International Journal of Agricultural Economics

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Determinants of Adoption of Improved Cocoa Technologies in Ekiti State, Nigeria

Received: Feb. 28, 2020    Accepted: Mar. 17, 2020    Published: Apr. 01, 2020
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Abstract

The study investigated the determinants of adoption of improved cocoa technologies in Ekiti State, Nigeria. Specifically, it examined the socio economic characteristics of the cocoa farmers in the study area; identified the various technologies practiced by cocoa farmers in the study area and determined the intensity of adoption of improved technologies. A multi-stage sampling technique was used to select eighty (80) respondents in four (4) local government areas namely: Ise/Orun LGA, Irepodun Ifelodun LGA, Oye LGA and Ekiti South-West LGA; which were predominated with cocoa farmers. Tobit model was used to examine the determinants and intensity of adoption of improved cocoa technologies. At 5% level of significance, variables that positively and significantly influence adoption of improved cocoa technologies include sex, level of education, source of information and visit by the extension agents; meaning they were important in the adoption of improved cocoa technologies and raises the probability of adoption by 9.14, 2.97, 2.98 and 3.94%. The age of the cocoa farmers; family size and the farm size were not significant and have negative coefficients meaning increase in these factors will reduce the likelihood of cocoa farmers adopting the improved techniques. Result of budgeting analysis implies a better performance of the adopters of improved cocoa technologies whereby the benefit cost ratio for the adopters and non-adopters of improved cocoa technologies were 3.50 and 1.26 respectively.

DOI 10.11648/j.ijae.20200502.11
Published in International Journal of Agricultural Economics ( Volume 5, Issue 2, March 2020 )
Page(s) 36-42
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Adoption, Intensity, Cocoa, Determinants, Benefit Cost Ratio, Adopters, Non-adopters, Budgeting Analysis

References
[1] Adegeye A. J, (1997). Paper on production and Marketing of Cocoa in Nigeria: Problems and Solutions, pp: 1 – 10. Agricultural Credit Guarantee Scheme Report, (2011).
[2] Ajayi, S. I and Oyejide T. A. (1974). The Role of Cocoa in Nigeria’s Economic Development: In Kotey, R. A., C. Okali and Rourke B. E. (Eds). The Economics of Cocoa Economics Research Conference, Legon, Ghana, April 1973. 232, Pp: 206-230.
[3] Akinbola C. A. (2001). International Project on Cocoa Marketing and Trade in Nigeria. Manual on Cocoa Quality and Training Manual for Extension Workers. Pp: 10-24.
[4] Altalb, A. A. T., Filipek, T. and Skowron, P. (2015). The Role of Agricultural Extension in the Transfer and Adoption of Agricultural Technologies. Asian Journal of Agriculture and Food Sciences (ISSN: 2321 – 1571) Volume 03.
[5] Ayoola, G. R. (1990). “Technology Progress in Agriculture; Some Issues” in Conference proceeding, Nigerian Economic Society, Minna Nigeria. Pp. 205-223.
[6] Falusi, A. O. (2008). “Sustainable Agriculture in Sub-Saharan Africa: A Critical Look into the Constraints and Prospects “Being Paper Presented at IARSAF Conference, IITA, Ibadan.
[7] Feder, L., Just R. E. and Zilberman O. (1985). Adoption of Agricultural Innovation, in Developing Countries: A Survey. Economic Development and Cultural Change, 32 (2): 255-298.
[8] Folayan, J. A., Daramola, A. G. & Oguntade, A. E. (2006). Structure and Performance Evaluation of Cocoa Marketing Institutions in South-Western Nigeria: An Economic Analysis. Journal of Food, Agriculture and Environment, 4 (2), 123-128.
[9] ICCO (2003). International Cocoa Organization’s Quarterly Bulletin of Cocoa Statistics, www.icco.com/cocoa stat, retrieved on 23/07/10.
[10] Johnston, J. And Dinardo, J. (1997). Econometrics Methods. Fourth Edition. The McGraw-Hill Companies, Inc, New York.
[11] Lawal J. O. and Oluyole K. A. (2008). Factors Influencing Adoption of Research Results and Agricultural Technologies Among Cocoa Farming Households in Oyo State, Nigeria. Int. J. Sustain. Crop Prod. 3 (5): 10-12.
[12] Monu E. D. And Omole M. A. (1983). Adoption of Recommended Farm Practices by Nigerian Cocoa Farmers., Nigerian J. AgricExtn 1 (2), 45-53.
[13] National Population Commission, (2006) Census. Federal Republic of Nigeria, December, 2006.
[14] Nweke F. I. And Akorhe J. A. (1983). Determinants Of Adoption Of New Technologies Among Smallholders And Implication For Administration Of Transfer Programmes. Agricultural Administration. 12, 77-90.
[15] Oladosu, I. O. and. Yekinni O. T (2008) An Assessment of Agricultural Extension Activities to Cocoa Farmers in Ekiti West Local Government Area of Ekiti State International Journal of Agricultural Economics & Rural Development - 1 (2): 2008© IJAERD, 2008.
[16] Oluyole K. A., Egbetokun O. A., Oni O. A., andAigbekaen E. O. (2011) Technological Changes and Labour Demand among Cocoa Farmers in Nigeria 1 Cocoa Research Institute of Nigeria, P. M. B. 5244, Ibadan, NigeriaWorld Journal of Agricultural Sciences 7 (5): 638-641, 2011 ISSN 1817-3047 © IDOSI Publications, 2011.
[17] Opeke L. K. (1987). Tropical Tree crops. Ibadan: Spectrum Books Ltd., pp. 108-120.
[18] Uwatt B. U. (1997). Technology Agricultural Productivity and Food Security in Akwa- Ibom state, Nigeria: Interim Report, ARSSRAN, Winrock International, USA
[19] Wessel, M. and P. M. F. Quist-Wessel (2015). Cocoa production in West Africa, a review and analysis of recent developments, NJAS-Wageningen Journal of Life Sciences 74-75 (2015) 1-7.
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  • APA Style

    Julius Olumide Ilesanmi, Jimoh Atanda Afolabi. (2020). Determinants of Adoption of Improved Cocoa Technologies in Ekiti State, Nigeria. International Journal of Agricultural Economics, 5(2), 36-42. https://doi.org/10.11648/j.ijae.20200502.11

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    Julius Olumide Ilesanmi; Jimoh Atanda Afolabi. Determinants of Adoption of Improved Cocoa Technologies in Ekiti State, Nigeria. Int. J. Agric. Econ. 2020, 5(2), 36-42. doi: 10.11648/j.ijae.20200502.11

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    AMA Style

    Julius Olumide Ilesanmi, Jimoh Atanda Afolabi. Determinants of Adoption of Improved Cocoa Technologies in Ekiti State, Nigeria. Int J Agric Econ. 2020;5(2):36-42. doi: 10.11648/j.ijae.20200502.11

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  • @article{10.11648/j.ijae.20200502.11,
      author = {Julius Olumide Ilesanmi and Jimoh Atanda Afolabi},
      title = {Determinants of Adoption of Improved Cocoa Technologies in Ekiti State, Nigeria},
      journal = {International Journal of Agricultural Economics},
      volume = {5},
      number = {2},
      pages = {36-42},
      doi = {10.11648/j.ijae.20200502.11},
      url = {https://doi.org/10.11648/j.ijae.20200502.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijae.20200502.11},
      abstract = {The study investigated the determinants of adoption of improved cocoa technologies in Ekiti State, Nigeria. Specifically, it examined the socio economic characteristics of the cocoa farmers in the study area; identified the various technologies practiced by cocoa farmers in the study area and determined the intensity of adoption of improved technologies. A multi-stage sampling technique was used to select eighty (80) respondents in four (4) local government areas namely: Ise/Orun LGA, Irepodun Ifelodun LGA, Oye LGA and Ekiti South-West LGA; which were predominated with cocoa farmers. Tobit model was used to examine the determinants and intensity of adoption of improved cocoa technologies. At 5% level of significance, variables that positively and significantly influence adoption of improved cocoa technologies include sex, level of education, source of information and visit by the extension agents; meaning they were important in the adoption of improved cocoa technologies and raises the probability of adoption by 9.14, 2.97, 2.98 and 3.94%. The age of the cocoa farmers; family size and the farm size were not significant and have negative coefficients meaning increase in these factors will reduce the likelihood of cocoa farmers adopting the improved techniques. Result of budgeting analysis implies a better performance of the adopters of improved cocoa technologies whereby the benefit cost ratio for the adopters and non-adopters of improved cocoa technologies were 3.50 and 1.26 respectively.},
     year = {2020}
    }
    

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    AB  - The study investigated the determinants of adoption of improved cocoa technologies in Ekiti State, Nigeria. Specifically, it examined the socio economic characteristics of the cocoa farmers in the study area; identified the various technologies practiced by cocoa farmers in the study area and determined the intensity of adoption of improved technologies. A multi-stage sampling technique was used to select eighty (80) respondents in four (4) local government areas namely: Ise/Orun LGA, Irepodun Ifelodun LGA, Oye LGA and Ekiti South-West LGA; which were predominated with cocoa farmers. Tobit model was used to examine the determinants and intensity of adoption of improved cocoa technologies. At 5% level of significance, variables that positively and significantly influence adoption of improved cocoa technologies include sex, level of education, source of information and visit by the extension agents; meaning they were important in the adoption of improved cocoa technologies and raises the probability of adoption by 9.14, 2.97, 2.98 and 3.94%. The age of the cocoa farmers; family size and the farm size were not significant and have negative coefficients meaning increase in these factors will reduce the likelihood of cocoa farmers adopting the improved techniques. Result of budgeting analysis implies a better performance of the adopters of improved cocoa technologies whereby the benefit cost ratio for the adopters and non-adopters of improved cocoa technologies were 3.50 and 1.26 respectively.
    VL  - 5
    IS  - 2
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Author Information
  • Department of Agricultural and Resource Economics, School of Agriculture and Agricultural Technology, Federal University of Technology, Akure, Nigeria

  • Department of Agricultural and Resource Economics, School of Agriculture and Agricultural Technology, Federal University of Technology, Akure, Nigeria

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