The integration of AI in agricultural management presents a world of opportunities and challenges. We have explored various aspects, from addressing inadequate information and limited capabilities to bridging the digital divide and concerns about job displacement. As we navigate this transformative journey, it is essential to prioritize the user, embrace human-centered design, and ensure that AI-powered solutions are not only feasible but also sustainable for farmers in diverse regions.

Climate change poses significant challenges to livestock systems worldwide, requiring urgent and innovative responses to ensure the resilience of these systems and the livelihoods that depend on them. This report presents the water, fodder, bush-fire and transhumance corridor monitoring system as well as the livestock climate information information dissemination in the pastoral zones of Senegal.

This study investigates the effect of married couples’ joint decision-making on rice variety selection on rice productivity—a measure of food security. The study uses the 2016 Rice Monitoring Survey and the endogenous switching regression (ESR) method. Results show that rice farms with joint decision-makers (husband and wife) would have higher yields, particularly in households that adopted MRVGen1 (before 1986) rice varieties. Thus, families with joint-decision making have higher food security.

In many countries in Southern and Eastern Africa, input subsidy programmes are common, often focussing on inorganic fertiliser. These programmes often do not achieve their food security objectives, partly because soil health is in decline as a result of years of application of inorganic fertilisers in the absence of other soil ameliorative measures.

Food system transformation is intrinsically tied to effective land and water resource management, especially in the regions facing competition among various land uses. The AhafoAno Southwest District in Ghana exemplifies this complexity, with agriculture, mining, and agroforestry practices competing against one another for arable land, impacting the local food system and contributing to water resource degradation.

This paper presents a temperature-based early warning alert system for fish farmers in Zambia. The decision support tool indicating the conditions under which air temperatures may result in a normal, high risk or emergency scenario, combined with the monitoring and management mitigations recommended under each scenario. During model development, five models were compared, including linear regression, stochastic regression, deep learning, random forest, and decision tree.

Bangladesh’s water management shifted toward a decentralized system in the 1990s, with more power to community, including the water management groups (WMGs). Empirical evidence, however, suggests unequal access to water among women and marginalized populations. To zoom into this, we reviewed studies published after 2000 to synthesize evidence on access to water among women and marginalized people, their recognition and representation in institutions, and barriers to those, in Bangladesh.

In Laos, farmers are using the validated agro-climatic advisories from the Alliance-supported Strengthening Agro-climatic Monitoring and Information System to improve their farming practices, such as crop variety, planting dates, and water and fertilizer applications. These advisories were integrated into the Laos Climate Services for Agriculture (LaCSA) system which disseminates information to over 100,000 farmers through farmer field schools, loudspeaker broadcasts, Whatsapp and Facebook. It is currently at the operational stage.

In an ever-evolving landscape of regulations and commitments to net-zero emission commodity chains, Terra-i+ offers a satellite-based solution for agroforestry supply chain sustainability management. At its core, Terra-i+ functions as an integrated platform to access critical information about the sustainability status of coffee supply chains. With Terra-i+, stakeholders gain access to essential metrics and insights, empowering them to make informed decisions that drive adoption of sustainable practices.

The aim of this course is to develop skills in soil carbon (SC) estimation and Soil Carbon Sequestration (SCS) methods/techniques to reduce GHG emissions for sustainable crop production systems.

Peatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050.