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Tytuł pozycji:

Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring.

Tytuł :
Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring.
Autorzy :
Krishna, Gopal
Sahoo, Rabi N.
Singh, Prafull
Patra, Himesh
Bajpai, Vaishangi
Das, Bappa
Kumar, Sudhir
Dhandapani, Raju
Vishwakarma, Chandrapal
Pal, Madan
Chinnusamy, V.
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Temat :
THERMOGRAPHY
REMOTE sensing
CROPS
WILD rice
LEAST squares
THERMAL imaging cameras
Źródło :
Geocarto International; Mar2021, Vol. 36 Issue 5, p481-498, 18p
Czasopismo naukowe
Water deficit in crops induces a stress that may ultimately result in low production. Identification of response of genotypes towards water deficit stress is very crucial for plant phenotyping. The study was carried out with the objective to identify the response of different rice genotypes to water deficit stress. Ten rice genotypes were grown each under water deficit stress and well watered or nonstress conditions. Thermal images coupled with visible images were recorded to quantify the stress and response of genotypes towards stress, and relative water content (RWC) synchronized with image acquisition was also measured in the lab for rice leaves. Synced with thermal imaging, Canopy reflectance spectra from same genotype fields were also recorded. For quantification of water deficit stress, Crop Water Stress Index (CWSI) was computed and its mode values were extracted from processed thermal imageries. It was ascertained from observations that APO and Pusa Sugandha-5 genotypes exhibited the highest resistance to the water deficit stress or drought whereas CR-143, MTU-1010, and Pusa Basmati-1 genotypes ascertained the highest sensitiveness to the drought. The study reveals that there is an effectual relationship (R2 = 0.63) between RWC and CWSI. The relationship between canopy reflectance spectra and CWSI was also established through partial least square regression technique. A very efficient relationship (calibration R2 = 0.94 and cross-validation R2 = 0.71) was ascertained and 10 most optimal wavebands related to water deficit stress were evoked from hyperspectral data resampled at 5 nm wavelength gap. The identified ten most optimum wavebands can contribute in the quick detection of water deficit stress in crops. This study positively contributes towards the identification of drought tolerant and drought resistant genotypes of rice and may provide valuable input for the development of drought-tolerant rice genotypes in future. [ABSTRACT FROM AUTHOR]
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