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Title Adoption and impacts of improved maize production technology: a case study of the Ghana Grains Development Project
 
Names Morris, M.L.
Tripp, R.
Dankyi, A.A.
Date Issued 1999 (iso8601)
Abstract This report, one of a series of adoption case studies coordinated by the Impacts Assessment and Evaluation Group (IAEG) of the Consultative Group on International Agricultural Research (CGIAR), examines the adoption by Ghanaian maize farmers of improved production technologies developed through the Ghana Grains Development Project (GGDP). The GGDP, which ran from 1979 to1997, was an agricultural research and extension project implemented primarily by the Ghanaian Crops Research Institute (CRI), with technical assistance from the International Maize and Wheat Improvement Center (CIMMYT) and the International Institute of Tropical Agriculture (IITA), and funding from the Canadian International Development Agency (CIDA). The objectives of the case study were to (1) evaluate the success of the GGDP in developing improved maize production technologies and in transferring those technologies to farmers, and (2) assess the impacts of adoption at the farm level. Data on the adoption of three GGDP-generated maize technologies—modern varieties (MVs), fertilizer recommendations, and plant configuration recommendations—were collected through a national survey of maize growers conducted between November 1997 and March 1998. A three-stage, clustered, randomized procedure was used to select a representative sample of 420 maize farmers. These farmers were questioned at length about their maize production, consumption, and marketing practices; their preferences for different maize varietal characteristics; and their knowledge of and access to improved inputs, such as seed and fertilizer. The survey revealed that adoption of GGDP-generated maize technologies has been extensive. During 1997, more than half of the sample farmers (54%) planted MVs on at least one of their maize fields, and a similar proportion (53%) implemented the plant configuration recommendations. The rate of fertilizer use on maize, however, was lower, as less than one-quarter of the sample farmers (21%) reported having applied fertilizer to their maize fields. Adoption rates varied by agro-ecological zone, with adoption of all three technologies lowest in the forest zone. Adoption rates were higher among male farmers than among female farmers, except in the case of fertilizer, in which no significant difference was found. What have been the impacts of the GGDP-generated maize technologies? In the absence of reliable baseline data, it was not possible to calculate quantitative measures of project impact. Based on farmers’ qualitative judgments, however, it is clear that adoption of the GGDP-generated technologies has been associated with significant farm-level productivity gains (measured in terms of maize yields) and noticeable increases in the income earned from sales of maize. Impacts on the nutritional status of rural households, however, appear to have been less pronounced. Even though the latest MVs have been extensively promoted for their improved nutritional status, relatively few of the survey respondents were aware of this. Those who were aware said they rarely seek out nutritionally enhanced MVs to prepare weaning foods for infants and young children. In addition to documenting the uptake and diffusion of the three GGDP-generated maize technologies, this case study provides valuable insights about the many factors that can affect the adoption of agricultural innovations in general. The survey results show that adoption of improved production technology is directly influenced by three sets of factors: (1) characteristics of the technology (e.g., complexity, profitability, riskiness, divisibility, compatibility with other technologies); (2) characteristics of the farming environment (e.g., agro-climatic conditions, prevailing cropping systems, degree of commercialization of agriculture, factor availabilities, farmer knowledge, availability of physical inputs); and (3) characteristics of the farmer (e.g., ethnicity and culture, wealth, education, gender). The survey results also make clear that technology adoption may be affected indirectly by factors beyond the control of researchers, including the agricultural extension service, the inputs distribution system, and the economic policy environment.
Genre Report
Access Condition Open Access
Identifier 1405-7735