Diagnostic Model For Crops Moisture Status Based On UAV Thermal Infrared

Precision irrigation is the development trend of agriculture.The unmanned aerial vehicle?UAV?thermal infrared remote sensing can quickly diagnose crop water stress,and has the advantages of dynamic,real-time and cheap.In this study,four kinds of cotton with different water control were used for I₁?50%field water holding capacity?,I₂?65%field water holding capacity?,I₃?80%field water holding capacity?,and I₄?control group 95%to 100%field water holding capacity?.In addition,application of UAV thermal infrared sensor to obtain thermal infrared images of cotton canopy in key growth period?full flowering period,full boll period,boll opening period?,and calculate the crop water stress index?CWSI?.At the same time,the stomatal conductance?Gs?,transpiration rate?Tr?,soil water content?SWC?,leaf relative water contents?RWC?and crop phenotype information of cotton leaves were collected.The effect of different algorithms for eliminating the UAV thermal infrared image on the soil water stress index.Analysis of the relationship between pure canopy temperature characteristics after removing soil background,simplified crop water stress index based on canopy temperature histogram and crop water stress status.Finally,the crop ground coverage and leaf area index were used to standardize the crop water stress index,and the correlation between the standard crop water stress index and the soil moisture,relative water content and dry matter weight was explored.The main results are as follows:?1?Different algorithms were used to eliminate the soil background in the thermal infrared image of the drone,revealing the influence of soil background on the accuracy of crop water stress index.Comparing the binarized Otsu algorithm and the Canny edge detection algorithm,the Canny edge detection algorithm can effectively remove the soil pixels in the thermal infrared image of the drone;Among the crop water stress index CWSI obtained by different treatment methods,the CWSI obtained by the Canny edge detection algorithm is the smallest,the CWSI of the binary Otsu algorithm was higher,and the CWSI containing the soil background was the largest;The determination coefficient of CWSI and cotton leaf stomatal conductance after removing the soil background by Canny edge detection algorithm reached0.84,followed by Otsu algorithm,including the worst soil background;In addition,the pure canopy temperature histogram after soil background removal was a unimodal shape,while the histogram without soil background may have two cases:bimodal and three peak,bimodal histogram including soil and canopy pixels,the three-peak histogram includes direct sunlight to the soil pixels,shadow soil pixels and canopy pixels.?2?The Canny edge detection algorithm was used to eliminate the soil background to obtain the pure canopy temperature,and the relationship model between the canopy temperature characteristics and the crop water deficit was constructed.The lateral and longitudinal temperatures of cotton canopy treated with different water stresses were significantly different.The determination coefficient of the canopy temperature standard deviation,canopy temperature coefficient of variation and Gs,Tr,CWSI were 0.884,0.625,0.673 and 0.853,0.583,0.620,respectively.Canopy temperature standard deviation is more sensitive to crop water stress and can be used as a new indicator for diagnosing crop water stress.?3?A simplified crop water stress index based on canopy temperature histogram was established.The soil background in the thermal infrared image of the drone was eliminated,the cotton canopy temperature histogram was drawn,and the simplified crop water stress index based on the canopy temperature histogram was calculated.There was a high correlation between the simplified crop water stress index and soil moisture content?0¹5 cm,0³0 cm,0⁴5 cm?in cotton root zone.In addition,the simplified crop water stress index had a high correlation with the stomatal conductance and transpiration rate of cotton leaves,and the coefficient of determination were 0.660 and 0.592,respectively.Therefore,the simplified the crop water stress index can better characterize the water stress of cotton.?4?A standardized crop water stress index was constructed,and the water deficit of cotton was diagnosed by standardized crop water stress index.Under different water stress conditions,the parameters of cotton showed significant changes,and with the increase of irrigation amount,cotton plant height,stem diameter,leaf area index?LAI?and ground vegetation coverage?Gc?gradually increased.Standardized treatment of crop water stress index CWSI by using LAI and Gc?CWSI/LAI?CWSIL??CWSI/Gc?CWSIG??.In the cotton flowering stage,the full boll stage,the boll opening stage,the coefficient of determination of CWSIL and CWSIG and leaf relative water content RWC were 0.73 and 0.81,0.82 and 0.66,0.61 and 0.56,respectively,which were higher than the unstandardized crop water stress index and RWC.In addition,there was no significant increase in the coefficient of determination of the standardized crop water stress index and the soil moisture content.