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Book (stand-alone)Technical bookBeyond timber: social, economic and cultural dimensions of non-wood forest products in Asia and the Pacific 1995
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Book (stand-alone)Technical bookUsing artificial intelligence to assess FAO’s knowledge base on the technology accelerator 2023
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No results found.Harnessing science, technology and innovation (STI) is key to meeting the aspirations of efficient, inclusive, resilient and sustainable agrifood systems and leveraging emerging opportunities to achieve the Sustainable Development Goals (SDGs). The FAO Strategic Framework 2022–2031 identifies STI as having enormous transformative potential and underlines the potential of emerging technologies. It also recognizes that STI can present substantial risks, such as reinforcing inequality and market concentration, or contributing to the degradation of natural resources. As one of four accelerators identified by the FAO Strategic Framework 2022–2031, technology is expected to “accelerate impact while minimizing trade-offs”. This report examines the technology accelerator trends across publicly available FAO knowledge reports, technical guidance and convening summaries. Leveraging AI-assisted classification of nearly 40 000 documents, this report offers a bird’s-eye perspective of six types of technology – digital technologies, biotechnologies, mechanization, irrigation technologies, renewable energy technologies and food processing technologies – as well as high-level trends for outcomes and social and demographic details about the communities using these technologies. -
ArticleJournal articleMaking food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and emerging risk identification tools 2024
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No results found.To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify early signals of emerging food safety risks and to provide early warning in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things tools and methods as part of early warning and emerging risk identification in the food safety domain. There is an ongoing rapid development of systems fed by numerous, real-time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real-time food safety risk early warning systems. Although these developments and tools increase the feasibility and effectiveness of prospective early warning and emerging risk identification, their implementation may prove challenging, particularly for low- and middle-income countries due to low connectivity and data availability. It is advocated to overcome these challenges by improving the capability and capacity of national authorities, as well as by enhancing their collaboration with the private sector and international organizations.
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Brochure, flyer, fact-sheetBrochureFamily farming is… harnessing traditional knowledge to strengthen biodiversity in the Philippines
Story by Nonito Timbang Malingay
2025This story presents the experiences and voices of family farmers leading the way towards greater sustainability in agrifood systems through a blend of traditional knowledge and innovation. The story itself showcases how family farmers are conserving and restoring biodiversity, adapting to climate change, and/or sustainablymanaging natural resources.This story was selected from 273 stories received from 68 countries around the world through an open call held in 2025, entitled “Global Call for Stories: Family farmers at the heart of climate-resilient and sustainable agrifood systems” led by the FAO Family Farming Knowledge Platform (FFKP), the FAO Family Farming Engagement, Parliamentary Networks and ComDev Initiatives Unit and a coalition of Allies. -
Brochure, flyer, fact-sheetBrochureLooking beyond impacts to fully understand a human-wildlife conflict situation 2024
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No results found.This case study focuses on the arid landscapes of southern Namibia, primarily private lands used for small livestock farming (sheep and goats). Due to a long history of predator persecution, large carnivores have largely disappeared from the area, leaving only transient cheetahs and leopards, which are swiftly removed when detected on farmland. As a result, the caracal (Caracal caracal) has emerged as the apex predator. This study demonstrates how a social science approach, combined with ecological research, provided crucial insights and led to the development of effective solutions to address ongoing predator persecution. -
Book (stand-alone)Technical bookMainstreaming biodiversity across agriculture and forestry in the Lao People's Democratic Republic
Roadmap 2024–2030
2025Also available in:
No results found.This Roadmap for the Lao People's Democratic Republic charts a path to mainstream biodiversity across agriculture, livestock, forestry, and fisheries. It addresses urgent threats like deforestation and climate change, proposing integrated, sector-wide solutions. By aligning biodiversity conservation with economic development, the document calls for collaborative, transformative action. The goal: a resilient, biodiverse country where people and nature thrive together.