15,966 research outputs found
Organic Farming in Latin America and the Caribbean
In Latin America, 220’000 producers managed 6.4 million hectares of agricultural land organically in 2007. This constitutes 20 percent of the world’s organic land. The leading countries are Argentina (2'777'959 hectares), Brazil (1'765'793 hectares) and Uruguay (930'965 hectares). The highest shares of organic agricultural land are in the Dominican Republic and Uruguay with more than six percent and in Mexico and Argentina with more than two percent. Most organic production in Latin America is for export. Important crops are tropical fruits, grains and cereals, coffee and cocoa, sugar and meats. Most organic food sales in the domestic markets of the countries occur in major cities, such as Buenos Aires and São Paulo.
Fifteen countries have legislation on organic farming, and four additional countries are currently developing organic regulations. Costa Rica and Argentina have both attained third country status according to the EU regulation on organic farming.
In recognition of the growing importance of the organic sector to Latin America’s agricultural economy, governmental institutions have begun to take steps towards increasing involvement; governments are beginning to play a central role in the promotion of organic agriculture. The types of support in Latin American countries range from organic agriculture promotion programs to market access support by export agencies. In a few countries, limited financial support is being given to pay certification cost during the conversion period. An important process underway in many Latin America countries is the establishment of regulations and standards for the organic sector
Data Management and Mining in Astrophysical Databases
We analyse the issues involved in the management and mining of astrophysical
data. The traditional approach to data management in the astrophysical field is
not able to keep up with the increasing size of the data gathered by modern
detectors. An essential role in the astrophysical research will be assumed by
automatic tools for information extraction from large datasets, i.e. data
mining techniques, such as clustering and classification algorithms. This asks
for an approach to data management based on data warehousing, emphasizing the
efficiency and simplicity of data access; efficiency is obtained using
multidimensional access methods and simplicity is achieved by properly handling
metadata. Clustering and classification techniques, on large datasets, pose
additional requirements: computational and memory scalability with respect to
the data size, interpretability and objectivity of clustering or classification
results. In this study we address some possible solutions.Comment: 10 pages, Late
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