The main purpose of this paper is to examine the relationship between trainers’ qualification and learning success and satisfaction of small-scale farmers during training activities in Bihar, India. Moderated mediation analysis is utilized to measure the direct and indirect effects of trainers’ qualification on learning success and satisfaction. Therefore, the psychological constructs of attitude and perceived control from the Theory of Planned Behaviour (TPB) operate as mediators, subjective norms act as moderator, and gender and age serve as covariates

There is a lack of quantitative information about farmers preferences of those activities, which are crucial to refine capacity development activities in the future. This study employs a discrete choice experiment analysing the willingness to pay to determine the preferences of small-scale farmers for agricultural training with respect to the training method, trainer, duration, location and additional offers

The framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming system's capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle processes of agricultural practices, farm demographics, governance and risk management.

Access to and usage of smartphones for agricultural purposes amongst small-scale farmers in rural areas of developing countries is still limited. Smartphones may provide an opportunity to develop farmers’ capacities with specific applications offering fast access to continually updated and reliable information. This study develops a framework to investigate the cognitive and affective behavioural drivers of smallholder farmers´ intention to use a smartphone in a developing country context.

The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.

A range of approaches and financial instruments have been used to stimulate and support innovation in agriculture and resolve interlocking constraints for uptake at scale. These include innovation platforms, results-based payments, value chain approaches, grants and prizes, incubators, participatory work with farmer networks, and many more.

Innovation for sustainable agricultural intensification (SAI) is challenging. Changing agricultural systems at scale normally means working with partners at different levels to make changes in policies and social institutions, along with technical practices. This study extracts lessons for practitioners and investors in innovation in SAI, based on concrete examples, to guide future investment.

A huge increase in investment in innovation for agricultural systems is critical to meet the Sustainable Development Goals and Paris Climate Agreement. Most of this increase needs to come from reorienting existing funding for innovation. However, understanding whether an investment will fully promote environmentally sustainable and equitable agri-food systems can be difficult.