应用AOTF-NIR(AOTF-近红外光谱分析技术)建立田间生长烟叶中5种化学成分的快速无损检测方法.以182个样品组成校正集标准样品,采用偏最小二乘回归法建立了近红外光谱信息与各成分含量之间的关联定量校正数学模型,并对30个验证集样品进行预测.预测结果表明:烟碱、总氮、总糖、还原糖、钾的平均预测相对误差分别为3.73％、3.89％、3.78％、2.88％ 、4.37％.对验证集样品的原始化学值和预测值进行成对数据t测验,检测结果显示,差异不显著,说明建立的数学模型是可用的,该方法分析结果准确可靠,重现性好,方便无损.可用于快速定量检测田间生长烟叶中的烟碱、还原糖、总糖、总氮、钾.%In this paper, AOTF - NIR (AOTF - Near Infrared Reflectance Spectroscopy) technique was used to establish a rapid and nondestructive detection method for the determination of 5 chemical components of growing tobacco leaf in the field. Partial least square regressive method was used to build the calibration mathematical models between the NIR spectra information and the content of each chemical component based on the calibration set which consisted of 182 samples, and 30 samples in the validation set were predicted. The predictive results showed that the average relative errors of the prediction for nicotine, total nitrogen, total sugar, reducing sugar and potassium were 3.73% , 3. 89% , 3. 78% , 2. 88% and 4. 37% respectively. The original chemical values and predictive values of validation set samples were tested by the twin t -test, and no significant difference was found between them, indicating that the established mathematical models were available. The presented method was accurate, reliable, convenient and nondestructive, and it could be used for the rapid and quantitative detection of nicotine, reducing sugar, total sugar, total nitrogen and potassium of growing tobacco leaf in the field.
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