Abstract
The main of this work was to identify teleconnection patterns that influence soybean yield variability in Rio Grande do Sul in order to find potential predictors of agricultural yield in the State. Soybean yield data from 87 municipalities provided by the Brazilian Institute of Geography and Statistics were used. These series were grouped into three homogeneous groups of yield by cluster analysis. Lag correlations between climatic indexes associated with teleconnection patterns and mean soybean yield of each of the three groups evidenced the importance of each index for the crop in Rio Grande do Sul. Among the teleconnection patterns, the ones that presented most significant correlations, confidence higher than 90%, and persistent with soybean yield were the Arctic Oscillation (negative between October and December), North Atlantic Oscillation (negative between October and January) and Sea Surface Temperature anomalies in the Atlantic Ocean, between 20°S-30°S and 20°O-40°W, (positive between December and March). These indices also showed a high correlation with the precipitation between December and March for each homogeneous group evidencing the importance of their monitoring for the planning of the soybean farming in Rio Grande do Sul.
Keywords:
climate index; Glycine max L; correlation; interannual variability
