Detalhes bibliográficos
| Ano de defesa: |
2021 |
| Autor(a) principal: |
SOUZA, Diego Henrique Silva de
 |
| Orientador(a): |
SILVA, Ênio Farias de França e |
| Banca de defesa: |
MONTENEGRO, Abelardo Antônio de Assunção,
LIMA, Renato Paiva de,
BANDEIRA, Douglas Henrique,
VIDAL VÁZQUEZ, Eva |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Agrícola
|
| Departamento: |
Departamento de Engenharia Agrícola
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9081
|
Resumo: |
The different configurations of relief and of the pedogenetic processes determine the type and distribution of the soil in the landscapes. The landscape conditions the environment, and its configuration is closely related to the relief, forming specific conditions in different areas. Agricultural practices adopted in areas with sugarcane production promote changes in the physical properties of the soil, causing changes that directly harm the development of the crop. The spatial variability of the physical attributes of the soil can occur at different scales, due to the complex behavior of these attributes. TTherefore, the geostatistical, multifractal and multifractal analyzes of the physical attributes of the soil allow to identify spatial dependence from the variability distribution, characterize patterns of spatial variability from the heterogeneity of scale, and determine scale-dependent relationships between the data, contributing to more appropriate management in agricultural areas. In this context, the objective of the work was to evaluate the behavior of the spatial distribution, the degree of multifractality and the correlation at different scales of the physical attributes of a toposequence of Gray Argisol and Spodosum Humiluvic, of the sugarcane productivity and of the altitude at over a transect. Soil samples (deformed and non-deformed) were collected, in the layers of 0.00-0.20 and 0.20-0.40 m deep, from the sugarcane plant, at 20 m intervals along of a 2,900 m transect, totaling 145 sampling points, plus altitude data. Average productivity was estimated through the average weight of sugarcane over the transect. The data of the analyzed variables were correlated through linear correlation, and submitted to descriptive statistics and normality analysis by the Kolmogorov-Smirnov test. The spatial dependence analysis was performed using geostatistics. The multifractality of the data was characterized by the generalized dimension, Dq and the singularity spectrum, f (α) - α, using the multifractal analysis. The correlation on multiple scales was characterized by the singularity indices, α (q, t) and β (q, t), from the joint multifractal analysis. The average productivity of sugarcane in the transect was higher than the estimated productivity for the State of Pernambuco in the 2019/2020 harvest. The spherical model was the one that best fitted for most of the analyzed variables. The spatial dependence of soil particle size fractions was best characterized by the Mie and Fraunhofer laser diffraction method. The granulometric curves in the densimeter method showed greater discontinuity than the curves in the Mie and Fraunhofer laser diffraction method, for the two soil layers studied. The silt fraction was overestimated when quantified by the Fraunhofer theory, and the clay fraction was underestimated when quantified by Mie diffraction. The analyzed variables showed behavior with a multifractal tendency, in different degrees of multifractality, and in general, obeyed the following order: Ds <PT <Mi <productivity <altitude <Ma. For soil particle size fractions in the densimeter method, the order observed was: total sand <coarse sand <fine sand <clay <silt, while in the Mie and Fraunhofer laser diffraction method, the order was: fine sand <silt <total sand <clay <coarse sand. Sugarcane productivity and soil physical attributes correlated at multiple scales stronger than altitude and soil physical attributes. |
