Differentiation of Rice Panicles Blast by Hyperspectral Remote Sensing based on Probabilistic Neural Network

The incidence of rice panicles blast led to the decrease of yield and quality,precise differentiation of disease severe rice that their necks were contagious(D),lodging rice that their panicles were severely contagious(L) and healthy rice(H) was the basis of disease and pest prevention measures and damage assessment.This study adopted 27 samples of H’s canopy,9 samples of D’s canopy and 10 samples of L’s canopy,and their red edge,red edge area,green peak and green peak area parameters were treated.Samples were analyzed by probabilistic neural network(PNN)and the hierarchical cluster,and the discrimination accuracy of D,L and H were separately as high as 93.5% and 91.3%.PNN was better than the hierarchical cluster in classification and differentiation.The study demonstrated that PNN had a great classified function.Differentiation of rice panicles blast by hyperspectral remote sensing based on PNN,and this method was feasible to precisely differentiate D and L from Hs,and supplement or perfect the conventional visual survey.