Relação da população de plantas de soja (Glicine max L.) por ambientes produtivos definidos pelo mapa de colheita

• Ano de defesa: 2019
• Autor(a) principal: Pesini, Felipe
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Tecnologia em Agricultura de Precisão; UFSM; Programa de Pós-Graduação em Agricultura de Precisão; Colégio Politécnico da UFSM
• Palavras-chave em Português: Agricultura de precisão; População de plantas; Mapa de colheita; Precision agriculture; Plant population; Harvest map; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/19460

Brazil has world prominence in soy production, farmers seek new technologies to improve their profitability. Precision Farming is an essential tool for detecting problems within the property and assisting in decision making. In the field we observed many plots that the soybean plant population gets very stained even if sowing at a fixed rate and this can often affect productivity. The objective of this work was to evaluate the variability of soybean plant population in different productive environments and its impact on crop maps. The work was carried out in a commercial field of 35.05 hectares and the soybean cultivar NS 5959 was used. Sowing was carried out at a variable rate, with a variation of only 5% according to the productive potential of the field, precisely to evaluate the behavior. of the final plant population. At stage R6 a 0.25 ha sample grid was generated, ie one plot every 50 meters, each plot was evaluated 6.75 m² and the final plant population was counted. This field was harvested and the harvest map was generated, soon after the soil was collected with georeferenced samples with a 2 ha grid. After several cycles of georeferenced soil sampling and variable rate interventions, the studied area presented a good nutrient balance, thus meeting the demands of the soybean crop that was implanted. Saturation of Bases, Calcium, Magnesium, Potassium, Copper and Manganese were negatively correlated, while Phosphorus, Boron and Sulfur were positively correlated with the soybean study. The population variability of final plants presented a amplitude of 26.16% and a CV of 4.95%, showing that the environment had an influence on the loss of viable seeds in the soil. With the principal component analysis it was possible to identify the measures responsible for the largest variations among the results, reducing the volume from 18 initial attributes to 5, directing the study. Excess plant population caused the cultivar to become bedridden and reduced soybean yield. With a population of 31 plants.m-2 the productivity was 3984.4 kg.ha1 , when the population increased to 36 plants.m-2 the productivity was 3785.7 kg.ha-1 and in the maximum population, of 39 plants.m-2 yield was 3625.2 kg.ha-1 , which treatment differed statistically with the first treatment described, causing variability in the harvest map. It is a difference of 359.2 kg.ha-1 , in the average price of the year in the amount of R$ 65.00 the bag is a value of R$ 389.13/ha difference. This shows the insecurity of the farmer at the time of sowing, which for fear of seed quality, climate and sowing condition end up putting more seeds than it should, resulting in increased cost and decreased productivity.