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• W1997731662 abstract "Soil organic carbon (SOC) management is urgently required to satisfy the demand for precision agriculture and soil C monitoring since SOC content has great important influence on soil parameters and crop productions. This research is aimed to develop the simple and low cost monitoring methods to determine the SOC pools using hyper spectral camera in Andisol. In this research, soil samples were taken at different soil management practices including cover crop residue incorporation and tillage system which located in Field Science Research and Education Center of Ibaraki University, Ami, Ibaraki, Japan(36o01'N 140o21'E). Partial least square regression (PLSR) with cross-validation was used to calibrate the spectral data. The research estimated the potential of SOC qualitative analysis using visible (VIS) (400nm-1000nm) spectral-graphs, near infrared (NIR) (900nm- 1700nm) spectral-graphs and combination of these two spectral-graphs. Results showed that model assessment accuracy by V10 (360nm-1010nm) spectrograph is higher than by N17E (900nm-1700nm) spectrograph. In addition, combined these two spectrographs increased the model prediction accuracy. Evaluation index (EI) test was employed in this research, and the research showed that prediction is acceptable to use of practical to predict SOC content." @default.
• W1997731662 created "2016-06-24" @default.
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• W1997731662 date "2012-12-30" @default.
• W1997731662 modified "2023-09-27" @default.
• W1997731662 title "Assessing Soil Organic Carbon Using Portable Hyper-spectral Camera in Andisols" @default.
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• W1997731662 doi "https://doi.org/10.14511/jasa.2012.010407" @default.
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