基于近红外光谱的紫丁香叶片叶绿素含量的估测研究

近红外具有快速无损检测特点,利用该特点能够对紫丁香叶片叶绿素的含量进行估测。采用的试验方法是采取东北林业大学城市示范实验林场中的紫丁香叶片60片,从中随机抽取40片作为建模集,其余20片为验证集,并用偏最小二乘法建立建模集的叶片的近红外光谱和叶绿素含量的关系模型。再利用该模型来估测验证集紫丁香的叶绿素含量。本次试验,建模集的预测集和校验集的R2分别达到0.86和0.73,相关系数均达到85%以上,并且验证集的R2值达到0.82,相关系数为90.85%,说明近红外技术具有应用于叶片叶绿素含量估测的潜力。

Study on the Prediction of Chlorophyll Content in Syringa Oblata Leaves Based on Near Infrared Spectrum

Near Infrared Spectrum has the characteristics of fast and non-destructive, so the paper used those characteristics to predict the value of chlorophyll in Syringa oblata leaves. A total of 60 Syringa oblata leaves were collected from the experimental forest of Northeast Forestry University in Harbin, among which 40 leaves were randomly selected for modeling and the remaining 20 leaves were used as calibration set. A relationship model between Near Infrared Spectrum of the modeling set leaves and the content of the chlorophyll was established with the partial least squares method. And then the model was used to predict the content of the Syringa oblata chlorophyll of the validation set. The results showed that the R2 of the prediction model set and calibration set were 0. 86 and O. 73, respectively, and the correlation coefficient were all above 85%. R2 value of the verification set was O. 82 and the correlation coefficient was 90. 85%. It means that near infrared technology has the capacity to predict the content of chlorophyll.