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Determining the Effective Meteorological Parameters on Potato Yield in Niğde Province and Yield Prediction with Machine Learning and Deep Learning Models

Year 2024, Volume: 7 Issue: 6, 641 - 645, 15.11.2024
https://doi.org/10.47115/bsagriculture.1536162

Abstract

In this study, we explore the impact of meteorological parameters on potato yield in Niğde province, a key agricultural region in Türkiye for potato production. Understanding the relationship between weather conditions and crop yield is crucial for optimizing agricultural practices and ensuring food security, especially in regions susceptible to climate variability. The study includes all meteorological parameters observed and recorded in Niğde Directorate of Meteorology, covering the period between 1990 and 2023. Through the analysis of historical weather data and potato yield records, we aim to identify the most influential meteorological factors affecting potato production. Then, artificial intelligence techniques such as Random Forest, Gradient Boost, Convolutional Neural Networks and Recurrent Neural Networks are utilized to predict the potato yield in order to provide valuable insights into how different weather patterns influence crop performance. The findings suggest that potato yield is correlated with meteorological parameters to some degree and AI techniques can predict the potato yield but lacks the precision. The reason is that potato production in Niğde is mostly done with irrigation. However, this further increases the risk that could result from the changes in groundwater levels and pollution in irrigation ponds for agricultural practices in Niğde.

References

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  • Kocalar AC. 2022. Niğde su varlığındaki değişimin sürdürülebilirliği-Akkaya Baraj Göleti. E-J Vocat Colleges, 12(2): 76-90.
  • MEVBIS. 2024. Meteorological Data Service. URL: https://mevbis.mgm.gov.tr/ (accessed date: August 18, 2024).
  • Selek B, Demirel Yazici D, Aksu H, Özdemir AD. 2016. Seyhan Dam, Turkey, and climate change adaptation strategies. In: Tortajada C. (eds) Increasing resilience to climate variability and change. Water resources development and management. Springer, Singapore, pp: 205-231. https://doi.org/10.1007/978-981-10-1914-2_10
  • Sen B, Güngör S. 2019. Effects of climate change over potato (Solanum tuberosum L.) production. 4th International Congress on Biosystems Engineering (ICOBEN2019), September 24-27, Hatay, Türkiye, pp: 263-271.
  • Shanmugavalli M, Ignatia KM. 2023. Comparative study among MAPE, RMSE and R square over the treatment techniques undergone for PCOS influenced women. Rec Patents Eng, 19: e041223224190. https://doi.org/10.2174/0118722121269786231120122435
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Year 2024, Volume: 7 Issue: 6, 641 - 645, 15.11.2024
https://doi.org/10.47115/bsagriculture.1536162

Abstract

References

  • FAOSTAT. 2022. Crop production database. URL= https://www.fao.org/faostat/en/#data/QCL (accessed date: August 18, 2024).
  • Karsan A, Gul M. 2017. Patates üretim maliyetleri ve karlılığındaki değişim: Niğde ili örneği. Turkish J Agri Food Sci Technol, 5(5): 530-535. https://doi.org/10.24925/turjaf.v5i5.530-535.1029
  • Kocalar AC. 2022. Niğde su varlığındaki değişimin sürdürülebilirliği-Akkaya Baraj Göleti. E-J Vocat Colleges, 12(2): 76-90.
  • MEVBIS. 2024. Meteorological Data Service. URL: https://mevbis.mgm.gov.tr/ (accessed date: August 18, 2024).
  • Selek B, Demirel Yazici D, Aksu H, Özdemir AD. 2016. Seyhan Dam, Turkey, and climate change adaptation strategies. In: Tortajada C. (eds) Increasing resilience to climate variability and change. Water resources development and management. Springer, Singapore, pp: 205-231. https://doi.org/10.1007/978-981-10-1914-2_10
  • Sen B, Güngör S. 2019. Effects of climate change over potato (Solanum tuberosum L.) production. 4th International Congress on Biosystems Engineering (ICOBEN2019), September 24-27, Hatay, Türkiye, pp: 263-271.
  • Shanmugavalli M, Ignatia KM. 2023. Comparative study among MAPE, RMSE and R square over the treatment techniques undergone for PCOS influenced women. Rec Patents Eng, 19: e041223224190. https://doi.org/10.2174/0118722121269786231120122435
  • TUIK. 2023. Bitkisel üretim istatistikleri. URL= https://biruni.tuik.gov.tr/ (accessed date: August 18, 2024).
There are 8 citations in total.

Details

Primary Language English
Subjects Zootechny (Other)
Journal Section Research Articles
Authors

Esma Uzan 0000-0003-1532-6268

Cevher Özden 0000-0002-8445-4629

Publication Date November 15, 2024
Submission Date August 20, 2024
Acceptance Date September 30, 2024
Published in Issue Year 2024 Volume: 7 Issue: 6

Cite

APA Uzan, E., & Özden, C. (2024). Determining the Effective Meteorological Parameters on Potato Yield in Niğde Province and Yield Prediction with Machine Learning and Deep Learning Models. Black Sea Journal of Agriculture, 7(6), 641-645. https://doi.org/10.47115/bsagriculture.1536162

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