The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues |
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| Institution: | 1. School of Information Engineering, China University of Geosciences, 29 Xueyuan Road, Beijing 100083, China;2. School of Geography Science, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China;1. Università degli Studi di Milano, DiSAA, Cassandra lab, via Celoria 2, 20133 Milan, Italy;2. Università degli Studi di Milano, DESP, Cassandra lab, via Celoria 2, 20133 Milan, Italy;3. CREA, Research Centre for Agriculture and Environment, via di Corticella 133, 40128 Bologna, Italy;4. UREP, INRA, 63000 Clermont-Ferrand, France;1. Centre de Recherche Public – Gabriel Lippmann (CRP-GL), Environment and Agro-biotechnologies Department (EVA), 41, rue du Brill, L-4422 Belvaux, Luxembourg;2. Trier University, Department of Environmental Remote Sensing and Geoinformatics, D-54286 Trier, Germany;3. Julius Kühn-Institut (JKI), Institute for Crop and Soil Science, Bundesallee 50, D-38116 Braunschweig, Germany;1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;2. Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China;3. Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA;4. United States Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, Stoneville, MS 38776, USA;5. State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China;6. Department of Geography, College of Geosciences, Texas A&M University, College Station, TX 77843, USA;7. National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China;8. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;1. Università degli Studi di Milano, DiSAA, Cassandra lab, via Celoria 2, I-20133 Milan, Italy;2. Agricola 2000 S.C.p.A., via Trieste 9, I-20067 Tribiano, Italy;3. Università degli Studi di Milano, DiSAA, via Celoria 2, I-20133 Milan, Italy;4. Università degli Studi di Milano, DEMM, Cassandra lab, via Celoria 2, I-20133 Milan, Italy;1. Key Laboratory for Meteorological Disaster Prevention and Mitigation of Shandong, Jinan 250031, Shandong, China;2. Shandong Provincial Climate Center, Jinan 250031, Shandong, China;3. School of Atmospheric Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China;4. College of Resources and Environmental Science, China Agricultural University, Beijing 100193, China;5. National Meteorological Center, Beijing 100081, China;6. CMA-CAU Jointly Laboratory of Agriculture Addressing Climate Change (LACC/CMA-CAU), China;1. State Key Laboratory of Water Resources and Hydropower Engineering Sciences, Wuhan University, Wuhan, Hubei, 430072, China;2. Guangxi Hydraulic Research Institute, Nanning, Guangxi, 530023, China |
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| Abstract: | The accurate detection of heavy metal-induced stress on crop growth is important for food security and agricultural, ecological and environmental protection. Spectral sensing offers an efficient and undamaged observation tool to monitor soil and vegetation contamination. This study proposed a methodology for dynamically estimating the total cadmium (Cd) accumulation in rice tissues by assimilating spectral information into WOFOST (World Food Study) model. Based on the differences among ground hyperspectral data of rice in three experiments fields under different Cd concentration levels, the spectral indices MCARI1, NREP and RH were selected to reflect the rice stress condition and dry matter production of rice. With assimilating these sensitive spectral indices into the WOFOST + PROSPECT + SAIL model to optimize the Cd pollution stress factor fwi, the dynamic dry matter production processes of rice were adjusted. Based on the relation between dry matter production and Cd accumulation, we dynamically simulating the Cd accumulation in rice tissues. The results showed that the method performed well in dynamically estimating the total amount of Cd accumulation in rice tissues with R2 over 85%. This study suggests that the proposed method of integrating the spectral information and the crop growth model could successfully dynamically simulate the Cd accumulation in rice tissues. |
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| Keywords: | Spectral information Crop growth model Assimilation Cadmium accumulation Dynamic simulation |
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