摘要
应用傅里叶变换近红外(FT NIR)光谱法测定了1210个具代表性的烤烟各个生长期的根、茎、叶样品的近红外光谱数据,并采用偏最小二乘法(PLS)分别对实验数据进行处理,建立了预测根茎和烟叶氮、磷、氯和钾等主要营养元素含量的校正模型。通过对模型进行数理统计检验,在显著性水平大于5%的条件下,其预测值与测定值不存在显著性差异。
The calibration models for predicting the contents of N, Cl, P and K in tobacco root, stalk and leaves with NIR spectrography were established by processing the data collected from FT-NIR spectra of 1210 representative samples during various growing stages with PLS method. The statistical results showed that there was no significant difference between the predicted and found values when the level of significance was over 5%.
出处
《烟草科技》
EI
CAS
2004年第12期24-27,共4页
Tobacco Science & Technology