Demand-Driven Technologies for Sustainable Maize ... - IITA

indeed many dimensions to the issue as well as a diversity of opinions onhow to resolve the food and development problems in Africa (Byerlee1994; Bosc and Hanak Freud 1995; Abalu 1997; Johnson and Evenson2000; Badu–Apraku and Fakorede 2003). For the future of agricultureon the continent, particularly in West and Central Africa (WCA), twomore perplexing issues exist. The fi rst is to identify the conditionsfavoring adoption to improve productivity; the second is to developmechanisms for measuring the extent of adoption by smallholderfarmers to prioritize the research and development agenda.Adoption of technological innovations is a major source ofproductivity growth and an important factor in determining investmentin agricultural research and extension. Bosc and Hanak Freud (1995)noted that the category of research results most interesting tosmallholder farmers appears to be the improved genetic materials.These farmers face serious constraints such as shortage of labor andcapital; they have a high aversion to risk, combined in many caseswith a lack of fertile land thus making adoption of complete technicalpackages less attractive, if not impossible.Smallholder farmers in WCA have a history of spontaneousexperimentation with crops and are constantly on the lookout forvarieties that interest them, which they readily exchange with oneanother (Adesina and Zinnah 1993; Manyong et al. 1998; Onyibe etal. 2003a; Gyasi et al. 2003). Yet the development of simple and timesavingmechanisms for monitoring the spread and extent of adoptionof genetic materials has not been given due research attention. Thishas constrained continuous assessment of impact of research andextension programs and makes justifi cation for increased investmentson research and extension diffi cult.A recent study by Menkir (2003) elucidated the role of GIS intargeting maize germplasm to farmer’s needs in WCA. From the studyit is obvious that scope exists for the use of this technology, especiallywhen integrated with a biophysical spatial database to develop a robustframework for systematic monitoring and assessment of adoption andimpact of maize germplasm. But securing the technical and humanresource capability for such endeavor is a challenge that will take awhile to resolve.Conducting on-site adoption and impact assessment studies,therefore, remains an option, which, like most other socio-economicstudies, is a highly resource-demanding activity. For that reason,researchers are frequently compelled to adopt resource-use effi cientmethods of collecting data, which sometimes compromise the qualityof their results and their interpretation. Presently, most adoptionstudies rely on the use of secondary data sources, interviews andquestionnaires to generate data. Even when direct observations are341