Research Article

The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye

Volume: 8 Number: 3 September 29, 2024
EN

The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye

Abstract

The growing development of technology has had an impact on many sectors particularly business, communication, education and agriculture. In addition to its popularity, technology has brought many new concepts to the use of sectors, most of the important of which are cloud computing, artificial intelligence and cryptocurrencies. While the opportunities and concepts provided by technology have destroyed the existing job opportunities, they also introduced many positive opportunities like artificial intelligence, which can be considered as one of such positive innovations. The OECD artificial intelligence data of G7 countries and Turkey were used within the scope of this study. This study analyses the investment opportunities in agriculture and other sectors based on the artificial intelligence data. In addition to this study, both country-based and sectoral comparisons were made respectively. As a result, AI investments in the agricultural sector are generally at a lower level than other sectors. According to the analysis results, countries such as Türkiye and Canada are the countries that invest the most in the agricultural sector. This may reflect these countries' interest in agricultural potential and agricultural technology.

Keywords

Agriculture, G7 countries, artificial intelligence, venture capital investments, OECD.ai

References

  1. Akour, M., & Alenezi, M. (2022). Higher education future in the era of digital transformation. Education Sciences, 12(11), 784.
  2. Al Bashar, M., Taher, M. A., Islam, M. K., & Ahmed, H. (2024). The Impact Of Advanced Robotics And Automation On Supply Chain Efficiency In Industrial Manufacturing: A Comparative Analysis Between The Us And Bangladesh. Global Mainstream Journal of Business, Economics, Development & Project Management, 3(03), 28-41.
  3. Alaimo, C., Kallinikos, J., & Valderrama, E. (2020). Platforms as service ecosystems: Lessons from social media. Journal of information technology, 35(1), 25-48.
  4. Anna, S. (2022). Implementing the OECD AI Principles: Challenges and Best Practices.
  5. Atieh, A. T. (2021). The next generation cloud technologies: a review on distributed cloud, fog and edge computing and their opportunities and challenges. ResearchBerg Review of Science and Technology, 1(1), 1-15.
  6. Atlı, H. F. (2023). Safety of agricultural machinery and tractor maintenance planning with fuzzy logic and MCDM for agricultural productivity. International Journal of Agriculture Environment and Food Sciences, 8(1), 25-43.
  7. Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, 103745.
  8. Bharadiya, J. P. (2023). Machine learning and AI in business intelligence: Trends and opportunities. International Journal of Computer (IJC), 48(1), 123-134.
  9. Canton, H. (2021). Organisation for economic co-operation and development—OECD. In The Europa Directory of International Organizations 2021 (pp. 677-687). Routledge.
  10. Ceglar, A., & Toreti, A. (2021). Seasonal climate forecast can inform the European agricultural sector well in advance of harvesting. Npj Climate and Atmospheric Science, 4(1), 42.
APA
Çağlar, E. (2024). The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye. International Journal of Agriculture Environment and Food Sciences, 8(3), 486-494. https://doi.org/10.31015/jaefs.2024.3.1
AMA
1.Çağlar E. The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye. int. j. agric. environ. food sci. 2024;8(3):486-494. doi:10.31015/jaefs.2024.3.1
Chicago
Çağlar, Ersin. 2024. “The Impact of Sectors on Agriculture Based on Artificial Intelligence Data: A Case Study on G7 Countries and Turkiye”. International Journal of Agriculture Environment and Food Sciences 8 (3): 486-94. https://doi.org/10.31015/jaefs.2024.3.1.
EndNote
Çağlar E (September 1, 2024) The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye. International Journal of Agriculture Environment and Food Sciences 8 3 486–494.
IEEE
[1]E. Çağlar, “The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye”, int. j. agric. environ. food sci., vol. 8, no. 3, pp. 486–494, Sept. 2024, doi: 10.31015/jaefs.2024.3.1.
ISNAD
Çağlar, Ersin. “The Impact of Sectors on Agriculture Based on Artificial Intelligence Data: A Case Study on G7 Countries and Turkiye”. International Journal of Agriculture Environment and Food Sciences 8/3 (September 1, 2024): 486-494. https://doi.org/10.31015/jaefs.2024.3.1.
JAMA
1.Çağlar E. The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye. int. j. agric. environ. food sci. 2024;8:486–494.
MLA
Çağlar, Ersin. “The Impact of Sectors on Agriculture Based on Artificial Intelligence Data: A Case Study on G7 Countries and Turkiye”. International Journal of Agriculture Environment and Food Sciences, vol. 8, no. 3, Sept. 2024, pp. 486-94, doi:10.31015/jaefs.2024.3.1.
Vancouver
1.Ersin Çağlar. The impact of sectors on agriculture based on artificial intelligence data: a case study on G7 countries and Turkiye. int. j. agric. environ. food sci. 2024 Sep. 1;8(3):486-94. doi:10.31015/jaefs.2024.3.1