Remote Sensing of Occurrence Place of Rice Blast Disease by Infrared Thermal Image.

Yamamoto, Hirokazu; Suzuki, Yôiti; Iwano, Masanori; Hayakawa, Seiji

doi:10.1626/jcs.64.467

Cited by 10 publications

(6 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This implied that the ADAR system was highly valuable in remote sensing of crop disease detection but its spectral resolution might not be high enough to accurately discriminate plants with light infections. In Japan, Yamamoto et al (1995) examined the applicability of infrared thermal images in identification of rice blast disease through visual interpretation. Though the occurrence of rice blast disease was visible in thermal images, quantitative analysis using various indices for accurate identification had not been done in their study.…”

Section: Distribution Of the Rice Disease On Imagesmentioning

confidence: 99%

See 1 more Smart Citation

Detection of rice sheath blight for in-season disease management using multispectral remote sensing

Qin

Zhang

2005

International Journal of Applied Earth Observation and Geoinfor

112

View full text Add to dashboard Cite

Section: Distribution Of the Rice Disease On Imagesmentioning

confidence: 99%

“…One example in this aspect was the research of Yamamoto et al (1995), which reported remote sensing of occurrence of rice blast disease by infrared thermal image. Blast and sheath blight are the two most important rice diseases that impact rice farming in the world (Ou, 1985).…”

Section: Introductionmentioning

confidence: 99%

Detection of rice sheath blight for in-season disease management using multispectral remote sensing

Qin

Zhang

2005

International Journal of Applied Earth Observation and Geoinfor

112

View full text Add to dashboard Cite

“…At the yellow-ripe stage, R550/ R970 and R725/R900 were useful for estimating the panicle blast severity as measured in terms of the percentage of diseased spikelets. Yamamoto et al (1995) found that an infection of rice blast fungus increased leaf temperatures by 1.1°C (determined with an infrared radiative thermometer) under upland nursery conditions. However, there have been no reports on the response of rice spectral reflectance to leaf blast infection within the visible, near-infrared, and midinfrared regions, which include most of the incident solar spectrum.…”

Section: Introductionmentioning

confidence: 97%

Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer

Kobayashi

Kanda

Naito

et al. 2003

Journal of General Plant Pathology

View full text Add to dashboard Cite

Rice reflectance was measured to determine the spectral regions most sensitive to leaf blast infection with a multispectral radiometer. As disease severity increased, reflectance also increased in the 400-500 nm (blue), 570-700 nm (red), and 900-2000 nm regions but decreased in the 500-570 nm and 700-900 nm regions. The increased reflectance in the blue and red regions may be attributed to decreased chlorophyll and carotenoid contents in response to the blast infection. The maximum and minimum reflectance differences occurred at 680 nm and 760 nm for the nondiseased and diseased rice, respectively. The spectral location of maximum sensitivity was 675 nm regardless of disease severity. Rice reflectance ratios were evaluated as indicators of leaf blast severity. Two ratios, R550/R675 (reflectance at 550 nm divided by reflectance at 675 nm), and R570/R675 quantified the significant disease severity. These wavelengths were selected based on the sensitivity minima and maxima. The ratios of nondiseased rice plants varied depending on growth stage. The variation in ratios must be considered when they are used to estimate leaf blast severity.

show abstract

“…Infrared thermal imaging has been used for the detection of more than six fungal and bacterial diseases in seven crops [10,12]. Yamamoto et al [46] reported the use of infrared thermal image to detect the occurrence of rice blast in Japan.…”

Section: Remote Sensorsmentioning

confidence: 99%

UAV Remote Sensing: An Innovative Tool for Detection and Management of Rice Diseases

Zhou¹,

Zhang²,

Lin³

2021

Diagnostics of Plant Diseases

View full text Add to dashboard Cite

Unmanned aerial vehicle (UAV) remote sensing is a new alternative to traditional diagnosis and detection of rice diseases by visual symptoms, providing quick, accurate and large coverage disease detection. UAV remote sensing offers an unprecedented spectral, spatial, and temporal resolution that can distinguish diseased plant tissue from healthy tissue based on the characteristics of disease symptoms. Research has been conducted on using RGB sensor, multispectral sensor, and hyperspectral sensor for successful detection and quantification of sheath blight (Rhizoctonia solani), using multispectral sensor to accurately detect narrow brown leaf spot (Cercospora janseana), and using infrared thermal sensor for detecting the occurrence of rice blast (Magnaporthe oryzae). UAV can also be used for aerial application, and UAV spraying has become a new means for control of rice sheath blight and other crop diseases in many countries, especially China and Japan. UAV spraying can operate at low altitudes and various speeds, making it suitable for situations where arial and ground applications are unavailable or infeasible and where precision applications are needed. Along with advances in digitalization and artificial intelligence for precision application across fertilizer, pest and crop management needs, this UAV technology will become a core tool in a farmer’s precision equipment mix in the future.

show abstract

Remote Sensing of Occurrence Place of Rice Blast Disease by Infrared Thermal Image.

Cited by 10 publications

References 2 publications

Detection of rice sheath blight for in-season disease management using multispectral remote sensing

Detection of rice sheath blight for in-season disease management using multispectral remote sensing

Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer

UAV Remote Sensing: An Innovative Tool for Detection and Management of Rice Diseases

Contact Info

Product

Resources

About