Detecting Bare Spots in Wild Blueberry Fields using Digital Color Photography

Abstract

Wild blueberry fields are developed from native stands on deforested land by removing competing vegetation The majority of fields are situated in naturally acidic and non-fertile sods that have high proportions of bare spots, weed patches, and gentle to severe topography Producers presently apply agrochemicals uniformly without considering bare spots The unnecessary or over-application of agrochemicals in bare spots may increase cost of production and environmental pollution An automated cost-effective machine vision system using digital color photography was developed and tested to detect and map bare spots for site-specific application of agrochemicals within wild blueberry fields The experiment was conducted at a 4-ha wild blueberry field in central Nova Scotia The machine vision system consisting of a digital color camera, differential global positioning system, and notebook computer was mounted on a specialized farm vehicle Custom software for grabbing and processing color images was developed m Delphi 5 0 and C++ programming languages The images taken by the digital camera were stored in the notebook computer automatically and then processed in red, green, and blue (RGB), and hue, saturation, and value (HSV) color spaces to detect bare spots in real-tune within blueberry fields The best results were achieved in hue image color space with 99% accuracy and a processing speed of 661 ms per image The results indicated that bare spots could be identified and mapped with this cost-effective digital photography technique in wild blueberry fields This information is useful for site-specific application, and has the potential to reduce agrochemical usage and associated environmental impacts in the wild blueberry production system