Method for UAV spraying pattern measurement with PLS model based spectrum analysis - zhang, Ruirui; Wen, Yao; Li, Longlong; Chen, Liping; Xu, Gang; Huang, Yanbo; Tang, Qing; Yi, Tongchuan (International Journal of Agricultural and Biological Engineering, 2020)
Unmanned aerial vehicle (UAV) chemical application is widely used for crop protection, and spraying pattern is one of the most important factors that influence the chemical control efficacy. A method for UAV spraying pattern measurement with partial least squares (PLS) model based spectrum analysis was proposed in this study to measure the UAV spraying pattern more accurately. The method involved the steps of fluorescent tracer solution spray and its droplets collection, the spectrum on paper strip acquiring, spectrum processing and analysis, PLS modeling. In order to verify the applicability of the method and obtain the parameters of the PLS model, UAV spraying experiments were performed in the field. Then Fluorescent tracer solution was sprayed and its droplets are collected by paper strip, and the original spectrum on paper strip obtained by a spectrometer was processed by the Savitzky-Golay and standard normalized variable (SNV) method. The prediction model of coverage rate selected as the droplet deposition parameter to measure the UAV spraying pattern, was established by using PLS method. To verify the superiority of the PLS model, a traditional linear regression (LR) model of coverage rate was established simultaneously. The results demonstrate that the method with PLS model based spectrum analysis can measure the UAV spraying pattern effectively, and PLS model has a better performance of RV2=0.94 and RMSEP=0.9446 than that of the LR model. Keywords: pattern measurement, UAV spraying, spectrum model, coverage rate, partial least squares method DOI: 10.25165/j.ijabe.20201303.5341 Citation: Zhang R R, Wen Y, Li L L, Chen L P, Xu G, Huang Y B, et al. Method for UAV spraying pattern measurement with PLS model based spectrum analysis. Int J Agric & Biol Eng, 2020; 13(3): 22–28.