Geoestatística e sistemas “Fuzzy” na proteção de plantas

• Ano de defesa: 2006
• Autor(a) principal: Alves, Marcelo de Carvalho
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: UNIVERSIDADE FEDERAL DE LAVRAS; DAG - Programa de Pós-graduação; UFLA; BRASIL
• Palavras-chave em Português: Geoprocessamento; Agricultura de precisão; Geociência; Geotecnologia; Geoinformática; Epidemiologia; Estatística; Inteligência artificial; Ecologia; Grandes culturas; Geoprocessing; Precision farming; Geoscience; Geotechnologies; Geoinformatics; Epidemiology; Statistics; Artificial intelligence; Ecology; Great crops; CNPQ_NÃO_INFORMADO
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/4298

The Geoscience and Artificial Intelligence presents enormous potential of application in a country of continental dimensions, such as Brazil, where it can be used to support the lack of decision support information about agriculture and environment problems. It has been even more necessary to use those methodologies to optimize resources and to reduce costs of rural enterprises quality control programs. In that context, it was aimed at with Geographical Information Systems, Geostatistics, Remote Sensing, Digital Image Processing, Fuzzy Logic Systems, Neural Networks and Statistics, in order to explore and to understand some biotical and abiotical factors related to Plant Protection. In the chapter 2 and 3, Fuzzy Logic System and Neuro-Fuzzy System were respectively developed, validated and implemented to estimate the asian soybean rust and coffee rust monocyclic process based in temperature and leaf wetness period. In the chapter 4, techniques of Precision Farming were used to detect spatial variability patterns of agronomic variables and to study the dynamics of some processes that influence in the coffee crop management. Last, in the chapter 5, Geographical Information Systems and Geostatistics were applied to study the ecology and epidemiology aspects of common bean antracnose and cotton ramulose seed borne fungi.