IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v10y2020i6p194-d365695.html
   My bibliography  Save this article

Modelling of Harvesting Machines’ Technical Parameters and Prices

Author

Listed:
  • Tatevik Yezekyan

    (Department of Land, Environment, Agriculture and Forestry, University of Padova, Via dell’Università 16, 35020 Legnaro, Italy)

  • Francesco Marinello

    (Department of Land, Environment, Agriculture and Forestry, University of Padova, Via dell’Università 16, 35020 Legnaro, Italy)

  • Giannantonio Armentano

    (Edizioni L’Informatore Agrario srl, Via Bencivenga-Biondani, 16, 37133 Verona, Italy)

  • Samuele Trestini

    (Department of Land, Environment, Agriculture and Forestry, University of Padova, Via dell’Università 16, 35020 Legnaro, Italy)

  • Luigi Sartori

    (Department of Land, Environment, Agriculture and Forestry, University of Padova, Via dell’Università 16, 35020 Legnaro, Italy)

Abstract

Technical and performance parameters of agricultural machines directly impact the operational efficiency and entire crop production. Sometimes, overestimation of technical and dimensional parameters of harvesting equipment is carried out with the intention of enhancing the operational efficiency, but this approach might turn out to negatively impact productivity due to unbalanced system design, and ultimately lead to financial losses. Therefore, a balanced preliminary estimation of technical parameters of equipment needs to be carried out before investment quantification, especially on the large capital-intensive machinery units, such as harvesting systems. In addition, availability of ready to use, simplified models for the price estimation from input technical parameters would reduce the complexity involved in this latter analysis. The current study is an attempt to provide tools to address these issues. A large dataset of combine and forage harvesters has been analyzed to investigate relevant parameter-to-parameter and parameter-to-price relations. The study of the available data allowed the determination of indicative models for the estimation of machine price, power, weight, tank capacity and working width. A significant correlation between power and price ( R 2 > 0.8) has been observed for two groups of harvesting machines. For combine harvesters, satisfactory correlations were found between power and weight, and power and tank capacity. A regression model for combine harvesters showed a satisfactory behavior at predicting the average working width that can be operated by a given power. On the other hand, for the forage harvesting group, the relation between these quantities has lower values; therefore, for better accuracy of the association, more sophisticated considerations should be incorporated, taking into account other parameters.

Suggested Citation

  • Tatevik Yezekyan & Francesco Marinello & Giannantonio Armentano & Samuele Trestini & Luigi Sartori, 2020. "Modelling of Harvesting Machines’ Technical Parameters and Prices," Agriculture, MDPI, vol. 10(6), pages 1-12, June.
  • Handle: RePEc:gam:jagris:v:10:y:2020:i:6:p:194-:d:365695
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/10/6/194/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/10/6/194/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tatevik Yezekyan & Francesco Marinello & Giannantonio Armentano & Samuele Trestini & Luigi Sartori, 2018. "Definition of Reference Models for Power, Weight, Working Width, and Price for Seeding Machines," Agriculture, MDPI, vol. 8(12), pages 1-13, November.
    2. Cavallo, Eugenio & Ferrari, Ester & Bollani, Luigi & Coccia, Mario, 2014. "Attitudes and behaviour of adopters of technological innovations in agricultural tractors: A case study in Italian agricultural system," Agricultural Systems, Elsevier, vol. 130(C), pages 44-54.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tatevik Yezekyan & Marco Benetti & Giannantonio Armentano & Samuele Trestini & Luigi Sartori & Francesco Marinello, 2021. "Definition of Reference Models for Power, Mass, Working Width, and Price for Tillage Implements," Agriculture, MDPI, vol. 11(3), pages 1-15, February.
    2. Hadi Lalghorbani & Ali Jahan, 2022. "Selection of a Wheat Harvester according to Qualitative and Quantitative Criteria," Sustainability, MDPI, vol. 14(3), pages 1-17, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tatevik Yezekyan & Marco Benetti & Giannantonio Armentano & Samuele Trestini & Luigi Sartori & Francesco Marinello, 2021. "Definition of Reference Models for Power, Mass, Working Width, and Price for Tillage Implements," Agriculture, MDPI, vol. 11(3), pages 1-15, February.
    2. Mario Coccia, 2019. "Killer Technologies: the destructive creation in the technical change," Papers 1907.12406, arXiv.org.
    3. Mario Coccia, 2017. "The relation between typologies of executive and technological performances of nations," IRCrES Working Paper 201701, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    4. Alessia Cogato & Andrea Pezzuolo & Claus Grøn Sørensen & Roberta De Bei & Marco Sozzi & Francesco Marinello, 2020. "A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area," Land, MDPI, vol. 9(11), pages 1-17, November.
    5. Mario Coccia, 2017. "Disruptive technologies and competitive advantage of firms in dynamic markets," IRCrES Working Paper 201704, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    6. Andrea González & Juan Carlos Hallak & Gabriel Scattolo & Andres Tacsir, 2021. "Requisitos técnicos, integración regional y respuestas empresariales: los casos de arándanos y maquinaria agrícola en Argentina," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2021-59, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    7. Davide Facchinetti & Stefano Santoro & Lavinia Eleonora Galli & Domenico Pessina, 2021. "Agricultural Tractor Roll-Over Related Fatalities in Italy: Results from a 12 Years Analysis," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
    8. Giorgia Bagagiolo & Vincenzo Laurendi & Eugenio Cavallo, 2017. "Safety Improvements on Wood Chippers Currently in Use: A Study on Feasibility in the Italian Context," Agriculture, MDPI, vol. 7(12), pages 1-19, December.
    9. Muthini, D., 2018. "Variety Awareness, Nutrition Knowledge and Adoption of Nutritionally Enhanced Crop Varieties: Evidence from Kenya," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277135, International Association of Agricultural Economists.
    10. Coccia, Mario, 2017. "Asymmetric paths of public debts and of general government deficits across countries within and outside the European monetary unification and economic policy of debt dissolution," The Journal of Economic Asymmetries, Elsevier, vol. 15(C), pages 17-31.
    11. Niccolò Pampuro & Federica Caffaro & Eugenio Cavallo, 2018. "Reuse of Animal Manure: A Case Study on Stakeholders’ Perceptions about Pelletized Compost in Northwestern Italy," Sustainability, MDPI, vol. 10(6), pages 1-10, June.
    12. Jaroslav Vrchota & Martin Pech & Ivona Švepešová, 2022. "Precision Agriculture Technologies for Crop and Livestock Production in the Czech Republic," Agriculture, MDPI, vol. 12(8), pages 1-18, July.
    13. Muhammad Usman & Gulnaz Hameed & Abdul Saboor & Lal K. Almas & Muhammad Hanif, 2021. "R&D Innovation Adoption, Climatic Sensitivity, and Absorptive Ability Contribution for Agriculture TFP Growth in Pakistan," Agriculture, MDPI, vol. 11(12), pages 1-18, November.
    14. Mario COCCIA, 2017. "Disruptive firms and industrial change," Journal of Economic and Social Thought, KSP Journals, vol. 4(4), pages 437-450, December.
    15. Niccolò Pampuro & Federica Caffaro & Eugenio Cavallo, 2020. "Farmers’ Attitudes toward On-Farm Adoption of Soil Organic Matter in Piedmont Region, Italy," Agriculture, MDPI, vol. 10(1), pages 1-7, January.
    16. Mario Coccia, 2018. "Socioeconomic driving forces of scientific research," Papers 1806.05028, arXiv.org.
    17. Nikam, Vinayak & Ashok, Arathy & Pal, Suresh, 2022. "Farmers' information needs, access and its impact: Evidence from different cotton producing regions in the Maharashtra state of India," Agricultural Systems, Elsevier, vol. 196(C).
    18. Sabrina Bellochio & Airton Alonço & Gessieli Possebom & Francieli Vargas & Lutiane Pagliarin, 2018. "Use of Safety Components to Avoid Accidents With Agricultural Tractors in Public Roads," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 10(6), pages 217-217, May.
    19. Tatevik Yezekyan & Francesco Marinello & Giannantonio Armentano & Samuele Trestini & Luigi Sartori, 2018. "Definition of Reference Models for Power, Weight, Working Width, and Price for Seeding Machines," Agriculture, MDPI, vol. 8(12), pages 1-13, November.
    20. Hironori Yagi & Tsuneo Hayashi, 2021. "Machinery utilization and management organization in Japanese rice farms: Comparison of single‐family, multifamily, and community farms," Agribusiness, John Wiley & Sons, Ltd., vol. 37(2), pages 393-408, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:10:y:2020:i:6:p:194-:d:365695. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.