Análise técnica de diferentes grids amostrais para identificar a variabilidade de fósforo e potássio no solo

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Schons, Francis Luan
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
Brasil
Tecnologia em Agricultura de Precisão
UFSM
Programa de Pós-Graduação em Agricultura de Precisão
Colégio Politécnico da UFSM
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufsm.br/handle/1/11763
Resumo: Soil fertility managed by precision agriculture has georeferenced sampling grid as its main data collection method. Although technology is well-accepted , there is a need to improve how techniques are applied in different environments and production systems. The main objective of this study was to analyze different sampling grids in order to identify soil variability of phosphorus and potassium. The research was carried out in the city of Victor Graeff, Rio Grande do Sul, in an area of 19.3 hectares. Three grid samples with regular squares were generated: 71,71x 71,71m (0.5 ha),71,71x141,42 m (1 ha) and 141,42x141,42 m (2 ha), a total of 36, 18 and 9 sampling points, respectively. A descriptive analysis of the data and an evaluation of the relative standard deviation (RSD) was performed, which showed that for both phosphorus and potassium, as the sampling grid size increases and the distance between the points, the dissimilarity of maps increases as well, while evaluating reference sampling grid (71,71x 71,71 m). According to the study, it is recommended to use thicker sampling grid, with a larger number of samples to generate thematic maps with a suitable representation of the spatial variation of phosphorus and potassium. Keywords: Precision Agriculture. Spatial Variability. Relative Deviation Coefficient.