This guide lays out the importance of genetic resources to protect human needs, by explaining how they underpin our food and nutritional security while sustaining our environments. It also explains how the public and private sectors can work together to conserve and share the benefits of these critical resources for future generations.

the working group on data disaggregation, the Food and Agriculture Organization of the United Nations (FAO) has taken numerous steps towards supporting Member Countries in the production of disaggregated estimates. Within this framework, these Guidelines offer methodological and practical guidance for the production of direct and indirect disaggregated estimates of SDG indicators having surveys as their main or preferred data source. Furthermore, the publication provides tools to assess the accuracy of these estimates and presents strategies for the improvement of output quality, including Small Area Estimation methods.

Effective and sustainable tools, mechanisms and strategies are needed to significantly improve the prevailing agricultural productivity, farmer remuneration, and food availability globally to be able to meet the food, livelihood, and nutritional needs of the projected population in coming decades. Digital agriculture has the potential to efficiently bring together the benefits of the advances in agricultural research and the developments in information and communication technology space to help positively transform the entire spectrum of pre-farm to post-fork activities in the agriculture sector. Through interactions with over 338 stakeholders across India and Africa, supplemented with study of various digital agricultural interventions across the globe, the author observed that most digital agricultural interventions did not succeed, causing great loss of time and resources, which the world can ill afford. The world is falling behind on achieving the Sustainable Development Goals (SDGs). Drawing lessons from the failures and successes of the past digital agricultural interventions, the author has developed an innovative MS Excel tool called HeDAPSEE, to help estimate the success of a digital agricultural intervention before implementing it. This can help strengthen it in planning stages and enhance its chances of success.

This handbook has been developed to complement the MOOC on Survey Solutions. It is suitable for anyone who has experience in conducting traditional face-to-face interviews and wishes to learn the workflows and skills needed to conduct a CAPI project. The handbook’s instructions are tailored toward people with beginner or intermediate experience in Survey Solutions, particularly if they are looking to reinforce existing knowledge or learn additional functionalities. handbook is designed to help national statistical officers and other interested readers embrace the efficiencies of CAPI-based data collection to supersede the traditional pen and paper interviewing method. We hope that it contributes to the adoption of other innovative tools and technologies that further strengthen national statistical systems.