These Guidelines on methods for estimating livestock production and productivity are directed towards those seeking to design, test and implement data collection activities to measure livestock production and productivity, particularly in developing countries.
Guidelines & Handbooks
The purpose of these guidelines is to develop cost-effective statistical methods for measuring post-harvest losses (PHL). The Guidelines aim to present cost-effective methods for measuring food grain losses that could be used especially by developing countries to generate timely and quality data.
This report provides guidelines and a framework for developing multistage crop forecasting systems built on existing national institutions, but also leveraging on new technical advancements in a sustainable manner.
The purpose of these guidelines is to provide operational guidance to developing countries on how to set up an effective Administrative Data System for Agricultural Statistics (ADSAS), as well as on the improvement, use and integration of administrative data in the national statistical system.
The AGRIS handbook presents the rationale of the system, focusing on the new needs and challenges in surveying farms in the 21st century. In this handbook, the link with SDGs is acknowledged, as the proposed AGRIS Generic Questionnaires will generate basic data for monitoring directly four SDG indicators and provide essential information for another 15 SDG indicators.
These guidelines seek to increase individual-level, sex-disaggregated and gender-relevant data available from agricultural surveys.
The objective of these guidelines is to provide countries with the methodological framework and tools to compile high-quality Food Balance Sheets for crop and livestock products.
Also available in: French
The purpose of this handbook is to provide guidelines on the use of remote sensing in the context of agricultural statistics.
In most countries, although the proportion of national GDP constituted by the agricultural sector has been declining for decades, the forecasting of food production remains a major challenge for all the economic actors of modern societies.
This review examines the current status of the remote sensing (RS) tools, products, methodologies and data that can help to improve agricultural crop production forecasting systems.
These Guidelines have been prepared on the basis of assessments of the methods currently used by countries to produce data on stocks, and seek to help countries design and implement both on-farm and off-farm stocks.