Innovations scaling and assessment: Spatial referencing and tracking of farmers in Democratic Republic of the Congo

This report presents a dataset of the e-registration of actors in the agricultural production and value chains in Democratic Republic of the Congo for assessing the adoption of innovations and the diffusion of new technologies. Data was collected after a census conducted in three steps. In the first step, main crops production regions and value chain actors were identified. In the second step, we updated the list of actors based on membership of actors’ associations. In the laststep, we did the census of all individual actors and geo-localized all farmers’ fields and villages using GPS device. Data were collected for the 2022 growing seasons and the dataset contains 3,550 observations with 159 variables divided into six sections: (i) preliminary information on the respondents; (ii) socio-economic characteristics; (iii) information on the rice plots; (iv) knowledge, use and access to rice varieties; (v) knowledge, use and access to agricultural equipment and methods; and (vi) information on post-harvest activities. Six categories of actors were identified: seed producers (1,565), crops producers (1,539), parboilers (2), millers (39), traders (606) and service providers (98). On average, a farmer grows two crops. The main crops of farmers are beans (1,017) followed by maize (919), potato (359), cassava (325), rice (284) and soybean (203). The dataset is valuable for the diffusion of a large scale of improved technologies and effective monitoring of the dissemination. Data can be used by scientists to have better understanding of crops value chains, production systems, the level of knowledge, accessibility and adoption of improved rice varieties and agricultural technologies, for further research regarding rice value chain development, technologies testing and socioeconomics studies of rice value chain actors and others crops such as maize, cassava, soybeans, sweet potato, banana and beans. Because of the large number of observations (3,550 actors), data can be used as sampling frame for further experiments or surveys based on random samples. Moreover, the dataset has the potential of generating descriptive statistics at the most disaggregated level of administrative units or villages for different equipment, methods and varieties adopted by gender and country.