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Agronomy Journal, 2001
During the last two decades, computer simulation models have become powerful tools for investigating agricultural crop dynamics and solving practical problems. Many models have been developed in various countries, which permits exploration of the influence of weather conditions and agricultural strategies on the fate of a crop.
Ratmir A. Poluektov, Alexandre G. Topaj
semanticscholar +4 more sources
During the last two decades, computer simulation models have become powerful tools for investigating agricultural crop dynamics and solving practical problems. Many models have been developed in various countries, which permits exploration of the influence of weather conditions and agricultural strategies on the fate of a crop.
Ratmir A. Poluektov, Alexandre G. Topaj
semanticscholar +4 more sources
Building crop models within different crop modelling frameworks
Agricultural Systems, 2012Modular frameworks for crop modelling have evolved through simultaneous progress in crop science and software development but differences among these frameworks exist which are not well understood, resulting in potential misuse for crop modelling. In this paper we review differences and similarities among different developed frameworks and identify ...
Adam, Myriam +5 more
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Journal of Advances in Modeling Earth Systems, 2020
Representing climate‐crop interactions is critical to Earth system modeling. Despite recent progress in modeling dynamic crop growth and irrigation in land surface models (LSMs), transitioning these models from field to regional scales is still ...
Zhe Zhang +7 more
semanticscholar +1 more source
Representing climate‐crop interactions is critical to Earth system modeling. Despite recent progress in modeling dynamic crop growth and irrigation in land surface models (LSMs), transitioning these models from field to regional scales is still ...
Zhe Zhang +7 more
semanticscholar +1 more source
MODELLING FOR CROP GROWTH CONTROL
Acta Horticulturae, 1989In relation to the control of crop growth it is necessary to consider the aspect of time constants. Some growth characteristics, such as photosynthesis and transpiration have a rapid response to control actions, whereas other characteristics, such as development and morphogenesis show a much slower response.
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Soil data for crop-soil models
1993Systems approaches for agricultural development can be realized at different levels of detail which are associated with different data needs. For soils five levels were defined, ranging from farmer’s knowledge and expert systems to use of complex simulation models.
Bouma, J. +3 more
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The DSSAT crop modeling ecosystem
Advances in crop modelling for a sustainable agriculture, 2019Gerrit Hoogenboom +2 more
semanticscholar +2 more sources
2002
Summary: Crop growth and yield is influenced by various factors in an implicit manner. The seed characteristics and climatological parameters make effective contributions during germination, crop development and final grain yield. A mathematical model for crop development and yield is constructed and different control strategies are discussed.
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Summary: Crop growth and yield is influenced by various factors in an implicit manner. The seed characteristics and climatological parameters make effective contributions during germination, crop development and final grain yield. A mathematical model for crop development and yield is constructed and different control strategies are discussed.
openaire +1 more source
2017
In agro-meteorological research, the crop models basically help in testing scientific hypothesis, highlight where information is missing, organizing data and integrating across disciplines. The crop growth models can be used to predict crop performance in regions where the crop has not been grown before or not grown under optimal conditions.
Latief Ahmad +3 more
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In agro-meteorological research, the crop models basically help in testing scientific hypothesis, highlight where information is missing, organizing data and integrating across disciplines. The crop growth models can be used to predict crop performance in regions where the crop has not been grown before or not grown under optimal conditions.
Latief Ahmad +3 more
openaire +1 more source