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Moving-window bis-correlation coefficients method for visible and near-infrared spectral discriminant analysis with applications

机译:可见和近红外光谱判别分析的动窗双相关系数法及其应用

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The moving-window bis-correlation coefficients (MW-BiCC) was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and β-thalassemia with visible and near-infrared (Vis–NIR) spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA) was also conducted for comparison. A total of 306 transgenic (positive) and 150 nontransgenic (negative) leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG) smoothing with first-order derivative (d=1), third-degree polynomial (p=3) and 25 smoothing points (m=25). The selected waveband was 736–1054nm with MW-BiCC, and the positive and negative validation recognition rates (V_REC+, V_REC?) were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 β-thalassemia (positive) and 148 nonthalassemia (negative) of human hemolytic samples were collected. ...
机译:提出了移动窗口双相关系数(MW-BiCC)并将其用于可见和近红外(Vis-NIR)光谱判别分析转基因甘蔗叶和β地中海贫血。还进行了性能良好的移动窗口主成分分析线性判别分析(MW-PCA-LDA)进行比较。总共收集了306个甘蔗转基因(阳性)和150个非转基因(阴性)叶子样品,并将其分为校正,预测和验证。使用具有一阶导数(d = 1),三次多项式(p = 3)和25个平滑点(m = 25)的Savitzky-Golay(SG)平滑校正了漫反射光谱。 MW-BiCC选择的波段为736–1054nm,阳性和阴性确认识别率(V_REC +,V_REC?)分别为100%和98.0%,与MW-PCA–LDA达到相同的效果。另一个例子是,收集了人类溶血样品的93个β地中海贫血(阳性)和148个非地中海贫血(阴性)。 ...

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