Climate-smart agriculture (CSA) is an approach to help agricultural systems worldwide, concurrently addressing three challenge areas: increased adaptation to climate change, mitigation of climate change, and ensuring global food security – through innovative policies, practices, and financing. It involves a set of objectives and multiple transformative transitions for which there are newly identified knowledge gaps. We address these questions raised by CSA within three areas: conceptualization, implementation, and implications for policy and decision-makers.
This paper analyses a monitoring, evaluation and learning (MEL) system developed within an agricultural research for development institution. The system applies aspects of the Outcome Harvesting tool and focuses on learning for adaptation and improvement of innovation processes. Developmental evaluation principles are applied to discuss its application. The MEL system provides insight into the processes and interactions with next users that generate outcomes.
Les travaux portant sur l’inclusion des petits exploitants dans l’agriculture contractuelle dans le monde dressent des constats contradictoires. En Algérie, l’État a engagé en 2009 un programme d’appui à l’intégration des filières lait et tomate industrielle, en accordant des primes aux entreprises et aux agriculteurs qui s’engagent ensemble dans des contrats de commercialisation.
Dans un contexte de controverse sur la capacité des modèles agricoles à répondre conjointement aux enjeux alimentaires, environnementaux et de développement en Afrique, nous analysons les conditions de viabilité d’une agriculture à caractère biologique au Cameroun. La démarche mobilise une enquête par entretiens semi-directifs auprès des acteurs engagés dans les filières de production biologique et une mise en débat des connaissances générées lors d’ateliers participatifs multi-acteurs. Elle met en interaction les connaissances scientifiques, entrepreneuriales et techniques.
Internet of things (IoT) results in massive amount of streaming data, often referred to as “big data”, which brings new opportunities to monitor agricultural and food processes. Besides sensors, big data from social media is also becoming important for the food industry. In this review we present an overview of IoT, big data, and artificial intelligence (AI) and their disruptive role in shaping the future of agri-food systems.
The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production.
The prevalence of “grass-fed” labeled food products on the market has increased in recent years, often commanding a premium price. To date, the majority of methods used for the authentication of grass-fed source products are driven by auditing and inspection of farm records. As such, the ability to verify grass-fed source claims to ensure consumer confidence will be important in the future. Mid-infrared (MIR) spectroscopy is widely used in the dairy industry as a rapid method for the routine monitoring of individual herd milk composition and quality.
This brochure presents FAO ’s work on agricultural innovation. FAO advocates a shift from interventions focusing on single components of agricultural innovation towards a system-approach aimed at strengthening institutions and stakeholders’ networks that better respond to the needs of smallholder farmers.
This working paper summarizes the findings of a portfolio review conducted to explore the gender and youth responsiveness of climate-smart agriculture technologies tested across climate-smart villages. The innovative and integrative aspect of the Climate-Smart Village (CSV) approach can provide useful insights into how to decrease the gender gap in the context of climate change.
The video (in Vietnamese language- English subtitles) tackles how to mainstream Gender and Social Inclusion (GSI in setting up a Climate-Smart Village (CSV). GSI should be integrated in the eight guide steps in establishing a CSV, such as: determining the purpose and scope of CSV; identifying the climate risk in the target area/s; locating the CSV in a small landscape; consulting the stakeholders; evaluating the CSA options; developing portfolio; scaling-up; and monitoring and evaluating uptake and outcome.