Development of risk assessment method for rice yield reduction by disease using crop model and drone data

2022 Fiscal Year Final Research Report

• Project/Area Number: 19H03078
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 41040:Agricultural environmental engineering and agricultural information engineering-related
• Research Institution: Chiba University
• Principal Investigator: Hongo Chiharu 千葉大学, 環境リモートセンシング研究センター, 准教授 (20272354)
• Co-Investigator(Kenkyū-buntansha): 牧 雅康 福島大学, 食農学類, 准教授 (50375391) ; 本間 香貴 東北大学, 農学研究科, 教授 (60397560)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: 水稲病害 / UAVデータ / 作物モデル / 収量評価

Outline of Final Research Achievements

This study aimed to develop a method for determining the severity of bacterial leaf blight disease and rice blast disease and evaluating the degree of yield reduction using UAV images and crop models in Indonesia. Although field surveys by visiting Indonesia from Japan could not be conducted due to the COVID-19 pandemic, rice disease data and UAV images were obtained from our counterparts, and image normalization was applied to develop a method for determining disease severity that is not affected by different cropping seasons.
Furthermore, yield prediction using the SIMRIW-RS simulation model after adjusting parameters in West Java was confirmed to correspond to the measured yields. The same model was also used to evaluate yields incorporating effects of blast disease, and it was possible to predict a trend toward lower yields in areas where the area of leaf blast lesion was large.

Free Research Field

植物栄養学、農業リモートセンシング

Academic Significance and Societal Importance of the Research Achievements

日本国内では病害発生を阻止するための対策が取られているため、熱帯地域と比較して病害情報や罹病水田のリモートセンシングデータの蓄積が多くない。一方で、近年の気候変動による温暖化傾向を受けて、将来的に国内での病害発生の高頻度化と重症化が予測されている。本研研究課題で行う熱帯アジアにおける病害判定手法と減収リスク評価手法の構築は、現在の熱帯地域において不足している病害防除のための情報提供、日本国内での将来的な病害多発に対する適応戦略モデルの準備という観点からも意義がある。