Sustainable agricultural intensification requires the use of multiple agricultural technologies in an integrated manner to enhance productivity while conserving the natural resource base. This study analyses the adoption and impacts of sustainable intensification practices (SIPs) using a dataset from Ghana. A multivariate probit (MVP) model was estimated to assess the adoption of multiple SIPs. Moreover, we used a multivalued semi-parametric treatment effect (MVTE) model to estimate the effects of adopting multiple SIPs on maize productivity.
Relying on cross-sectional data from 300 smallholder rice farmers, the study examined the effects of agricultural extension on improved rice variety adoption and farm income in northern Ghana. A recursive bivariate probit (RBP) model was used to assess the effect of agricultural extension on adoption while regression with endogenous treatment effect model (RETEM) was adopted to evaluate the effect of agricultural extension on farm income. The results indicate a statistically significant effect of agricultural extension on both adoption and farm income.
Precision agriculture (PA) is growing considerably in Brazil. However, there is a lack of information regarding to PA adoption and use in the country. This study sought to: (i) investigate the perception of growers and service dealership about PA technologies; (ii) identify constraints to PA adoption; (iii) obtain information that might be useful to motivate producers and agronomists to use PA technologies in the crop production systems.
The study explored the contribution of information and communication technology (ICT)-based information sources to market participation among smallholder livestock farmers. Use of ICTs is considered paramount for providing smallholder farmers with required market information, and also to reduce market asymmetries. A double hurdle regression was utilized to analyze data collected from 150 smallholder livestock farmers in the study area.
The adoption of innovations and Precision Agriculture Technologies (PAT) is fundamental for establishing the patterns of agricultural production. However, the dynamics of adoption of PAT by farmers differs by regions. Although there is large number of related researches, there are considerable gaps in the literature: studies on adoption of PAT can be systematically reviewed and integrated in a conceptual model of technology adoption by rural producers, which still lacking in the literature.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions.
These advanced training materials have been produced to foster the capacity of practitioners from private, nongovernmental and public sectors on one hand, and academics and scientists on the other, to practically implement cost-efficient RWHI technologies and practices in arid and semi-arid areas. Therefore, these training materials intend to provide the required information to support proper planning, design and construction of cost-efficient RWHI technologies and practices, with special emphasis on the specific problems encountered in Ethiopia, Kenya, Mozambique and Zimbabwe.
AFINET is one of the seventeen thematic networks that the European Union has financed under the H2020 framework and it is supervised by the EIP-Agri in order to foster innovation in Europe. The main topic of AFINET is agroforestry a practice of deliberately integrating woody vegetation with crops and/or animal systems and the promotion of this practice to foster climate changes. AFINET follows a multi-actor approach linked to the nine Regional Innovations Networks created to identify main challenges and develop main innovations about agroforestry.
The Africa Leadership Training and Capacity Building Program (Africa Lead), aims to support the capacity building program of the US Government’s Feed the Future Initiative, which aligns U.S. Government development assistance with Africa-owned agriculture development plans that are, in turn, aligned with the African Union’s Comprehensive Africa Agriculture Development Program.
This report outlines AIIM-Assist activities performed under four components (management of the annual program statement process, building the capacity of AIIM grantees and finalists, technical assistance to other USAID missions in Feed the Future focus countries, technical support to African regional partners outside of AIIM), and highlights qualitative and quantitatvie achievements between August 6, 2012 and November 4, 2016.