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Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery

Author

Listed:
  • Efthymios Rodias

    (Department of Agriculture, Forestry and Food Science (DISAFA), Faculty of Agriculture, University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy)

  • Remigio Berruto

    (Department of Agriculture, Forestry and Food Science (DISAFA), Faculty of Agriculture, University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy)

  • Patrizia Busato

    (Department of Agriculture, Forestry and Food Science (DISAFA), Faculty of Agriculture, University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy)

  • Dionysis Bochtis

    (Institute for Bio-economy and Agri-Technology (IBO), Centre for Research & Technology—Hellas (CERTH), 57001 Thessaloniki, Greece
    Department of Engineering, Faculty Science and Technology, Aarhus University, 8000 Aarhus, Denmark)

  • Claus Grøn Sørensen

    (Department of Engineering, Faculty Science and Technology, Aarhus University, 8000 Aarhus, Denmark)

  • Kun Zhou

    (Department of Engineering, Faculty Science and Technology, Aarhus University, 8000 Aarhus, Denmark)

Abstract

Various types of sensors technologies, such as machine vision and global positioning system (GPS) have been implemented in navigation of agricultural vehicles. Automated navigation systems have proved the potential for the execution of optimised route plans for field area coverage. This paper presents an assessment of the reduction of the energy requirements derived from the implementation of optimised field area coverage planning. The assessment regards the analysis of the energy requirements and the comparison between the non-optimised and optimised plans for field area coverage in the whole sequence of operations required in two different cropping systems: Miscanthus and Switchgrass production. An algorithmic approach for the simulation of the executed field operations by following both non-optimised and optimised field-work patterns was developed. As a result, the corresponding time requirements were estimated as the basis of the subsequent energy cost analysis. Based on the results, the optimised routes reduce the fuel energy consumption up to 8%, the embodied energy consumption up to 7%, and the total energy consumption from 3% up to 8%.

Suggested Citation

  • Efthymios Rodias & Remigio Berruto & Patrizia Busato & Dionysis Bochtis & Claus Grøn Sørensen & Kun Zhou, 2017. "Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery," Sustainability, MDPI, vol. 9(11), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:11:p:1956-:d:116624
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    References listed on IDEAS

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    1. Alessandro Sopegno & Efthymios Rodias & Dionysis Bochtis & Patrizia Busato & Remigio Berruto & Valter Boero & Claus Sørensen, 2016. "Model for Energy Analysis of Miscanthus Production and Transportation," Energies, MDPI, vol. 9(6), pages 1-16, May.
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    3. Efthymios Rodias & Remigio Berruto & Dionysis Bochtis & Patrizia Busato & Alessandro Sopegno, 2017. "A Computational Tool for Comparative Energy Cost Analysis of Multiple-Crop Production Systems," Energies, MDPI, vol. 10(7), pages 1-15, June.
    4. Läpple, Doris & Renwick, Alan & Thorne, Fiona, 2015. "Measuring and understanding the drivers of agricultural innovation: Evidence from Ireland," Food Policy, Elsevier, vol. 51(C), pages 1-8.
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    Cited by:

    1. Efthymios Rodias & Remigio Berruto & Dionysis Bochtis & Alessandro Sopegno & Patrizia Busato, 2019. "Green, Yellow, and Woody Biomass Supply-Chain Management: A Review," Energies, MDPI, vol. 12(15), pages 1-22, August.
    2. Charisios Achillas & Dionysis Bochtis, 2020. "Toward a Green, Closed-Loop, Circular Bioeconomy: Boosting the Performance Efficiency of Circular Business Models," Sustainability, MDPI, vol. 12(23), pages 1-6, December.
    3. Caicong Wu & Zhibo Chen & Dongxu Wang & Bingbing Song & Yajie Liang & Lili Yang & Dionysis D. Bochtis, 2020. "A Cloud-Based In-Field Fleet Coordination System for Multiple Operations," Energies, MDPI, vol. 13(4), pages 1-15, February.
    4. Li-Chun Huang & Yu-Hui Chen & Ya-Hui Chen & Chi-Fang Wang & Ming-Che Hu, 2018. "Food-Energy Interactive Tradeoff Analysis of Sustainable Urban Plant Factory Production Systems," Sustainability, MDPI, vol. 10(2), pages 1-12, February.
    5. Charisios Achillas & Dionysis Bochtis, 2021. "Supply Chain Management for Bioenergy and Bioresources: Bridging the Gap between Theory and Practice," Energies, MDPI, vol. 14(19), pages 1-4, September.

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