Detalhes bibliográficos
| Ano de defesa: |
2015 |
| Autor(a) principal: |
FERNANDES, Marcelo M. P.
 |
| Orientador(a): |
SILVA, Antônio A. C.
|
| Banca de defesa: |
NOGUEIRA, Denismar D. A.;Nogueira, Denismar Alves
,
SILVA, Adriano A. B.;SILVA, ADRIANO BORTOLOTTI DA
|
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade José do Rosário Vellano
|
| Programa de Pós-Graduação: |
Programa de Mestrado em Sistemas de Produção na Agropecuária
|
| Departamento: |
Pós-Graduação
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tede2.unifenas.br:8080/jspui/handle/jspui/162
|
Resumo: |
The crop prediction is a strategic activity for agribusiness because it enables the decision-making relative to various points in the production chain. In this context, the objective of this paper was to develop a software that implements the mathematical model of coffee crops prediction based on phenological indices of production established and tested by Reinato (2012) and Miranda et al. (2014). For this purpose it developed a mobile application for the Android platform that has as main features: 1) registration of farms and plots, with the possibility of calculating the area of plots through the GPS device; 2) productivity prediction calculation: implementing a mathematical model, which is composed by calculating the value of production phenological indices followed by a linear regression that converts the indice into sacks per hectare, generating also the prediction confidence interval and 3) reports consultation of previously made predictions. The application was developed and tested in the farming, and the results obtained by the application are consistent with those obtained by Reinato (2012) and Miranda et al. (2014). |
