Research Article
BibTex RIS Cite

Forecasting Patent Trends in the Agricultural Sector Using the ARIMA Model: A Case Study of IPC A01 Class

Year 2025, Volume: 12 Issue: 4, 1056 - 1067, 17.10.2025
https://doi.org/10.30910/turkjans.1680752

Abstract

Patents play an important role in stimulating growth and innovation across various sectors, including agriculture. This study focuses on tracking technological progress in the agricultural domain by examining patent data as a proxy for innovation activity. Patents categorized under IPC A01, obtained from the European Patent Office (EPO) database, were analyzed to generate strategic insights that can inform future research and development initiatives. Applying the ARIMA time series model, patent application trends within the agricultural sector were examined, and forecasts were generated for the period ahead. The study showed that the best model for forecasting agricultural patents was the ARIMA(1,1,0) model. The MAPE value of the model was calculated as 7,88, and the RMSE value of the model was calculated as 7328,31. According to the model, the number of applications is expected to reach approximately 150.778 in 2023 and rise to 161.220 by 2028. This upward trajectory reflects a sustained momentum in agricultural innovation. The findings not only demonstrate the sector’s increasing engagement with technological advancement but also offer valuable foresight regarding future innovation patterns. The global rise in agricultural patenting, along with these projections, serves as a useful indicator of the sector's growing emphasis on inventive activity and its commitment to long-term technological development.

References

  • Abbas, A., Zhang, L., & Khan, S. U. (2014). A literature review on the state-of-the-art in patent analysis. World Patent Information, 37, 3-13.
  • Akaike, H. (1974). A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), 716-723.
  • Akarsu, Y., Alacahan, N. D., & Atakişi, A. (2020). Ülke karşılaştırmaları ile araştırma geliştirme harcamaları ve ekonomik büyüme ilişkisi: Panel veri analizi. Sosyal Bilimler Araştırma Dergisi, 9(4), 159-167.
  • Anwer, M. E., Padmaja, S. S., & Kandpal, A. (2023). Trends and Patterns of Patent in Agriculture and Allied Sector. Journal of Intellectual Property Rights (JIPR), 28(6), 529-543.
  • Archibugi, D., & Pianta, M. (1996). Measuring technological change through patents and innovation surveys. Technovation, 16(9), 451-468.
  • Baumann, M., Domnik, T., Haase, M., Wulf, C., Emmerich, P., Rösch, C., & Weil, M. (2021). Comparative patent analysis for the identification of global research trends for the case of battery storage, hydrogen and bioenergy. Technological forecasting and social change, 165, 120505.
  • Blind, K. (2012). The influence of regulations on innovation: A quantitative assessment for OECD countries. Research Policy, 41(2), 391-400.
  • Castells, P. E., Salvador, M. R., & Bosch, R. M. (2000). Technology mapping, business strategy, and market opportunities. Competitive Intelligence Review: Published in Cooperation with the Society of Competitive Intelligence Professionals, 11(1), 46-57.
  • Chun, E., Jun, S., & Lee, C. (2021). Identification of promising smart farm technologies and development of technology roadmap using patent map analysis. Sustainability, 13(19), 10709.
  • Clancy, M., Heisey, P., Ji, Y., & Moschini, G. (2020). The roots of agricultural innovation: Patent evidence of knowledge spillovers. In Economics of Research and Innovation in Agriculture. University of Chicago Press.
  • Dahlborg, C., Lewensohn, D., Danell, R., & Sundberg, C. J. (2017). To invent and let others innovate: A framework of academic patent transfer modes. The Journal of Technology Transfer, 42, 538-563.
  • Dam, M. M., & Yıldız, B. (2016). BRICS-TM ülkelerinde AR-GE ve inovasyonun ekonomik büyüme üzerine etkisi: Ekonometrik bir analiz. Akdeniz İİBF Dergisi, 16(33), 220-236.
  • Dang, J., & Motohashi, K. (2015). Patent statistics: A good indicator for innovation in China Patent subsidy program impacts on patent quality. China Economic Review, 35, 137-155.
  • Dechezleprêtre, A., Ménière, Y., & Mohnen, M. (2017). International patent families: from application strategies to statistical indicators. Scientometrics, 111, 793-828.
  • Dereli, D. D. (2019). The relationship between high-technology exports, patent and economic growth in Turkey (1990-2015). Journal of Business Economics and Finance, 8(3), 173-180.
  • Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.
  • EPO (European Patent Office). (2025). PATSTAT: The EPO Worldwide Patent Statistical Database. https://www.epo.org/en/searching-for-patents/business/patstat (Accessed: 10.04.2025).
  • Ferrari, V. E., da Silveira, J. M. F. J., & Dal-Poz, M. E. S. (2021). Patent network analysis in agriculture: a case study of the development and protection of biotechnologies. Economics of Innovation and New Technology, 30(2), 111-133.
  • Fischer, B. B., Kotsemir, M., Meissner, D., & Streltsova, E. (2020). Patents for evidence-based decision-making and smart specialisation. The Journal of Technology Transfer, 45(6), 1748-1774.
  • Furman, J. L., Porter, M. E., & Stern, S. (2002). The determinants of national innovative capacity. Research Policy, 31(6), 899-933.
  • Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature, 28(4), 1661-1707.
  • Griliches, Z. (1998). Patent statistics as economic indicators: a survey. In R&D and productivity: the econometric evidence (pp. 287-343). University of Chicago Press.
  • Hosking, J. R. (1984). Modeling persistence in hydrological time series using fractional differencing. Water Resources Research, 20(12), 1898-1908.
  • Hu, R., & Xu, W. (2022). Exploring the technological changes of green agriculture in China: evidence from patent data (1998–2021). Sustainability, 14(17), 10899.
  • Jaffe, A. B., & Trajtenberg, M. (2002). Patents, citations, and innovations: A window on the knowledge economy. MIT Press.
  • Karaca, Z. (2021). İllerin Patent Sayısını Etkileyen Faktörler Üzerine Bir Uygulama. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 23(3), 1179-1192.
  • Kırankabeş, M. C., Erçakar, M. E. (2012). Importance of Relationship Between R&D Personnel and Patent Applications on Economics Growth: A Panel Data Analysis. International Research Journal of Finance and Economics, 92, 72-81.
  • Koçakoğlu, M. A., & Bayraktar, Ö. V. (2019). AR-GE harcamaları, patent başvuruları ve yüksek teknoloji içeren ürünlerin ihracat rakamları arasındaki ilişkiye yönelik bir çalışma. İktisadi Yenilik Dergisi, 6(2), 120-128.
  • Leusin, M. E., Günther, J., Jindra, B., & Moehrle, M. G. (2020). Patenting patterns in Artificial Intelligence: Identifying national and international breeding grounds. World Patent Information, 62, 101988.
  • Li, E., Yao, F., Xi, J., & Guo, C. (2018). Evolution characteristics of government-industry-university-research cooperative innovation network for China’s agriculture and influencing factors: Illustrated according to agricultural patent case. Chinese Geographical Science, 28, 137-152.
  • Li, Y., Herzog, F., Levers, C., Mohr, F., Verburg, P. H., Bürgi, M., & Williams, T. G. (2024). Agricultural technology as a driver of sustainable intensification: insights from the diffusion and focus of patents. Agronomy for Sustainable Development, 44(2), 14.
  • Liu, L. J., Cao, C., & Song, M. (2014). China's agricultural patents: How has their value changed amid recent patent boom? Technological Forecasting and Social Change, 88, 106-121.
  • Ma, J., Porter, A.L. (2015). Analyzing patent topical information to identify technology pathways and potential opportunities. Scientometrics 102, 811–827. https://doi.org/10.1007/s11192-014-1392-6
  • Özcan, S. E., & Özer, P. (2017). Ar-Ge Harcamaları ve Patent Başvuru Sayısının Ekonomik Büyüme Üzerindeki Etkileri: OECD Ülkeleri Üzerine Bir Uygulama. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 18(1), 15-28.
  • Özdemir, Y. E., & Yavuz, M. (2021). Yenilenebilir Enerjide Teknoloji Analizi. Avrupa Bilim ve Teknoloji Dergisi, 29, 138-143.
  • Özkurt, İ. C. (2024). Türkiye’de inovasyon faaliyetleri ve ekonomik büyüme ilişkisi: Nedensellik analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 26(1), 164-176.
  • Presidency of the Republic of Turkey Presidency of Strategy and Budget (PSBRT), (2023). The Twelfth Development Plan (2024–2028). www.resmigazete.gov.tr/eskiler/2023/11/20231101M1-1-1.pdf. (Accessed: 10.02.2025).
  • Sandal, N., & Kumar, A. (2015). Integrated silicon photonics: Visualisation of patent datasets for mapping technology. DESIDOC Journal of Library & Information Technology, 35(2), 132-137.
  • Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
  • Sharma, V. K., & Nigam, U. (2020). Modeling and forecasting of COVID-19 growth curve in India. Transactions of the Indian National Academy of Engineering, 5(4), 697-710.
  • Shokouhyar, S., Maghsoudi, M., Khanizadeh, S., & Jorfi, S. (2024). Analyzing supply chain technology trends through network analysis and clustering techniques: a patent-based study. Annals of Operations Research, 341(1), 313-348.
  • Sozzi, M., Cogato, A., Nale, S., & Gatto, S. (2018). Patent trends in agricultural engineering. Proceedings 17th International Scientific Conference" Engineering for Rural Development", 23-25 May 2018, Jelgava, Latvia
  • Tekin, A., & Demirel, O. (2022). Bilimsel ve Teknolojik Performansın Ekonomik Büyümeye Etkisi: OECD Ülkeleri Üzerine Bir Panel Veri Analizi. Sosyoekonomi, 30(51), 353-364.
  • Tey, Y. S., Brindal, M., Wong, S. Y., Ardiansyah, Ibragimov, A., & Yusop, M. R. (2024). Evolution of precision agricultural technologies: a patent network analysis. Precision Agriculture, 25(1), 376-395.
  • Tian, H., Wang, T., Liu, Y., Qiao, X., & Li, Y. (2020). Computer vision technology in agricultural automation—A review. Information Processing in Agriculture, 7(1), 1-19.
  • Wei, T., Jiang, T., Feng, D., & Xiong, J. (2023). Exploring the Evolution of Core Technologies in Agricultural Machinery: A Patent-Based Semantic Mining Analysis. Electronics, 12(20), 4277.
  • Wiśniewski, R. (2011). Identification of nonstationarity type in time series of land property prices in Poland. Studia i Materiały Towarzystwa Naukowego Nieruchomości, 19(1), 33-47.
  • WIPO (World Intellectual Property Organization). (2025). International Patent Classification (IPC). Retrieved June 18, 2025, from https://www.wipo.int/classifications/ipc/en/
  • Yağış, O. (2024). Türkiye’de Teknolojik Yenilikler ve Ekonomik Büyümenin Çevre Kalitesi Üzerindeki Etkileri: Ardl Sınır Testi. Abant Sosyal Bilimler Dergisi, 24(1), 103-117. https://doi.org/10.11616/asbi.1391389
  • Yang, G. C., Li, G., Li, C. Y., Zhao, Y. H., Zhang, J., Liu, T., Chen, D. Z., & Huang, M. H. (2015). Using the comprehensive patent citation network (CPC) to evaluate patent value. Scientometrics, 105, 1319-1346.
  • Yang, W., Yu, X., Zhang, B., & Huang, Z. (2021). Mapping the landscape of international technology diffusion (1994–2017): Network analysis of transnational patents. The Journal of Technology Transfer, 46(1), 138-171.
There are 51 citations in total.

Details

Primary Language English
Subjects Agricultural Policy, Agricultural Economics (Other)
Journal Section Research Articles
Authors

Hüseyin Meral 0000-0002-9003-1518

Yunus Emre Özdemir 0000-0003-0379-5278

Cuma Akbay 0000-0001-7673-7584

Publication Date October 17, 2025
Submission Date April 21, 2025
Acceptance Date July 1, 2025
Published in Issue Year 2025 Volume: 12 Issue: 4

Cite

APA Meral, H., Özdemir, Y. E., & Akbay, C. (2025). Forecasting Patent Trends in the Agricultural Sector Using the ARIMA Model: A Case Study of IPC A01 Class. Turkish Journal of Agricultural and Natural Sciences, 12(4), 1056-1067. https://doi.org/10.30910/turkjans.1680752