Modelling Energy Use and Fuel Consumption in Wheat Production Using Indirect Factors and Artificial Neural Networks

  • Majeed Safa
  • Sandhya Samarasinghe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)


This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury, New Zealand in the 2007-2008 harvest year. The Artificial Neural Network models (ANNs), after examining more than 140 several direct and indirect parameters, can predict energy use and fuel consumption based on farm conditions, farmers’ social considerations, farm operation, machinery condition and farm inputs, arable farms in Canterbury with an error margin of ±12% (± 2900 MJ/ha) and ±8% (± 5.6 l/ha), respectively.


Modelling Energy consumption Fuel consumption Neural Networks Wheat 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Majeed Safa
    • 1
  • Sandhya Samarasinghe
    • 2
  1. 1.Department of Agricultural Management and Property StudiesLincoln UniversityNew Zealand
  2. 2.Department of Environmental ManagementLincoln UniversityNew Zealand

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