@InProceedings{Nolasco:2018:ExScFr,
author = "Nolasco, Camille Lanzarotti",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Towards adaptation of food systems to meet nutritional
recommendations: exploring scenarios of fresh vegetable demand and
production in Brazil",
year = "2018",
organization = "Adaptation Futures: International Climate Change Adaptation
Conference, 5.",
abstract = "Despite the production of enough food to feed all the people in
the planet, every day 815 million people go hungry accordingly to
The U.N. Food and Agriculture Organizations (FAO) 2017 report on
the State of Food Security and Nutrition (SOFI). Feed the world
with nutritious food with the lower impact on environments and
ecosystems functions is the most important challenge of nowadays
and linked with almost all the the 2030 Agenda for Sustainable
Development. The World Health Organization recommends a daily
consumption of 400 g of fruits and vegetables, an amount consumed
in 2009 by only 18.9% of the Brazilian population. In 2014
Brazilīs Government launched a new Dietary Guidelines for the
Brazilian Population which encourage the consumption of raw
vegetable, however little is known and mapped about fresh
vegetable accessibility regarding the regional links between
demand and production. Key issues in this sector must be tackled
by government and civil society, not only to foster consumers
appetite for healthier food, but more importantly, to diminish the
gaps between local demand and production, fostering adaptations
towards a sustainable food system. In this sense, this study aimed
to developed vegetable demand scenarios in Brazil for 2008 and
2030, based on demand density maps built at the district level (>
300,000 units) using production census surveys, household
acquisition data, and population growth estimates. We calculate
and spatialize the demand for vegetables in each census tract
creating detailed scenarios that could allow further investigation
on the connections between demand, regional/local production, and
their drivers. These maps are useful in the space-time
understanding of the demand for food distribution from
horticulture, and relevant both when considering the continental
dimensions of Brazil and its immense spatial heterogeneity in
relation to human and environmental dimensions, and the consequent
need for public policies adapted to the different regions
respecting their potential, customs and different vulnerabilities.
The results revealed an imbalance in vegetable consumption between
the southern and central northern regions of Brazil that follows
food insecurity regional indicators. Even in more urbanized
regions and metropolitan areas, where the best balance between
vegetable production and acquisition is found, simulated demand is
far from WHO recommendations. The National Plan for Food and
Nutrition Security aimed to promote food and nutritional security
with integrated actions to strengthen food production, including
stimuli for small crop farming, alternative food supply channels,
and the promotion of healthy/adequate food consumption.
Nevertheless, food and nutritional security depends on a variety
of public and private institutions, largely profit-prioritizing
transnational corporations such as retail food chains and
agrochemical industries, which promotes unequal access to fresh
food. The failure to meet the National Plan reflects an
institutional inability to apply efficient governance to the
economic, ecological, and social dimensions of the problem at
different spatial scales. The search for alternatives that
consider all these dimensions across spatial scales has motivated
this work, as understanding national demands for more nutritious
and culturally accepted food is a first step to adapt food systems
in the face of socioenvironmental changes. This work was the
foundation to the Delivering Food Security on Limited Land (DEVIL)
project in Brazil supported by Belmont Forum consortium.",
conference-location = "Cape Town, South Africa",
conference-year = "18-21 June",
language = "en",
urlaccessdate = "27 abr. 2024"
}