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Assessing the Impact of AI-Powered Agricultural Extension Systems on Farm Productivity and Decision-Making among Smallholder Farmers

Ladejo Yomi

Subject area: Agriculture and Veterinary Sciences  ·  Area of research: AI in Agricultural Extension Systems

DOI: https://doi.org/10.64388/IREV8I2-1715335

Abstract

Digital technologies are moving fast and offering new ways to boost farm output and strengthen support for smallholder farmers in developing areas. These systems often struggle with little money, few staff, and difficulty reaching remote villages, which keeps farmers from getting timely advice. At least in theory, AI-driven tools offer real-time, data-based recommendations tailored to individual farms. This research looks at how such systems affect productivity and farmer choices. A survey gathered responses from smallholder farmers across different regions. The data were analyzed using basic stats and regression models to see how using AI extension services connects with farm results. Results show awareness of these tools is average, but actual use stays low because of poor digital skills, weak internet, and lack of smartphones or tablets. Still, farmers who use the services report better crop results and improved access to farming knowledge. Thing is, getting more farmers involved still depends on solving real-world access issues. The benefits exist, but theyre not reaching everyone yet. Small farms often face hurdles that go beyond just technology. Access to reliable power and devices remains a big gap. Turned out, many farmers simply dont have the chance to start using these tools regularly.

Keywords

Artificial Intelligence, Agricultural Extension Systems, Farm Productivity, Smallholder Farmers, Digital Agriculture, Decision-Making.

References

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[9] Rose, D.C. & Chilvers, J., 2018. Agriculture 4.0: Broadening responsible innovation in an era of smart farming. Frontiers in Sustainable Food Systems, 2, pp.1–7.

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[12] Zhang, Q., Chen, Y., Wang, S. & Li, Z., 2020. Applications of artificial intelligence in agriculture: A review. Agricultural Engineering International: CIGR Journal, 22(2), pp.1–15.

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How to cite this paper

Ladejo Yomi "Assessing the Impact of AI-Powered Agricultural Extension Systems on Farm Productivity and Decision-Making among Smallholder Farmers" Iconic Research And Engineering Journals Volume 8 Issue 2 2024 Page 1317-1324 https://doi.org/10.64388/IREV8I2-1715335
Ladejo Yomi "Assessing the Impact of AI-Powered Agricultural Extension Systems on Farm Productivity and Decision-Making among Smallholder Farmers" Iconic Research And Engineering Journals, vol. 8, no. 2, Aug. 2024, doi: https://doi.org/10.64388/IREV8I2-1715335
Ladejo Yomi (2024). Assessing the Impact of AI-Powered Agricultural Extension Systems on Farm Productivity and Decision-Making among Smallholder Farmers. Iconic Research And Engineering Journals, 8(2). doi: https://doi.org/10.64388/IREV8I2-1715335
Ladejo Yomi "Assessing the Impact of AI-Powered Agricultural Extension Systems on Farm Productivity and Decision-Making among Smallholder Farmers" Iconic Research And Engineering Journals, vol. 8, no. 2, Aug. 2024. Crossref, https://doi.org/10.64388/IREV8I2-1715335
@article{1715335,
      author = {Ladejo Yomi},
      title = {Assessing the Impact of AI-Powered Agricultural Extension Systems on Farm Productivity and Decision-Making among Smallholder Farmers},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {2},
      pages = {1317-1324},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715335.pdf},
      abstract = {Digital technologies are moving fast and offering new ways to boost farm output and strengthen support for smallholder farmers in developing areas. These systems often struggle with little money, few staff, and difficulty reaching remote villages, which keeps farmers from getting timely advice. At least in theory, AI-driven tools offer real-time, data-based recommendations tailored to individual farms. This research looks at how such systems affect productivity and farmer choices. A survey gathered responses from smallholder farmers across different regions. The data were analyzed using basic stats and regression models to see how using AI extension services connects with farm results. Results show awareness of these tools is average, but actual use stays low because of poor digital skills, weak internet, and lack of smartphones or tablets. Still, farmers who use the services report better crop results and improved access to farming knowledge. Thing is, getting more farmers involved still depends on solving real-world access issues. The benefits exist, but theyre not reaching everyone yet. Small farms often face hurdles that go beyond just technology. Access to reliable power and devices remains a big gap. Turned out, many farmers simply dont have the chance to start using these tools regularly.},
      keywords = {Artificial Intelligence, Agricultural Extension Systems, Farm Productivity, Smallholder Farmers, Digital Agriculture, Decision-Making.},
      month = {August},
      doi = {https://doi.org/10.64388/IREV8I2-1715335}
  }