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The next generation models for crops and agro-ecosystems

查看全文 作  者:ZHU [1,2]XinGuang;ZHANG [1]GuiLian;THOLEN [1]Danny;WANG [1]Yu;XIN [1]ChangPeng;SONG [1]QingFeng 高影响力作者 机构地区:[1]Plant Systems Biology Group, CAS-MPG Partner Institute and Key Laboratory for Computational Biology~ Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China;[2]Institute of Plant Physiology and Ecology, Shanghai institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China高影响力机构 出  处:《Science China(Information Sciences)》索引2011年第54卷第3期,共9页高影响力期刊 基  金:supported by the National Natural Science Foundation of China (Grant No. 30970213);the Young Talent Frontier Program of Shanghai Institutes for Biology Sciences/Chinese Academy of Sciences (Grant No. 09Y1C11501) 摘  要:Growth in population, decrease in arable land area, and change in climate are endangering our food security. Precision agriculture has the potential to increase crop productivity thorough tailored agricultural practices for different growing areas. Many models of crops and agro-ecosystems capable of predicting interaction between plants and environments have been developed for precision agriculture. Currently, there are several representative categories of crop and agro-ecosystem models, including the de Wit school models, the DSSAT series models and the APSIM series models, which have contributed substantially to improvement of agricultural practices. However, these models are weak in predicting performances of crops under environmental and genetic perturbations are generally weak, which severely limits the application of these models in guiding precision agriculture. We need to develop the next generation crop and agro-ecosystems models with a high level of mechanistic basis, which can be integrated with high throughput data and can predict the heterogeneity of environmental factors inside canopy and dynamic canopy photosynthesis. In developing such a model close collaboration is inevitably required among scientists from different disciplines. The successful development and application of such models will undoubtedly advance precision agriculture through providing better agronomical practices tailored for different growing environments. These models will also form a basis to identify breeding targets for increased productivity at given location with given soil and climatic conditions. 关 键 词:农业生态系统模式 农作物 车型 生态系统模型 作物生产率 预测能力 环境因子 精准农业
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