基于叶绿素荧光光谱的生菜硝酸盐含量检测

为了寻求生菜叶片硝酸盐含量的快速无损检测方法,该文利用叶绿素荧光光谱分析技术对生菜(Lactuca sativa L.)叶片硝酸盐含量进行检测研究。对比及分析500~550、650~715和715~800 nm 3个波段的叶绿素荧光光谱特征参数与生菜叶片硝酸盐含量的关系,得出650~715 nm波段的叶绿素荧光光谱特征参数与生菜叶片硝酸盐含量之间线性关系显著,决定系数R2为0.816,标准误差为0.147,以此建立的回归模型能够很好地反映生菜叶片硝酸盐含量与叶绿素荧光光谱特征参数的关系;将同批进行试验的30个样本作为回归方程的校验集,进行模型验证,预测值与实测值之间决定系数R2为0.752,表明回归模型对生菜叶片硝酸盐含量有良好的预测效果。研究结果为生菜叶片硝酸盐含量的快速无损检测提供参考。

Detection of nitrate content in lettuce based on chlorophyll fluorescence spectrum

Abstract: With the development of spectral technology, many researchers have done a lot of research on the nondestructive testing methods of nitrate content in leaves and have achieved some results. However, most of the studies have used visible and near infrared spectroscopy or mid infrared spectroscopy technology, and the chlorophyll fluorescence spectrum technology is still not used. Therefore, this paper used chlorophyll fluorescence spectrum analysis technology to study the relationship between nitrate content and fluorescence spectrum. With aerosol cultured lettuce as the research object, the chlorophyll fluorescence spectrum characteristic parameters were extracted to establish the function relationship between the characteristic parameters of chlorophyll fluorescence spectrum and the nitrate content of lettuce leaves, which laid a theoretical foundation for the rapid and nondestructive detection of nitrate content in lettuce leaves. The peak values of fluorescence intensity of 500-550, 650-715 and 715-800 nm were the characteristic parameters of chlorophyll fluorescence spectrum. It could be seen that the characteristic parameter of 500-550 nm was relatively weak, and it showed irregular variation with the change of nitrate content in lettuce leaves. Therefore, this band was not the desired band of this paper. The characteristic parameters of 650-715 and 715-800 nm showed clear and regular variation with the change of nitrate content in lettuce leaves, so they could be used for further study. In this paper, non dimensional treatment and standardized treatment of nitrate content in lettuce leaves and the characteristic parameters of 650-715 and 715-800 nm were in progress, and the linear fitting method was adopted. The results showed that the characteristic parameter of 650-715 nm and the nitrate content of lettuce leaves presented a significant linear relationship. The determination coefficient of regression model between them was 0.816 and the standard error was 0.147. Adding another variable in the regression model could improve the accuracy of the model a little; and the determination coefficient of regression model was 0.820 and the standard error was 0.146. And as the sample capacity was certain, the increase of the independent variable would cause the decrease of the degree of freedom, which then would affect the goodness of the fit of the regression model. Therefore, this paper chose the characteristic parameter of 650-715 nm to establish the regression model, which could well reflect the relationship between nitrate content of lettuce leaves and characteristic parameters of chlorophyll fluorescence spectrum. Thirty samples from the same batch were used as the calibration set of the regression model, and the regression model already established was used to predict the nitrate content of lettuce leaves. After verification, the determination coefficient between the predicted value and the measured value was 0.752, and the standard error was 0.172. The results show that the regression model has a good predictive effect on nitrate content of lettuce leaves and it can be used as the basis for rapid and nondestructive detection of nitrate content in lettuce leaves.