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作 者:罗琼[1,2] 金岚峰[1] 薛冬[1,2] 张媛[1,2] 徐光忠[1,2] 韩丽萍[1,2]
机构地区:[1]江苏中烟淮阴卷烟厂品质管理处,江苏省淮安市223002 [2]中国科学技术大学研究生院,合肥市230052
出 处:《烟草科技》2008年第9期45-47,51,共4页Tobacco Science & Technology
摘 要:为了快速分析烟草中草酸、苹果酸、柠檬酸的含量,采用近红外(NIR)漫反射光谱仪对113个烤烟烟叶样品进行了扫描,GC法测定了其草酸、苹果酸、柠檬酸含量,再采用消除常数法、最大最小归一化法和一阶导数+多元散射校正(MSC)法分别对4246.7~7502.1cm^-1谱区范围内的光谱进行预处理和偏最小二乘法数据拟合,建立了烟草中草酸、苹果酸、柠檬酸的NIR预测模型,并对这些模型进行了外部验证。结果表明,草酸、苹果酸、柠檬酸的预测值与GC测定值的平均相对偏差均在5%以内,RSD均〈4%。这些模型可用于批量烟草样品中这3种酸的快速测定。In order to fast analyze the oxalic, malic and citric acids in tobacco, the near infrared (NIR) spectra of 113 tobacco samples were measured with near infrared diffusive spectroscopy and the contents of oxalic, malic and citric acids in the samples were determined by GC. The models for predicting the acids' contents in tobacco were established by the spectral data in the range of 4246.7 to 7502. 1 cm^-1 through preprocessing by constant offset elimination, min - max normalization and first derivative and multiplicative scattering correction (MSC), respectively and regressed by partial least square (PLS). The models went through external validation as well. The results showed that the average relative deviations between the predicted and found values of the three acids were less than 5% with the RSDs of 〈4%. It suggested that the models were applicable to rapid determination of the three acids in batches of tobacco samples.
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