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Crop Growth Modeling: A Review

P Thimme Gowda, Sunil A Satyareddi, and SB Manjunath

Crop/soil simulation models basically applied in three sections (1) tools for research, (2) tools for decision-making, and (3) tools for education, training and technology-transfer. The greatest use of crop/soil models so far has been by the research community, as models are primarily tools for organizing knowledge gained in experimentation. However, there is an urgent need to make the use of models in research more relevant to problems in the real world, and find effective means of dissemination of results from work using models to potential beneficiaries. Nevertheless, crop models can be used for a wide range of applications. As research tools, model development and application can contribute to identify gaps in our knowledge, thus enabling more efficient and targeted research planning. Models that are based on sound physiological data are capable of supporting extrapolation to alternative cropping cycles and locations, thus permitting the quantification of temporal and spatial variability. Over a relatively short time span and at comparatively low costs, the modeler can investigate a large number of management strategies that would not be possible using traditional methodologies. Despite some limitations, the modelling approach remains the best means of assessing the effects of future global climate change, thus helping in the formulation of national policies for mitigation purposes. Other policy issues, like yield forecasting, industry planning, operations management, consequences of management decisions on environmental issues, are also well supported by modelling. Models are not simple mechanisms to archive and synthesize information for producing forecasts. Modelling represents a better way of synthesizing knowledge about different components of a system, summarizing data, and transferring research results to users.

索引于

化学文摘社 (CAS)
哥白尼索引
打开 J 门
学术钥匙
研究圣经
引用因子
宇宙IF
电子期刊图书馆
参考搜索
哈姆达大学
欧洲农业信息技术联合会 (EFITA)
印度科学网
学者指导
国际创新期刊影响因子(IIJIF)
国际组织研究所 (I2OR)
宇宙
秘密搜索引擎实验室
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