If the world is to transition towards agrifood systems that are more sustainable and equitable, small-scale production systems will be key to progress. Large parts of the world depend on small-scale systems for maintaining food security and nutrition (Lowder, Sánchez and Bertini, 2021; Herrero et al., 2017). Despite this centrality, neither small-scale production systems nor small-scale producers have received due recognition under predominant agrifood systems paradigms.
This report aims at inspiring strategic thinking and actions to transform agrifood systems towards a sustainable, resilient and inclusive future, by building on both previous reports in the same series as well as on a comprehensive corporate strategic foresight exercise that also nurtured FAO Strategic Framework 2022–31. It analyses major drivers of agrifood systems and explores how their trends could determine alternative futures of agrifood, socioeconomic and environmental systems.
This training manual, which is based on a methodology developed by FAO’s Research and Extension Unit (OINR), presents a training course on assessing AIS consisting of eight modules.
Due to the increasing gap between input costs and the final prices they receive for their produce, Indian farmers have been increasingly affected by the current agrarian crisis. It is within this context that Zero Budget Natural Farming (ZBNF) - a farming method promising low to zero input costs - has been gaining momentum.
This paper contends that the exclusion of millions of poor from agricultural development gains is inexorably linked to the innovation system features that have evolved over time. An oft repeated lament of the Government of India about the inadequacy of reforms in agricultural research and extension, is used to explore the structure and institutions of agricultural innovation. Three main components of the agricultural innovation system, are the agricultural research and extension actors, the farming communities, and policy making agencies.
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.
Productivity growth in smallholder agriculture is an important driver of rural economic development and poverty reduction. However, smallholder farmers often have limited access to information, which can be a serious constraint for increasing productivity. One potential mechanism to reduce information constraints is the public agricultural extension service, but its effectiveness has often been low in the past.
Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks.
Livestock have strong empowerment potential, particularly for women. They offer millions of women in the Global South the opportunity to provide protein-rich foods for home consumption and sale. Livestock provide women with income and opportunities to expand their livelihood portfolios and can strengthen women’s decision-making power. Fully realizing livestock’s empowerment potential for women is necessary for sustainable livestock development. It requires, though, that gender-equitable dynamics and norms are supported in rural communities.