The exposure and adoption of New Rice for Africa (NERICAs) among Ghanaian rice farmers: What is the evidence?

Abstract

The sustainable development of the rice sector in Ghana is constrained by environmental, socioeconomic, research and development factors. Productivity is generally low, about 1 mt/ha under upland and rain-fed lowland rice ecologies which dominate rice production systems in the country. The release and diffusion of the New Rice for Africa (NERICA) varieties across many countries in Africa (including Ghana) brought renewed hope to both farmers and the research community because of the desirable qualities associated with the NERICAs, and therefore their potential to improve food security on a sustainable basis. This study therefore sought to assess the extent of exposure and adoption of the NERICA varieties across the rice growing districts in Ghana, and determine the key factors that affect adoption. A total of 489 rice producing households from three districts (Ejura-Sekyedumase, Hohoe and Tolon-Kumbungu) were involved in the study. The study employs the average treatment effect (ATE) methodology which provides an appropriate framework for the identification and consistent estimation of the population adoption rate and that of the determinants of adoption. The study finds that exposure to NERICA varieties is generally low in Ghana with an average rate of about 6%. Similarly, the adoption of improved rice varieties is low, and the adoption of NERICA varieties is about 6% of the total sample surveyed. The study shows that experience, education and location are important determinants of exposure, while age and access to extension also affect adoption. It is therefore recommended that much effort and resources should be invested in promotional activities to facilitate both the exposure and adoption of the NERICAs among farmers in Ghana.

Factors affecting adoption of improved sorghum varieties in Tanzania under information and capital constraints

“…After adopting the technology, the farmer may decide to continue using it or stop using it. This action depends on the experienced benefits and associated risks after adoption (Asuming-Brempong et al 2011;Kabunga, Dubois, and Qaim 2012).…”

Understanding the Process of Agricultural Technology Adoption: Mineral Fertilizer in Eastern DR Congo

“…Only very few studies disentangle the adoption process of farmers in different intermediate steps. For example, Diagne and Demont (2007) and Asuming-Brempong et al (2011) disentangle between exposure and adoption to more accurately estimate technology adoption rates and investigate the factors determining adoption. Kabunga, Dubois, and Qaim (2012) further distinguish between awareness exposure (having heard about a technology) and knowledge exposure (understanding the attributes of a technology) to estimate adoption.…”

Agricultural Research, Technology and Nutrition in Sub-Saharan Africa

“…They find that the lower the distance from source of information, the higher is the probability of being aware of and trying out technologies and that education partly offsets the effect of distance, implying that more educated farmers may have access to information despite the distance. Subsequent studies have examined awareness and adoption rates (Diagne and Demont, 2007;Asuming-Brempong et al, 2011;Simtowe et al, 2012), while others (eg Moser and Barrett, 2006) focus on the try-out and adoption rates. Lambrecht et al (2014) examine the determining factors of all three lags.…”

“…Specifically, the main factors that determine the awareness of a new technology include the social characteristics of farmers and agro-ecological conditions in a targeted area. In particular, farmers who are more aware of a technology have higher education (Simtowe et al, 2012), live in proximity to research institutions and universities (Asuming-Brempong et al, 2011), and have more social capital, which includes participation in collective actions, membership of non-agricultural organisations and a network of credit channels (Lambrecht et al, 2014;Yokouchi and Saito, 2016). 5 Both social characteristics and economic constraints determine the try-out step.…”

“…In particular, younger farmers living near the market, with social capital and labour endowments, are more likely to experiment with a new technology (Lambrecht et al, 2014). The continued adoption step is largely influenced by economic constraints, demographic determinants and dissemination mechanisms, such as extension (Asuming-Brempong et al, 2011). Following Moser and Barrett (2006), in addition to liquidity, social capital (learning from others) and peer effects (attitude of conformity to neighbouring farmers' behaviour) play an important role in determining continued adoption.…”