Agricultural Systems Modelling

Cranfield University
In Bedfordshire

Price on request
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Important information

Typology Short course
Location Bedfordshire
  • Short course
  • Bedfordshire
Description

Agriculture occupies about 40% of the world’s land area and over 70% in the UK, hence it has massive human influences on the environment. Agricultural systems are complex, interactive and vitally important to supply our basic needs. Empirical suck it and see real time experiments of farms are doomed. 



Using established models allows farming futures to be analysed, improved and optimised. Taking a systems approach combines mechanistic and economic understanding with approachable mathematics. Alternative outcomes can be investigated without putting today’s farming in jeopardy. Explore with us how to optimise farm resource use with linear programming, use life cycle assessment to compare the environmental impacts of farming systems or use stochastic approaches to control weeds in an optimal way. Examples range from maximising profits to forecasting Europe-wide land use.

Venues

Where and when

Starts Location
On request
Bedfordshire
Cranfield University Cranfield, MK43 0AL, Bedfordshire, England
See map
Starts On request
Location
Bedfordshire
Cranfield University Cranfield, MK43 0AL, Bedfordshire, England
See map

What you'll learn on the course

systems
Farming

Course programme

Course structure The course will last three days, including lectures, practical and group sessions. Practical work includes using Cranfield’s diverse models, e.g. optimising whole farms to maximise profits under legislative or environmental constraints, compare contrasting ruminant production systems, compare approaches to pest control.
What you will learn On successful completion of this short course, student will:

  • Develop skills to analyse systems and identify opportunities
  • Learn to apply models to complex systems, yet extract useable outcomes
  • Gain insights into interactions and quantify the effects
  • Quantify different environmental impacts with mechanistic systems models coupled with life cycle assessment and go beyond trial and error
  • Use and apply unique models from an internationally renowned team.


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