Multispectral and thermal imagery approaches to insect pest and disease detection in horticultural crops

Early identification and control of insect pests and diseases is a key aspect of profitable crop production, especially for high input, high value horticultural crops. Remote sensing approaches using sensor technologies to detect insect pests and diseases have been previously demonstrated in a range of field crops and were researched in this project as a tool for plant health monitoring in chilli crops. A methodology for image capture using a multispectral camera mounted on an Unmanned Aerial Vehicle (UAV) and image processing based on distribution of individual pixel values in collected images was developed. This methodology was demonstrated to be as effective as manual crop scouting in early detection of insect pest and disease affected plants within a crop but could be automated to significantly reduce the cost of crop health monitoring. Initial method development trials demonstrated that detectable changes in NDVI, but not temperature changes measured using a thermal camera, occurred on leaves affected by bacterial spot disease before obvious visible symptoms were apparent. Bacterial spot (Xanthomonas euvesicatoria (Xeu)) is a ubiquitous disease infecting field-grown chilli crops, particularly during warm and humid conditions, and symptoms of infection were not apparent until about 7 days after inoculation of leaves with the pathogen. The age of inoculated leaves did not significantly affect the rate of change of NDVI. Non-inoculated leaves tended to have a lower NDVI value on plants with a greater number of inoculated leaves than on plants with none or few inoculated leaves. iii Aphids Myzus persicae (Sulzer) cause significant damage to chilli crops both directly via feeding on the host plant and indirectly as vectors for virus transmission. Reflectance data, obtained by multispectral, hyperspectral and thermal sensors, showed that the reflectance of aphid infested leaves in near infrared wavelengths decreased with time as the aphid population infesting a leaf increased. Remote sensing data acquired from low-altitude UAV flights deliver high spectral and spatial resolutions, with sufficient pixels representing individual leaf reflectance to allow detection of changes occurring when disease infection or insect pest infestation first occurs in part of a plant. This capacity for detection at early infection/infestation stage is crucial for effective management in high value horticultural crops. Conventional remote sensing approaches may detect changes occurring at a whole plant or region within a crop but lack the resolution capacity to readily detect changes at the sub-plant level. A five-band multispectral camera (MicaSense, RedEdge) and a low-altitude (15m) airborne platform provided adequate data, recording changes in reflectance imagery. The effectiveness of multispectral imagery decreased as flight altitude increased. The project has demonstrated that early identification of insect pest and pathogen-induced plant stress in chilli crops can be achieved using a methodology that can be automated to deliver a low-cost strategy for horticultural producers