Assessment of Rice Panicle Blast Disease Using Airborne Hyperspectral Imagery
نویسندگان
چکیده
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 R 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 700to 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 (R = 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.
منابع مشابه
The reaction of 109 rice lines to blast disease
Shahbazi H, Tarang A, Padasht F, Hosseini Chaleshtari M, Allah-Gholipour M, Khoshkdaman M, Mousavi Qaleh Roudkhani SA, Nazari Tabak S, Asadollahi Sharifi F, Pourabbas Dolatabad M (2022) The reaction of 109 rice lines to blast disease. Plant Pathology Science 11(1):24-35. Doi: 10.2982/PPS.11.1.24. Introduction: Blast caused by Pyricularia oryzae is the most important fungal disease of ri...
متن کاملCharacterization and Fine Mapping of a Blast Resistant Gene Pi-jnw1 from the japonica Rice Landrace Jiangnanwan
Rice blast is a destructive disease caused by Magnaporthe oryzae, and it has a large impact on rice production worldwide. Compared with leaf blast resistance, our understanding of panicle blast resistance is limited. The japonica landrace Jiangnanwan from Taihu Lake region in China shows highly resistance to panicle and leaf blast. In this study, three generations (F2:5, F2:6, F2:7) consisting ...
متن کاملAnalysis of Hyperspectral Imagery for Oil Spill Detection Using SAM Unmixing Algorithm Techniques
Oil spill is one of major marine environmental challenges. The main impacts of this phenomenon are preventing light transmission into the deep water and oxygen absorption, which can disturb the photosynthesis process of water plants. In this research, we utilize SpecTIR airborne sensor data to extract and classify oils spill for the Gulf of Mexico Deepwater Horizon (DWH) happened in 2010. For t...
متن کاملPreliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing.
The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sen...
متن کاملComparison of airborne multispectral and hyperspectral imagery for mapping cotton root rot
* Corresponding author. Tel.: þ1 956 969 483 E-mail address: [email protected] 1537-5110/$ e see front matter Published by doi:10.1016/j.biosystemseng.2010.07.011 Cotton root rot, caused by the soilborne fungus Phymatotrichum omnivorum, is a major cotton disease in the south western and south central United States. Accurate delineation of root rot infestations is necessary for site-specifi...
متن کامل