Skip to main content

Jatropha adoption: a statistical observational study of factors influencing Malian farmers’ decision to grow Jatropha


An accurate understanding of the factors that influence farmers’ adoption of a crop is critical for effective policy promotion and technical support. Agroforestry crop adoption is a complex topic involving many factors not often addressed by tradition crop adoption models. This complexity, when applied to Jatropha (Jatropha curcas L.), an often widely promoted yet poorly understood biofuel feedstock crop, requires a detailed analysis across diverse topics. Such an analysis was carried out through applying rigorous statistical tools to the data acquired from an interview-based household survey among Malian farmers and was combined with relevant geospatial datasets. The results showed that though farmers’ adoption is based on a wide variety of factors from household preferences, resource endowments, bio-physical factors, and market incentives, factors related to risk and uncertainty appear to provide the strongest correlation. Specifically, the number of visits that an agriculture extension agent makes with a farmer was found to be the most significant factor influencing adoption.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2


  • Achten WMJ, Verchot L et al (2008) Jatropha bio-diesel production and use. Biomass Bioenergy 32(12):1063–1084

    Article  CAS  Google Scholar 

  • Banerji R, Chowdhury AR et al (1985) Jatropha seed oils for energy. Biomass 8(4):277–282

    Article  CAS  Google Scholar 

  • Barrett CB, Place F et al (2002) The challenge of stimulating adoption of improved natural resource management practices in African agriculture. In: Barrett CB, Place F, Aboud A (eds) Natural resources management in African agriculture: understanding and improving current practices. CABI Publishing, Wallingford, pp 1–22

    Chapter  Google Scholar 

  • Carle AC (2009) Fitting multilevel models in complex survey data with design weights: recommendations. BMC Med Res Methodol 9:49

    PubMed  Article  Google Scholar 

  • Duflo E, Kremer M, Robinson J (2005) Understanding fertilizer adoption: evidence from field experiments. Mimeo, MIT

  • Environmental Systems Research Institute (1993) Digital chart of the world

  • European Space Agency (2008) GlobCover land cover (v2.2)

  • Filmer D, Pritchett LH (2001) Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography 38(1):115–132

    PubMed  CAS  Google Scholar 

  • Gelman A (2008) Scaling regression inputs by dividing by two standard deviations. Stat Med 27:2865–2873

    PubMed  Article  Google Scholar 

  • Gubitz GM, Mittelbach M et al (1999) Exploitation of the tropical oil seed plant Jatropha curcas L. Bioresour Technol 67(1):73–82

    Article  CAS  Google Scholar 

  • Hijmans R, Garcia N et al (2010a) GADM: database of global administrative areas

  • Hijmans RJ, Cameron S et al (2010b) WorldClim global climate data

  • Jeffrey-Coker F, Basinger M (2010) Open Data Kit—technology review.

  • Korn EL, Graubard BI (1995a) Examples of differing weighted and unweighted estimates from a sample survey. Am Stat 49:291–295

    Article  Google Scholar 

  • Korn EL, Graubard BI (1995b) Analysis of large health surveys: accounting for the sampling design. J R Stat Soc A 158:263–295

    Article  Google Scholar 

  • Kumar A, Sharma S (2008) An evaluation of multipurpose oil seed crop for industrial uses (Jatropha curcas L.): a review. Ind Crop Prod 28(1):1–10

    Article  CAS  Google Scholar 

  • Lohr SL (2009) Sampling: design and analysis. Brooks/Cole Cengage Learning, Boston, MA

    Google Scholar 

  • Meier L, van de Geer S et al (2008) The group lasso for logistic regression. J R Stat Soc B 70(1):53–71

    Article  Google Scholar 

  • Mercer DE (2004) Adoption of agroforestry innovations in the tropics: a review. Agrofor Syst 61–62:311–328

    Article  Google Scholar 

  • Minnesota Population Center (2009) Integrated public use microdata series, international: version 5.0 [machine-readable database]. University of Minnesota, Minneapolis

  • Openshaw K (2000) A review of Jatropha curcas: an oil plant of unfulfilled promise. Biomass Bioenergy 19(1):1–15

    Article  Google Scholar 

  • Pattanayak SK, Mercer DE et al (2003) Taking stock of agroforestry adoption studies. Agrofor Syst 57(1):173–186

    Article  Google Scholar 

  • Pfeffermann D, Skinner CJ, Holmes DJ, Goldstein H, Rasbash J (1998) Weighting for unequal selection probabilities in multilevel models. J R Stat Soc B 60:23–40

    Article  Google Scholar 

  • Rabe-Hesketh S, Skrondal A (2006) Multilevel modeling of complex survey data. J R Stat Soc A 169:805–827

    Article  Google Scholar 

  • Rodriguez-Sanchez FS (2010) Development and testing of business models for Jatropha powered multifunctional platforms (MFPs) for energy access services. Internal Report for cooperation agreement between Mali Biocarburant SA and ETC Foundation Agreement Number 079265-2009-033

  • Singer T (2008) Socio-economic baseline study. Mali Biocarburantm, Bamako

    Google Scholar 

  • Su Y-S, Gelman A, Hill J, Yajima M (in review) Multiple imputation with diagnostics (mi) in R: opening windows into the black box. J Stat Softw

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to M. Basinger.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Basinger, M., Chen, J., Jeffrey-Coker, F. et al. Jatropha adoption: a statistical observational study of factors influencing Malian farmers’ decision to grow Jatropha. Agroforest Syst 84, 59–72 (2012).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Jatropha
  • Adoption
  • Mali
  • Biodiesel
  • Agroforestry