The Open Agriculture Journal

ISSN: 1874-3315 ― Volume 13, 2019

Assessment of Rice Panicle Blast Disease Using Airborne Hyperspectral Imagery

Takashi Kobayashi1, *, Masashi Sasahara2, Eiji Kanda3, Kiyoshi Ishiguro4, Shu Hase1, Yoichi Torigoe5
1 Faculty of Agriculture, Yamagata University, Tsuruoka 997-8555, Japan
2 Miyagi Prefectural Furukawa Agricultural Experiment Station, Osaki 989-6227, Japan
3 Faculty of Agriculture, Kagoshima University, Kagoshima 890-0065, Japan
4 National Agriculture and Food Research Organization, Tohoku Agricultural Research Center, Morioka 020-0198, Japan
5 College of Bioresource Sciences, Nihon University, Fujisawa 252-0880, Japan


Rice blast disease occurs in rice production areas all over the world and is the most important disease in Japan. Remote sensing techniques may provide a mean for detecting disease intensity for large area without being subjected to raters. This study evaluated the use of airborne hyperspectral imagery to measure the severity of panicle blast in field crops. Hyperspectral remote sensing imagery was acquired at the dough stage of rice grain development in northern Japan. The most consistent relationship, with high R2 and low P, was the simple band ratio R498 to 515/R700 to 717 (i.e., the reflectance at 498 to 515-nm divided by the reflectance at 700- to 717-nm). The band ratio of R498 to 515/R700 to 717 increased significantly (P < 0.001) with increasing visual estimates of disease incidence, defined as the percentage of diseased spikelets (R2 = 0.83). Assessment of disease distribution and severity could provide useful information for making decisions regarding the necessity of fungicide application and estimate potential yield loss due to the disease.

Keywords: Hyperspectral imagery, Panicle blast, Remote sensing, Rice blast disease.

Article Information

Identifiers and Pagination:

Year: 2016
Volume: 10
First Page: 28
Last Page: 34
Publisher Id: TOASJ-10-28
DOI: 10.2174/1874331501610010028

Article History:

Received Date: 25/12/2015
Revision Received Date: 25/5/2016
Acceptance Date: 26/5/2016
Electronic publication date: 23/06/2016
Collection year: 2016

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© Kobayashi et al ; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the Faculty of Agriculture, Yamagata University, Tsuruoka 997-8555, Japan; Tel: 81-235-2849; Fax: 81-235-2849; E-mail:


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