Skip to main content

Advertisement

SpringerLink
Log in

Evolution of Fertiliser Use and its Impact on Maize Productivity in Kenya: Evidence from Multiple Surveys

  • Original Paper
  • Published:
Food Security Aims and scope Submit manuscript

Abstract

During the 1990s, the Kenyan agricultural sector became increasingly liberalised. For many years, both government- and non-government organisations have advised farmers on fertiliser doses, and therefore, an increase in fertiliser adoption resulting in higher yields has been expected. We analyse the evolution of fertiliser use and its impact on maize productivity and household incomes in Kenya, using four household surveys conducted between 1992 and 2013. Each survey represented all six maize-producing zones of Kenya. The results show that the percentage of fertiliser users among maize farmers has increased slightly over the years (from 62% in 1992 to 65% in 2013), and the quantity of fertiliser applied per ha has increased (from 82 kg/ha in 1992 to 100 kg/ha in 2013) but remains far below recommended levels. Therefore, maize yields have remained stagnant, or even decreased slightly (from 1360 kg/ha in 1992 to 1116 kg/ha in 2013). We also observe that the following factors affect fertiliser use and maize yields: education of the household head; area under maize cultivation; agroecological zone; uneven access to extension services; and food insecurity. We also find that fertiliser use has a positive impact on both maize yields and household income. We conclude that the liberalisation of fertiliser markets in Kenya did not have the desired effect of increasing fertiliser use and consequently maize yields, except in the high potential maize-growing areas. Possible explanations include both market factors, e.g. high prices, and non-market factors, e.g. access to information. We make two policy recommendations based on these findings – firstly, the targeted outreach of extension services should be considered, to increase fertiliser use and yields in less-productive regions, and secondly, policies should be considered that incorporate provisions for weather shocks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data Availability

The dataset is available as a separate Stata file.

Notes

  1. The HFIAS variable (household food insecurity access scale) used in the regression is a quantitative indicator of food insecurity constructed from the responses to nine occurrence questions that represent a generally increasing level of severity of food insecurity (access) (from “In the past four weeks, did you worry that your household would not have enough food?” to “In the past four weeks, did you or any household member go a whole day and night without eating anything because there was not enough food?”), and nine “frequency-of-occurrence” questions that are asked as a follow-up to each occurrence question to determine how often the condition occurred (Coates et al. 2007).

References

  • Allison, P. D. (2005). Fixed Effects Regression Methods for Longitudinal Data Using SAS. Cary, NC: The SAS Institute.

    Google Scholar 

  • Ariga, J., & Jayne, T, S. (2009). Private Sector Responses to Public Investments and Policy Reforms The Case of Fertiliser and Maize Market Development in Kenya. IFPRI discussion papers (Vol. 00921).

  • Ariga, J., & Jayne, T. S. (2011). Fertiliser in Kenya: Factors Driving the Increase in Usage by Smallholder Farmers. In P. Chuhan-Pole & M. Angwafo (Eds.), Yes Africa Can: Success Stories from a Dynamic Continent (pp. 269–288). Washington, DC: World Bank.

    Google Scholar 

  • Berazneva, J., McBride, L., Sheahan, M., & Güereña, D. (2018). Empirical assessment of subjective and objective soil fertility metrics in east Africa: Implications for researchers and policy makers. World Development, 105, 367–382.

    Article  Google Scholar 

  • Binswanger-Mkhize, H. P., & Savastano, S. (2017). Agricultural intensification: the status in six African countries. Food Policy, 67, 26–40.

    Article  Google Scholar 

  • Bumb, B. L., & Gregory, D. I. (2006). Factors affecting supply for fertiliser in Sub-Saharan Africa Agriculture and Rural Development Discussion Paper (Vol. 24, pp. 1-81). Washington, DC: World Bank.

    Google Scholar 

  • CBS (2001). 1999 Population and Housing Census. Volume 1. Population Distribution by Administrative Areas and Urban Nairobi, Kenya: Central Bureau of Statistics (CBS), Ministry of Planning and National Development.

  • Coates, J., Swindale, A., & Bilinsky, P. (2007). Household Food Insecurity Access Scale (HFIAS) for Measurement of Food Access: Indicator Guide. Food and Nutrition Technical Assistance III Project (FANTA), 3, 1–34.

    Google Scholar 

  • De Groote, H., Owuor, G., Doss, C., Ouma, J., Muhammad, L., & Danda, K. (2005). The Maize Green Revolution in Kenya Revisited. Electronic Journal of Agricultural and Development Economics (eJADE), 2(1), 32–49.

    Google Scholar 

  • De Groote, H., Narrod, C., Kimenju, S., Bett, C., Scott, R., & Tiongco, M. (2016). Measuring rural consumers’ willingness to pay for quality labels using experimental auctions: the case of aflatoxin free maize in Kenya. Agricultural Economics, 47(1), 33–45. https://doi.org/10.1111/agec.12207/.

    Article  Google Scholar 

  • De Groote, H., Marangu, C., & Gitonga, Z. M. (2018). Trends in Agricultural Mechanization in Kenya’s Maize Production Areas from 1992-2012. Agricultural Mechanization in Asia, Africa and Latin America, 49(4), 20.

  • De Groote, H., Kimenju, S, C., Munyua, B., Palmas, S., Kassie, M., & Bruce, A. (2020). Spread and impact of fall armyworm (Spodoptera frugiperda J.E. Smith) in maize production areas of Kenya. Agriculture, Ecosystems & Environment, 292, doi:https://doi.org/10.1016/j.agee.2019.106804.

  • Duflo, E., Kremer, M., & Robinson, J. (2007). Why are Farmers Not Using Fertiliser: Fertiliser in Western Kenya, Preliminary Results from Field Experiments. Mimeo. Boston: MIT.

  • Duflo, E., Kremer, M., & Robinson, J. (2008). How High Are Rates of Return to Fertiliser? Evidence from Field Experiments in Kenya. American Economic Review, 98(2), 482–488. https://doi.org/10.1257/aer.98.2.482.

    Article  Google Scholar 

  • FAO (2009). The state of food insecurity in the world 2009. Food and Agriculture Organization, United Nations, International Fund for Agricultural Development, and World Food Programme, Rome

  • FAO (2014). The state of food insecurity in the world 2014. Food and Agriculture Organization, United Nations, International Fund for Agricultural Development, and World Food Programme, Rome

  • FAO (2019). FAOSTAT Crops. In Food and Agricultutal Organisation of the United Nations (Ed.). Rome

  • FAOSTAT (2020a). FAOSTAT Food Supply - Crops Primary Equivalent, http://www.fao.org/faostat/en/#data/CC, accessed on June 9, 2020.

  • FAOSTAT (2020b). FAOSTAT Production Data Base. URL: http://faostat.fao.org/site/339/default.aspx, accessed on June 9, 2020.

  • Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., & Toulmin, C. (2010). Food security: the challenge of feeding 9 billion people. Science, 327(5967), 812–818.

    Article  CAS  Google Scholar 

  • Greene, W, H. (2012). Econometric Analysis, 7th Edition (6th Edition ed.). Boston, MA: Prentice Hall.

  • Gregory, P. J., & George, T. S. (2011). Feeding nine billion: the challenge to sustainable crop production. Journal of Experimental Botany, 62(15), 5233–5239. https://doi.org/10.1093/jxb/err232.

    Article  CAS  PubMed  Google Scholar 

  • Hassan, R. (1998). Maize Technology Development and Transfer: A GIS Application for Research in Planning in Kenya. Oxon, UK Mexico Nairobi, Kenya: Centre for Agricultural Bioscience International (CABI) International Maize and Wheat Improvement Center (CIMMYT) KARI.

  • Hassan, R, M., Lynam, J., & Okoth, P. (1998). Maize Technology Development and Transfer. A GIS Application for Research Planning in Kenya. Oxon: CAB International.

  • Henao, J., & Baanante, C. A. (1999). Nutrient depletion in the agricultural soils of Africa. In 2020 Brief 62. Washinton DC: International Food Policy Research Institute (IFPRI).

    Google Scholar 

  • IFDC (2007). Africa Fertiliser Summit proceedings: June 9–13, 2006, Abuja, Nigeria. Alabama, USA International Fertiliser Development Center (IFDC).

  • Jaleta, M., Kassie, M., Tesfaye, K., Teklewold, T., Jena, P. R., Marenya, P., & Erenstein, O. (2016). Resource saving and productivity enhancing impacts of crop management innovation packages in Ethiopia. Agricultural Economics, 47(5), 513–522. https://doi.org/10.1111/agec.12251.

    Article  Google Scholar 

  • Jayne, T, S., Yamano, T., Nyoro, J, K., & Awour, T. (2001). Do Farmers Really Benefit from High Food Prices? Balancing Rural Interests in Kenya’s Maize Pricing and Marketing Policy. Working Papers 202678 (pp. 1-6): Egerton University, Tegemeo Institute of Agricultural Policy and Development.

  • Jena, P. R. (2019). Can minimum tillage enhance productivity? Evidence from smallholder farmers in Kenya. Journal of Cleaner Production, 218, 465–475. https://doi.org/10.1016/j.jclepro.2019.01.278.

    Article  Google Scholar 

  • Jena, P, R., & Odendo, M. (2014). Assessment of the maize situation, outlook and investment opportunities in Eastern and Southern Africa (Regional Synthesis -Regional Assessment Eastern and Southern Africa). Nairobi: International Maize and Wheat Improvement Center.

  • Jena, P. R., Stellmacher, T., & Grote, U. (2017). Can coffee certification schemes increase incomes of smallholder farmers? Evidence from Jinotega, Nicaragua. Environment, Development and Sustainability, 19(1), 45–66. https://doi.org/10.1007/s10668-015-9732-0.

    Article  Google Scholar 

  • Kassie, M., Teklewold, H., Marenya, P., Jaleta, M., & Erenstein, O. (2015). Production Risks and Food Security under Alternative Technology Choices in Malawi: Application of a Multinomial Endogenous Switching Regression. Journal of Agricultural Economics, 66(3), 640–659. https://doi.org/10.1111/1477-9552.12099.

    Article  Google Scholar 

  • Kenya Agricultural Research Institute (1995). Fertiliser Use Recommendations Volume 15 Kericho District Fertiliser Use Recommendation Project (FURP) (pp. 1–20): Kenya Agricultural Research Institute (KARI).

  • Kibunja, C. N., Ndungu-Magiroi, K. W., Wamae, D. K., Mwangi, T. J., Nafuma, L., Koech, M. N., et al. (2017). Optimizing Fertiliser Use within the Context of Integrated Soil Fertility Management in Kenya. In C. S. Wortmann & K. Sones (Eds.), Fertiliser use optimization in sub-Saharan Africa (pp. 82-99). Wallingford, UK: CABI.

    Google Scholar 

  • Kleemann, L., Abdulai, A., & Buss, M. (2014). Certification and Access to Export Markets: Adoption and Return on Investment of Organic-Certified Pineapple Farming in Ghana. World Development, 64, 79–92. https://doi.org/10.1016/j.worlddev.2014.05.005.

    Article  Google Scholar 

  • Lokshin, M., & Sajaia, Z. (2004). Maximum likelihood estimation of endogenous switching regression models. The Stata Journal, 4(3), 282–289.

    Article  Google Scholar 

  • Maddala, G. S. (1983). Limited-dependent and qualitative variables in econometrics. New York: Cambridge University Press.

    Book  Google Scholar 

  • Makau, J. M., Irungu, P., Nyikal, R. A., & Kirimi, L. W. (2016). An assessment of the effect of a national fertiliser subsidy programme on farmer participation in private fertiliser markets in the North Rift region of Kenya. African Journal of Agricultural and Resource Economics, 11(4), 292–304. https://doi.org/10.22004/ag.econ.252459.

    Article  Google Scholar 

  • Mather, D. L., & Jayne, T. S. (2018). Fertiliser subsidies and the role of targeting in crowding out: evidence from Kenya. Food Security, 10(2), 397–417.

    Article  Google Scholar 

  • Matsumoto, T., & Yamano, T. (2009). Soil Fertility, Fertiliser, and the Maize Green Revolution in East Africa. [Journal Article]. Policy Research Working Paper. World Bank, Washington, DC.(5158), 1-34, doi:https://doi.org/10.1596/1813-9450-5158.

  • Morris, M., Kelly, V. A., Kopicki, R. J., & Byerlee, D. R. (2007). Fertiliser use in African agriculture: Lessons learned and good practice guidelines (Directions in development). Washington, DC: World Bank.

    Book  Google Scholar 

  • Olwande, J., Sikei, G., & Mathenge, M. (2009). Agricultural technology adoption: A panel analysis of smallholder farmers’ fertiliser use in Kenya. . CEGA Working Paper Series No. AfD0908.

  • Schnier, H. F., Recke, H., Muchena, F. N., & Muriuki, A. W. (1996). Towards a practical approach to fertiliser recommendations for food crop production in smallholder farms in Kenya. Nutrient Cycling in Agroecosystems, 47(3), 213–226. https://doi.org/10.1007/BF01986276.

    Article  Google Scholar 

  • Sheahan, M., Black, R., & Jayne, T. S. (2013). Are Kenyan farmers under-utilizing fertiliser? Implications for input intensification strategies and research. Food Policy, 41, 39–52. https://doi.org/10.1016/j.foodpol.2013.04.008.

    Article  Google Scholar 

  • Smaling, E. M. A., Nandwa, S. M., Prestele, H., Roetter, R., & Muchena, F. N. (1992). Yield response of maize to fertilisers and manure under different agroecological conditions in Kenya. Agriculture, Ecosystems & Environment, 41(3–4), 241–252. https://doi.org/10.1016/0167-8809(92)90113-P.

    Article  Google Scholar 

  • Takeshima, H., & Lee, H, L. (2012). Agricultural Inputs Subsidy and Their Developmental Impact: Conventional Wisdom. MozSSP Policy Note 1. Washington, D.C.: IFPRI Policy Note 1, October 2012. Washington DC, IFPRI. Tsulostettu 25.11 ….

  • Teklewold, H., Kassie, M., Shiferaw, B., & Köhlin, G. (2013). Cropping system diversification, conservation tillage and modern seed adoption in Ethiopia: Impacts on household income, agrochemical use and demand for labor. Ecological Economics, 93, 85–93. https://doi.org/10.1016/j.ecolecon.2013.05.002.

    Article  Google Scholar 

  • Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R., & Polasky, S. (2002). Agricultural sustainability and intensive production practices. Nature, 418(6898), 671–677.

    Article  CAS  Google Scholar 

  • Tully, K. L., Hickman, J., McKenna, M., Neill, C., & Palm, C. A. (2016). Effects of fertiliser on inorganic soil N in East Africa maize systems: vertical distributions and temporal dynamics. Ecological Applications, 26(6), 1907–1919. https://doi.org/10.1890/15-1518.1.

    Article  PubMed  Google Scholar 

  • Vanlauwe, B., & Giller, K. E. (2006). Popular myths around soil fertility management in sub-Saharan Africa. Agriculture, Ecosystems & Environment, 116(1–2), 34–46.

    Article  Google Scholar 

  • Vanlauwe, B., AbdelGadir, A., Adewopo, J., Adjei-Nsiah, S., Ampadu-Boakye, T., Asare, R., et al. (2017). Looking back and moving forward: 50 years of soil and soil fertility management research in sub-Saharan Africa. International Journal of Agricultural Sustainability, 15(6), 613–631.

    Article  CAS  Google Scholar 

  • Wainaina, P., Tongruksawattana, S., & Qaim, M. (2016). Tradeoffs and complementarities in the adoption of improved seeds, fertiliser, and natural resource management technologies in Kenya. Agricultural Economics, 47(3), 351–362. https://doi.org/10.1111/agec.12235.

    Article  Google Scholar 

  • Waithaka, M. M., Thornton, P. K., Shepherd, K. D., & Ndiwa, N. N. (2007). Factors affecting the use of fertilisers and manure by smallholders: the case of Vihiga, western Kenya. Nutrient Cycling in Agroecosystems, 78(3), 211–224. https://doi.org/10.1007/s10705-006-9087-x.

    Article  Google Scholar 

  • Wangia, C., Wangia, S., & De Groote, H. (2004). Review of maize marketing in Kenya: Implementation and impact of liberalisation, 1989-1999. In D. K. Friesen & A. F. E. Palmer (Eds.), Integrated Approaches to Higher Maize Productivity in the New Millennium. Proceedings of the 7th Eastern and Southern Africa Regional Maize Conference Nairobi, Kenya, February 2002 (pp. 10–20). Mexico, D. F: CIMMYT.

    Google Scholar 

  • Wooldridge, J. M. (2002). Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.

    Google Scholar 

Download references

Acknowledgements

The authors thank two anonymous reviewers and the editor of this journal for very useful comments and suggestions, and Elizabeth Way good for copy-editing the manuscript.

Funding

Data collection for this research was financially supported by the Kenya Maize Data Base (KMDB) project (the 1992 survey); the Insect Resistant Maize for Africa (IRMA) project (2002 survey); the Aflacontrol project (2010 survey); and the CGIAR Research Program (CRP) on Climate Change, Agriculture, and Food Security (CCAFS) (2013 survey). Staff time for the analysis was provided by the Bill and Melinda Gates Foundation through the Improved Maize for African Soils (IMAS) project and the CGIAR Research Program on Maize Agrifood Systems (CRP-MAIZE).

Author information

Authors and Affiliations

  1. School of Management, National Institute of Technology Karnataka, Surathkal, 575025, India

    Pradyot Ranjan Jena

  2. International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya

    Pradyot Ranjan Jena, Hugo De Groote & Annina Hittmeyer

  3. School of Livelihood, Tata Institute of Social Sciences, Hyderabad, India

    Bibhu Prasad Nayak

Authors
  1. Pradyot Ranjan Jena
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hugo De Groote
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bibhu Prasad Nayak
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Annina Hittmeyer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pradyot Ranjan Jena.

Ethics declarations

Conflicts of interest/Competing interests

The authors hereby declare that they have no conflict of interest.

Code Availability

Not applicable.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jena, P.R., De Groote, H., Nayak, B.P. et al. Evolution of Fertiliser Use and its Impact on Maize Productivity in Kenya: Evidence from Multiple Surveys. Food Sec. 13, 95–111 (2021). https://doi.org/10.1007/s12571-020-01105-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12571-020-01105-z

Keywords

Search

Navigation