14 pages., Edutainment, the combination of education with entertainment through various media such as television, radio, mobile phone applications and games, is increasingly being used as an approach to stimulate innovation and increase agricultural productivity amongst smallholder farmers in sub-Saharan Africa. Shamba Shape Up, a widely publicised makeover reality TV programme, is an example of edutainment that has received considerable attention, and airs in three countries in East Africa where it is estimated to be watched by millions of viewers.
There is no published academic research on the influence of makeover television formats on innovation systems and processes in smallholder agriculture. Using an Agricultural Innovation Systems approach, this paper explores how makeover edutainment is influencing smallholder farmer innovation systems together with the effect this is having on smallholder farms. In the absence of previous research, it articulates a Theory of Change which draws on research traditions from mass communication, agricultural extension and innovation systems.
Data came from two large scale quantitative (n = 9885 and n = 1572) surveys and in-depth participatory qualitative research comprising focus group discussions, participatory budgets, agricultural timelines, case studies and key information interviews in Kenya. An estimated 430,000 farmers in the study area were benefiting from their interaction with the programme through increased income and / or a range of related social benefits including food security, improving household health, diversification of livelihood choices, paying school fees for children and increasing their community standing / social capital.
Participatory research showed SSU enhanced an already rich communication environment and strengthened existing processes of innovation. It helped set the agenda for discussions within farming communities about opportunities for improving smallholder farms, while also giving specific ideas, information and knowledge, all in the context of featured farm families carefully selected so that a wide range of viewers would identify with them and their challenges.
Broadcasts motivated and inspired farmers to improve their own farms through a range of influences including entertainment, strong empathy with the featured host farm families, the way ideas emerged through interaction with credible experts, and importantly through stimulating widespread discussion and interaction amongst and between farmers and communities of experts on agricultural problems, solutions and opportunities. The fact that local extension workers also watched the programmes further enhanced the influence on local innovation systems.
The findings indicate that well designed makeover edutainment can strongly influence agricultural innovation processes and systems resulting in impact on the agricultural production and behaviours of large numbers of smallholder farmers.
10 pages, This study examined content of YouTube videos on cassava production and processing posted in Nigeria between 2009 and 2019. Purposive sampling method was used in selecting 155 YouTube videos with cassava production and processing contents. Primary data on video source, content, duration, quality, number of views, subscribers, likes, comments, presentation format and year of upload were obtained by watching these videos. Data were analysed using frequency counts, percentages, means, standard deviation. Many (53.5%) of the videos were on processing of cassava, while most (80.0%) of the videos were relatively recent (2014 - 2019). Private individuals (38.7%) and media houses (34.2%) were the main sources of videos on cassava production and processing on YouTube. The major content of the video was on agronomic practices in cassava production (12.9%) and value addition (11.0%). Also, 66.0% of the videos had video description (descriptive texts), 36.8% had mobilizing information while 52.3% had a video quality of 720p. Furthermore, 72.9% of the videos had between 1-to-7-minute runtime and these videos had more likes than dislikes with mean values of 92.8 and 5.6 respectively. The mean number of views, subscribers and comments were 11,138.1, 179,537.6 and 13.6, respectively. The presentation patterns in the videos were in form of news (24.5%) and documentary (20.0%). YouTube videos on cassava production and processing were well viewed with a substantial number of subscribers. More YouTube videos on cassava production and processing should be produced with varied contents by different stakeholders in the agricultural sector.
6 pages, Despite the huge potential for milk production, interventions to improve productivity in sub-Saharan Africa (SSA) are barely based on specified farm classifications. This study aimed to develop robust and context-specific farm typologies to guide content of extension farm advice/services in Uganda. From a sample of 482 dairy farmers, we collected data on farmer socio-demographics, farm management practices, ownership of farm tools and facilities, willingness to pay for extension services, milk production, and marketing. Farm typologies were obtained based on principal component and cluster analyses. Thereby, of the three dairy production systems that emerged, small-scale, largely subsistence yet extensive and low productive farms were more prominent (82.6%). Farms that were classified as large-scale, less commercialized yet extensive with modest productive systems were more than the medium-scale commercial farms with intensive and highly productive systems. However, the later were considered to potentially transform dairy farming in Uganda. It was also predicted that the validity of our farm classification may persist until half of the farms have moved between clusters. The study gives new insights on dairy production systems in Uganda, which can be used to organize more targeted research on farmers’ extension needs for facilitating delivery of relevant and effective extension services and designing appropriate extension policies
INTERPAKS, Examines the level of significance of extension services and the marginal contribution of extension services to increased agricultural production in Gujarat State (1976-77). In addition, the marginal contributions of extension services are compared for the high and low productivity areas of the state. Results of the regression analysis indicate that extension investment has played a significant role in increasing agricultural production only in the high productivity areas while in the low productivity areas it has played an insignificant and even negative role.
21 pages, Despite decades of investment in agricultural extension, technology adoption among farmers and agricultural productivity growth in Sub-Saharan Africa remain slow. Among other shortcomings, extension systems often make recommendations that do not account for price risk or spatial heterogeneity in farmers' growing conditions. However, little is known about the effectiveness of extension approaches for nutrient management that consider these issues. We analyze the impact of farmers' access to site-specific nutrient management recommendations and to information on expected returns, provided through a digital decision support tool, for maize production. We implement a randomized controlled trial among smallholders in the maize belt of northern Nigeria. We use three waves of annual panel data to estimate immediate and longer term effects of two different extension treatments: site-specific recommendations with and without complementary information about variability in output prices and expected returns. We find that site-specific nutrient management recommendations improve fertilizer management practices and maize yields but do not necessarily increase fertilizer use. In addition, we find that recommendations that are accompanied by additional information about variability in expected returns induce larger fertilizer investments that persist beyond the first year. However, the magnitudes of these effects are small: we find only incremental increases in investments and net revenues over two treatment years.
18 pages, Based on panel data from the Rural Fixed Point Survey of the Ministry of
Agriculture over the period 2004-2016 and supplementary survey data on information
and communications technology (ICT) applications in the countryside, this paper employs
the difference in differences (DID) method to analyze the effects of ICT applications on
rural households’ agricultural total factor productivity (TFP) with mobile phone signal,
internet and 3G mobile network connections as indicators, and decomposes and evaluates
the constituent factors. Our findings reveal a positive effect of ICTs on rural households’
TFP, which primarily stemmed from rising agricultural technical efficiency. However, ICTs
exerted no significant effect on agricultural technical progress during this paper’s data
period due to limited rural human capital. These findings are consistent with robustness test
results based on counterfactual and matching methods.
