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Spatial Diversity of Organic Farming in Poland

Author

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  • Małgorzata Kobylińska

    (Department of Theory of Economics, Faculty of Economic Science, University of Warmia and Mazury in Olsztyn, Prawocheńskiego 19, 10-719 Olsztyn, Poland)

Abstract

Economic development requires following the principles of sustainable development for the socio-economic progress of a country. The organic farming sector is important in ensuring sustainable development. The advancement of organic farming is an important issue which combines the environment, human health and socio-economic development. It is a management method that facilitates supplying high-quality food products and aims at eliminating the use of artificial fertilisers and pesticides. Organic farming has a beneficial impact on natural environmental protection, biodiversity conservation and food safety and quality improvement. The natural conditions in a region have a decisive impact on organic farming development. The purpose of this study is to assess the spatial diversity of organic farming and selected organic crop production in Poland by voivodship in 2013 and 2018. The statistical analysis of organic farming spatial diversity was conducted in a one- and two-dimensional approach. The analysis conducted made it possible to identify four clusters of voivodships based on the production volume of selected organic crops using the k-means algorithm. Graphs of observation depth contours in a sample were used to visualise and to analyse the two-dimensional data. STATISTICA software and selected packages of the R environment, available under the GPL licence, were used in the analysis. The analysis shows that the organic farm number and acreage in Poland is characterised by considerable variability between voivodships, with their noticeable concentration in several country regions. In the analysed years, organic farming was the most widespread in the Warmińsko-Mazurskie Voivodship and the Zachodniopomorskie Voivodship.

Suggested Citation

  • Małgorzata Kobylińska, 2021. "Spatial Diversity of Organic Farming in Poland," Sustainability, MDPI, vol. 13(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9335-:d:617917
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    References listed on IDEAS

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    1. Rita Remeikiene & Ligita Gaspareniene, 2017. "Green farming development opportunities: the case of Lithuania," Oeconomia Copernicana, Institute of Economic Research, vol. 8(3), pages 401-416, September.
    2. Eva-Marie Meemken & Matin Qaim, 2018. "Organic Agriculture, Food Security, and the Environment," Annual Review of Resource Economics, Annual Reviews, vol. 10(1), pages 39-63, October.
    3. Peter J. Rousseeuw & Ida Ruts, 1996. "Bivariate Location Depth," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(4), pages 516-526, December.
    4. Michał Dudek & Wioletta Wrzaszcz, 2020. "On the Way to Eco-Innovations in Agriculture: Concepts, Implementation and Effects at National and Local Level. The Case of Poland," Sustainability, MDPI, vol. 12(12), pages 1-22, June.
    5. Władysława Łuczka & Sławomir Kalinowski, 2020. "Barriers to the Development of Organic Farming: A Polish Case Study," Agriculture, MDPI, vol. 10(11), pages 1-19, November.
    6. Sadowski, Arkadiusz & Wojcieszak-Zbierska, Monika & Zmyślona, Jagoda, 2021. "Economic Situation of Organic Farms in Poland on the Background of the European Union," Problems of Agricultural Economics / Zagadnienia Ekonomiki Rolnej 319699, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).
    7. Karol Kociszewski & Andrzej Graczyk & Krystyna Mazurek-Łopacinska & Magdalena Sobocińska, 2020. "Social Values in Stimulating Organic Production Involvement in Farming—The Case of Poland," Sustainability, MDPI, vol. 12(15), pages 1-21, July.
    8. Ruts, Ida & Rousseeuw, Peter J., 1996. "Computing depth contours of bivariate point clouds," Computational Statistics & Data Analysis, Elsevier, vol. 23(1), pages 153-168, November.
    9. Hubert, M. & Vandervieren, E., 2008. "An adjusted boxplot for skewed distributions," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5186-5201, August.
    10. Monther M. Tahat & Kholoud M. Alananbeh & Yahia A. Othman & Daniel I. Leskovar, 2020. "Soil Health and Sustainable Agriculture," Sustainability, MDPI, vol. 12(12), pages 1-26, June.
    11. Rita Remeikiene & Ligita Gaspareniene, 2017. "Green Farming Development Opportunities: the Case of Lithuania," Working Papers 99/2017, Institute of Economic Research, revised May 2017.
    12. Atanu Mukherjee & Emmanuel C. Omondi & Paul R. Hepperly & Rita Seidel & Wade P. Heller, 2020. "Impacts of Organic and Conventional Management on the Nutritional Level of Vegetables," Sustainability, MDPI, vol. 12(21), pages 1-25, October.
    13. Ching-Cheng Shen & Yen-Rung Chang & Der-Jen Liu, 2020. "Sustainable Development of an Organic Agriculture Village to Explore the Influential Effect of Brand Equity from the Perspective of Landscape Resources," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
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