We evaluate the volatility spillovers among coffee, ethanol, soybeans, reformulated blendstock for oxygenate blending (RBOB) futures prices, and Brazilian spot prices from 2010 to 2020. Using the Diebold and Yilmaz volatility spillover analytical framework (DY), we estimate the total volatility spillover, the gross and net directional volatility spillover. We also analyze the optimal hedge ratio applying the linear quantile regression (QR) model, comparing the optimal hedge ratios with the minimum variance (MV) and error correction model (ECM). Results show an increasing trend in the total volatility spillover index, suggesting an increase in the Brazilian market's connectedness. In addition, we identify quantile ranges where the QR hedge is economical and statistically significant, particularly for extreme spot prices, lower-and-upper quantiles. The knowledge of the volatility spillover effect in agricultural commodity markets may provide additional information for efficient resource allocation decisions about harvesting, output, storage, commercialization, and hedging.