The next generation models for crops and agro-ecosystems
The next generation models for crops and agro-ecosystems
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DOI：
10.1007/s11432-011-4197-8
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发表时间：
2011-03
期刊：
影响因子：
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通讯作者：
Xinguang Zhu;Guiliang Zhang;D. Tholen;Yu Wang;Changpeng Xin;Qingfeng Song
中科院分区：
文献类型：
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作者：
Xinguang Zhu;Guiliang Zhang;D. Tholen;Yu Wang;Changpeng Xin;Qingfeng Song
人口增长、耕地面积减少和气候变化正在危及我们的粮食安全。精准农业有潜力通过针对不同种植地区量身定制的农业实践来提高作物生产力。已经为精准农业开发了许多能够预测植物与环境之间相互作用的作物和农业生态系统模型。目前，农作物和农业生态系统模型有几个具有代表性的类别，包括de Wit学校模型、DSSAT系列模型和APSIM系列模型，这些模型为农业实践的改进做出了巨大贡献。然而，这些模型在预测作物在环境和遗传扰动下的表现方面普遍较弱，这严重限制了这些模型在指导精准农业方面的应用。我们需要开发具有高水平机械基础的下一代作物和农业生态系统模型，该模型可以与高通量数据集成，并可以预测冠层内部环境因素的异质性和动态冠层光合作用。在开发这样的模型时，不可避免地需要来自不同学科的科学家之间的密切合作。这些模型的成功开发和应用无疑将通过针对不同生长环境提供更好的农艺实践来推进精准农业。这些模型还将构成确定育种目标的基础，以提高特定地点、特定土壤和气候条件下的生产力。
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.