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http://dx.doi.org/10.7745/KJSSF.2011.44.5.779

Estimation of Nitrogen Uptake and Biomass of Rice (Oryza sativa L.) Using Ground-based Remote Sensing Techniques  

Gong, Hyo-Young (Department of Environmental & Biological Chemistry, Chungbuk National University)
Kang, Seong-Soo (National Academy of Agricultural Science, RDA)
Hong, Soon-Dal (Department of Environmental & Biological Chemistry, Chungbuk National University)
Publication Information
Korean Journal of Soil Science and Fertilizer / v.44, no.5, 2011 , pp. 779-787 More about this Journal
Abstract
This study was conducted to evaluate the usefulness of ground-based remote sensing for the estimation of rice yield and application rate of N-fertilizer during growing season. Dongjin-1, Korean cultivar of rice was planted on May 30, 2006 and harvested on October 9, 2006. Chlorophyll content and LAI (leaf area index) were measured using Minolta SPAD-502 and AccuPAR model LP-80, respectively. Reflectance indices were determined with passive sensors using sunlight and four types of active sensors using modulated light, respectively. Reflectance indices and growth rate were measured three times from 29 days to 87 days after rice plating and at harvesting day. The result showed that values of growing characteristics and reflectance indices were highly correlated. Growing characteristics to show significant correlation with reflectance indices were in order of followings: fresh weight > N uptake > dry weight > height > No. of tiller > N content. Chlorophyll contents measured by chlorophyll meter (SPAD 502) showed high correlation with nitrogen concentration (r=$0.743^{**}$), although the correlation coefficients between remote sensing data and nitrogen concentration were higher. LAI was highly correlated with dry weight (r=$0.931^{**}$), but relationship between LAI and nitrogen concentration (r=$0.505^*$) was relatively low. The data of CC-passive sensor were negatively correlated with those of the near-infrared. NDVI correlation coefficients found more useful to identify the growth characteristics rather than data from single wavelength. Both passive sensor and active sensor were highly significantly correlated with growth characteristics. Consequently, quantifying the growth characteristics using reflectance indices of ground-based remote sensing could be a useful tool to determine the application rate of N fertilizer non-destructively and in real-time.
Keywords
Biomass; Ground-based remote sensor; NDVI; Nitrogen uptake; Rice;
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