Uso de ferramentas de agricultura de precisão para a determinação de zonas de manejo e análise do suprimento hídrico do arroz irrigado por inundação

• Ano de defesa: 2024
• Autor(a) principal: Hamann, Pedro Trevisan
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Agronomia; UFSM; Programa de Pós-Graduação em Agricultura de Precisão; Colégio Politécnico da UFSM
• Palavras-chave em Português: Oryza sativa (L.); Geotecnologias; RPAS; Geotechnologies; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/33987

Increasing the efficiency of water use and other productive resources, in addition to maximizing crop productivity, is of great importance in the current context of preserving water and environmental resources. Thus, this study aimed to determine management zones (ZM) and analyze the water supply of flood-irrigated rice using precision agriculture tools. The document is organized into two chapters: article 1 analyzes the spatial variability of soil attributes, the establishment of ZM, and their relationship with irrigated rice productivity; article 2 evaluates the efficiency of using geotechnologies, especially RPAS images, as a tool for analyzing the water supply of flood-irrigated rice. The fieldwork was carried out on a rural property in the municipality of Cachoeira do Sul-RS, in the 2022-23 agricultural year, in two plots. For article 1, a 50-hectare plot was sampled (1 point per hectare) to collect information on soil attributes: soil bulk density, clay content, chemical attributes, and soil apparent electrical conductivity (CEa). After obtaining these variables, a database was created and the Smart-Map plugin in QGIS version 3.16 was used to perform the geostatistical analysis and preparation of spatial variability maps for each attribute that presented spatial dependence. Then, ZMs were defined based on the CEa. The analysis of soil productivity and attributes was performed by ZM. It was possible to delimit four ZMs that presented variability in relation to seven soil chemical attributes and clay content. The most productive ZMs (16,435.11 kg ha-1) had lower clay, aluminum, and soil bulk density contents, and relationships between these attributes and productivity could be established. For article 2, the water supply assessment was performed in a 33-hectare plot. The mapping of the irrigation water entry time and the VARI vegetation index was performed using images obtained by RPAS (drone). The results indicated a tendency for a linear reduction in the productivity components and rice productivity (16,645.50 to 12,993.69 kg ha-1), as the irrigation water entry delay occurs in the field. The mapping of the vegetation index indicated that there is a positive linear correlation between the VARI index values and the values of the productivity components and rice productivity. Based on the results obtained, it can be concluded that the use of precision agriculture tools can contribute to the definition of management practices that increase the productivity of flood-irrigated rice.