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作 者:王冬[1,2] 闵顺耕[1] 曹金莉[3] 赵国民[3] 秦小男[1]
机构地区:[1]中国农业大学理学院,北京100193 [2]北京农产品质量检测与农田环境监测技术研究中心,北京100097 [3]云南省烟草公司大理州公司,云南大理671000
出 处:《中国烟草科学》2013年第4期103-106,共4页Chinese Tobacco Science
基 金:云南省烟草公司资助项目(09YN016)
摘 要:为深入研究温度对烟草总植物碱近红外模型的影响,分别在20、25、30和35℃的环境温度下采集烟草的近红外光谱,采用偏最小二乘算法建立总植物碱各温度的校正模型,并把温度作为建立校正模型的因素之一,建立了具有温度自动矫正能力的混合温度校正模型。结果发现,对于烟草中的总植物碱,采用与烟草样品温度相同或相近的模型对样品的近红外光谱进行预测,所得预测结果的准确度较高;混合温度校正模型对不同温度的样品具有较好的适应性。此结果对指导用近红外光谱法进行快速烟草分级、复烤具有较大意义。In order to further study the effect of temperature on NIR model of total plant alkaloid in tobacco, the NIR spectra of tobacco samples were collected under environmental temperatures of 20, 25, 30 and 35 ℃的 respectively. The calibration models of total plant alkaloid in tobacco under the 4 temperatures were developed by partial least square algorithm. Moreover, temperature being regarded as one of the factors during the development of the calibration models, the multi-temperature calibration model was developed which had the ability to rectify temperature automatically. The result indicated that for the ingredient of total plant alkaloid in tobacco, being predicted by calibration models developed by the same temperature or the similar temperature, an accurate prediction result could be acquired; moreover, the multi-temperature calibration model had a better feasibility to the samples under different temperatures. This finding, to some extent, is significant for the rapid tobacco grading and redrying by NIR spectroscopy.
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