Integrating animals, pasture, and crops within AusFarm for modelling mixed farming
Mixed enterprise farming systems that integrate more than one production system are important in agricultural production world-wide. Understanding and improving them can be made easier by modelling them with software tools. Modelling mixed enterprise farming systems can be a complex task as the inte...
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Published in | Environmental modelling & software : with environment data news Vol. 179; p. 106115 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.08.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Mixed enterprise farming systems that integrate more than one production system are important in agricultural production world-wide. Understanding and improving them can be made easier by modelling them with software tools. Modelling mixed enterprise farming systems can be a complex task as the interaction between the enterprises will introduce many dependencies. There are many software tools available that can model single enterprise systems, while there are few with the ability to model the biophysical systems in mixed farming. AusFarm has been designed and used to model mixed enterprise farming systems, integrating livestock, pasture, and crop models in one software tool and allowing flexible management of the whole farm. This paper demonstrates some key techniques that have been used for building and simulating mixed enterprise Australian farm systems in AusFarm. Examples of how to structure a cropping system and a livestock system are given. Key livestock and crop management tasks are implemented using flexible management rules.
•Component based modelling in AusFarm can represent many types of mixed farming systems.•AusFarm's flexible management allows modelling of many types of farming practices.•Multi-dimensional experiments can be constructed using AusFarm for examining comparable scenarios.•AusFarm is designed to encapsulate a workflow for building, testing and analysing farming systems. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2024.106115 |