Modeling the Nutritive Value of Defoliated Tall Fescue Pastures Based on Leaf Morphogenesis

The leaf morphogenetic‐based model predicted the pasture nutritive value variance generated by in an ad hoc experiment.Variation in fiber digestibility with the age and length of leaves is the main driver for declines in pasture digestibility of vegetative regrowth.The morphogenetic approach was designed to enable its potential integration with some of the available pasture growth models.The model provided mechanistic understanding and predictions that allow for the exploration of new management strategies. The leaf morphogenesis of plants is the most important determinant of the nutritive value dynamics in vegetative pasture regrowth. The aim of this study was to develop a simulation model of the pasture nutritive value dynamics based on a morphogenetic approach that takes into account the effects of leaf age and leaf length on forage digestibility in relation to defoliation management. The model was developed and evaluated with detailed data from two independent experiments (Exp. 1 and Exp. 2, respectively) on tall fescue [Lolium arundinaceum(Schreb.) Darbysh.], including descriptions of morphogenesis, neutral detergent fiber (NDF) and digestibility of NDF (NDFD) and dry matter (DMD) of leaf blades. The model precisely and accurately simulated the forage digestibility dynamics of pasture regrowth observed under different residual pasture heights in Exp. 2. The main calculated statistics for NDF, NDFD, and DMD were root mean square deviation < 4% points, R2≥ 0.92, concordance correlation coefficient ≥ 0.86 and bias correlation factor ≥ 0.89. The evaluated model was used to investigate the responses of forage nutritive value to several combinations of residual pasture heights (2–15 cm) and defoliation intervals (one to five leaves per tiller). This study highlights the inclusion of the NDFD trait associated to leaf morphogenesis as a mechanistic way to improve predictions of DMD dynamics in vegetative regrowth under different defoliation managements.