Support vector machine-based open crop model (SBOCM): Case of rice production in China

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2017
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Abstract
Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM) was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used. Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records. This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system. The parameters, methods, error resources, and other factors were analyzed. Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges. It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration. It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.
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su2017supportsaudi Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Su, Ying-xue;Xu, Huan;Yan, Li-jiao;
Journal saudi journal of biological sciences
Year 2017
DOI
DOI not found
URL
http://www.sciencedirect.com/science/article/pii/S1319562X17300335
Keywords
Education Biology (General) Literature (General) Diseases of the circulatory (Cardiovascular) system Immunologic diseases. Allergy social sciences (general) social sciences french literature - italian literature - spanish literature - portuguese literature history of education english language National Center for Biotechnology Information NCBI NLM MEDLINE pubmed abstract nih national institutes of health national library of medicine pmid:28386178 pmc5372395 doi:10.1016/j.sjbs.2017.01.024 ying-xue su huan xu li-jiao yan

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