Detalhes bibliográficos
| Ano de defesa: |
2019 |
| Autor(a) principal: |
Petter, Rudimar Luís
 |
| Orientador(a): |
Klein, Vilson Antonio
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade de Passo Fundo
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Agronomia
|
| Departamento: |
Faculdade de Agronomia e Medicina Veterinária – FAMV
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tede.upf.br:8080/jspui/handle/tede/1844
|
Resumo: |
The Geostatistical stands out mainly because it is an interdisciplinary science that allowsknowledge of the spatial variability of soil attributes. Information on biophysical parameters of vegetation can be used for many different applications, and remote sensing has proved to be a good tool to get them, both important for planning the use of an area for agricultural production. The objective of this study was to evaluate the spatial variability of chemical and physical attributes of an Oxisol managed under no tillage and its consequences in reflectance and yield of soybeans.The work was conducted with the soybean crop in crop year 2018/19, an area of41hectares in the city of Não Me Toque, RS. They were collected disturbed and undisturbed soil samples in the 0-5 cm, 5-10 cm, 10-20 cm, 90 georeferenced points along the area. It was determined chemical and physical properties of the soil.At each sample point, the reflectance of the culture was measured at two different growth stages, V6 and R5, measurement was using data from three platforms: sentinel-2 satellite,remotely piloted aerial vehicle and isPortable spectrorradiômetro. After measuring the reflectance of the culture they were calculated using the equationsvegetation indices.The production of soybean components analyzed were leaf area index, grain yield and thousand kernel weight. The attributes were analyzed by descriptive statistics and geostatistics.classes maps were generated by ordinary kriging and indicator kriging for the GS + version 7.0 software. The correlation between maps and spatial correlation was carried out after the construction of the spatial pattern of the variables under study. We used the output file .krg kriging (GS +)without loss of spatial position data. Was selected the estimated and calculated to its association with SPSS software.Most variables present spatial dependence structure with varying degree of dependence between moderate and strong, except for the variables that showed pure nugget effect. The use of geostatistical techniques for interpolation and ordinary Kriging indicator enables the identification of different areas of management by mapping the variables studied, showing regions of higher or lower levels for each variable; Through correlation maps are identified capacity cation exchange hydrogenionic potential base saturation, free magnesium content and the free calcium content in soil, respectively, as the chemical properties of the greatest influence in determining yield soybeans and total porosity, bulk density, good water range and silt content, respectively, compared to the physical soil properties. To estimate the soybean yield vegetation indices showed no significance. In determining the handling zones in the soil, the indicator kriging procedure introduced a more reliable and better visibility than ordinary Kriging. |
