This paper reviewed the current application status of technologies such as hyperspectral imaging,machine vision,and acoustic vibration detection in pear tree disease detection,and discussed the development prospects of intelligent detection.Hyperspectral imaging captures physiological and biochemical changes in plants through continuous narrow-band spectral information,showing outstanding performance in leaf disease identification.Machine vision,based on RGB or multispectral images combined with image segmentation,color and texture features,and deep learning models,enables rapid lesion identification and orchard inspection,offering advantages such as low cost,fast imaging,and ease of deployment on mobile devices.Acoustic vibration detection identifies internal diseases by analyzing vibration signals from excited fruit,primarily targeting fruit diseases such as black heart disease,and can complement leaf disease detection.Overall,non-destructive detection of pear tree diseases has initially formed a multi-dimensional technical system of"spectral imaging-acoustic vibration sensing-intelligent diagnosis".However,practical application still needs to address field light fluctuations,canopy occlusion,leaf curling,motion blur,and sand-dust interference.Future efforts should focus on constructing dedicated disease datasets,developing multi-source information fusion,lightweight and highly robust models,and portable real-time detection equipment;establishing detection standards and evaluation systems;and strengthening the integration of biological control with non-destructive detection,so as to promote the intelligent detection of pear tree diseases toward precision,standardization,and practical application.