IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v22y2020i3d10.1007_s10668-019-00308-5.html
   My bibliography  Save this article

A comparison of different tillage systems in irrigated conditions by risk and gross margin analysis in Erzurum region of Turkey

Author

Listed:
  • Okan Demir

    (Atatürk University)

  • Zinnur Gözübüyük

    (Directorate of Eastern Anatolia Agricultural Research)

Abstract

The potential of tillage systems for generating environmental pollution and the economic risks of the systems are influential factors for farmers to adopt conservation tillage practices. This study was carried out between 2000 and 2008 in order to evaluate the economic and risk of different tillage and planting systems in the province of Erzurum, Turkey. Tillage treatments consist of conventional tillage [moldboard plow + disk harrow + combined harrows + precision seeder, (CT)], reduced tillage 1 [cultivator + combined harrows + precision seeder, (RT1)], reduced tillage 2 [rotary power harrow + precision seeder, (RT2)] and no-till seeding [no-till seeder, (NT)] systems which were studied. A trial field has been tilled with four different tillage systems with a crop rotation of common vetch–winter wheat–sunflower. The economic evaluation of the tillage and planting systems was made by calculating the gross margin and the risk appraisal and the standard deviation of the yield and gross margins. The conventional tillage system required the most labor, fuel, oil and variable costs. According to conventional tillage and planting system, the most cost-saving system is direct planting by NT. The highest pollutant in terms of environment was the CT system with the highest carbon dioxide release, while the NT system was the most environmentally friendly system. The order of systems from high to low, in terms of obtained gross margin, ranked a CT, RT1, RT2 and NT. The lowest variation in terms of productivity was in the NT system for all products, and the highest variation was in the RT1 system. In terms of gross margin, the lowest variation was again in the NT system. A farmer who decides on the basis of gross margin should choose the CT system with the highest average gross margin. A producer considering gross margin should decide on the NT system based on risk assessment.

Suggested Citation

  • Okan Demir & Zinnur Gözübüyük, 2020. "A comparison of different tillage systems in irrigated conditions by risk and gross margin analysis in Erzurum region of Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(3), pages 2529-2544, March.
  • Handle: RePEc:spr:endesu:v:22:y:2020:i:3:d:10.1007_s10668-019-00308-5
    DOI: 10.1007/s10668-019-00308-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-019-00308-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-019-00308-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Richard E. Just & Rulon D. Pope, 1979. "Production Function Estimation and Related Risk Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 276-284.
    2. David J. Pannell, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, International Association of Agricultural Economists, vol. 5(4), pages 361-383, August.
    3. Konyar, Kazim, 2001. "Assessing the role of US agriculture in reducing greenhouse gas emissions and generating additional environmental benefits," Ecological Economics, Elsevier, vol. 38(1), pages 85-103, July.
    4. Bacenetti, Jacopo & Restuccia, Andrea & Schillaci, Gianpaolo & Failla, Sabina, 2017. "Biodiesel production from unconventional oilseed crops (Linum usitatissimum L. and Camelina sativa L.) in Mediterranean conditions: Environmental sustainability assessment," Renewable Energy, Elsevier, vol. 112(C), pages 444-456.
    5. Wu, Huijun & Yuan, Zengwei & Geng, Yong & Ren, Jingzheng & Jiang, Songyan & Sheng, Hu & Gao, Liangmin, 2017. "Temporal trends and spatial patterns of energy use efficiency and greenhouse gas emissions in crop production of Anhui Province, China," Energy, Elsevier, vol. 133(C), pages 955-968.
    Full references (including those not matched with items on IDEAS)

    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. Hasibuan, Abdul Muis & Gregg, Daniel & Stringer, Randy, 2022. "Risk preferences, intra-household dynamics and spatial effects on chemical inputs use: Case of small-scale citrus farmers in Indonesia," Land Use Policy, Elsevier, vol. 122(C).
    2. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    3. Nolan, Elizabeth & Santos, Paulo, 2012. "Insurance premiums and GM traits," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125942, International Association of Agricultural Economists.
    4. J. K. Horowitz & E. Lichtenberg, 1994. "Risk‐Reducing And Risk‐Increasing Effects Of Pesticides," Journal of Agricultural Economics, Wiley Blackwell, vol. 45(1), pages 82-89, January.
    5. Bontemps, Christophe & Bougherara, Douadia & Nauges, Céline, 2020. "Do Risk Preferences Really Matter? The Case of Pesticide Use in Agriculture," TSE Working Papers 20-1095, Toulouse School of Economics (TSE).
    6. Luigi Tedone & Francesco Giannico & Vincenzo Tufarelli & Vito Laudadio & Maria Selvaggi & Giuseppe De Mastro & Maria Antonietta Colonna, 2022. "Camelina sativa (L. Crantz) Fresh Forage Productive Performance and Quality at Different Vegetative Stages: Effects of Dietary Supplementation in Ionica Goats on Milk Quality," Agriculture, MDPI, vol. 12(1), pages 1-17, January.
    7. Francis Tsiboe & Jesse Tack, 2022. "Utilizing Topographic and Soil Features to Improve Rating for Farm‐Level Insurance Products," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 52-69, January.
    8. Mingyue Li & Jingjing Wang & Kai Chen & Lianbei Wu, 2020. "Willingness and Behaviors of Farmers’ Green Disposal of Pesticide Packaging Waste in Henan, China: A Perceived Value Formation Mechanism Perspective," IJERPH, MDPI, vol. 17(11), pages 1-18, May.
    9. 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.
    10. Chiwaula, Levison & Waibel, Hermann, 2011. "Does seasonal vulnerability to poverty matter? A case study from the Hadejia-Nguru Wetlands in Nigeria," Proceedings of the German Development Economics Conference, Berlin 2011 19, Verein für Socialpolitik, Research Committee Development Economics.
    11. Kawasaki, Kentaro, 2010. "The costs and benefits of land fragmentation of rice farms in Japan," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 1-18.
    12. Zhen, Wei & Qin, Quande & Wei, Yi-Ming, 2017. "Spatio-temporal patterns of energy consumption-related GHG emissions in China's crop production systems," Energy Policy, Elsevier, vol. 104(C), pages 274-284.
    13. Muhammad Rizwan & Ping Qing & Abdul Saboor & Muhammad Amjed Iqbal & Adnan Nazir, 2020. "Production Risk and Competency among Categorized Rice Peasants: Cross-Sectional Evidence from an Emerging Country," Sustainability, MDPI, vol. 12(9), pages 1-15, May.
    14. Marzieh Ronaghi & Michael Reed & Sayed Saghaian, 2020. "The impact of economic factors and governance on greenhouse gas emission," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 22(2), pages 153-172, April.
    15. Francisco J. André & Laura Riesgo, 2006. "A Duality Procedure to Elicit Nonlinear Multiattribute Utility Functions," Working Papers 06.02, Universidad Pablo de Olavide, Department of Economics.
    16. Samira Shayanmehr & Shida Rastegari Henneberry & Mahmood Sabouhi Sabouni & Naser Shahnoushi Foroushani, 2020. "Climate Change and Sustainability of Crop Yield in Dry Regions Food Insecurity," Sustainability, MDPI, vol. 12(23), pages 1-24, November.
    17. Zhen, Wei & Qin, Quande & Miao, Lu, 2023. "The greenhouse gas rebound effect from increased energy efficiency across China's staple crops," Energy Policy, Elsevier, vol. 173(C).
    18. Just, Richard E. & Rausser, Gordon C. & Zilberman, David D., 1993. "A framework for analyzing specific agricultural policy reform," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5sv4s9m4, Department of Agricultural & Resource Economics, UC Berkeley.
    19. Kishor, Nalin M., 1992. "Pesticide externalities, comparative advantage, and commodity trade : cotton in Andhra Pradesh, India," Policy Research Working Paper Series 928, The World Bank.
    20. Yesuf, Mahmud & Kassie, Menale & Köhlin, Gunnar, 2009. "Risk Implications of Farm Technology Adoption in the Ethiopian Highlands," Working Papers in Economics 404, University of Gothenburg, Department of Economics.

    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:spr:endesu:v:22:y:2020:i:3:d:10.1007_s10668-019-00308-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.