Abstract
Abstract This study aims at the shortcomings of traditional artificial ground detection methods for Bursapherenchus xylophophilus disease and applies HSV(Hue-Saturation-Value) color model to realize automatic identification of Bursapherenchus xylophophilus disease and determine its degree of disaster.The entire process is divided into forest data collection, image processing, nematode disease identification and grade determination.The study conducted repeated comparisons and adjusted HSV threshold tests to obtain the HSV threshold with optimal recognition results, and then identify Bursaphelenchus xylophophilus disease and calculate its disease severity. This method is simple to operate and has good identification effects. It can also effectively improve the accuracy and efficiency of pine wood nematode diagnosis. It can be widely used in the field of agriculture and forestry to help better complete disease detection and carry out prevention and control measures more accurately, thereby effectively Protect forest natural resources and improve forestry production efficiency.
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