before and after peeling was 16.71% and 12.36%, respectively, suggesting that the apple peel played a negative role in constructing good predictive models. Moreover, the traditional spectral pretreatments （such as MSC, derivative） can hardly resolve the problem. In this research, GA-DOSC played an important role in reducing the interference of apple peel. It not only reduced the wavelength variables from 1480 to 36, but also reduced the latent variables from 5 to 1. The correlation coefficient （r） was improved from 0. 753 to 0. 805, and the RMSECV and RMESP were reduced from 1. 019 kgf · cm ^-2 and 1. 197 kgf · cm^-2 to 0. 919 kgf · cm ^-2 and 0. 924 kgf· cm ^-2, respectively. Especially, the RSDp was decreased remarkably from 16.71% to 12.89%. The performance of the model after GA-BOSC treatment was similar to the model using spectra of apple flesh （12. 36%）. It was concluded that the prediction precision based on GA-DOSC satisfied the requirement of NIR non-destruction determination of apples firmness.