AGR203 Production Analysis and Optimisation (8)


The importance of yield and productivity as key contributors to the profitability and sustainability of agricultural production systems is introduced in this subject.  The subject aims to provide students with tools to investigate and analyse the influences of genetic, environmental and management factors on the yield and productivity of crop and livestock systems.  The subject will cover key concepts in the design and analysis of agricultural field experiments and how models can be developed to aid decision-making and optimise production systems.  Students will develop skills in presenting the outputs of experimental and model-based investigations in ways that are meaningful in an agricultural context.   The aims and methods of qualitative research techniques and their use in agricultural settings will also be introduced.

+ Subject Availability Modes and Location

Session 1
InternalWagga Wagga Campus
DistanceWagga Wagga Campus
Continuing students should consult the SAL for current offering details: AGR203
Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration Grading System School:
One sessionHD/FLSchool of Agricultural and Wine Sciences

Assumed Knowledge

Students are expected to undrestand the quantitative concepts as taught in AGS107

Learning Outcomes

Upon successful completion of this subject, students should:
  • Be able to describe the interactions between yield, productivity and profitability, and how these inform decision-making in agriculture at farm and sector levels.
  • Be able to design, analyse and interpret the results of simple and more complex experiments and present the results of statistical analyses in ways that are meaningful in an agricultural context.
  • Be able to demonstrate an understanding of the underlying assumptions and possible faults that could contribute to poorly designed experiments.
  • Be able to demonstrate an understanding of how models of different forms can be developed and used to support decision-making for and optimisation of agricultural production systems.
  • Be able to demonstrate an understanding of the roles and use of qualitative data analysis in agricultural contexts.


The subject will cover the following topics:
  • Measures of yield and productivity in agricultural production systems and their use in analysing farm and industry sector performance.
  • Principles of experimental design in agricultural systems, building from single factor experiments to randomised block, split-plot and factorial experiment designs.
  • The principles underpinning the development of simulation and decision-support tools and the application of selected examples in agricultural production systems.
  • Principles of qualitative data analysis and survey design.
  • The interpretation and presentation of experimental and model-based data in agricultural contexts.


The information contained in the 2016 CSU Handbook was accurate at the date of publication: 06 September 2016. The University reserves the right to vary the information at any time without notice.