GrasProg: Pasture Model for Predicting Daily Pasture Growth in Intensive Grassland Production Systems in Northwest Europe

Abstract

Knowledge about pasture growth rates is crucial for optimizing forage use efficiencies in intensively managed pasture and silage-based dairy systems, enabling optimized cutting/grazing times for high yields with high forage quality. The aim of this study was to parameterise a simple model, GrasProg, for predicting pasture growth in an intensively managed dairy production system under a cut-and-carry management. For this, pasture crop-growth rates were measured over a period of two years (2016 and 2017) at five contrasting sites in Schleswig-Holstein, Northern Germany. The pastures received nitrogen (N) fertilizer at a rate of 280 kg N ha−1 and were cut on a four-week interval. Average annual dry matter (DM) yields ranged from 10.9 to 11.6 t/ha for the three different locations. The DM accumulation simulated by GrasProg matched actual measurements over the varying intervals well (R2 = 0.65; RMSE = 49.5 g DM m−2; and NSE = 0.44). Two model parameters were adjusted within the vegetation period, namely, the relative growth rate, a proxy of the number of generative tillers, and the initial biomass at the start of each growth period, a proxy for the tillering density. Both predicted and measured pasture growth rates showed the same typical seasonal pattern, with high growth rates in spring, followed by decreasing growth rates to the end of the vegetation period. These good calibration statistics, with adjusting of only two model parameters, for the different sites and different climatic conditions mean that GrasProg can be used to identify optimum grazing or cutting strategies, with optimal yield and forage quality.