Desempenho de aspersor móvel para pequenas áreas e hortas
Ano de defesa: | 2021 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Estadual do Oeste do Paraná
Cascavel |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Agrícola
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Departamento: |
Centro de Ciências Exatas e Tecnológicas
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País: |
Brasil
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Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://tede.unioeste.br/handle/tede/5386 |
Resumo: | Water flow applied in most irrigated agricultural areas is higher than what is actually needed for food production. Irrigation is considered one of the most important water consuming activities, so, its application must be treated with precision avoiding unnecessary use. Thus, it becomes important to use water efficiently with the right knowledge and to use alternatives that optimize its use. Several measures can be taken for the rational use of water, such as the use of correct designed equipment that presents good optimization of water amount to be applied and the best management. Thus, this work aimed at evaluating a small alternative mobile sprinkler, that could work in a static pattern. So, a mobile sprinkler and a sampling grid 1 with collectors on its sides were evaluated, in which the tests were carried out during the morning (from 8 AM to 12 PM), in the afternoon (from 1 PM to 6 PM) and at night (from 7 PM to 11 PM) and a sampling grid 2 with the same times, but with the collectors on their sides and also in their front and back. Therefore, the data and comparison with different wind intensities were obtained as well as the operating pressure of a conventional low pressure faucet. The performance of descriptive statistics and control graphics, using the Minitab program, RStudio software, SigmaPlot® and the data were submitted to the analysis of variance and average test. In the analysis of variance, the F test was used at 5% level of probability. The averages were compared to the Tukey test, at 5% probability. Based on the descriptive analysis, it was observed that, in general, the raw spacing among collectors of 0.50 m for both grids presented the highest averages, smallest deviations, variances and variation coefficient of data for Christiansen's Uniformity Coefficient, Distribution uniformity coefficient and Static uniformity coefficient. However, the Christiansen's Uniformity Coefficient, Distribution Uniformity Coefficient showed the best averages, the smallest deviations, variances and variation coefficient when using the mesh grid. On the other hand, the Static uniformity coefficient in the cross grid showed the highest average, the lowest standard deviation, variance and variation coefficient. The variations observed in the uniformity coefficients throughout the tests were associated with climatic changes, since the tests were carried out at different times of the day. Consequently, the irrigator and / or technician must monitor the local climatic conditions, mainly the wind speed, so that there is no interference in the uniformity of water application by the sprinkler irrigation system. Grids did not influence Christiansen's Uniformity Coefficient, Distribution Uniformity Coefficient and Static Uniformity Coefficient. The 0.50 m collector spacing provided the best values for uniformity coefficients. The wind speed affected directly the uniformity coefficients. The study of static quality control made it possible to observe data variability throughout the tests and, generally, a large part of the data was within the quality limits. According to the process capacity, all uniformity coefficients are within the process instruction point. |