Development of image based detection methods for twospotted spider mite, Tetranychus urticae Koch, on strawberries

The twospotted spider mite (TSSM), Tetranychus Urticae Koch, is the most prominent and economically damaging mite pest that affects field-grown and greenhouse strawberries. At high infestation levels, early on in plant development, TSSM can significantly affect plant growth and markedly reduce fruit yield. Traditional monitoring techniques can be labor intensive, expensive to implement in large scale production, and ineffective due to the highly clustered distribution patterns of TSSM in strawberry fields. Visual imaging technologies could potentially improve TSSM monitoring and assessment strategies, in strawberries, by creating a real-time detection and treatment system. The potential for this image based detection of TSSM is possible due to the observable change in leaf color and texture associated with mite feeding. We are currently examining the feasibility of simple visual imagery techniques, coupled with post-processing analysis, to correlate RGB band reflectance values to mite infestation levels. Color images were obtained for two different varieties of strawberries (Albion and Festival) located on a strawberry farm in Floral City, FL. Six imaging sites were chosen for each variety representing a wide range of mite infestation levels. Images were taken at three different times throughout the day to account for differences in solar angle. Images were calibrated and analyzed using ENVI 5.1 remote sensing software and SPSS statistical software. Current preliminary data suggests that single band and normalized band difference models may be able to predict mite infestation levels.