Determination of Calcium Content in Powdered Milk Using Near and Mid-Infrared Spectroscopy with Variable Selection and Chemometrics

Determination of Calcium Content in Powdered Milk Using Near and Mid-Infrared Spectroscopy with Variable Selection and Chemometrics
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使用近红外光谱和中红外光谱、变量选择和化学计量学测定奶粉中的钙含量

DOI:
10.1007/s11947-010-0492-4
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发表时间:
2012-05
影响因子:
5.6
通讯作者:
Bao, Yidan
Bao, Yidan
中科院分区:
农林科学2区
文献类型:
--
作者:
Wu, Di;Nie, Pengcheng;He, Yong;Bao, Yidan

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研究了近红外和中红外光谱法测定奶粉中钙含量的方法。采用一种结合无信息变量剔除(UVE)和连续投影算法(SPA)的混合光谱变量选择算法,分别从2,756个近红外和3,727个中红外光谱变量中选择出11个和15个。最小二乘支持向量机模型对预测集样本的预测结果表明,15个MIR变量取得了较好的效果(决定系数(r2)为0.930,残差预测偏差(RPD)为3.703,预测集均方根误差(RMSEP)为30.162,预测相对误差(RSEP)为5.22(r2为0.636,RPD为1.587,RMSEP为78.815,RSEP为13.40%)。总体结果表明,中红外光谱法可以作为一种精密和快速的方法来测定奶粉中的钙含量。结果表明,UVE-SPA在近红外和中红外有效变量筛选中具有潜在的应用价值。
Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine calcium content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0.930 for coefficient of determination (r2), 3.703 for residual predictive deviation (RPD), 30.162 for root mean square error of prediction set (RMSEP) and 5.22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0.636 forr2, 1.587 for RPD, 78.815 for RMSEP, and 13.40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine calcium content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables.
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