Le présent rapport devrait, grâce à tous les éléments analysés, aider les décideurs et l’ensemble des acteurs du secteur agricole dans leur prise de décision quant à l’utilisation et à la gestion des nouvelles technologies numériques en agriculture avec comme objectif afin de s’assurer que cette industrie demeure très compétitive.
Innovation rests not only on discovery but also on cooperation and interactive learning. In agriculture, forestry and related sectors, multi-actor partnerships for ‘co-innovation’ occur in many forms, from international projects to informal ‘actor configurations’. Common attributes are that they include actors with ‘complementary forms of knowledge’ who collaborate in an innovation process, engage with a ‘larger periphery’ of stakeholders in the Agricultural Knowledge and Innovation System (AKIS) and are shaped by institutions.
Depuis que les êtres humains sont passés à un mode de vie agraire, les progrès technologiques ont permis des évolutions dans l'agriculture, résultant en de plus grandes variétés et rendements des cultures. Après les révolutions de la sélection végétale et de la génétique, une troisième révolution verte prend le contrôle du monde agricole basé sur l'application des technologies de l'information et de la communication (TIC) telles que les capteurs et actionneurs, l'Internet des objets (IoT : Internet of Things), l'intelligence artificielle, les véhicules aériens sans pilote (UAVs, drones).
Les capteurs, allant du simple thermomètre jusqu’aux drones, se sont démocratisés dans les exploitations agricoles. Ils permettent désormais de collecter une multitude d’informations sur l’ensemble de l’exploitation et de transmettre en temps réel des données sur l’état et les performances des machines, des cultures et des animaux.
Undoubtedly, high demands for food from the world-wide growing population are impacting the environment and putting many pressures on agricultural productivity. Agriculture 4.0, as the fourth evolution in the farming technology, puts forward four essential requirements: increasing productivity, allocating resources reasonably, adapting to climate change, and avoiding food waste.
Monitoring animal performance is a challenge due to lack of systematic recording in the smallholder dairy sector in Malawi. A mobile recording system using short messaging service (SMS) was therefore trialled for data capturing and subsequent feedback provision to farmers following analyses and interpretation. This study aimed at drawing lessons regarding use of SMS recording system among dairy farmers. Of the 210 participants, 85% were farmers and 25% were other dairy value chain players.
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.
Since development agencies often implement interventions through collective-action groups such as farmer cooperatives and self-help groups, there is a need to understand how participation is affected by group-level and leader attributes. This study collected gender-disaggregated, quantitative and qualitative data on sixty-eight self-help groups in Zambia to understand the participation of men and women farmers in different crop-production activities. Results show that participation rates of men and women are the same across all maize production activities except harvesting.
Ghana’s cocoa production belt also serves as the main forests repository of the country. Cocoa farm- ing is both a direct and indirect driver of deforesta- tion in Ghana (UNEP, 2008). This implies that critical interventions are needed to deal with deforestation emanating from cocoa production.
This report presents and reflects on the opportunities that new technological developments related to automation and precision agriculture (e.g. robotics) can offer to agriculture in developing countries. These technologies are mainly targeted to support farmers that struggle with the cost of labour when harvesting crops and to tackle the declining availability of manpower for general cropping operations.