Estimation of chlorophyll content in Brassica napus based on unmanned aerial vehicle images

Abstract

The chlorophyll content has a direct effect on photosynthesis of crops. In order to explore a quick and convenient method for estimating the chlorophyll content of Brassica napus and facilitate efficient crop monitoring, we measured the actual value of chlorophyll with a SPAD-502 chlorophyll detector, and collected aerial images of B. napus with an unmanned aerial vehicle (UAV) carrying a RGB camera in this study. The total number of 270 samples collected images were divided into regions according to the planting conditions of different B. napus varieties in the field. Then, according to the empirical formula, there were 36 colors’ characteristic parameters calculated and combined. To estimate the chlorophyll content of rape, 189 samples were included in the modeling set, while the other 81 samples were enrolled in the validation set for testing the accuracy of this model. After the combination of R (red), G (green) and B (blue) color channels, the results showed that the color characteristics B/(R ​+ ​G), b, B/G, (G-B)/(G ​+ ​B), g-b were highly connected with the measured value of chlorophyll SPAD, and the correlation coefficient between the combination based on B/(R ​+ ​G) and SPAD value was 0.747. With R2 = 0.805, RMSE = 3.343, and RE = 6.84%, the regression model created using random forest had superior outcomes, according to the model comparison. This study offers a new method for quickly estimating the amount of chlorophyll in rapeseed and a workable reference for crop monitoring using the UAV platform.

Keywords

• Brassica napus
• Unmanned aerial vehicle
• Red green blue images
• SPAD
• Chlorophyll