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Modeling The Determinant Factor of Agricultural Productivity Growth: Small Scale Farmers in Aba Abia State

Dr C.K Okoro & Dr Ehibe, Prince

Abstract

This study investigates the determinants of agricultural productivity growth among small-scale farmers in Aba, Abia State, Nigeria. The study aims to identify key elements that contribute to enhancing agricultural output in the region, considering socio-economic, technological, and environmental aspects. Utilizing an advanced approach, data were collected through structured questionnaires, in-depth interviews, and field observations from a representative sample of small- scale farmers. This analysis employs statistical techniques to quantify the impact of various factors such as access to credit, extension services, farm inputs, land tenure systems, and technological adoption on productivity growth. The findings reveal that access to modern farming techniques, improved seed varieties, and effective extension services significantly boost agricultural productivity. Additionally, socio-economic variables like education level, farm size, and cooperative membership play crucial roles in facilitating productivity improvements. The study highlights the importance of policy interventions aimed at enhancing access to resources, training, and support services for small-scale farmers to sustain agricultural growth. Recommendations are provided for stakeholders, including government agencies, non-governmental organizations, and the private sector, to foster an enabling environment for agricultural productivity advancement in Aba State.

Keywords

Agricultural ProductivitySmall-Scale FarmersDeterminant FactorsExtension

References

Anand A and Nayyar, (2016), Smart farming: IoT based smart sensors agriculture stick for live temperature and moisture monitoring using Arduino, cloud computing & solar technology. The International Conference on Communication and Computing Systems (ICCCS)- November 2016 Andrew Meola, (2016), Why IoT, big data & smart farming are the future of agriculture. An article in business insider. https://www.businessinsider.com/internet-of-things-smart-agriculture- 2016 10 Antonis Tzounis, Nikolaos Katsoulas, Thomas and Bartzanas Constantinos Kittas (2017), Internet of Things in agriculture, recent advances and future challenges. Biosystems Engineering, Volume 164, December 2017, Pages 31-48 Archana A, Kadam and Dr. Rajashekarappa, (2018). Internet of Things in Agriculture International Journal of Advanced Studies of Scientific Research, Volume 3, Issue 8, 2018 Baggio, A. (2005). Wireless Sensor Networks in Precision Agriculture. Delft University of Technology, Vol 1, Pages 1-2. Beckwith, R., Teibel, D., & Bowen, P. (2004). Unwired wine: sensor networks in vineyards. Vol 1, pages 4-5. Bertha Mazon – olivo, Dixys Hernandez-Rojas, Jose Maza Salinas, Alberto Pan (2018), Rules engine and complex evemt processor in the context of internet of things for agriculture. Computers and Electronics in Agriculture P 347-360. Chandra, S., M. (2014). Internet of Things: Challenges and Opportunities. Springer: New York. Eze, C. C., & Nwokocha, L. M. (2018). Soil Mapping and Soil Health Assessment Techniques: A Review. International Journal of Soil Science, 13(1), 1-11. Ibrahim, H., & Mohammed, I. (2017). Internet of Things (IoT) Sensors for Agriculture: Applications and Challenges. International Journal of Computer Applications, 164(4), 38-42. Ogbonna, C. I., & Okeke, A. C. (2021). Farm Management Software and Decision Support Systems in Precision Agriculture: A Review. Journal of Agricultural Informatics, 12(1), 45-58. Okonkwo, C. E., & Eze, C. C. (2018). Precision Agriculture in Nigeria: Challenges and Opportunities. Nigerian Journal of Agriculture, Food, and Environment, 14(2), 45-54. Uzoma, N. A., & Okafor, F. N. (2020). Advances in Remote Sensing Technologies for Crop Monitoring: A Review. International Journal of Agricultural Sciences, 12(3), 237-246.