EAPSI: Multispectral Imaging for Marssonina Blotch Disease Detection in Fuji Apples

Posadas Brianna B, Gainesville FL

Investigators

Abstract

Apple Marssonina Blotch disease (AMB) is caused by the fungus Diplocarpon mali. Within 40 days of infection, the affected leaf grows small brown lesions while the leaf?s pigment turns from a healthy green to a sickly yellow. The trees soon defoliate prematurely, reducing the number of apples that particular tree can produce that year and considerably reducing profits. Once an orchard has been infected, the only possible control measure is to remove the diseased tree. Preventative measures include spraying with fungicide, but Diplocarpon mali has shown low sensitivity to copper fungicides and is becoming resistant to thiophantante-methyl. Countries where AMB is a serious problem include the Republic of Korea where half their orchards are infected. This research builds on an existing collaboration between the Precision Agriculture Laboratory (PAL) at the University of Florida (UF) and the Rural Development Agency (RDA) under the National Academy of Agricultural Science in South Korea. The RDA maintains its own Apple Research Station in Gunwi and has been researching AMB since 2012. This award provides an opportunity for a U.S. graduate student to collaborate with RDA researchers under the mentorship of Dr. Sangcheol Kim. This research will improve our understanding of AMB and help U.S. researchers and growers to mitigate damage should the disease return to the U.S. The project will investigate the potential to utilize near infrared (NIR) spectroscopy and hyperspectral imaging techniques to detect AMB. Radiance measurements of 50 different leaves will be measured using a hyperspectral camera with a range of 400 to 1000 nm. Images will be taken daily to determine changes in the radiance in the leaves as the disease progresses. These images will be used to identify the spectral signatures and important wavelengths that can determine the disease status in the leaf. An algorithm will be developed that can best determine this distinction and will be used to design an early detection device for the local growers. A survey of the growers will also be conducted to determine the parameters of the early detection device prototype. This award is funded in collaboration with the National Research Foundation of Korea.