Atıktan Bilgiye: Tarımda Döngüsel Ekonomi İlkelerinin Dijital ve Yapay Zekâ Teknolojileriyle Bütünleşmesi

Abstract

İklim değişikliği, doğal kaynakların azalması ve gıda güvencesizliği, tarım sektöründe çevresel, ekonomik ve sosyal açıdan giderek artan baskılar yaratmaktadır. Bu durum, üretim sistemlerinde köklü değişimlere ihtiyaç duyulduğunu göstermektedir. Bu derleme çalışması, döngüsel ekonomi (DE) ilkeleri, dijital dönüşüm (DD) ve yapay zekâ (YZ) teknolojilerinin birlikte nasıl kullanılarak sürdürülebilir tarımsal kalkınmanın desteklenebileceğini incelemektedir. PRISMA metodolojisi çerçevesinde yürütülen sistematik literatür taramasında, Web of Science ve Scopus veri tabanlarında 2016–2025 yılları arasında yayımlanmış hakemli makaleler değerlendirilmiştir. Çalışmaya, sürdürülebilirliğin en az bir boyutuna değinen ve tarımda DE, DD veya YZ uygulamalarını ele alan araştırmalar dâhil edilmiştir. Bulgular üç ana tema etrafında toplanmaktadır. İlk olarak, kompost üretimi, biyogaz sistemleri, suyun yeniden kullanımı ve tarımsal atıkların ekonomik değere dönüştürülmesi gibi DE uygulamaları hem çevresel etkileri azaltmakta hem de yeni gelir kaynakları yaratmaktadır. İkinci olarak, nesnelerin interneti (IoT) sensörleri, blokzincir ve veri analitiği gibi DD araçları, kaynak verimliliğini artırmakta, tedarik zincirinde şeffaflık sağlamakta ve karar süreçlerini iyileştirmektedir. Üçüncü olarak, ürün izleme, verim tahmini ve hastalık tespitinde kullanılan YZ çözümleri, daha az girdi ve düşük emisyonla önemli verim artışları sağlamaktadır. Ancak yüksek yatırım maliyetleri, düşük dijital okuryazarlık, mevzuattaki boşluklar ve özellikle küçük üreticilerde altyapı eksiklikleri, bu teknolojilerin yaygınlaşmasını engellemektedir. Çalışma, DE ve DD yatırımlarının uyumlu biçimde yönlendirilmesi, kırsalda internet erişiminin genişletilmesi, hedefe yönelik eğitimlerin artırılması ve sürdürülebilir uygulamaları teşvik eden entegre politika çerçevelerine ihtiyaç olduğunu ortaya koymaktadır. Ayrıca, teknolojik araçlarla çevresel, ekonomik ve sosyal faydalar arasındaki ilişkiyi gösteren kavramsal bir çerçeve sunulmaktadır. Bu engellerin çok paydaşlı ve koordineli stratejilerle aşılması, tarımda dayanıklı, düşük etkili ve kapsayıcı üretim sistemlerine geçişi hızlandırabilir.

Keywords

• dijital tarım
• hassas tarım
• iklim dostu tarım
• sürdürülebilir tarım
• yapay zekâ
• yeşil dönüşüm

Project Number

N/A

From Waste to Wisdom: Linking Circular Economy Principles with Digital and AI Technologies in Agriculture

Abstract

Agriculture is under increasing environmental, economic, and social pressure due to climate change, resource depletion and food insecurity, requiring new approaches to production systems. This review explores how circular economy (CE) principles, digital transformation (DT), and artificial intelligence (AI)can be used together to achieve sustainable agricultural development. Using a systematic literature review guided by the PRISMA method, peer-reviewed studies published between 2016 and 2025 were analysed from the Web of Science and Scopus databases. The inclusion criteria targeted papers that addressed at least one sustainability dimension and focused on CE, DT, or AI applications in agriculture. The results show three interlinked themes. First, CE practices such as composting, biogas production, water reuse, and valorisation of agricultural waste reduce environmental impacts while creating new economic value streams. Second, DT tools, including Internet of Things (IoT) sensors, blockchain, and data analytics, enhance resource efficiency, supply chain transparency, and decision-making precision. Third, AI applications in crop monitoring, yield forecasting, and disease detection offer substantial productivity gains while minimizing inputs and emissions. However, adoption is hindered by high investment costs, limited digital literacy, regulatory gaps, and uneven infrastructure, particularly among smallholders. The review highlights the need for integrated policy frameworks that align investments in CE and DT, expand rural broadband networks, provide targeted training, and incentivize sustainable practices. A conceptual synthesis is proposed that links technological enablers with environmental, economic, and social outcomes. Addressing these barriers through coordinated multi-stakeholder strategies could accelerate the transition to resilient, environmentally friendly, and inclusive agricultural systems. Keywords: artificial intelligence, climate-friendly agriculture, digital agriculture, green transition, precision agriculture, sustainable farming.

Keywords

• artificial intelligence
• climate-friendly agriculture
• digital agriculture
• green transition
• precision agriculture
• sustainable farming.

Supporting Institution

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Project Number

N/A

Ethical Statement

This study adhered to general ethical guidelines applicable to community question-answering research. As it did not involve human or animal subjects, specific ethical committee approval was not required.

References

1. Agegnehu G., Bass AM., Nelson PN., Bird MI. Benefits of biochar, compost, and biochar–compost for soil quality, maize yield, and greenhouse gas emissions in a tropical agricultural soil. Science of the Total Environment 2016; 543: 295–306. https://doi.org/10.1016/j.scitotenv.2015.11.054
2. Ali ZA., Zain M., Hasan R., Al Salman H., Alkhamees BF., Almisned FA. Circular economy advances with artificial intelligence and digital twin: Multiple-case study of Chinese industries in agriculture. Journal of the Knowledge Economy 2025; 16(1): 2192-2228. https://doi.org/10.1007/s13132-024-02101-w
3. Ángulo MG., Batista MT., Caicedo MIG. Advances and challenges of a circular economy (CE) in agriculture in Ibero-America: A bibliometric perspective. Sustainability 2024; 16(24): 11266. https://doi.org/10.3390/su162411266
4. Bocken NMP., de Pauw I., Bakker C., van der Grinten B. Product design and business model strategies for a circular economy. Journal of Industrial and Production Engineering 2016; 33(5): 308–320. https://doi.org/10.1080/21681015.2016.1172124
5. Banerjee G., Sarkar U., Das S., Ghosh I. Artificial intelligence in agriculture: A literature survey. International Journal of Scientific Research in Computer Science Applications and Management Studies 2018; 7(3): 1–6.
6. Braun V., Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology 2006; 3(2): 77–101. https://doi.org/10.1191/1478088706qp063oa
7. Cahyadi ER., Hidayati N., Zahra N., Arif C. Integrating circular economy principles into agri-food supply chain management: A systematic literature review. Sustainability 2024; 16(16): 7165. https://doi.org/10.3390/su16167165
8. Çakmakçı MF., Çakmakçı R. Remote sensing, artificial intelligence and smart agriculture technology trends of the future. European Journal of Science and Technology 2023; (52): 234–246. https://doi.org/10.5281/zenodo.10439935

9. Çalış-Duman M. Society 5.0: Human-focused digital transformation. Journal of Social Policy Conferences 2022; (82): 309–336. https://doi.org/10.26650/jspc.2022.82.1008072
10. Chen T., Lv L., Wang D., Zhang J., Yang Y., Zhao Z., Wang C., Guo X., Chen H., Wang Q., Xu Y., Zhang Q., Du B., Zhang L., Tao D. Empowering agrifood system with artificial intelligence: A survey of the progress, challenges and opportunities. arXiv 2024; arXiv:2305.01899. https://doi.org/10.48550/arXiv.2305.01899
11. Crippa M., Solazzo E., Guizzardi D., Monforti-Ferrario F., Tubiello FN., Leip A. Food systems are responsible for a third of global anthropogenic GHG emissions. Nature Food 2021; 2: 198–209. https://doi.org/10.1038/s43016-021-00225-9
12. Dimitrov DK., Ivanova M. Trends in organic farming development in Bulgaria: Applying circular economy principles to sustainable rural development. Visegrad Journal on Bioeconomy and Sustainable Development 2017; 6(1): 10–16. https://doi.org/10.1515/vjbsd-2017-0002
13. Edquist C. Systems of innovation: Perspectives and challenges. In J. Fagerberg, D. C. Mowery, and R. R. Nelson (Eds.), 2025. The Oxford handbook of innovation (pp. 181–208). Oxford: Oxford University Press.
14. Elkington J. Cannibals with forks: The triple bottom line of 21st century business. Oxford, UK: Capstone. 1997. Ellen MacArthur Foundation. Towards the circular economy: Economic and business rationale for an accelerated transition. Ellen MacArthur Foundation 2013. https://ellenmacarthurfoundation.org European Commission. Farm to Fork Strategy. European Commission 2020. https://ec.europa.eu/food/farm2fork_en
15. FAO. The state of food and agriculture 2020: Overcoming water challenges in agriculture. Food and Agriculture Organization of the United Nations 2020. https://doi.org/10.4060/cb1447en
16. Gedik Y. Döngüsel ekonomiyi anlamak: teorik bir çerçeve. Turkish Business Journal 2020; 1(2): 110–137. https://dergipark.org.tr/tr/pub/tbj/issue/59142/812070
17. Geels FW. Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study. Research Policy 2002; 31(8–9): 1257–1274. https://doi.org/10.1016/S0048-7333(02)00062-8
18. Geissdoerfer M., Savaget P., Bocken NM., Hultink EJ. The circular economy – A new sustainability paradigm? Journal of Cleaner Production 2017; 143: 757–768. https://doi.org/10.1016/j.jclepro.2016.12.048
19. Geng, W., Zhao, J., Liu, L., Wang, W., Kang, X. Digital technologies adoption and economic benefits in agriculture: A Mixed-methods approach. Sustainability 2024); 16(11), 4431. https://doi.org/10.3390/su16114431
20. Greenhalgh T., Robert G., Macfarlane F., Bate P., Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. The Milbank Quarterly 2004; 82(4): 581–629. https://doi.org/10.1111/j.0887-378X.2004.00325.x
21. Haque F., Fan C., Lee YY. From waste to value: Addressing the relevance of waste recovery to agricultural sector in line with circular economy. Journal of Cleaner Production 2023; 415: 137873. https://doi.org/10.1016/j.jclepro.2023.137873
22. Kamilaris A., Prenafeta-Boldú FX. Deep learning in agriculture: A survey. Computers and Electronics in Agriculture 2018; 147: 70–90. https://doi.org/10.1016/j.compag.2018.02.016
23. Khajuria A., Atienza VA., Chavanich S., Henning W., Islam I., Kral U., Liu M., Liu X., Murthy IK., Oyedotun TDT., Verma P., Xu G., Zeng X., Li J. Accelerating circular economy solutions to achieve the 2030 agenda for sustainable development goals. Circular Economy 2022; 1(1):100001. https://doi.org/10.1016/j.cecir.2022.100001
24. Moreddu C. Public-Private Partnerships for Agricultural Innovation: Lessons From Recent Experiences. OECD Food, Agriculture and Fisheries Papers 2016; 92. https://doi.org/10.1787/5jm55j9p9rmx-en
25. Nguyen, TK., Minh Khue, NT., Tran, QP., Quynh Anh, NT., Cuong, LK., Chu Du, N., Cuong, CV., Thuong, VT., Anh, DH., Anh Vu, N. Examining the factors influencing the level of circular economy adoption in agriculture: Insights from Vietnam. Research on World Agricultural Economy 2024; 5(1): 48–58. https://doi.org/10.36956/rwae.v5i1.992
26. Otero P., Echave J., Chamorro F., Soria-Lopez A., Cassani L., Simal-Gandara J., Prieto MA., Fraga-Corral M. Challenges in the application of circular economy models to agricultural by-products: pesticides in Spain as a case study. Foods 2023; 12(16): 3054. https://doi.org/10.3390/foods12163054
27. Page MJ., McKenzie JE., Bossuyt PM., Boutron I., Hoffmann TC., Mulrow CD., Shamseer L., Tetzlaff JM., Akl EA., Brennan SE., Chou R., Glanville J., Grimshaw JM., Hróbjartsson A., Lalu MM., Li, T., Loder EW., Mayo-Wilson E., McDonald S., McGuinness LA., Stewart LA., Thomas J., Tricco AC., Welch VA., Whiting, P., Moher D. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021; 372: n71. https://doi.org/10.1136/bmj.n71
28. Rodino S., Pop R., Sterie C., Giuca A., Dumitru E. Developing an evaluation framework for circular agriculture: A pathway to sustainable farming. Agriculture 2023; 13(11): 2047. https://doi.org/10.3390/agriculture13112047
29. Rotolo GC., Vassillo C., Rodriguez AA., Magnano L., Milo Vaccaro M., Civit BM., Covacevich MS., Arena AP., Ulgiati S. Perception and awareness of circular economy options within sectors related to agriculture in Argentina. Journal of Cleaner Production 2022; 373: 133805. https://doi.org/10.1016/j.jclepro.2022.133805
30. Santos RDA., Teles EO., Freires FGM. Applying the circular economy framework to blockchain agricultural production. Sustainability 2024; 16(18): 8004. https://doi.org/10.3390/su16188004
31. Snyder H. Literature review as a research methodology: An overview and guidelines. Journal of Business Research 2019; 104: 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
32. Sousa-Zomer TT., Magalhães L., Seuring S. Minimizing food loss and utilizing agricultural waste: The role of supply chain governance in the circular economy. Journal of Cleaner Production 2023; 378: 134639. https://doi.org/10.1016/j.jclepro.2022.134639
33. Toop TA., Ward S., Oldfield T., Hull M., Kirby ME., Theodorou MK. AgroCycle – Developing a circular economy in agriculture. Energy Procedia 2017; 123: 76–80. https://doi.org/10.1016/j.egypro.2017.07.269
34. Velasco-Muñoz JF., Mendoza JMF., Aznar-Sánchez JA., Gallego-Schmid A. Circular economy implementation in the agricultural sector: Definition, strategies and indicators. Resources, Conservation and Recycling 2021; 170: 105618. https://doi.org/10.1016/j.resconrec.2021.105618
35. Wang T., Liu J., Feng Z. Digital economy and sustainable agricultural development: An empirical assessment. Sustainability 2023; 17(10): 4372. https://doi.org/10.3390/su17104372
36. Zheng Y., Liao F., Tian M. Examining the factors influencing the digital transformation of new agricultural operating entities: insights from Zhejiang, China. Humanities and Social Sciences Communications 2025; 12: 608. https://doi.org/10.1057/s41599-025-04949-y