An Improved Crop Scouting Technique Incorporating Unmanned Aerial Vehicle–Assisted Multispectral Crop Imaging into Conventional Scouting Practice for Gummy Stem Blight in Watermelon

Abstract

Multispectral imaging is increasingly used in specialty crops, but its benefits in assessment of disease severity and improvements in conventional scouting practice are unknown. Multispectral imaging was conducted using an unmanned aerial vehicle (UAV), and data were analyzed for five flights from Florida and Georgia commercial watermelon fields in 2017. The fields were rated for disease incidence and severity by extension agents and plant pathologists at randomized locations (i.e., conventional scouting) followed by ratings at locations that were identified by differences in normalized difference vegetation index (NDVI) and stress index (i.e., UAV-assisted scouting). Diseases identified by the scouts included gummy stem blight, anthracnose, Fusarium wilt, Phytophthora fruit rot, Alternaria leaf spot, and cucurbit leaf crumple disease. Disease incidence and severity ratings were significantly different between conventional and UAV-assisted scouting (P

Plant phenotyping relevance

UAV multispectral画像とNDVI・ストレス指数を用いてスイカの病害発生・重症度を推定し、従来法と比較評価しているため、植物病害表現型の取得手法が中心です。

Code and data availability

The article describes UAV multispectral imaging and scouting data for watermelon disease, but no public phenotype dataset, imagery deposit, or author analysis code is mentioned. Supplementary figures/table are referenced without any availability URL, and the only URLs in the text are a USDA statistics page and a cited,

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