Influence of Information and Crop Management Practices on Productivity among Smallholder Potato Farmers in North Rift Kenya

  • Charles K. Kamuren ICT Section, KALRO – FCRI, P. O. Box 450 – 30200 Kitale, Kenya
Keywords: Precision Agriculture; Smallholder Potato Farming; Socioeconomics; Climate Smart Agriculture

Abstract

Potato (Solanum tuberosum L) tuber is a major food whose demand is increasing worldwide. Its value-chain in Kenya generates employment for approximately 800,000 farmers and 3.3M citizens. Nonetheless, in spite of dissemination of appropriate technologies, innovations, and management practices (TIMPs), Kenya’s productivity has persisted at lows of 9-15t/Ha compared to Netherland’s 36-42t/Ha. Implementation of field-specific decision support system (DSS) has been proposed as a possible intervention. However, no studies exist showing the influence of prevailing information management (IM) practices on crop management practices. Therefore, in the context of precision agriculture (PA) and the theory of the firm, this study sought to assess, subject to farming duration, the influence of information sources on crop spacing and resultant effect on productivity among smallholder potato farmers in Kenya’s North-Rift highlands. Using stratified random sampling, a survey was conducted on 353 households of whom potato was the main crop and whose farms were located at least 2300masl. Descriptive statistics, linear regression and post-estimation data analysis techniques were employed. Extension services, radio, farmer groups, Internet and telephone usage stood at 62%, 45%, 18%, 6% and 3% respectively while 11% possessed an email address. Regardless of farming duration, in decreasing order, radio and Internet (implicitly) showed positive aggregate influence while farmer groups and extension services showed negative aggregate influence. Notably, all information sources were significantly associated with ‘not known’ seed spacing response with corresponding significant negative effect on productivity. The results demonstrate poor IM and imprecise crop management practices thereby validating the necessity for entrenchment field-specific DSS.

References

Adhiguru, P., Birthal, P. S., & Ganesh, K. B. (2009). Strengthening pluralistic agricultural information delivery systems in India. Agricultural Economics Research Review, 22,, (pp. 71-79).

Amara, A., Traore, N., Landry, R., & Romain, R. (1999). Technical Efficiency and Farmers' Attitudes Towards Technological Innovations: The Case of The Potato Farmers in Quebec. Canadian Jouranal of Agricultural Economics, 47, 31 - 43.

Anderson, J. R. (2007). Background paper for the World Development Report 2008. Washington, DC: Agricultural and Rural Development Department, World Bank.

Arnott, D., & Pervan, G. (2005). A Critical Analysis of Decision Support Systems Research. Journal of Infromation Technology, 20(2), 67 - 85.

Baba, V. V., & HakemZadeh, F. (2012). Towards a Theory of evidence Based Decision Making. Management Decision, 50(5), 832 - 867.

Bhanumurthy, K. V. (2002). Arguing A Case for the Cobb-Douglas Production Function. Review of Commerce Studies, 75 - 91.

Country Government of Uasin Gishu. (2018). County Intergrated Development Plan (CIDP) 2018 - 2022. Eldoret: Country Government of Uasin Gishu.

County Government of Elgeyo Marakwet. (2018). County Intergrated Development Plan CIDP II 2018 - 2022. Iten: County Government of Elgeyo Marakwet.

Dommermuth, H. (1988). PHYTPROH -I: A Warning Service for Combating Late Blight of Potato (Phytophthora Infestans) in the Federal Republic of Germany. Acta Horticulturae, (214),, 171 – 178. doi:10.17660/actahortic.1988.214.13

FAO. (2018). The future of food and agriculture – Alternative pathways to 2050. Rome. Retrieved 12 23, 2021, from https://www.fao.org/: https://www.fao.org/global-perspectives-studies/food-agriculture-projections-to-2050/en/

FAO. (2020). http://www.fao.org/faostat/en/#data/QC/visualize. Retrieved from http://www.fao.org/: http://www.fao.org/faostat/en/#data/QC/visualize

Ferroni, M., & Zhou, Y. (2012). Achievements and Challenges in Agricultural Extension in India. Global Journal of Emerging Market Economies, 4(3) 319–346.

Franklin, C. L. (2013). Developing Expertise in Management Decision Making. Academy of Strategic Management Journal, 12(1), 21 - 36.

Gibbons, G. (2000). Turning a Farm Art into Science - an Overview of Precision Farming. Retrieved from http://www.precisionfarming.com: http://www.precisionfarming.com

Gujarati, N. D., & Porter, C. D. (2009). Basic Econometrics (5th ed.). New York: McGraw-Hill/ Irwin.

Hamzah, M., Sobey, A., & Koronios, A. (2010). Supporting Decision making Process with Information Visualization: A Theoretical Framework. Second IEEE International Conference on Information Management and Engineering (ICIME).

KIPPRA. (2019). Education and Training Budget Brief. Naiorbi: KIPPRA. Retrieved from https://www.unicef.org/esa/sites/unicef.org.esa/files/2019-03/UNICEF-Kenya-2018-Education-Budget-Brief.pdf

Malmgren, H. B. (1961). Information, Expectations and the Theory of the Firm. The Quarterly Journal of Economics, 75(3), 399-421. Retrieved from http://www.jstor.org/stable/1885131

Mansouri, S. A., Gallear, D., & Askariazad, M. (2012). Decision Support for Build-to-Order Supply Chain Management Through Multiobjective Optimization. International Journal of Production Economics, 135(1), 24 - 36. doi:http://dx.doi.org/10.1016/j.ijpe.2010.11.016

McBratney, A., Whelan, B., & Ancev, T. (2005). Future Directions of Precision Agriculture. 7th International Conference on Precision Agriculture. 6, pp. 7 - 23. Minneapolis, USA: Springer Science+Business Media Inc.

Mittal, S., Gandhi, S., & Tripathi, G. (2010). Socio-economic Impact of Mobile Phone on Indian Agriculture. (p. Working Paper no. 246). New Delhi: International Council for Research on International Economic Relations.

MoALF. (2016). The National Potato Strategy. Nairobi: Agricultural Information Resource Center.

MoALF. (2018, April 15). Climate Risk Profile for Elgeyo Marakwet County, Kenya County Climate Risk Profile Series. Nairobi: The Kenya Ministry of Agriculture, Livestock and Fisheries (MoALF). Retrieved from https://cgspace.cgiar.org/: https://cgspace.cgiar.org/bitstream/handle/10568/96285

Nenkari, H., Gakuru, M., Mulagoli, I., & Kabutha, C. (2010). http://iaald2010.agropolis.fr/proceedings/poster/NENKARI-2010-Extension_services_through_Mobile_telephony_and_internet-IAALD-Congress-158.pdf. Retrieved from http://iaald2010.agropolis.fr/: http://iaald2010.agropolis.fr/proceedings/poster/NENKARI-2010-Extension_services_through_Mobile_telephony_and_internet-IAALD-Congress-158.pdf

Nonaka, I., Toyama, R., & Nagata, A. (2000). A Firm as a Knowledge-creating Entity: A New Perspective on the Theory of the Firm. Industrial and Corporate Change, 9(1), 932 - 1292.

Obare, A. G., Nyagaka, D. O., Omiti, J. M., & Nguyo, W. (2010). Technical Efficiency in Resource Use: Evidence from Smallholder Irish Potato Farmers in Nyandarua North District, Kenya. African Journal of Agricultural Research Vol. 5(11), pp. 1179-1186, 4 June, 2010, 5(11), 1179 - 1186. Retrieved from http://www.academicjournals.org/AJAR

Raabe, K. (2008). Reforming the agricultural extension system in India—What do we know about what works where and why? Department Strategy and Governance Division, IFPRI. (p. IFPRI Discussion Paper 00775. ). Washington, DC.: Department Strategy and Governance Division, IFPRI.

Shibusawa, S. (1998). Precision Farming and Terra-Mechanics. 5th ISTVS Asia-Pacific Regional Conference in Korea, (pp. 20 - 22). Korea.

Simon, H. A. (1945). Administrative Behaviour. New York: Macmillan.

Stafford, J. V. (2000). Implementing Precision Agriculture in the 21st Centrury. Journal of Agricultural Engineering Research, 76, 267 - 275.

Swanson, B. E. (2009). Changing extension paradigms within a rapidly changing global economy. Retrieved from www.agraria.unipg.it: http://www.agraria.unipg.it/ESEE2009PERUGIA/files/Proceedings.pdf

Taechatanasat, P., & Armstrong, L. (2014). Decision Support System Data for Farmer Decision Making. Proceedings of Asian Federation for Information Technology in Agriculture, (pp. 472 - 486). Perth, W.A. Australia. Retrieved from https://ro.ecu.edu.au/ecuworkspost2013/855

Turban, E., Aronson, J. E., & LIang, T. P. (2005). Decision Support Systems and Intelligent Systems (7th ed.). New Jersey, USA: Pearson Prentice Hall.

Vos, J. (1992). A Case History: Hundred Years of Potato Production in Europe With Special Reference to the Netherlands. American Potato Journal, 69, 731 - 751. doi:10.1007/BF02853816

Wang'ombe, J. G., & Djik, M. P. (2013). Low Potato Yields in Kenya: Do Conventional Input Innovations Account for the Yields Disparity? Agriculture & Food Security 2013, 2 - 14. Retrieved from http://www.agricultureandfoodsecurity.com/content/2/1/14

Whelan, B. M., McBratney, A. B., & Boydell, B. C. (1997). The Impact of Precision Agriculture. Proceedings of the ABARE Outlook Conference, 'The Future of Cropping in NW NSW, (p. 5). Moree, UK.

Williamson, O. E. (1975). Markets and Hierarchies: Analysis and Antitrust Implications. New York: Free Press.

Williamson, O. E. (1985). The Economic Institutions of Capitalism. New York: Free Press.

Yamane, T. (1967). Statistics: An Introductory Analysis (2nd ed.). New York: Harper and Row.

Zhang, N., Wang, M., & Wang, N. (2002). Precision Agriculture - a Worldwide Overview. Computers and Electronics in Agriculture, 36, 113 - 132.
Published
2023-04-07
How to Cite
Kamuren, C. (2023, April 7). Influence of Information and Crop Management Practices on Productivity among Smallholder Potato Farmers in North Rift Kenya. African Journal of Education,Science and Technology, 7(3), Pg 174-186. https://doi.org/https://doi.org/10.2022/ajest.v7i3.838
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Articles