Utilização de recursos de agricultura de precisão na geração de mapas de atributos, mapas de produtividade e aplicação de insumos a taxas variáveis. - Werner, Valmir (2004)
Abstract chapter 1 - Variability of a soy farming (Glycine Max (L.) Merrill) using simplified techniques of precision agriculture. This work had as main objective to determine and analyze the spatial variability in soy farming, comparing a yield map with maps of soil chemical and physical attributes and plants technical parameters, using simplified techniques of Precision Farming. This research was accomplished in a commercial soy farming (crop of 200 1/2002) of approximately 7,64 hectares, used by the Agricultural School of Santa Maria - CASM - located in the campus of the Federal University of Santa Maria, Santa Maria - RS. The area was in the third year of the soy cultivation using the winter pasture with black oat grass (Avena sativa) and ryegrass (Lolium multiflorum) in the cultural rotation. The samplings were accomplished in a grid of 50m x 50m, georeferencing with a navigation GPS. At the end of the research, it was concluded that the area shows located problems of calagem and fertility that can be corrected with variable rate applications. This area also presents problems with little deep soil (area with a larger soil penetration resistance) that limited the productivity on that agricultural year. The lineal correlation of the attributes studied with the productivity has presented the following values: Soil penetration resistance presented negative correlation of 46%; calcium 39,4%; magnesium 37,1%; harmful plants with negative correlation of 27%; organic matter 18%; potassium 13,9%; pH 13,8%; plants of the culture 10,5% and the phosphorus with negative correlation of 9,1%. Abstract chapter 2 - Application of fertilizer at variable rate in precision farming varying the speed of displacement. This work had as main objective to evaluate the performance of the denominated "virtual implement" in the field, applying fertilizers throws. The virtual Implement consists of a group in that the tractor (equipped for the Precision Farming) uses any implement to accomplish the applications. The work variation and the specific management for the different areas are just controlled by the tractor performance and your possibilities of the speed variations. For so much, was determined on the field the work width, distribution uniformity, distribution variation along the outline and the applied rate variation. The study was accomplished in one soy farming, in the locality of Senador Salgado Filho, municipal district of Santa Rosa-RS. For better representation of the tests, it was looked for a soil condition and farming relief that represent the real situation of use of the machine group. The fertilizer used in the tests had the formulation NPK 2-16-28. The machine group using in the realization of the work was a tractor and a solids centrifugal distributor. The results of this work shown that, in the situation of the study and with the used fertilizer, it is possible to recommend the equipment for widths between 20,5 and 22,5 meters in the two application circuits, with variation coefficients (CV) below 15%. In the longitudinal distribution it was obtained values of variation coefficients between 8,78% and 12,48%. The used machine group allows to compose several application rates, could be used the speed variation to alter them in the Precision Agriculture system. Abstract chapter 3 - Correlation between yield maps generated by a harvester and manually, in precision farming This work had as main objective to map the productivity of a commercial soy farming collecting the data in two different ways (manual and automated), correlating these maps amongst themselves. This research was accomplished in a commercial area of soy, destined to works in Precision Farming, in the municipal district of “NãoMe-Toque-RS”. This area is part of the Project Aquarius where participat several companies that work with Precision Farming, in the State of “Rio Grande do Sul”. This work was accomplished in an area with 124 ha, located between the coordinates E 324883,39 - E 326192,19 and N 6843914,29 - N 6845403,71. From this area it was used 87,9 totaling 87 points of manual productivity collection. In the crop in precision farming was used a grain harvester equipped with a automatic System data collection. The accompaniment, cleaning, calibrations of the group of equipments are very important and they should be accomplished periodically during the crop (collection of data) for the obtaining of maps of better quality. In the crossing of the digital models, it was determined an overlaping of 61% of the total area in the productivity between 3213 and 3713 kg, in the two models. Already in the classes two (2713-3213) and three (3213 - 3713), an inversion of the productivities happens.