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http://dx.doi.org/10.5532/KJAFM.2020.22.4.340

Processing and Quality Control of Big Data from Korean SPAR (Soil-Plant-Atmosphere-Research) System  

Sang, Wan-Gyu (National Institute of Crop Science, Rural Development Administration)
Kim, Jun-Hwan (National Institute of Crop Science, Rural Development Administration)
Shin, Pyong (National Institute of Crop Science, Rural Development Administration)
Baek, Jae-Kyeong (National Institute of Crop Science, Rural Development Administration)
Seo, Myung-Chul (National Institute of Crop Science, Rural Development Administration)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.22, no.4, 2020 , pp. 340-345 More about this Journal
Abstract
In this study, we developed the quality control and assurance method of measurement data of SPAR (Soil-Plant-Atmosphere-Research) system, a climate change research facility, for the first time. It was found that the precise processing of CO2 flux data among many observations were sig nificantly important to increase the accuracy of canopy photosynthesis measurements in the SPAR system. The collected raw CO2 flux data should first be removed error and missing data and then replaced with estimated data according to photosynthetic lig ht response curve model. Comparing the correlation between cumulative net assimilation and soybean biomass, the quality control and assurance of the raw CO2 flux data showed an improved effect on canopy photosynthesis evaluation by increasing the coefficient of determination (R2) and lowering the root mean square error (RMSE). These data processing methods are expected to be usefully applied to the development of crop growth model using SPAR system.
Keywords
Quality control; $CO_2$ flux; SPAR system;
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Times Cited By KSCI : 4  (Citation Analysis)
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