Vis-NIR wavelength selection for non-destructive discriminant analysis of breed screening of transgenic sugarcane

文献类型： 外文期刊

第一作者： Guo, Haosong

作者： Guo, Haosong;Chen, Jiemei;Pan, Tao;Wang, Jihua;Cao, Gan;Guo, Haosong;Chen, Jiemei;Pan, Tao;Wang, Jihua;Cao, Gan;Wang, Jihua;Cao, Gan

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期刊名称：ANALYTICAL METHODS （ 影响因子：2.896； 五年影响因子：2.716 ）

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收录情况： SCI

摘要： The Saviteky-Golay (SG) method and moving-window waveband screening are applied to a coupling model of principal component (PCA) and linear discriminant analyses (LDA). An SG-pretreatment-based method (MW-PCA-LDA) for spectral pattern recognition is proposed, which is successfully employed for the non-destructive recognition of transgenic sugarcane leaves using visible (Vis) and near-infrared (NiR) diffuse reflectance spectroscopy. A Kennard-Stone-algorithm-based process of calibration, prediction and validation in consideration of uniformity and representative was performed to produce objective models. A total of 456 samples of sugarcane leaves in the elongation stage were collected from a planted field. These samples were composed of 306 transgenic samples containing both Bacillus thuringiensis (Bt) and bialaphos resistance (Bar) genes, and 150 non-transgenic samples. According to the spectral recognition effects, two parallel optimal SG modes were selected. The one of the 1~(st) order derivative, 3~(rd) degree polynomial and 25 smoothing points was taken as an example to pretreat the diffuse reflectance spectra. Based on the MW-PCA-LDA method, the optimal waveband was 768 nm to 822 nm, the optimal PC combination was PQ.-PC3 and the corresponding validation recognition rates of transgenic and non-transgenic samples achieved 99.1% and 98.0%, respectively. The results show that Vis-NIR spectroscopy combined with SG pretreatment and the MW-PCA-LDA method can be used for accurate recognition of transgenic sugarcane leaves and provides a quick and convenient means of V screening transgenic sugarcane breeding for large-scale agricultural production.

分类号： O65

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