Research On The Methods Of Crop Nitrogen Status Diagnosis Based On Carotenoid And Chlorophyll Ratio Values

Chlorophyll and carotenoid are the major pigments that are responsible for photosynthesis and indicative of crop nutrient content.Variations of chlorophyll and carotenoid content,especially,carotenoid content variation and its ratio to chlorophyll content are frequently used for plant physiological status investigation,since carotenoid content and its ratio to chlorophyll content will change when plant are in nutrient stress condition or during senescence process.Therefore,research on mechanism estimation methods of carotenoid content and its ratio to chlorophyll content is crucial,and provides valuable insight into crop nitrogen status diagnosis.However,little consensus has been made on the mechanism retrieval methods of crop carotenoid content and its ratio to chlorophyll content,and researchers rarely focused on crop nitrogen status diagnosis with carotenoid and chlorophyll ratio values.Realizing the shortcomings of current research on crop nitrogen status diagnosis,this paper conducted researches on estimating methods of crop carotenoid content and its ratio to chlorophyll content,proposed a new approach to assess crop nitrogen status based on carotenoid and chlorophyll ratio values,and made improvement and progress on crop chlorophyll content and nitrogen content assessment.Our major conclusions were listed as follows:1.A new carotenoid index(CARI)for leaf carotenoid content assessment was proposed based on a large synthetic dataset simulated from the leaf radiative transfer model PROSPECT-5,and its capability was evaluated with both simulated data from PROSPECT-5 and 4SAIL and extensive experimental datasets: the ANGERS dataset and experimental data acquired in field experiments.Compared with published spectral indices,CARI showed accurate and robust estimation of leaf carotenoid content with various measured leaf level data.Further assessment with simulated and measured canopy reflectance data indicated that CARI might not be very sensitive to leaf carotenoid content changes at low leaf area index(LAI)value,and in these conditions soil moisture influenced the leaf carotenoid content retrieval accuracy.2.A novel carotenoid/chlorophyll ratio index(CCRI)for carotenoid/chlorophyll ratio estimation was proposed based on a synthetic dataset simulated from the leaf radiative transfer model PROSPECT-5,and its capability was evaluated with extensive leaf-and canopy-level experimental datasets: the ANGERS dataset,winter wheat data and maize data acquired in field experiments.Compared with published spectral indices,CCRI showed accurate and robust estimation of carotenoid/chlorophyll ratio with both leafand canopy-level measured datasets,suggesting that the newly proposed CCRI was an optimal indicator for carotenoid/chlorophyll ratio assessment.3.Based on the carotenoid/chlorophyll ratio assessment,this paper analyzed the relationship between carotenoid/chlorophyll ratio and plant nitrogen concentration(PNC)in winter wheat,which were grown in nitrogen-and water-stress conditions.With Pushbroom hyperspectral imager(PHI)airborne hyperspectral data,a model for assessing winter wheat PNC using CCRI spectral index was established,and its estimation accuracy was better than that of chlorophyll spectral index(i.e.red-edge chlorophyll index,CIred-edge)model.Moreover,the established winter wheat PNC estimation model based on CCRI spectral index was suitable for simulated hyperspectral data of Environmental Mapping and Analysis Program(EnMAP)satellite with high estimation accuracy.4.With PHI airborne hyperspectral data,this paper investigated the assessment of winter wheat canopy nitrogen content(CNC)using spectral index methods.Results suggested that a significant linear relationship existed between nitrogen and chlorophyll content at the canopy level,and it was not affected by cultivars,growing conditions and nutritional status of winter wheat.Nevertheless,it varied with growth stages.Periods around heading stage mainly worsened the relationship and CNC estimation,and CNC assessment for growth stages before and after heading could improve CNC retrieval accuracy to some extent.Spectral indices established based on red-edge band including CIred-edge,NDVI-like and ND705 showed convincing results in CNC retrieval with PHI data,and spectral indices(CIred-edge and CIgreen)that established on narrow or broad bands showed no obvious difference in CNC assessment.5.Based on the newly-launched Sentinel-2 satellite imagery,this paper explored its potential in multi-temporal winter wheat leaf chlorophyll content(LCC)retrieval.Results suggested that performance of different spectral indices in LCC assessment varied.Spectral indices that established on red-edge bands showed accurate estimation of LCC in winter wheat.Compared with spectral indices methods,Gaussian process regression(GPR)in LCC retrieval achieved excellent accuracy.With the established GPR model,multi-temporal winter wheat LCC at the regional scale were acquired with high accuracy,and LCC values could indirectly reflect nitrogen status of winter wheat,which could provide information for crop nitrogen status monitoring.The main innovative contributions of this paper are as follows:1.Aiming at leaf carotenoid content retrieval with high accuracy,this paper proposed a new carotenoid index(CARI)for leaf carotenoid content assessment based on the spectral absorption features of carotenoid in the visible range,with a large synthetic data.CARI showed accurate and robust estimation of leaf carotenoid content with various measured leaf level data,suggesting that it is suitable for carotenoid content retrieval.2.Aiming to solve the problem of estimating carotenoid/chlorophyll ratio with high accuracy,this paper proposed a new carotenoid/chlorophyll ratio index(CCRI)for carotenoid/chlorophyll ratio assessment based on carotenoid index and red-edge chlorophyll index,with a large simulated data.CCRI showed accurate and robust estimation of carotenoid/chlorophyll ratio with both leaf-and canopy-level measured datasets,indicating that it is suitable for carotenoid/chlorophyll ratio assessment.3.Based on the estimation method of carotenoid/chlorophyll ratio,this paper established a model with high accuracy for assessing winter wheat PNC using CCRI spectral index with PHI airborne hyperspectral data,and it could be applied to simulated Environmental Mapping and Analysis Program(EnMAP)satellite hyperspectral data.