Establishment Of Drought Resistance Evaluation Index Of Wheat Based On Hyperspectral And Chlorophyll Fluorescence Imaging Technologies

Drought is the key climate limiting factor for the development of wheat industry in China and the world.The occurrence of drought has a significant spatial and temporal distribution,which coincides with the main wheat producing areas in a large area,resulting in non-dryland wheat is also significantly affected by drought.Therefore,it is the key way to guarantee national food security by improving the breeding level of drought-tolerant wheat.However,the traditional wheat drought resistance identification method has the defects that large workload and low-throughput.It is urgent to establish a high-throughput method for assessing wheat drought resistance to accelerate the process of breeding.In this study,hyperspectral images,chlorophyll fluorescence(Chl F)parameters,and drought resistance indicators of 335 wheat at seedling and filling stages under different soil moisture conditions were used to explore the relationship between hyperspectral images of wheat leaves and their photosynthetic,drought tolerance,and to establish the high-throughput evaluation models for wheat photosynthesis and drought resistance.The main results are as follows:1.Under drought conditions,the spectral reflectance of wheat leaves increased at550-700 nm and the first derivative decreased at 700-750 nm.he sensitive bands of hyperspectral to Chl F parameters were mainly concentrated near 500 nm,550 nm,680 nm,700 nm and 750 nm in the green to red region,and the sensitive bands to chlorophyll were mainly concentrated near 500-550 nm and 600-750 nm.The above bands can be used as an index to evaluate drought resistance,and the sensitive bands of seedling stage and filling stage are basically the same.In addition,the first derivative of the spectrum has a stronger correlation with Chl F parameters and chlorophyll,and has a better evaluation effect on wheat photosynthesis and drought resistance.2.Regression analysis showed that both spectral and image features could accurately estimate the chlorophyll content of large-scale wheat,with R~2reaching0.82 and 0.64,respectively.The highest R~2of QY＿max estimated by the estimation model based on image and spectral features is 0.31.3.The hyperspectral characteristics of a single variety have a good fitting relationship with Chl F parameters,and have the best estimation effect on Fm＿Lss,R~2is 0.77,but as the number of varieties increases,the relationship between the two weakens.The results indicated that the relationship between wheat Chl F and spectrum is affected by variety differences,and it is necessary to establish methods that are less affected by variety differences.4.The hyperspectral evaluation of wheat drought resistance can be achieved by establishing classification models.In this study,the accuracy of classification model based on six wheat varieties at seedling stage was up to 82%,the model accuracy based on 293 wheat varieties at filling stage was up to 66%.In summary,this experiment explored the relationship between spectrum and photosynthesis,drought resistance of large-scale wheat varieties at seedling and filling stages under drought stress,found spectral bands sensitive to photosynthesis,and established chlorophyll estimation models and drought resistance evaluation models with high accuracy.The models established in this study can effectively evaluate the chlorophyll content and drought resistance level of wheat,and provide reference for high-throughput phenotypic analysis and genetic breeding of wheat and other crops.