Studies on Rice Yield and Quality Estimated by Remote Sensing Techniques
Date Issued
2012
Date
2012
Author(s)
Yang, Zhi-Wei
Abstract
We examined the contents of chlorophyll (Chl), biosynthetic intermediates (protoporphyrin IX, PPIX; magnesium protoporphyrin IX, MGPP; protochlorophyllide, Pchlide), degradative intermediates (chlorophyllide, Chlide; pheophytin, Phe; pheophorbide, Pho), and carotenoid in the leaves of rice with five different types of chlorophyll b-deficient or -lacking mutant during their growth and development. The levels of less polar (LP) intermediates such as Chl, Phe and LP Car decreased with increasing growth stage, while the levels of more polar (MP) intermediates such as porphyrins (PPIX, MGPP, Pchlide), Chlide and MP Car were also decreased. The biosynthetic and degradative rate of Chl in rice variety Norin No. 8 was higher than rice mutant type due to smaller amounts of Chl, intermediates and Car. Chl→Phe→Pho was the major route of Chl degradation at vegetative stage in five rice, while Chl→Chlide→Pho was the minor route. When leaves were aging and senescent, Chl→Chlide→Pho was the major route and Chl→Phe→Pho became the minor route of Chl degradation.
The reflectance spectra of five rice leaves were recorded. By using of reflectance spectra, vegetation indices were calculated to remotely estimate the pigment content. The signature analysis of reflectance spectra indicated that in the leaves of five rice the maximum sensitivity to pigment concentration was found to be at 705 nm. The minimal sensitivity to pigment concentration coincided with the red absorption maximum of chlorophyll at 675 nm. Therefore, it seemed inappropriate to use this spectral band for pigment estimation. The near-infrared band ranging above 750 nm was not sensitive to pigment concentration, as found for 675 nm. The reflectance at near-infrared band could be used as reference in the calculation of vegetation indices. Vegetation indices calculated using reflectance at 705 nm and 750 nm correlated very well with pigment concentration (correlation R2>0.78). Vegetation indices calculated using broad-band reflectance also correlated well with pigment concentration (correlation R2>0.70). Thus, it appears possible to create indices using reflectance spectra for non-destructive estimation pigment content and monitoring crop growth.
The satellite remote sensing normalization difference vegetation index (NDVI) of rice field at booting stage correlated very well with rice yield and rice quality in first period rice. The developed prediction models for rice yield and taste meter value were: yield (kg/ha) = 8602.2 × NDVI + 2845.3; taste meter value = －30.84 × NDVI＋79.313, r2 = 0.83; taste meter value = －88.737 × NDVI＋79.23, r2 = 0.89. The developed algorithms predicting rice yield and rice quality from satellite remote sensing data were validated in Chutang, Shinwu, Meinong and Yuli in 2007. Results indicated that estimation models were high accuracy.
Subjects
Paddy Rice
Chlorophyll
Carotenoid
Biosynthesis
Degradation Intermediates
Reflectance spectra
Remote sensing
Vegetation indices
Pigments
Nitrogenous fertilizer
Rice yield
Rice quality
Prediction models
Estimation
SDGs
Type
thesis
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