Diagnosis Of Nitrogen Nutrition Status And Yield Estimation Of Summer Maize In North China

Nitrogen is the most important limiting factor for growth process of summer maize,lacking of nitrogen will significantly reduce the yield and quality,and excessive nitrogen application will be harmful to the environment.Therefore,monitoring nitrogen status accurately and timely is of great significance to improve yield and quality of summer maize.In this study,summer maize with different nitrogen application levels was taken as the research object.The canopy of summer maize was divided into four layers according to the difference of plant height on average,and its growth process was divided into emerging-jointing stage,jointing-heading stage,heading-filling stage and filling-maturing stage.The change of leaf nitrogen content,chlorophyll content,leaf and plant nitrogen nutrition index and leaf biomass with growth process and nitrogen application levels of summer maize was studied,and this study used the empirical and physical models to construct the monitoring models of all kinds of agronomic parameters,at the same time,based on a variety of agronomic parameters to build some models of comprehensive growth process for estimation of yield.It provides an effective means for the diagnosis of nitrogen status and estimation of yield in large area.（1）Aiming at the problem of remote sensing monitoring of the vertical distribution of nitrogen content in canopy leaves of summer maize,the vertical distribution of nitrogen content in leaves and the variation of nitrogen content in leaves of each layer with the growth process and nitrogen application levels was analyzed,and the models of comprehensive growth process by spectral index were constructed to simulate the nitrogen content in leaves of each layer and the total nitrogen content in leaves of summer maize.After two years of data verification,R²is higher than 0.1200 and RE is lower than 58.00%.The results provide theoretical and technical support for the application of vertical stratification simulation of crop nitrogen content.（2）The correlation between nitrogen nutrition index and yield of summer maize plants and leaves was analyzed.It was found that the correlation between nitrogen nutrition index and yield is better in each growth process.At the same time,the correlation between leaf chlorophyll content of each layer,average leaf chlorophyll content and leaf nitrogen nutrition index was analyzed,and it was found that average leaf chlorophyll content is more representative of leaf nitrogen nutrition index.Therefore,the best model for estimating leaf nitrogen nutrition index based on average leaf chlorophyll content in each growth process was constructed and screened,with R²higher than 0.2300 and RE lower than 26.00%,which realizes the estimation method of monitoring leaf nitrogen nutrition index by leaf chlorophyll content,laying a foundation for monitoring leaf nitrogen nutrition index based on PROSAIL model.（3）Aiming at the problem of remote sensing monitoring the vertical distribution of chlorophyll content in canopy leaves of summer maize,the vertical distribution of chlorophyll content and the variation of chlorophyll content in each layer with the growth process and nitrogen application level were analyzed,and the sensitive bands of chlorophyll content were screened by combining PROSAIL model and EFAST method.The monitoring models of chlorophyll content and average chlorophyll content in leaves of each layer were constructed.After two years of data testing,the RE of each model is lower than 46%,which realizes the vertical stratification simulation of chlorophyll content in summer maize based on PROSAIL model,providing theoretical and technical support for the application of vertical stratification simulation of crop chlorophyll.（4）The best monitoring models for leaf biomass and leaf nitrogen nutrition index I at each growth stages was constructed using spectral index,while an indirect estimation model for leaf nitrogen nutrition index was constructed based on the leaf nitrogen nutrition index model using the best monitoring models for leaf nitrogen content and leaf biomass.At the same time,a monitoring model of leaf nitrogen nutrition index was constructed using PROSAIL model with average chlorophyll content as intermediate variable（PCN model）.After two years of data testing,it was found that the PCN model has the best monitoring accuracy and stability,with R²higher than 0.3200,RMSE lower than 0.3000,MAE lower than 0.2400 and RE lower than 23.00%in each growth process.Therefore,the images from Sentinel-2 were used to estimate the leaf nitrogen nutrition index by the PCN model in each growth process of Daxing District.（5）Using leaf nitrogen content in each layer,total leaf nitrogen content,leaf chlorophyll content in each layer,average chlorophyll content,leaf biomass and leaf nitrogen nutrition index as intermediate variables,some monitoring models for estimation of yield in the comprehensive growth process were constructed.After two years of data testing,it was found that the accuracy and stability of the model for yield estimation based on PROSAIL model with average chlorophyll as intermediate variable is the best,with R²above 0.7800,RMSE below 0.9600 t·ha^-1,MAE below 2.9600 t·ha^-1and RE within 16.00%.Therefore,based on PROSAIL model and the images from Sentinel-2,the yield of summer maize in Daxing District was estimated.In this study,physical and empirical models were used to construct estimation models of vertical stratified nitrogen content and chlorophyll content,leaf biomass and leaf nitrogen nutrition index of summer maize,and some yield estimation models were constructed with a variety of agricultural parameters as intermediate variables.The optimal monitoring model was selected by comparison and verification of two-year data and applied to Daxing District of Beijing.The results provide theoretical basis for regional scale crop nitrogen diagnosis and yield estimation,and provide theoretical support for agricultural modernization.