Research Article
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Year 2021, Volume: 5 Issue: 3, 271 - 278, 15.09.2021
https://doi.org/10.31015/jaefs.2021.3.3

Abstract

References

  • Arun, G. C., & Ghimire, K. (2018). A SWOT analysis of Nepalese agricultural policy. International Journal of Agriculture Environment and Food Sciences, 2(4), 119-123. https://doi.org/10.31015/jaefs.18020
  • Doğan, H. & Gürler, A. (2015). Supply responses of agricultural crops cultivated in Yesilirmak agricultural basin within Turkey agricultural basins production and support model. Yuzuncu Yıl University Journal of Agricultural Sciences, 25(3), 231-243. https://doi.org/10.29133/yyutbd.236369
  • Gayak, B., Pandey, S.R., Bhatta, S. (2020). Economics of production and marketing of apple (Malus domestica) in Mustang, Nepal. Int. J. Agric. Environ. Food Sci., 4(4), 483-492. https://doi.org/10.31015/jaefs.2020.4.12
  • Hrytsiuk, P. M., & Babych, T. Y. (2017). Mathematical modelling of grain production profitability in Ukraine taking into account risks. International Journal of Risk Assessment and Management, 20(4), 307-321. https://doi.org/10.1504/IJRAM.2017.087901
  • Klima, K., Kliszcz, A., Puła, J., & Lepiarczyk, A. (2020). Yield and profitability of crop production in mountain less favoured areas. Agronomy, 10(5), 700. https://doi.org/10.3390/agronomy10050700
  • McBride, W., & Greene, C. (2009). The profitability of organic soybean production. Renewable Agriculture and Food Systems, 24(4), 276-284. Retrieved from http://www.jstor.org/stable/44490677
  • Niyigaba, J., & Peng, D. (2020). Analysis and Forecasting the Agriculture Production Sector in Rwanda. International Journal of Economics and Finance, 12(8), 1-91. https://doi.org/10.5539/ijef.v12n8p
  • Pandey, A. K., Sinha, A. K., & Srivastava, V. K. (2008). A Comparative Study of Neural-Network & Fuzzy Time Series Forecasting Techniques–Case Study: Wheat Production Forecasting. International Journal of Computer science and network security, 8(9), 382-387. Retrieved from https://www.academia.edu/8430700
  • Rana, A. K. (2020). Comparative Study on Fuzzy Models for Crop Production Forecasting. Mathematics and Statistics, 8(4), 451-457. https://doi.org/10.13189/ms.2020.080412
  • Ucak, H. (2006). Monitoring agriculture of Turkey before accession process for EU membership. Journal of Central European Agriculture, 7(3), 545-548. Retrieved from https://jcea.agr.hr/en/issues/article/993
  • Ugurlu, M. (2019). Production Economy of Pomegranate in Manisa Province. Int. J. Agric. Environ. Food Sci., 3(4), 272-278. https://dx.doi.org/10.31015/jaefs.2019.4.12
  • Urfi, P., Hoffmann, A., & Kormosné Koch, K. (2011). The comparative cost and profit analysis of organic and conventional farming. Studies in Agricultural Economics, 113(1), 67-84. Retrieved from http://repo.aki.gov.hu/id/eprint/2214
  • Uzunöz, M., & Çiçek, A. (2003). A research on the effects of agricultural income and farming system of agricultural and social structure of the farms in the two regions having different development level (A case study: Kazova and Artova regions of Tokat province). Journal of Agricultural Faculty of Gaziosmanpasa University, 20(1), 51-59. Retrieved from https://dergipark.org.tr/tr/pub/gopzfd/issue/7347/96127

Profit Forecasting in Crop Production: The Case of Gazipaşa

Year 2021, Volume: 5 Issue: 3, 271 - 278, 15.09.2021
https://doi.org/10.31015/jaefs.2021.3.3

Abstract

Agriculture sector in Turkey is among the largest, employing one out of every five working people. In this study agricultural crop income of Turkey’s Gazipaşa district is analyzed. Located on the coast of the Mediterranean, the district’s main economy is based on agriculture with 81 different crops currently cultivated in 43 regions. For each crop type, total planted land size, yield, wholesale price and operating costs are determined using the data from Turkish Statistical Institute and the district’s Directorate of Agriculture. Crop types are ranked based on their economic returns and top 30 that corresponds to 96.45% of the total agricultural income are determined. Profit forecasts are made for those 30 crop types for each of the next 15 years. Future wholesale prices are forecasted using linear trend projection. The annual agricultural loan interest rate of 7.5% is used to estimate the increase in operating costs. Results show that the annual total profit increases slowly in the next 11 years and then decreases. Moreover, profitability increases only for 18 out of the 30 crop types. Internal rate of return is also found to be 15%. Findings suggest that the current crop diversity is not economically sustainable and a better agricultural production plan is required.

References

  • Arun, G. C., & Ghimire, K. (2018). A SWOT analysis of Nepalese agricultural policy. International Journal of Agriculture Environment and Food Sciences, 2(4), 119-123. https://doi.org/10.31015/jaefs.18020
  • Doğan, H. & Gürler, A. (2015). Supply responses of agricultural crops cultivated in Yesilirmak agricultural basin within Turkey agricultural basins production and support model. Yuzuncu Yıl University Journal of Agricultural Sciences, 25(3), 231-243. https://doi.org/10.29133/yyutbd.236369
  • Gayak, B., Pandey, S.R., Bhatta, S. (2020). Economics of production and marketing of apple (Malus domestica) in Mustang, Nepal. Int. J. Agric. Environ. Food Sci., 4(4), 483-492. https://doi.org/10.31015/jaefs.2020.4.12
  • Hrytsiuk, P. M., & Babych, T. Y. (2017). Mathematical modelling of grain production profitability in Ukraine taking into account risks. International Journal of Risk Assessment and Management, 20(4), 307-321. https://doi.org/10.1504/IJRAM.2017.087901
  • Klima, K., Kliszcz, A., Puła, J., & Lepiarczyk, A. (2020). Yield and profitability of crop production in mountain less favoured areas. Agronomy, 10(5), 700. https://doi.org/10.3390/agronomy10050700
  • McBride, W., & Greene, C. (2009). The profitability of organic soybean production. Renewable Agriculture and Food Systems, 24(4), 276-284. Retrieved from http://www.jstor.org/stable/44490677
  • Niyigaba, J., & Peng, D. (2020). Analysis and Forecasting the Agriculture Production Sector in Rwanda. International Journal of Economics and Finance, 12(8), 1-91. https://doi.org/10.5539/ijef.v12n8p
  • Pandey, A. K., Sinha, A. K., & Srivastava, V. K. (2008). A Comparative Study of Neural-Network & Fuzzy Time Series Forecasting Techniques–Case Study: Wheat Production Forecasting. International Journal of Computer science and network security, 8(9), 382-387. Retrieved from https://www.academia.edu/8430700
  • Rana, A. K. (2020). Comparative Study on Fuzzy Models for Crop Production Forecasting. Mathematics and Statistics, 8(4), 451-457. https://doi.org/10.13189/ms.2020.080412
  • Ucak, H. (2006). Monitoring agriculture of Turkey before accession process for EU membership. Journal of Central European Agriculture, 7(3), 545-548. Retrieved from https://jcea.agr.hr/en/issues/article/993
  • Ugurlu, M. (2019). Production Economy of Pomegranate in Manisa Province. Int. J. Agric. Environ. Food Sci., 3(4), 272-278. https://dx.doi.org/10.31015/jaefs.2019.4.12
  • Urfi, P., Hoffmann, A., & Kormosné Koch, K. (2011). The comparative cost and profit analysis of organic and conventional farming. Studies in Agricultural Economics, 113(1), 67-84. Retrieved from http://repo.aki.gov.hu/id/eprint/2214
  • Uzunöz, M., & Çiçek, A. (2003). A research on the effects of agricultural income and farming system of agricultural and social structure of the farms in the two regions having different development level (A case study: Kazova and Artova regions of Tokat province). Journal of Agricultural Faculty of Gaziosmanpasa University, 20(1), 51-59. Retrieved from https://dergipark.org.tr/tr/pub/gopzfd/issue/7347/96127
There are 13 citations in total.

Details

Primary Language English
Subjects Agricultural Policy
Journal Section Research Articles
Authors

Mehmet Caner Ersoy 0000-0003-0195-6648

Mehmet Gümüş 0000-0003-2588-0270

Publication Date September 15, 2021
Submission Date April 9, 2021
Acceptance Date June 6, 2021
Published in Issue Year 2021 Volume: 5 Issue: 3

Cite

APA Ersoy, M. C., & Gümüş, M. (2021). Profit Forecasting in Crop Production: The Case of Gazipaşa. International Journal of Agriculture Environment and Food Sciences, 5(3), 271-278. https://doi.org/10.31015/jaefs.2021.3.3
AMA Ersoy MC, Gümüş M. Profit Forecasting in Crop Production: The Case of Gazipaşa. int. j. agric. environ. food sci. September 2021;5(3):271-278. doi:10.31015/jaefs.2021.3.3
Chicago Ersoy, Mehmet Caner, and Mehmet Gümüş. “Profit Forecasting in Crop Production: The Case of Gazipaşa”. International Journal of Agriculture Environment and Food Sciences 5, no. 3 (September 2021): 271-78. https://doi.org/10.31015/jaefs.2021.3.3.
EndNote Ersoy MC, Gümüş M (September 1, 2021) Profit Forecasting in Crop Production: The Case of Gazipaşa. International Journal of Agriculture Environment and Food Sciences 5 3 271–278.
IEEE M. C. Ersoy and M. Gümüş, “Profit Forecasting in Crop Production: The Case of Gazipaşa”, int. j. agric. environ. food sci., vol. 5, no. 3, pp. 271–278, 2021, doi: 10.31015/jaefs.2021.3.3.
ISNAD Ersoy, Mehmet Caner - Gümüş, Mehmet. “Profit Forecasting in Crop Production: The Case of Gazipaşa”. International Journal of Agriculture Environment and Food Sciences 5/3 (September 2021), 271-278. https://doi.org/10.31015/jaefs.2021.3.3.
JAMA Ersoy MC, Gümüş M. Profit Forecasting in Crop Production: The Case of Gazipaşa. int. j. agric. environ. food sci. 2021;5:271–278.
MLA Ersoy, Mehmet Caner and Mehmet Gümüş. “Profit Forecasting in Crop Production: The Case of Gazipaşa”. International Journal of Agriculture Environment and Food Sciences, vol. 5, no. 3, 2021, pp. 271-8, doi:10.31015/jaefs.2021.3.3.
Vancouver Ersoy MC, Gümüş M. Profit Forecasting in Crop Production: The Case of Gazipaşa. int. j. agric. environ. food sci. 2021;5(3):271-8.


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