Utilização de ferramentas de agricultura de precisão na definição de zonas de manejo

• Autor(a) principal: Cocco, Leonardo Burin
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/0013000015b07
• Texto Completo: http://repositorio.ufsm.br/handle/1/4832
• topic: Agricultura de precisão; Atributos químicos do solo; Mapas de produtividade; Imagens de satélite; Zonas de manejo; Precision agriculture; Chemical soil attributes; Productivity maps; Satellite images; Management areas; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA

Precision agriculture (AP) appears as a permissible tool to manage rationally the spatial and temporal variability of soil chemical attributes in order to effectively maximize the use of agricultural areas. However, in some situations visualized a low correlation between the chemical soil properties and crop productivity, emphasizing the need for development of AP to seek alternatives and tools for the definition of management zones. In recent years, they have gained prominence studies of parameter attributes of plant canopies, and the Vegetation Index (NDVI) the best known. This study aimed to evaluate the use of AP tools to define management zones in the central region of Rio Grande do Sul. The work was conducted with the culture of the agricultural year 2014/15 corn in an area of 15.1 hectares in the municipality of Julio de Castilhos, RS, managed with irrigation center pivot. The spatial variability of soil attributes and plants was characterized based on the collection of information on a sampling grid of 0.5 ha, totaling 32 points in the experimental area. The Landsat satellite images (NDVI) with a spatial resolution of 30 x 30 m were processed enabling the production of productivity map and the definition of management zones in the area. The soil properties have high variance in the standard deviation (S) and coefficient of variation (CV%) of phosphorus (18.16 and 42.46), potassium (38.263 and 25.80), aluminum saturation (4,63 and 130.14) sulfur (6.72 and 40.57) and manganese (7.32 and 30.23). The analysis of the statistical and geostatistical to dry mass (28,10% CV and r2 = 0.96) and corn (11.85% CV and r2 = 0.99). The Pearson correlation was significant positively to productivity of corn kernels indicated the clay, base saturation, calcium, SMP index, magnesium and NDVI; indicated dry weight organic material, SMP index CTC pH7 and magnesium. Among the different methods of zones positive correlation between dry matter areas of stubble and productivity with altitude zone, chemical attributes zone and NDVI zone. The use of satellite images made it possible to guarantee the evaluation of different management zones.