首页> 外文会议>2011 IEEE/SICE International Symposium on System Integration >Prediction of vitamin C using FTIR-ATR terahertz spectroscopy combined with interval partial least squares (iPLS) regression
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Prediction of vitamin C using FTIR-ATR terahertz spectroscopy combined with interval partial least squares (iPLS) regression

机译:FTIR-ATR太赫兹光谱结合区间偏最小二乘(iPLS)回归预测维生素C

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In this study FTIR-ATR terahertz (THz) spectroscopy combined with interval PLS (iPLS) regression was used to measure concentration of vitamin C in aqueous solution. iPLS regression was used to select the efficient spectral regions and variables to develop calibration model. The performance of the iPLS model was then compared to that of full-spectrum PLS model. The result obtained by iPLS model with 5 PLS factors was superior than that of full-spectrum PLS model with 11 PLS factors when 7 spectral regions and 70 variables were selected. Prediction performance of vitamin C can be improved by using iPLS model with ratio prediction to deviation (RPD) value of 4.570. This work demonstrated that concentration of vitamin C in aqueous solution can be predicted by FTIR-ATR THz spectroscopy method, and iPLS regression method revealed its superiority in model calibration.
机译:在这项研究中,FTIR-ATR太赫兹(THz)光谱结合间隔PLS(iPLS)回归用于测量水溶液中维生素C的浓度。 iPLS回归用于选择有效的光谱区域和变量以建立校正模型。然后将iPLS模型的性能与全光谱PLS模型的性能进行了比较。当选择7个光谱区域和70个变量时,通过iPLS模型使用5个PLS因子获得的结果要优于使用11个PLS因子的全光谱PLS模型。使用iPLS模型可以提高维生素C的预测性能,iPLS模型的预测偏差比(RPD)值为4.570。这项工作表明,可以通过FTIR-ATR THz光谱法预测水溶液中维生素C的浓度,而iPLS回归方法显示了其在模型校准中的优越性。

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