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dc.contributor.authorFASIABEN, M. do C. R.pt_BR
dc.contributor.authorOLIVEIRA, A.pt_BR
dc.contributor.authorMAIA, A.pt_BR
dc.contributor.authorMARIN, F.pt_BR
dc.contributor.authorALMEIDA, M.pt_BR
dc.contributor.authorOLIVEIRA, O. dept_BR
dc.date.accessioned2013-11-04T11:11:11Zpt_BR
dc.date.available2013-11-04T11:11:11Zpt_BR
dc.date.created2013-11-04pt_BR
dc.date.issued2013pt_BR
dc.identifier.citationIn: INTERANTIONAL CONFERENCE ON AGRICULTURAL STATISTICS, 6., 2013, Rio de Janeiro. Improving Statistics for Food Security, Sustainable Agriculture, and Rural Development Rio de Janeiro: IBGE, 2013.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/970198pt_BR
dc.descriptionAbstract: Given the large territorial extension and the high social and economic diversity, Brazil has a remarkable variability in agricultural cropping systems. The description and the understanding of this variability is fundamental for proposing research gaps, technology transfer and appropriate public policies for the sector. Sugarcane is used for several purposes on farms, such as household consumption, energy and sugar production, and forage production. Data collected during the 2006 agricultural census, accomplished by the Brazilian Institute of Geography and Statistics (IBGE), shows that 192,931 farms (3.7% of Brazilian farms) reported having grown sugarcane in 2006. This paper addresses the classification and characterization of the sugarcane producing municipalities in Brazil, using techniques of multivariate statistical analysis (factor and cluster analysis). The 41 variables used were created from the data collected by the 2006 agricultural census, covering 3,576 municipalities. Data went through a sugarcane filter, and was then regrouped by municipality. Those variables gather socioeconomic and technological information on the farms, such as land usage, harvested area, production goal, productivity, input usage, use of industrial wastes, irrigation, source of producer?s income, percentage of the income that comes from sugarcane, family or conventional farming, size of herds, distance from the farms to sugar mills, among the most important. Analyses identified 9 different groups of sugarcane production in the municipalities, remarking large variability of sugarcane sector in Brazil, and the clear spatial differences of production and technology use in the territory. The results of the statistical analysis and the characteristics of the groups were discussed among scholars specialized in sugarcane research and were considered coherent with Brazilian reality.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectCana-de-açúcarpt_BR
dc.subjectTipologiapt_BR
dc.titleTypology of sugarcane production in Brazil: the use of multivariate statistics on municipal data.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2020-01-22T11:11:11Zpt_BR
dc.subject.thesagroAnálise Estatísticapt_BR
dc.subject.thesagroEstatísticapt_BR
dc.subject.nalthesaurusStatistical analysispt_BR
dc.subject.nalthesaurusCluster analysispt_BR
dc.subject.nalthesaurusStatisticspt_BR
dc.subject.nalthesaurusSugarcaneeng
dc.description.notesICAS VI.pt_BR
dc.format.extent2p. 1-16.pt_BR
riaa.ainfo.id970198pt_BR
riaa.ainfo.lastupdate2020-01-22 -02:00:00pt_BR
dc.contributor.institutionMARIA DO CARMO RAMOS FASIABEN, CNPTIA; ARYEVERTON FORTES DE OLIVEIRA, CNPTIA; ALEXANDRE MAIA, Unicamp; FABIO RICARDO MARIN, CNPTIA; MAXWELL ALMEIDA, IBGE; OCTÁVIO DE OLIVEIRA, IBGE.pt_BR
Aparece nas coleções:Artigo em anais de congresso (CNPTIA)

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