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机构地区:[1]西南大学化学化工学院,重庆市400715 [2]长江师范学院化学化工学院,重庆市涪凌区408100
出 处:《光谱实验室》2009年第5期1310-1315,共6页Chinese Journal of Spectroscopy Laboratory
基 金:重庆市科委攻关项目资助(CSTC2008EA5008)
摘 要:用紫外-可见分光光度计的短波近红外光谱区域(800—1100nm),测量了3种二糖麦芽糖、乳糖和蔗糖混合水溶液的近红外光谱,并用偏最小二乘方法建立了同时定量分析水溶液中麦芽糖、乳糖和蔗糖的模型,并对光谱数据预处理方法进行了讨论。通过对校正集样品的建模和对预测集样品的检验,结果良好。对浓度范围分别在0—60mg·L^(-1),0—12mg·L^(-1),0—60mg·L^(-1)的麦芽糖、乳糖和蔗糖预测模型相关系数分别为0.9904、0.9971和0.9926,模型交叉检验均方差分别为0.0213、0.2525和0.1859。预测集相对标准偏差分别为3.54%、3.55%和3.32%。并将此模型应用在简单成份的实际样品中进行了初步探索。该方法对同时定量分析多组分体系,具有简便、快速价廉、易于推广应用等优点。The calibration model for simultaneous determination of maltose, lactose and sucrose in aqueous solution was built by partial least squares and short-wavelength near infrared spectroscopy (800--1100nm),and the method of spectral pretreatment was discussed. According to the models from calibration set lactose and sucrose and validation for prediction set the better results. For concentrations of maltose, in the ranges of 0--60mg·L^-1,0-12mg·L^-1, 0--60mg·L^-1,the correlation coefficients in the calibration set are 0. 9904,0. 9971 and 0. 9926 respectively,RMSECVs are 0. 0213, 0. 2525 and 0. 1859,and the relative standard deviations in the prediction set are 3.54%,3.55% and 3. 32% respectively. In application, it makes initial exploration of models in actual samples. The advantages of the method are simple and effective, with low cost for the simultaneous determination of multi-component system.
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