IDEAS home Printed from https://ideas.repec.org/a/spr/joiaen/v10y2021i1d10.1186_s13731-021-00189-x.html
   My bibliography  Save this article

A systemic comparative economic approach efficiency of fodder production

Author

Listed:
  • Milyausha Lukyanova

    (Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”)

  • Vitaliy Kovshov

    (Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”)

  • Zariya Zalilova

    (Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”)

  • Vasily Lukyanov

    (Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”)

  • Irek Araslanbaev

    (Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”)

Abstract

The purpose of the study is to determine the optimal volume of fodder and grain-fodder crops of appropriate quality to meet the needs of the livestock industry using a systemic comparative economic approach. For the economic assessment of crops for fodder purposes, a systemic comparative economic approach to their production efficiency has been developed. Accounting was carried out according to the three most important indicators in fodder units: quantitative indicators—productivity per hectare of sowing, qualitative—the content of vegetable protein and cost—the production cost. Oats were taken as the primary culture. Their comparison made it possible to determine economically interrelated partial indices, which are reduced to the index of the systemic comparative economic approach, which contributes to optimizing the structure of the cultivated areas of these crops. This technique allows to determine each forage crop’s location in each farm or region’s conditions, analyzing the real situation and assessing the prospects for the development of production. The optimal structure of sown areas for grain-fodder and fodder crops, focused on the cultivation of high-protein crops, for the enterprises of the Northern forest-steppe zone of the Republic of Bashkortostan is proposed. Due to a change in sown areas’ structure, the gross harvest increases by 8%, digestible protein by 2%, and reduced production costs by 48%.

Suggested Citation

  • Milyausha Lukyanova & Vitaliy Kovshov & Zariya Zalilova & Vasily Lukyanov & Irek Araslanbaev, 2021. "A systemic comparative economic approach efficiency of fodder production," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-17, December.
  • Handle: RePEc:spr:joiaen:v:10:y:2021:i:1:d:10.1186_s13731-021-00189-x
    DOI: 10.1186/s13731-021-00189-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13731-021-00189-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1186/s13731-021-00189-x?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. Vitalii Kovshov & Miliausha Lukianova & Zagir Galin & Niaz Faizov & Oksana Frolova, 2019. "Methodology of Strategic Planning of Socio-Economic Development of the Agricultural Sector of the Region," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 15(3), pages 179-188.
    2. Ledgard, Stewart F. & Wei, Sha & Wang, Xiaoqin & Falconer, Shelley & Zhang, Nannan & Zhang, Xiying & Ma, Lin, 2019. "Nitrogen and carbon footprints of dairy farm systems in China and New Zealand, as influenced by productivity, feed sources and mitigations," Agricultural Water Management, Elsevier, vol. 213(C), pages 155-163.
    3. Anthony King, 2017. "Technology: The Future of Agriculture," Nature, Nature, vol. 544(7651), pages 21-23, April.
    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. Alison Kennedy & Jessie Adams & Jeremy Dwyer & Muhammad Aziz Rahman & Susan Brumby, 2020. "Suicide in Rural Australia: Are Farming-Related Suicides Different?," IJERPH, MDPI, vol. 17(6), pages 1-13, March.
    2. Khalied Albarrak & Yonis Gulzar & Yasir Hamid & Abid Mehmood & Arjumand Bano Soomro, 2022. "A Deep Learning-Based Model for Date Fruit Classification," Sustainability, MDPI, vol. 14(10), pages 1-16, May.
    3. Yaoyao Wang & Yuanpei Kuang, 2023. "Evaluation, Regional Disparities and Driving Mechanisms of High-Quality Agricultural Development in China," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    4. Dimitrios Loukatos & Vasileios Arapostathis & Christos-Spyridon Karavas & Konstantinos G. Arvanitis & George Papadakis, 2024. "Power Consumption Analysis of a Prototype Lightweight Autonomous Electric Cargo Robot in Agricultural Field Operation Scenarios," Energies, MDPI, vol. 17(5), pages 1-24, March.
    5. Thorsøe, Martin Hvarregaard & Noe, Egon Bjørnshave & Lamandé, Mathieu & Frelih-Larsen, Ana & Kjeldsen, Chris & Zandersen, Marianne & Schjønning, Per, 2019. "Sustainable soil management - Farmers’ perspectives on subsoil compaction and the opportunities and barriers for intervention," Land Use Policy, Elsevier, vol. 86(C), pages 427-437.
    6. Rübcke von Veltheim, Friedrich & Claussen, Frans & Heise, Heinke, 2020. "Autonomous Field Robots in Agriculture: A Qualitative Analysis of User Acceptance According to Different Agricultural Machinery Companies," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305587, German Association of Agricultural Economists (GEWISOLA).
    7. Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Maxim Kotsemir & Alina Lavrynenko, 2018. "Mapping the Radical Innovations in Food Industry: A Text Mining Study," HSE Working papers WP BRP 80/STI/2018, National Research University Higher School of Economics.
    8. Eirini Aivazidou & Naoum Tsolakis, 2023. "Transitioning towards human–robot synergy in agriculture: A systems thinking perspective," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(3), pages 536-551, May.
    9. Sheng Hang & Jing Li & Xiangbo Xu & Yun Lyu & Yang Li & Huarui Gong & Yan Xu & Zhu Ouyang, 2021. "An Optimization Scheme of Balancing GHG Emission and Income in Circular Agriculture System," Sustainability, MDPI, vol. 13(13), pages 1-15, June.
    10. Rübcke von Veltheim, Friedrich & Claussen, Frans & Heise, Heinke, 2020. "Autonomous Field Robots in Agriculture: A Qualitative Analysis of User Acceptance According to Different Agricultural Machinery Companies," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305587, German Association of Agricultural Economists (GEWISOLA).
    11. Friedrich Rübcke von Veltheim & Heinke Heise, 2020. "The AgTech Startup Perspective to Farmers Ex Ante Acceptance Process of Autonomous Field Robots," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
    12. Dashuai Wang & Sheng Xu & Zhuolin Li & Wujing Cao, 2022. "Analysis of the Influence of Parameters of a Spraying System Designed for UAV Application on the Spraying Quality Based on Box–Behnken Response Surface Method," Agriculture, MDPI, vol. 12(2), pages 1-14, January.
    13. Nathan J. Shipley & William P. Stewart & Carena J. Riper, 2022. "Negotiating agricultural change in the Midwestern US: seeking compatibility between farmer narratives of efficiency and legacy," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(4), pages 1465-1476, December.
    14. Ting Zhang & Qingdong Zeng & Fan Ji & Honghong Wu & Rodrigo Ledesma-Amaro & Qingshan Wei & Hao Yang & Xuhan Xia & Yao Ren & Keqing Mu & Qiang He & Zhensheng Kang & Ruijie Deng, 2023. "Precise in-field molecular diagnostics of crop diseases by smartphone-based mutation-resolved pathogenic RNA analysis," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    15. Muhammad Junaid & Asadullah Shaikh & Mahmood Ul Hassan & Abdullah Alghamdi & Khairan Rajab & Mana Saleh Al Reshan & Monagi Alkinani, 2021. "Smart Agriculture Cloud Using AI Based Techniques," Energies, MDPI, vol. 14(16), pages 1-15, August.
    16. Michels, Marius & von Hobe, Cord-Friedrich & Mußhoff, Oliver, 2020. "Understanding the Adoption of Drones in German Agriculture," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305579, German Association of Agricultural Economists (GEWISOLA).
    17. Kitonsa, H. & Kruglikov, S. V., 2018. "Significance of drone technology for achievement of the United Nations sustainable development goals," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 4(3), pages 115-120.
    18. Chenyang Liu & Xiuyi Shi & Cuixia Li, 2023. "Digital Technology, Factor Allocation and Environmental Efficiency of Dairy Farms in China: Based on Carbon Emission Constraint Perspective," Sustainability, MDPI, vol. 15(21), pages 1-22, October.
    19. Ciliberti, Stefano & Frascarelli, Angelo & Polenzani, Bianca & Brunori, Gianluca & Martino, Gaetano, 2024. "Digitalisation strategies in the agri-food system: The case of PDO Parmigiano Reggiano," Agricultural Systems, Elsevier, vol. 218(C).
    20. Anja Gaudig & Bernd Ebersberger & Andreas Kuckertz, 2021. "Sustainability-Oriented Macro Trends and Innovation Types—Exploring Different Organization Types Tackling the Global Sustainability Megatrend," Sustainability, MDPI, vol. 13(21), pages 1-19, October.

    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:joiaen:v:10:y:2021:i:1:d:10.1186_s13731-021-00189-x. 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.