基于可见-近红外光谱技术预测茶鲜叶全氮含量

为快速无损监测茶树氮素营养及其生长状况，基于可见-近红外光谱技术建立了茶鲜叶全氮含量的预测模型。以茶鲜叶为对象，田间试验使用便携式光谱仪采集叶片漫反射光谱信息，通过不同预处理和统计分析，建立茶鲜叶全氮含量预测的光谱模型。试验共采集111个样品，其中86个样品作校正集，25个样品作预测集。通过一阶导数与滑动平均滤波相结合的预处理方法，用7个主成分建立的偏最小二乘模型最好，其校正集均方根误差(RMSEC)为0.097 3，预测集的相关系数为0.888 1，预测均方根误差(RMSEP)为0.130 4，预测的平均相对误差为4.339%。研究结果表明，利用可见-近红外光谱技术可以很好地预测茶鲜叶全氮含量，对于快速实时监测茶树长势和施肥管理具有重要指导意义。

Determination of Total Nitrogen Content in Fresh Tea Leaf Using Visible-Near Infrared Spectroscopy

To monitor tea tree growth and nitrogen nutrition in tea leaves,visible-near infrared spectroscopy was used to determine total nitrogen content.One hundred eleven fresh tea leaves of different nitrogen levels were sampled according to different tea type,plant age,leaf age,leaf position and soil nutrients,which covered a wide range of nitrogen content.Visiblenear infrared reflectance spectra were scanned under the sunlight with a portable spectroradiometer(ASD FieldSpec 3) in field.The software of NIRSA developed by Jiangsu University was used to establish the calibration models and prediction models,which included spectra data editing,preprocessing,sample analysis,spectrogram comparison,calibration model and prediction model,analysis reporting and system configuration.Eighty six samples were used to establish the calibration model with the preprocessing of first/second-order derivative plus moving average filter and the algorithm of PLS regression,stepwise regression,principal component regression,PLS regression plus artificial neural network and so on.The result shows that the PLS regression calibration model with 7 principal component factors after the preprocessing of first-order derivative plus moving average filter is the best and correspondingly the root mean square error of calibration is 0.973.Twenty five unknown samples were used to establish the prediction model and the correlation coefficient between predicted values and real values is 0.888 1,while the root mean square error of prediction is 0.130 4 with the mean relative error of 4.339%.Therefore,visible-near infrared spectroscopy has a huge potential for the determination of total nitrogen content in fresh tea leaves in a rapid and nondestructive way.Consequently,the technique can be significant to monitoring the tea tree growth and fertilization management.