IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i8p1080-d869459.html
   My bibliography  Save this article

Precision Agriculture Technologies for Crop and Livestock Production in the Czech Republic

Author

Listed:
  • Jaroslav Vrchota

    (Department of Management, Faculty of Economics, University of South Bohemia in Ceske Budejovice, Studentska 13, 370 05 Ceske Budejovice, Czech Republic)

  • Martin Pech

    (Department of Management, Faculty of Economics, University of South Bohemia in Ceske Budejovice, Studentska 13, 370 05 Ceske Budejovice, Czech Republic)

  • Ivona Švepešová

    (Faculty of Economics, University of South Bohemia in Ceske Budejovice, Studentska 13, 370 05 Ceske Budejovice, Czech Republic)

Abstract

Modern technologies are penetrating all fields of human activity, including agriculture, where they significantly affect the quantity and quality of agricultural production. Precision agriculture can be characterised as an effort to improve the results of practical farming, achieving higher profits by exploiting the existing spatial unevenness of soil properties. We aim to evaluate precision agriculture technologies’ practical use in agricultural enterprises in the Czech Republic. The research was based on a questionnaire survey in which 131 farms participated. We validated the hypothesis through a Chi-squared test on the frequency of occurrence of end-use technology. The results showed that precision farming technologies are used more in crop than livestock production. In particular, 58.02% of enterprises use intelligent weather stations, 89.31% use uncrewed vehicles, and 61.83% use navigation and optimisation systems for optimising journeys. These technologies are the most used and closely related to autonomous driving and robotics in agriculture. The results indicate how willing are agricultural enterprises to adopt new technologies. For policy makers, these findings show which precision farming technologies are already implemented. This can make it easier to direct funding towards grants and projects.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:8:p:1080-:d:869459
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/8/1080/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/8/1080/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrey I. Vlasov & Pavel V. Grigoriev & Aleksey I. Krivoshein & Vadim A. Shakhnov & Sergey S. Filin & Vladimir S. Migalin, 2018. "Smart management of technologies: predictive maintenance of industrial equipment using wireless sensor networks," Post-Print hal-02342832, HAL.
    2. Audronė Nakrošienė & Ilona Bučiūnienė & Bernadeta Goštautaitė, 2019. "Working from home: characteristics and outcomes of telework," International Journal of Manpower, Emerald Group Publishing Limited, vol. 40(1), pages 87-101, January.
    3. Vaibhav Bhatnagar & Ramesh C. Poonia & Surendra Sunda, 2019. "State of the Art and Gap Analysis of Precision Agriculture: A Case Study of Indian Farmers," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 10(3), pages 72-92, July.
    4. Maciejczak, Mariusz & Faltmann. Janis, 2018. "Assessing Readiness Levels Of Production Technologies For Sustainable Intensification Of Agriculture," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 12(1-2), June.
    5. 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.
    6. Schimmelpfennig, David, 2016. "Farm Profits and Adoption of Precision Agriculture," Economic Research Report 249773, United States Department of Agriculture, Economic Research Service.
    7. Tulsi P. Kharel & Amanda J. Ashworth & Phillip R. Owens, 2022. "Linking and Sharing Technology: Partnerships for Data Innovations for Management of Agricultural Big Data," Data, MDPI, vol. 7(2), pages 1-11, January.
    8. Muhammad Fahad & Tariq Javid & Hira Beenish & Adnan Ahmed Siddiqui & Ghufran Ahmed, 2021. "Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application," Sustainability, MDPI, vol. 13(17), pages 1-14, August.
    9. Castle, Mike & Lubben, Bradley D. & Luck, Joe, 2015. "Precision Agriculture Usage and Big Agriculture Data," Cornhusker Economics 306898, University of Nebraska-Lincoln, Department of Agricultural Economics.
    10. Chin-Ling Lee & Robert Strong & Kim E. Dooley, 2021. "Analyzing Precision Agriculture Adoption across the Globe: A Systematic Review of Scholarship from 1999–2020," Sustainability, MDPI, vol. 13(18), pages 1-15, September.
    11. Yongxun Zhang & Qingwen Min & Heyao Li & Lulu He & Canqiang Zhang & Lun Yang, 2017. "A Conservation Approach of Globally Important Agricultural Heritage Systems (GIAHS): Improving Traditional Agricultural Patterns and Promoting Scale-Production," Sustainability, MDPI, vol. 9(2), pages 1-12, February.
    12. Späti, Karin & Huber, Robert & Finger, Robert, 2021. "Benefits of Increasing Information Accuracy in Variable Rate Technologies," Ecological Economics, Elsevier, vol. 185(C).
    13. Andrey I. Vlasov & Pavel V. Grigoriev & Aleksey I. Krivoshein & Aleksey I. Krivoshein & Vadim A. Shakhnov & Sergey S. Filin & Sergey S. Filin & Vladimir S. Migalin, 2018. "Smart management of technologies: predictive maintenance of industrial equipment using wireless sensor networks," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(2), pages 489-502, December.
    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. Yeboah, Samuel, 2023. "Unlocking the Potential of Technological Innovations for Sustainable Agriculture in Developing Countries: Enhancing Resource Efficiency and Environmental Sustainability," MPRA Paper 118215, University Library of Munich, Germany, revised 26 Jul 2023.
    2. Yeboah, Samuel, 2023. "Unlocking the Potential of Technological Innovations for Sustainable Agriculture in Developing Countries: Enhancing Resource Efficiency and Environmental Sustainability," MPRA Paper 118216, University Library of Munich, Germany, revised 04 Aug 2023.
    3. Jin Yuan & Wei Ji & Qingchun Feng, 2023. "Robots and Autonomous Machines for Sustainable Agriculture Production," Agriculture, MDPI, vol. 13(7), pages 1-4, July.

    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. Stefania Troiano & Matteo Carzedda & Francesco Marangon, 2023. "Better richer than environmentally friendly? Describing preferences toward and factors affecting precision agriculture adoption in Italy," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-15, December.
    2. Wang, Tong & Jin, Hailong & Sieverding, Heidi & Kumar, Sandeep & Miao, Yuxin & Rao, Xudong & Obembe, Oladipo & Mirzakhani Nafchi, Ali & Redfearn, Daren & Cheye, Stephen, 2023. "Understanding farmer views of precision agriculture profitability in the U.S. Midwest," Ecological Economics, Elsevier, vol. 213(C).
    3. Wadim Strielkowski & Andrey Vlasov & Kirill Selivanov & Konstantin Muraviev & Vadim Shakhnov, 2023. "Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
    4. Silvia Macchia, 2022. "Unbundling the information needs of new-generation agricultural companies," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2 Suppl.), pages 117-141.
    5. Andrey I. Vlasov & Ivan V. Gudoshnikov & Vladimir P. Zhalnin & Aksultan T. Kadyr & Vadim A. Shakhnov, 2020. "Market for memristors and data mining memory structures for promising smart systems," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 98-115, December.
    6. Wang, Tong & Jin, Hailong & Sieverding, Heidi L. & Rao, Xudong & Miao, Yuxin & Kumar, Sandeep & Redfearn, Daren & Nafchi, Ali, 2022. "Understanding farmer perceptions of precision agriculture profitability in the U.S. Midwest," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322502, Agricultural and Applied Economics Association.
    7. Andrey I. Vlasov & Boris V. Artemiev & Kirill V. Selivanov & Kirill S. Mironov & Jasur O. Isroilov, 2022. "Predictive Control Algorithm for A Variable Load Hybrid Power System on the Basis of Power Output Forecast," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 1-7, May.
    8. DeLay, Nathan & Mintert, James & Thompson, Nathanael, 2021. "Farm Data Collection and Software Adoption in Commercial Scale U.S. Corn-Soybean Farms," Western Economics Forum, Western Agricultural Economics Association, vol. 19(2), December.
    9. LoPiccalo, Katherine, 2022. "Impact of broadband penetration on U.S. Farm productivity: A panel approach," Telecommunications Policy, Elsevier, vol. 46(9).
    10. Nathan D. DeLay & Nathanael M. Thompson & James R. Mintert, 2022. "Precision agriculture technology adoption and technical efficiency," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 195-219, February.
    11. Mario Coccia, 2019. "Killer Technologies: the destructive creation in the technical change," Papers 1907.12406, arXiv.org.
    12. 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.
    13. Smith, Craig M. & Dhuyvetter, Kevin C., 2016. "Determining the Economically Optimal Level of Control on Sprayers and Planters," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2016.
    14. Khanna, Madhu, 2021. "Digital Transformation for a Sustainable Agriculture: Opportunities and Challenges," 2021 Conference, August 17-31, 2021, Virtual 315052, International Association of Agricultural Economists.
    15. Hrozencik, Aaron & Aillery, Marcel, 2021. "Trends in U.S. Irrigated Agriculture: Increasing Resilience Under Water Supply Scarcity," Economic Information Bulletin 327359, United States Department of Agriculture, Economic Research Service.
    16. Julian M. Alston & Philip G. Pardey, 2020. "Innovation, Growth, and Structural Change in American Agriculture," NBER Chapters, in: The Role of Innovation and Entrepreneurship in Economic Growth, pages 123-165, National Bureau of Economic Research, Inc.
    17. Paige Seitz & Robert Strong & Steve Hague & Theresa P. Murphrey, 2022. "Evaluating Agricultural Extension Agent’s Sustainable Cotton Land Production Competencies: Subject Matter Discrepancies Restricting Farmers’ Information Adoption," Land, MDPI, vol. 11(11), pages 1-17, November.
    18. Mario Coccia, 2017. "General purpose technologies in dynamic systems: visual representation and analyses of complex drivers," IRCrES Working Paper 201705, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    19. Gabriel Medina & Cassio Pereira & Joice Ferreira & Erika Berenguer & Jos Barlow, 2022. "Searching for Novel Sustainability Initiatives in Amazonia," Sustainability, MDPI, vol. 14(16), pages 1-13, August.
    20. Argento, F. & Liebisch, F. & Anken, T. & Walter, A. & El Benni, N., 2022. "Investigating two solutions to balance revenues and N surplus in Swiss winter wheat," Agricultural Systems, Elsevier, vol. 201(C).

    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:12:y:2022:i:8:p:1080-:d:869459. 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.