Using climatic variables to estimate dry matter production in the grazing stratum of Piatã palisadegrass

Abstract

AbstractThe modeling of pasture production could be used as a tool to make the process of working with increasingly erratic precipitation and temperature patterns resulting from climate change easier and more accurate. This study aimed to define models to determine dry matter, leaf and stem production associated with climatic variables for Palisadegrass (Brachiaria brizantha cv. Piatã) in the grazing stratum. Four treatments were established to provide the greatest variability throughout the experiment, consisting of two light interception percentages as cutting criteria (95 and 100%) and two residue heights (15 and 20 cm). Data were collected between January 2012 and December 2013. Dry matter production day−1 (DMPd), leaf production day−1 (LPd) and stem production day−1 (SPd) were regressed against 13 climatic variables. The variables were also corrected by multiplying each variable by the relationship: real evapotranspiration/potential evapotranspiration. The backward procedure was used to determine significant variables to estimate production; then a multiple regression was fitted. When the corrected variables presented better Akaike's Information Criterion (AIC), they replaced the original variables. The analysis showed that climate variables are adequate to estimate DMPd, LPd and SPd in palisadegrass cv. Piatã, and the models should significantly contribute to pasture management across tropical regions.