203-5 Multivariate and Non-Parametric Methods for Identification of Factors That Decide the Adoption of Fertilizer Use by Rwandan Farmers.

Poster Number 122

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: General Biometry and Statistical Computing: II
Tuesday, October 23, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
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Joaquin Sanabria1, Joshua Ariga2, Deborah Hellums2 and Martin Drevon2, (1)Research and Development Division, International Fertilizer Development Center (IFDC), Muscle Shoals, AL
(2)Research and Development Division, IFDC, Muscle Shoals, AL
Poster Presentation
  • Multivariate and Non-Parametric Methods for Identification of Factors POSTER_PDF.pdf (394.9 kB)
  • The quantity of fertilizer used is a good indicator of the degree of prosperity in any country.  Prior to 2008, the mean rate of fertilizer use in Rwanda was 4 kg ha-1, lower than the mean for sub-Saharan Africa of 11 kg ha-1, which is the world region with the lowest fertilizer use. In 2008 the Rwandan government, with the assistance of international aid agencies, started programs with the main objective of increasing the use of fertilizers in the diverse crops grown in the country. 

    As part of a project sponsored by USAID, a survey was developed to identify major factors that affect the farmer’s decision of starting fertilizer use.  The random sampling survey was designed to collect demographic, socioeconomic, and crop management practices data from 2022 small scale farm households located throughout the country.

    Principal Factor Analysis was employed to identify fertilizer adoption factors.  Each of the factors selected is made up by a series of explanatory variables.  Then the explanatory variables were tested comparing the Cumulative Empirical Distribution Functions (CEDF) or the Empirical Distribution Functions (EDF) of fertilizer users against no-fertilizer users. The hypothesis tests for the comparison of CEDF’s and EDF’s from the two groups of farmers were carried out with the non-parametric Kolmogorov-Smirnov test.  The ten most influential factors, in order of importance, are shown below. 

     

    Factor

    Name of Factor

    1

    Percent Maize Sales

    2

    Percent Vegetable sales

    3

    Farming Area

    4

     

    Interest on Increasing maize and vegetable Production

    5

    Interest on Getting Credit for maize and vegetable fertilization

    6

    Perception of fertilization effect on Maize and Vegetables

    7

    Interest on Increasing Potato Production

    8

    Fund Sources

    9

    Understanding fertilizer importance

    10

    Perception of Conditions Limiting Access to Fertilizers

    See more from this Division: ASA Section: Biometry and Statistical Computing
    See more from this Session: General Biometry and Statistical Computing: II
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