2017 Volume 63 Issue 1 Pages 15-22
In order to extend the stocking period in fall and winter, the best species and seeding time should be selected, and grazing management should be planned, to enable more animals to be stocked for a longer period. Therefore, we de-veloped a predictive model for herbage production of oat, rye, and Italian ryegrass sown in late summer or early fall. To construct a growth curve, data collected from both a field experiment, which measured the early growth of the species, and a database, which contains information on recommended varieties of the species, were used. Temperature at each seed-ing day was included as a covariate, and it was derived by multiple regression of the mean yearly temperature at the sowing place and the seeding date. Although the constructed model showed low accuracy, it could predict a trend in ob-served mass for days after seeding and temperatures on the seeding date. The model could also yield a stable estimate for cross-validation of independent unknown data. Thus, it can be concluded that the model aids in approximate estimation, which could contribute to the development of a grazing man-agement plan for extending the stocking period in fall and winter using winter annuals.
