01-02-2015, 03:21 AM
application of mathematics in agriculture
Name: Hina Patel
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application of mathematics in agriculture ppt
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application of mathematics in agriculture
Name: Hina Patel
09-03-2017, 11:56 AM
Modeling techniques applied to agriculture can be useful for defining research priorities and understanding the basic interactions of the soil-plant-atmosphere system. Using a model to estimate the importance and effect of certain parameters, a researcher may note which factors may be most useful. The modeler must define his objectives before starting his work and build a model that meets the proposed objectives.
As agriculture becomes more intensive, the demand for a greater level of control of the environment in which plants grow grows. This control ranges from better soil management strategies to "closed" environments, where most, if not all, atmospheric and soil variables can be adjusted. Based on this premise, plant growth and development models should be developed to provide a basis for agricultural production planning and management. Crop modeling can also be useful as a means to help the scientist define research priorities. Using a model to estimate the importance and effect of certain parameters, the researcher can see which factors should be further studied in future research, thus increasing the understanding of the system. The model also has the potential to help understand the basic interactions in the soil-plant-atmosphere system.
The adoption of mathematics in economic analysis brings a high level of precision to the analysis; The assumptions are clearly established, procedures are specified and the logical consistency of mathematically based models is (often) easier to verify than non-mathematical models. On the other hand, by reducing the problems to a manageable formulation, have we eliminated the real character of the problems? The possible answers to this last question can vary from
(1) not even try to reduce or limit the current problem by developing a mathematical model to
(2) we need to develop even more sophisticated mathematical models! The role of mathematics in student training has recently received attention in the published results of the Graduate Education Commission in Economics. As a discipline driven by real-world issues, legitimate concerns have arisen as to the practical relevance of the economy, as presented in the classroom and in magazines. Important issues to be addressed include: Is postgraduate training in agricultural economics a discipline distinct from undergraduate? Does this training emphasize technique on the analysis of economic issues? As a result, the graduates are not so widely trained? The challenge for instructors and students is to distinguish between teaching tools (eg, problem solving techniques, knowledge of theorems and concepts) and demonstrate the uses of mathematics in economic analysis by focusing on the skills of logic and modeling
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