How Does Nitrogen Application Rate Affect Plant Functional Traits and Crop Growth Rate of Perennial Ryegrass-Dominated Permanent Pastures?

High doses of nitrogen (N) fertiliser input on permanent pastures are crucial in terms of N surplus and N losses. Quantitative analyses of the response of plant functional traits (PFT) driving crop growth rate (CGR) under low N input are lacking in frequently defoliated pastures. This study aimed to understand the significance of PFTs for productivity and N uptake in permanent grasslands by measuring dynamics in tiller density (TD), tiller weight (TW), leaf weight ratio (LWR), leaf area index (LAI), specific leaf area (SLA), as well as leaf N content per unit mass (LNCm) and per unit area (LNCa) in perennial ryegrass (Lolium perenne)-dominated pastures, in a simulated rotational grazing approach over two consecutive growing seasons. Annual N application rates were 0, 140 and 280 kg N ha−1. The phenological development of perennial ryegrass was the main driver of CGR, N uptake and most PFTs. The effect of N application rate on PFTs varied during the season. N application rate showed the greatest effect on TD, LAI and, to a lesser extent, on SLA and LNCm. The results of this study highlight the importance of TD and its role in driving CGR and N uptake in frequently defoliated permanent pastures

Aspects of grassland management for pasture-based dairy farms with wet soils and fragmented farm area

A long grazing season improves the profitability of pasture-based dairy farms. However, an increasing proportion of Irish milk is produced on farms where achieving a long grazing season is difficult. This study investigated how grassland management on farms with wet soils and fragmented farm area can be adapted to establish systems that maximise farm productivity and profitability. An experiment with four grazing systems evaluated if soil moisture measurements can be an effective decision support to assess the risk of treading damage, impact on pasture productivity and dairy cow performance during wet soil conditions. The effect of grazing platform stocking rate (GPSR) on the productivity and profitability of fragmented pasture-based farms was evaluated in a second experiment with four grazing systems where a higher GPSR was supplemented with silage produced on non-GP parcels of the farm. Finally, it was investigated if accumulating herbage mass during autumn can lengthen the grazing season on pasture-based dairy farms. Less time spent at pasture during wet soil conditions lowered treading damage but had no effect on annual herbage production. Milk solids production and profitability were higher when cows spent more time at pasture despite also incurring higher treading damage. Measuring soil moisture was a useful decision support for assessing the risk of treading damage when turning cows out to pasture. GPSR did not affect herbage production or milk production per cow albeit with a lower proportion of grazed herbage in the diet with higher GPSR. A greater extent of farm fragmentation lowered the profitability of pasture-based dairy production. The profitability of increasing GPSR was mainly determined by external factors. Higher milk prices, shorter distances and lower land rental price increased the optimum GPSR of fragmented systems. Accumulating herbage mass during autumn facilitated a longer grazing season while not impacting on milk production

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

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