Abstract
The main concern in agricultural research is to ensure that research products are adopted by farmers. However, the rate of adoption is low. Most research on adoption rates are post-ante. The values of such research can be added if factors for adoption are ex-ante identified and measures taken to increase adoption. This study was conducted in Morogoro, Tanzania to ex-ante identify socio-economic characteristics that influence adoption of Integrated Lowland Rice Legume Technologies (ILRLT). The ILRLT included integration of rice (SARO variety), legumes (cow pea) water management (irrigation, rainfed and majaruba bunds), tillage (conventional and minimum) and fertilizers (UREA, TSP and MOP). Data were collected through questionnaire interviews to 200 representative farmers and key informants. Descriptive statistics, Multi-Criteria Analysis and a two functions adoption model were used to assess the suitability of ILRLT and analyze the likelihood of farmers to adopt. Results indicated that important criteria for rice variety preference and hence adoption are high prices (7.8%), good taste (6.1%), early maturity (4.8%), disease (3.2%) and drought tolerance (17.4%). ILRLT scored more (26.40%) than farmer’s (17.97%) in fulfilling criteria for rice legume variety preferences. ILRLT have a chance of being adopted to the maximum rate of 89.7%. Adoption is likely to be more with farmers who depend on irrigation than those who depend on rainfed rice farming.
Highlights
Adoption of research outputs to bring the desired impacts is among the main concern in research since its inception
This study was conducted in Morogoro, Tanzania to ex-ante identify socio-economic characteristics that influence adoption of Integrated Lowland Rice Legume Technologies (ILRLT)
Adoption is likely to be more with farmers who depend on irrigation than those who depend on rainfed rice farming
Summary
Adoption of research outputs to bring the desired impacts is among the main concern in research since its inception. The rate of adoption of most agricultural technologies is low and depends on the number of factors (Perret & Stevens, 2003; Tenge, De Graaff, & Hella, 2004; Knowler & Bradshaw, 2006). These factors include personal characteristics such as age, education, marital status and others (Tenge et al, 2004). Resources availability and uses such as farm sizes, farm ownerships, and level of income have been identified to influence the rate of adoption of agricultural technologies (De Graaff et al, 2008). The value of such studies can be added if factors for adoption of a certain technology can be identified before introduction, as it will be possible to take necessary measures and increase adoption
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