SavedAdd your journal

Journals / Türkiye İnsansız Hava Araçları Dergisi / 2025 / Cilt: 7 Sayı: 2

The Role of UAVs in Wheat Cultivation from a Carbon Footprint Perspective: An Analysis of Sustainability and Energy Efficiency

Karbon Ayak İzi Perspektifinden İHA’ların Buğday Tarımındaki Rolü: Sürdürülebilirlik ve Enerji Verimliliği Analizi

Çağdaş Can Toprak(SIIRT UNIVERSITY, FACULTY OF AGRICULTURE)0000-0002-0951-7458
Pages
99–108
Publication Date
2025-12-27
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study underscores that UAVs must be supported not only on a technical level but also through managerial and policy frameworks, offering a holistic perspective that may contribute to the development of future low-carbon agricultural systems.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The use of unmanned aerial vehicles (UAVs) in wheat cultivation aligns closely with environmental sustainability goals, particularly in reducing carbon footprint and enhancing energy efficiency.
📊
Key Findings & Data:In this context, the environmental advantages of UAVs over conventional agricultural methods have been demonstrated through an examination of their entire life cycle—from production to field application.
💡
Conclusion & Impact:This study underscores that UAVs must be supported not only on a technical level but also through managerial and policy frameworks, offering a holistic perspective that may contribute to the development of future low-carbon agricultural systems.
🔬Design:Derleme
📍Scope:Comprehensive Sample
⚙️Variables:Buğday · İklim · Enerji

Abstract

The use of unmanned aerial vehicles (UAVs) in wheat cultivation aligns closely with environmental sustainability goals, particularly in reducing carbon footprint and enhancing energy efficiency. In this context, the environmental advantages of UAVs over conventional agricultural methods have been demonstrated through an examination of their entire life cycle—from production to field application. UAVs contribute significantly to the reduction of greenhouse gas emissions due to their low energy consumption, high application precision, and non-soil-compacting structure, while also promoting soil health and biodiversity. Precision applications such as fertilization and pesticide spraying guided by spectral indices like NDVI help minimize resource waste and reduce environmental toxicity. However, for UAV technologies to be widely adopted, it is essential to strengthen technical infrastructure, expand training programs for farmers, and standardize carbon monitoring systems. This study underscores that UAVs must be supported not only on a technical level but also through managerial and policy frameworks, offering a holistic perspective that may contribute to the development of future low-carbon agricultural systems.

Özet

İnsansız hava araçlarının (İHA) buğday tarımında kullanımı, karbon ayak izinin azaltılması ve enerji verimliliğinin artırılması açısından çevresel sürdürülebilirlik hedefleriyle büyük ölçüde örtüşmektedir. Bu doğrultuda İHA’ların üretimden uygulamaya kadar olan tüm yaşam döngüsü süreçleri incelenerek, geleneksel tarımsal yöntemlere kıyasla sağladığı çevresel avantajlar ortaya konmuştur. İHA’ların düşük enerji tüketimi, yüksek uygulama hassasiyeti ve toprakla temas etmeyen yapıları sayesinde sera gazı emisyonlarında belirgin düşüş sağlandığı, ayrıca toprak sağlığı ve biyolojik çeşitlilik açısından olumlu katkılar sunduğu vurgulanmıştır. NDVI gibi spektral indeksler aracılığıyla yürütülen hassas gübreleme ve ilaçlama uygulamaları sayesinde kaynak israfının önüne geçilmekte, çevresel toksisite azaltılmaktadır. Bununla birlikte, İHA teknolojisinin yaygınlaştırılabilmesi için teknik altyapının güçlendirilmesi, üreticilere yönelik eğitimlerin artırılması ve karbon izleme sistemlerinin standartlaştırılması gereklidir. Çalışma, İHA’ların sürdürülebilir tarım politikalarının başarısı için yalnızca teknik değil, aynı zamanda yönetsel ve politik düzeyde desteklenmesi gerektiğini ortaya koyarak, gelecekteki düşük karbonlu tarım sistemlerine katkı sağlayacak bütüncül bir perspektif sunmaktadır.

🔖

Cite This Article

Toprak, Ç. C. (2025). The Role of UAVs in Wheat Cultivation from a Carbon Footprint Perspective: An Analysis of Sustainability and Energy Efficiency. Türkiye İnsansız Hava Araçları Dergisi, Cilt: 7 Sayı: 2, 99–108. https://doi.org/10.51534/tiha.1748061

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (50)

  1. Baibars Mekatronik. (2023). Tarımsal insansız hava aracı sistemleri. Retrieved from https://www.baibarsmekatronik.com
  2. Batey, T. (2009). Soil compaction and soil management: A review. Soil Use and Management, 25(4), 335–345.
  3. Baykar. (2023a). Bayraktar TB2 technical specifications. Retrieved from https://www.baykartech.com
  4. Cumhurbaşkanlığı Savunma Sanayii Başkanlığı (SSB). (2022). Savunma sanayii faaliyet raporu 2022. Ankara: T.C. Cumhurbaşkanlığı Savunma Sanayii Başkanlığı. Erişim adresi: https://www.ssb.gov.tr
  5. Çevre, Şehircilik ve İklim Değişikliği Bakanlığı. (2021). İklim değişikliğine uyum stratejisi ve eylem planı (2021–2030). Ankara, Türkiye.
  6. European Commission. (2020a). A European Green Deal: Striving to be the first climate-neutral continent. Retrieved from https://commission.europa.eu
  7. European Commission. (2020b). Farm to fork strategy. Retrieved from https://ec.europa.eu
  8. European Commission. (2020c). A farm to fork strategy for a fair, healthy and environmentally-friendly food system. Retrieved from https://food.ec.europa.eu
  9. FAO. (2023). FAOSTAT statistical database. Retrieved from https://www.fao.org/faostat
  10. Gaines, L. (2014). The future of automotive lithium-ion battery recycling: Charting a sustainable course. Sustainable Materials and Technologies, 1–2, 2–7.
  11. Gitelson, A. A., Gritz, Y., & Merzlyak, M. N. (2003). Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment.
  12. Journal of Plant Physiology, 160(3), 271–282.
  13. https://doi.org/10.1078/0176-1617-00887
  14. Gitelson, A. A., Kaufman, Y. J., & Merzlyak, M. N. (1996). Use of a green channel in remote sensing of global vegetation from EOS-MODIS.
  15. Remote Sensing of Environment, 58(3), 289–298.
  16. https://doi.org/10.1016/S0034-4257(96)00072-7
  17. Hunt, E. R., Hively, W. D., McCarty, G. W., Daughtry, C. S. T., Forrestal, P. J., & Kratochvil, R. J. (2010). NIR-green-blue high-resolution digital images for assessment of crop biomass. Remote Sensing, 2(1), 290–305.
  18. Intergovernmental Panel on Climate Change. (2007). Climate change 2007: The physical science basis (Contribution of Working Group I to the Fourth Assessment Report). Cambridge, UK: Cambridge University Press.
  19. ISO. (2006). Environmental management—Life cycle assessment—Principles and framework (ISO 14040:2006). Geneva, Switzerland: International Organization for Standardization.
  20. Lal, R. (2004). Carbon emission from farm operations. Environment International, 30(7), 981–990.
  21. Lal, R. (2020). Regenerative agriculture for food and climate. Journal of Soil and Water Conservation, 75(5), 123A–124A.
  22. Marasová, D., Andoga, R., Španihel, M., & Oslovič, M. (2024). Carbon footprint assessment of agricultural tractors. Agriculture, 14(11), 1856.
  23. Mulla, D. J. (2013). Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps.
  24. Biosystems Engineering, 114(4), 358–371.
  25. https://doi.org/10.1016/j.biosystemseng.2012.08.009
  26. Nemecek, T., Schnetzer, J., & Reinhard, J. (2012). Environmental impacts of Swiss agriculture and food consumption 1985–2007. Zurich, Switzerland: Agroscope.
  27. Notter, D. A., Gauch, M., Widmer, R., Wager, P., Stamp, A., Zah, R., & Althaus, H. J. (2010). Contribution of Li-ion batteries to the environmental impact of electric vehicles. Environmental Science & Technology, 44(17), 6550–6556. https://doi.org/10.1021/es903729a
  28. Peñuelas, J., Baret, F., & Filella, I. (1995). Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance.
  29. Photosynthetica, 31(2), 221–230.
  30. Rose, D. C., Sutherland, W. J., Barnes, A. P., Borthwick, F., Ffoulkes, C., Hall, C., & Dicks, L. V. (2021). Integrated farm management systems and agricultural sustainability: Barriers and incentives. Agricultural Systems, 191, 103173.
  31. Roy, P., Nei, D., Orikasa, T., Xu, Q., Okadome, H., Nakamura, N., & Shiina, T. (2009). A review of life cycle assessment (LCA) on some food products. Journal of Food Engineering, 90(1), 1–10.
  32. Safaeinejad, M., Ghasemi-Nejad-Raeini, M., & Taki, M. (2025). Reducing energy and environmental footprint in agriculture: A study on drone spraying vs. conventional methods. PLOS ONE, 20(6), e0323779.
  33. Šančić, T., Širok, B., & Smojver, I. (2023). Experimental characterization of composite-printed structures for UAV applications. Materials, 16(14), 5060.
  34. Sishodia, R. P., Ray, R. L., & Singh, S. K. (2020). Applications of remote sensing in precision agriculture: A review. Remote Sensing, 12(19), 3136.
  35. Smith, P., Martino, D., Cai, Z., Gwary, D., Janzen, H., Kumar, P., & Smith, J. (2008). Greenhouse gas mitigation in agriculture. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1492), 789–813.
  36. Torres-Sánchez, J., Peña, J. M., & de Castro, A. I. (2018). UAV-based remote sensing for precision agriculture: A review. Agronomy for Sustainable Development, 38(2), 1–20.
  37. Tubiello, F. N., Conchedda, G., Wanner, N., Federici, S., & Rossi, S. (2022). Greenhouse gas emissions from food systems: Building the evidence base. Rome, Italy: FAO. Retrieved from https://www.fao.org
  38. TUSAŞ. (2023). ANKA and AKSUNGUR platforms overview. Retrieved from https://www.tusas.com.tr
  39. Türk Havacılık ve Uzay Sanayii A.Ş. (2023). Unmanned aerial vehicle programs. Retrieved from https://www.tusas.com
  40. UN. (2023). Sustainable Development Goals report 2023. Retrieved from https://sdgs.un.org/goals
  41. Villa-Henriksen, A., Edwards, G. T., Pesonen, L. A., Green, O., & Sørensen, C. G. (2020). Internet of Things in arable farming: Implementation, applications, challenges and potential. Biosystems Engineering, 191, 60–84.
  42. Wang, G., Lan, Y., Yuan, H., Qi, H., Chen, P., Ouyang, F., & Han, Y. (2019). Comparison of spray deposition, control efficacy on wheat aphids and working efficiency in the wheat field of the unmanned aerial vehicle with boom sprayer and two conventional knapsack sprayers. Applied sciences, 9(2), 218.
  43. Wiedmann, T., & Minx, J. (2008). A definition of ‘carbon footprint’. In C. C. Pertsova (Ed.), Ecological economics research trends (pp. 1–11). New York, NY: Nova Science Publishers.
  44. Xue, X., Lan, Y., Sun, Z., Chang, C., & Hoffmann, W. C. (2017).
  45. Develop an unmanned aerial vehicle based automatic aerial spraying system.
  46. Computers and Electronics in Agriculture, 128, 58–66.
  47. Zarifneshat, S., Saeidirad, M. H., Safari, M., Motame AlShariati, H. R., & Naseri, M. (2022). Technical evaluation of agriculture drone sprayer for control of wheat weeds and compare with conventional methods. Agricultural Mechanization and Systems Research, 23(82), 53-70.
  48. Zhang, C., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: A review.
  49. Precision Agriculture, 13(6), 693–712.
  50. https://doi.org/10.1007/s11119-012-9274-5