dc.contributorGiotto, Enio
dc.contributorhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4783625T4
dc.contributorDornelles, Marçal Elizandro de Carvalho
dc.contributorhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4718767D8
dc.contributorMedeiros, Fabrício Ardais
dc.contributorhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4533070E6
dc.creatorBarato, Márcio Adair
dc.date.accessioned2015-05-06
dc.date.available2015-05-06
dc.date.created2015-05-06
dc.date.issued2014-09-26
dc.identifierBARATO, Márcio Adair. FIELD PRODUCTIVITY EVOLUTIVE ANALYSIS. 2014. 70 f. Dissertação (Mestrado em Agronomia) - Universidade Federal de Santa Maria, Santa Maria, 2014.
dc.identifierhttp://repositorio.ufsm.br/handle/1/4814
dc.description.abstractBased on productivity maps and data analysis it is possible for the producer to check and act over the low yielding areas, maximizing the final productivity that way. This paper intents to show the importance of the usage of precision agriculture maps on farms in order to help farmers to determine low yielding areas and act over it, improving productivity. This paper and the generated maps referred during the text were made using John Deere equipment and AMS (Agricultural Management Solutions). The studied area is a 19ha (190.000m²) total area, located at Faxinal, Paraná state. Five maps were analyzed totaling a 3 years range period of samples that were used later for interpolation. The interpolations and adjustments done were made using Apex® and CR Campeiro® software. The output of this interpolation is a single map that shows some tendencies for some areas to present low, medium and high yield. Those regions represent 5,95%, 86,25% and 7,80% respectively. This map is a base for the final analysis that will provide information to develop and increase productivity in low yielding areas.
dc.publisherUniversidade Federal de Santa Maria
dc.publisherBR
dc.publisherTecnologia em Agricultura de Precisão
dc.publisherUFSM
dc.publisherPrograma de Pós-Graduação em Agricultura de Precisão
dc.rightsAcesso Aberto
dc.subjectAgricultura de precisão
dc.subjectMapa de produtividade
dc.subjectSensor de massa
dc.subjectSensor de umidade
dc.subjectPrecision agriculture
dc.subjectYield map (or productivity map )
dc.subjectMass sensor
dc.subjectMoisture sensor
dc.titleDefinição de zonas de manejo em lavouras agrícolas a partir de mapas de produtividade: estudo de caso
dc.typeDissertação


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