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机构地区:[1]云南大学化学科学与工程学院,云南省昆明650091 [2]云南省烟草科学研究院烟草化学研究室,云南省昆明650106 [3]红云烟草集团有限责任公司技术中心,云南省昆明650202
出 处:《中国烟草学报》2009年第2期15-18,共4页Acta Tabacaria Sinica
摘 要:为适应快速分析烟草中植物色素含量的需要,应用傅立叶变换近红外(FT-NIR)光谱法测定了77个具有代表性的烟草样品的光谱数据,利用偏最小二乘法,以样品的光谱数据和对应的化学测定值为基础,建立了预测烟草中叶黄素、β-胡萝卜素和其它类胡萝卜素含量的数学模型。结果表明:模型优化后,模型的相关系数(R)分别为0.9802、0.9962和0.9751,预测标准偏差(RMSEP)分别为0.00947、0.0607和0.0446。该方法简便、快速、不破坏样品,可用于大批量烟草样品中叶黄素、β-胡萝卜素和其它类胡萝卜素的快速测定。In order to meet the needs of rapid analysis of pigments in tobacco, the near infrared (NIR) spectra of 77 representative tobacco samples were measured with FT-NIR spectroscopy. Based on the spectral data and determined chemical results of tobacco samples, the predictive models of lutein, β-carotene and other carotenoids in tobacco were established by partial least square (PLS) method. The correlation coefficients(R) of the models were 0.9802, 0.9962 and 0.9751 respectively, and the root mean square errors of prediction (RMSEP) were 0.00947, 0.0607 and 0.0446 respectively. This method was simple, rapid and nondestructive to sample, so it is suitable for rapid determination of lutein, β-carotene and other carotenoids in tobacco samples.
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