Food Security

, Volume 7, Issue 3, pp 709–724 | Cite as

Determinants of adoption of climate-smart push-pull technology for enhanced food security through integrated pest management in eastern Africa

  • A. W. Murage
  • C. A. O. Midega
  • J. O. Pittchar
  • J. A. Pickett
  • Z. R. Khan
Original Paper


Food security attainment in Africa has been hindered by poor yields of cereals that serve both as staple and cash crops for the majority of smallholder farmers. Among the various constraints responsible for lower yields are the parasitic weed Striga, and Stemborer pests whose control has remained a challenge. The International Centre of Insect Physiology and Ecology (icipe) with partners developed a novel conservation agricultural technology termed ‘push-pull’, based on companion cropping that effectively controls both constraints simultaneously. However, the effects of climate change threatened its expansion into drier areas where Striga is rapidly spreading. Further adaptation of the conventional (original) push-pull technology was thus achieved through identification and incorporation of drought tolerant companion crops, and the procedure termed ‘climate-smart’ push-pull technology. With maximum adoption of the adapted technology, food security in the drier agro-ecologies would be enhanced through increased cereal yields. Adoption, however, depends on how well technology dissemination is implemented. The objective of this study was to quantify the potential adoption and impact of climate-smart push-pull technology ex ante in order to plan for its wide scale dissemination. Using a sample of 898 respondents (360 in Kenya, 240 in Tanzania, 298 in Ethiopia), multinomial logit and marginal rate of return (MRR) methods were used to analyze the findings of the ex ante baseline survey. These showed a high potential for adoption of climate-smart push-pull as 87.8 % of the overall sample were willing to adopt; 92.1 % in Tanzania, 88.6 % in Ethiopia and 84.3 % in Kenya. Gender, perceptions of Striga severity, technology awareness and input market access were the most likely factors that would positively influence the decision to adopt (marginal effects 0.060, 0.010, 0.042, and 0.738 respectively). The MRR was 109.2 % for sorghum and 143.4 % for maize, implying an expected positive impact to the community should they adopt the technology.


Food security Striga weeds Stemborers Push-pull Technology adoption adaptation Economic benefits Western Kenya 



The authors acknowledge the support of the European Union (EU) for financial support that facilitated data collection, Biovision Foundation for supporting dissemination of push-pull and all the enumerators, farmers and partners who participated in data collection.

Conflict of interest

The authors declare that we have no conflict of interest with the organization that sponsored the research work.


  1. Adesina, A. A. (1996). Factors affecting the adoption of fertilizers by rice farmers in Cote d’Ivoire. Nutrient Cycling in Agro ecosystem, 46, 29–39.CrossRefGoogle Scholar
  2. Adesina, A. A., & Baidu-Forson, J. (1995). Farmers’ perceptions and adoption of new agricultural technology: evidence from analysis in Burkina Faso and guinea, West Africa. Journal of Agricultural Economics, 13, 1–9.CrossRefGoogle Scholar
  3. Adesina, A. A., Mbila, D., Nkamleub, G. B., & Endamana, D. (2000). Econometric analysis of the determinants of adoption of alley farming by farmers in the forest zone of southwest Cameroon Agriculture. Ecosystems and Environment, 80, 255–265.CrossRefGoogle Scholar
  4. Amudavi, D. M., Khan, Z. R., Wanyama, J. M., Midega, C. A. O., Pittchar, J., Hassanali, A., & Pickett, J. A. (2009a). Evaluation of farmers’ field days as a dissemination tool for push-pull technology in western kenya. Crop Protection, 28(3), 225–235.CrossRefGoogle Scholar
  5. Amudavi, D. M., Khan, Z. R., Wanyama, J. M., Midega, C. A. O., Pittchar, J., Nyangau, I. M., Hassanali, A., & Pickett, J. A. (2009b). Assessment of technical efficiency of farmer teachers in the uptake and dissemination of push-pull technology in western Kenya. Crop Protection, 28(11), 987–996.CrossRefGoogle Scholar
  6. CIMMYT, (1988). From agronomic data to farmer recommendations: An economics training manual. Completely revised edition. CIMMYT. Mexico, D. F., 79 pp.Google Scholar
  7. Cook, S., Khan, Z. R., & Pickett, J. A. (2007). The use of push-pull strategies in integrated pest management. Annual Reviews Entomology, 52, 375–400.CrossRefGoogle Scholar
  8. D’Antoni, J. M., Mishra, A. K., Powell, R., & Martin, S. (2012). Farmers’ perception of precision technology: the case of Autosteer adoption by cotton farmers. Southern Agricultural Economics Association Annual Meeting, Birmingham, AL, February, 4–7, 2012.Google Scholar
  9. Daberkow, S. G., & McBride, W. D. (2003). Farm and operator characteristics affecting the awareness and adoption of precision agricultural technologies in the US. Precision Agriculture, 4, 163–177.CrossRefGoogle Scholar
  10. De Groote, H., Vanlauwe, B., Rutto, E., Odhiambo, G. D., Kanampiu, F., & Khan, Z. R. (2010). Economic analysis of different options in integrated pest and soil fertility management in maize systems of Western Kenya. Agricultural Economics, 41(5), 471–482.CrossRefGoogle Scholar
  11. Feder, G., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries. A Survey. Economic Development and Cultural Change, 33(2), 255–298.CrossRefGoogle Scholar
  12. Fischler, M. (2010). Impact assessment of push-pull technology promoted by icipe and partners in eastern Africa. Full report; ISBN 92 9064 215 7. icipe Science Press.Google Scholar
  13. Food and Agricultural Organisation (FAO) (1986). Trade Yearbook 1985. No. 39, Rome: FAO.Google Scholar
  14. Food and Agricultural Organization (FAO) (2006). Food Security and Agricultural development in sub-Saharan Africa. Building a case for more public support. Working paper No. 01/E. Rome.Google Scholar
  15. Greene, W. H. (2000). Econometric analysis (4th ed.). Upper Saddle River: Prentice-Hall.Google Scholar
  16. Harper, J. K., Rister, M. E., Mjelde, J. W., Drees, B. M., & Way, M. O. (1990). Factors influencing the adoption of insect management technology. American Journal of Agricultural Economics, 72(4), 997–1005.CrossRefGoogle Scholar
  17. Hassan, R. M., Onyango, R., & Rutto, J. K. (1994). Adoption patterns and performance of improved maize in Kenya. In R. M. Hassan (Ed.), Maize technology development and transfer: A GIS approach to research planning in Kenya (pp. 21–54). London: CAB International.Google Scholar
  18. Kanampiu, F., Friesen, D., & Gressel, J. (2002). CIMMYT unveils herbicide-coated maize seed technology for Striga control. Haustorium, 42(4), 1–3.Google Scholar
  19. Keelan, C., Thorne, F. S., Flanagan, P., Newman, C., & Mullins, E. (2009). Predicted willingness of Irish farmers to adopt GM technology. AgBioForum, 12(3&4), 394–403. Available at: Scholar
  20. Kfir, R., Overholt, W. A., Khan, Z. R., & Polaszek, A. (2002). Biology and management of economically important Lepidopteran cereal stemborers in africa. Annual Review Entomology, 47, 701–731.CrossRefGoogle Scholar
  21. Khan, Z. R., & Pickett, J. A. (2004). The ‘push-pull’ strategy for stemborer management: A case study in exploiting biodiversity and chemical ecology. In G. M. Gurr, S. D. Wratten, & M. A. Altieri (Eds.), Ecological engineering for pest management: Advances in habitat manipulation for arthropods (pp. 155–164). Wallingford: CABI Publishing.Google Scholar
  22. Khan, Z. R., Pickett, J. A., Wadhams, L. J., & Muyekho, F. (2001). Habitat management strategies for the control of cereal stemborers and Striga weed in maize in kenya. Insect Science Applications, 21(4), 375–380.Google Scholar
  23. Khan, Z. R., Amudavi, M. A., Midega, C. A. O., Wanyama, J. M., & Pickett, J. A. (2008a). Farmers perception of a ‘push-pull’ technology for control of cereal stemborers and Striga weed in Western Kenya. Crop protection, 27, 976–987.CrossRefGoogle Scholar
  24. Khan, Z. R., Midega, C. A. O., Amudavi, D. M., Hassanali, A., & Pickett, J. A. (2008b). On-farm evaluation of the ‘push–Pull’ technology for the control of stemborers and Striga weed on maize in western Kenya. Field Crops Research, 106(3), 224–233.CrossRefGoogle Scholar
  25. Khan, Z. R., Midega, C. A. O., Njuguna, E. M., Amudavi, D. M., Wanyama, J. M., & Pickett, J. A. (2008c). Economic performance of the push-pull technology for stemborer and Striga control in smallholder farming systems in western Kenya. Crop Protection, 27, 1084–1097.CrossRefGoogle Scholar
  26. Khan, Z. R., Midega, C. A. O., Pittchar, J. O., Murage, A. W., Birkett, M. A., Bruce, T. J. A., & Pickett, J. A. (2014). Achieving food security for one million sub-Saharan African poor through push-pull innovation by 2020. Philosophical Transactions of the Royal Society B., 369(1639), 20120284.CrossRefGoogle Scholar
  27. Langyintuo, A. S., & Mungoma, C. (2008). Effect of household wealth on the adoption of improved maize varieties in Zambia. Food Policy, 33(6), 550–559.CrossRefGoogle Scholar
  28. Läpple, D. & Kelley H. (2010). Understanding farmers’ uptake of organic farming. An application of the theory of planned behavior. The 84th annual conference of the Agricultural Economics Society, 29th to 31st March 2010, Edinburgh.Google Scholar
  29. Matlon, P.J. (1994). Indigenous land use systems and investments in soil fertility in Burkina Faso. In: Bruce, J.W, Migot-Adholla, S.E. Ed., Searching for Land Tenure Security in Africa (pp. 41–69). Kendall/Hunt Publishing Company, Dubuque, Iowa, USA.Google Scholar
  30. Mauceri, M., Alwang, J., Norton, G., & Barrera, V. (2005). Adoption of integrated pest management technologies: a case study of potato farmers in Carchi, Ecuador. AAEA annual meeting, providence, Rhode Island, July, 24–27, 2005.Google Scholar
  31. McNamara, K. T., Wetzstein, M. E., & Douce, G. K. (1991). Factors affecting peanut producer adoption of integrated pest management. Review of Agricultural Economics, 13, 129–139.CrossRefGoogle Scholar
  32. Midega, C. A. O., Khan, Z. R., Van den Berg, J., Ogol, C. K. P. O., Dippenaar-Schoeman, A. S., Pickett, J. A., & Wadhams, L. J. (2008). Response of ground dwelling arthropods to a ‘push-pull’ system and Bt-maize: spiders as an indicator group. Journal of Applied Entomology, 132, 248–254.CrossRefGoogle Scholar
  33. Midega, C. A. O., Khan, Z. R., Amudavi, D. M., Pittchar, J., & Pickett, J. A. (2010). Integrated management of Striga hermonthica and cereal stemborers in finger millet (Eleusine Coracana (l.) Gaertn.). Through Intercropping with Desmodium Intortum, International Journal of Pest Management, 56(2), 145–151.Google Scholar
  34. Midega, C. A. O., Salifu, D., Bruce, T. J., Pittchar, J., Pickett, J. A., & Khan, Z. R. (2014). Cumulative effects and economic benefits of intercropping maize with food legumes on Striga hermonthica infestation. Field Crops Research, 155, 144–152.CrossRefGoogle Scholar
  35. Midega C.A.O., Bruce T.J., Pittchar J., Murage A., Pickett J.A., & Khan Z.R., (2015). A new drought tolerant companion cropping system increases agricultural productivity in sub-Saharan Africa. Journal of Experimental Botany, (Submitted).Google Scholar
  36. Miller, J. R., & Cowles, R. S. (1990). Stimulo-deterrent diversion: a concept and its possible application to onion maggot control. Journal of Chemical Ecology, 16(11), 3197–3212.CrossRefPubMedGoogle Scholar
  37. Morgenstern, R.D. (1996). Does the provision of free technical information really influence firm behavior? Discussion paper 96–16, Resource for the future, Washington DC, USA.Google Scholar
  38. Murage, A. W., Amudavi, D. M., Obare, G., Chianu, J., & Khan, Z. R. (2011). Determining smallholder farmers’ preferences for push-pull technology dissemination pathways in western Kenya. International Journal of Pest Management, 57(2), 133–145.CrossRefGoogle Scholar
  39. Murage, A. W., Obare, G., Chianu, J., Amudavi, D. M., Midega, C. A. O., Pickett, J. A., & Khan, Z. R. (2012). The effectiveness of dissemination pathways on adoption of “push-pull” technology in Western Kenya. Quarterly Journal of International Agriculture, 51(1), 51–71.Google Scholar
  40. Napier, T. L., & Napier, A. S. (1991). Perceptions of conservation compliance among farmers in a highly erodible area of Ohio. Soil Water Conservation., 48(3), 220–224.Google Scholar
  41. Napier, T., Carter, M. V., & Bryant, E. G. (1986). Local perceptions of reservoir impacts: A test of vested interests. Community Psychology, 14(1), 17–37.CrossRefGoogle Scholar
  42. Napier, T. L., Tucker, M., & McCarter, S. (2000). Adoption of conservation production systems in three Midwest watersheds. Journal of Soil & Water Conservation, 55(2), 123–134.Google Scholar
  43. Nerlove, M., & Press S. (1973).Univariate and Multivariate Log-Linear and Logistic Models. RAND-R1306-EDA/NIH, Santa Monica, 1973.Google Scholar
  44. Palis, F. G., Morin, S., & Hossain, M. (2002). Social capital and diffusion of integrated pest management technology: a case study in central Luzon. Philippines, Paper Presented at the Social Research Conference, CIAT, Cali, Columbia, September, 11–14, 2002.Google Scholar
  45. Prokopy, L. S., Baumgart‐Getz, A., Klotthor‐Weinkauf, D., & Floress, K. (2008). Determinants of agricultural best management practice adoption: evidence from the literature. Journal of Soil and Water Conservation, 63(5), 300–311.CrossRefGoogle Scholar
  46. Roberts, R. K., English, B. C., Larson, J. A., Cochran, R. L., Goodman, W. R., Larkin, S. L., Marra, M. C., Martin, S. W., Shurley, W. D., & Reeves, J. M. (2004). Adoption of site‐specific information and variable‐rate technologies in cotton precision farming. Journal of Agricultural and Applied Economics, 36(1), 143–158.Google Scholar
  47. Rubas, D. (2004). Technology adoption: who is likely to adopt and how does the timing affect the benefits? PhD Dissertation, Texas, A&M University,
  48. Tsanuo, M. K., Hassanali, A., Hooper, A. M., Khan, Z. R., Kaberia, F., Pickett, J. A., & Wadhams, L. (2003). IsoFlavanones from the Allelopathic aqueous root exudates of desmodium uncinatum. Phytochemistry, 64(1), 265–273.CrossRefPubMedGoogle Scholar
  49. Useche, P., Barham B. & Foltz J. (2005). A Trait Specific Model of GM Crop Adoption among U.S. Corn Farmers in the Upper Midwest. American Agricultural Economics Association Annual Meeting, Providence, Rhode Island, July 24–27, 2005.Google Scholar
  50. Zepeda, L. (1990). Predicting bovine Somatotropin use by California dairy farmers. Western Journal of Agricultural Economics, 15(1), 55–62.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht and International Society for Plant Pathology 2015

Authors and Affiliations

  • A. W. Murage
    • 1
  • C. A. O. Midega
    • 1
  • J. O. Pittchar
    • 1
  • J. A. Pickett
    • 2
  • Z. R. Khan
    • 1
  1. 1.International Centre of Insect Physiology and Ecology (ICIPE)NairobiKenya
  2. 2.Rothamsted ResearchHarpendenUK

Personalised recommendations