The Moorepark grass growth model: application in grazing systems

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The Moorepark grass growth model: application in grazing systems

Elodie Ruelle, Luc Delaby

To cite this version:

Elodie Ruelle, Luc Delaby. The Moorepark grass growth model: application in grazing systems.

26. General meeting of the European Grassland Federation (EGF), Sep 2016, Trondheim, Norway.

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Grassland Science in Europe, Vol. 21 – The multiple roles of grassland in the European bioeconomy 409

The Moorepark grass growth model: application in grazing systems

Ruelle E. ¹ and Delaby L. ²

1 Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland; ² INRA, AgroCampus Ouest, UMR 1348, Physiologie, Environnement and Génétique pour l’Animal et les Systèmes d’Elevage, 35590 Saint-Gilles, France; [email protected]

Abstract

The Moorepark Grass Growth model (MGGm) is a dynamic model developed in C++ describing the grass biomass evolution of a paddock over time with a daily time step. It is assumed that each urine and faeces deposition affects 2 m ² area of the paddock, with the model describing the different variables and events such as grass growth, mineralisation, immobilisation, leaching and nitrogen (N) uptake by the plant at the 2 m ² level. Different N mineral fertilisations in a grazing context have been simulated, and the impact on grass growth and N content of the grass has been evaluated. The grazing simulations examined, described the effect of N returns on grass growth and N fluxes accurately. The model has been able to react to different weather conditions, and to different levels of N mineral fertilisation. The response of the grass growth, the biomass produced and the grass N content to the N mineral fertilisation level is in line with the literature. In average, the mineral N fertilisation leaded to an increase of grass utilised of 12 and 17 kg of dry matter per kg of N fertilised for the French and Irish simulation respectively.

Keywords: grass growth, model, grazing, dairy cow

Introduction

In temperate climates grass provides the cheapest and highest quality feed for dairy cows (Dillon et al., 2005). However, even though a temperate climate allows grass growth throughout the year, grass growth is highly seasonal and depends heavily on climate conditions. Management of pasture (such as fertilisation, cutting and grazing heights) is also an important factor influencing grass growth. There is increased interest in the potential to increase grass growth and utilisation through more advanced grassland management. This paper presents the prediction of the Moorepark Grass Growth model (MGGm) in terms of grass growth and nitrogen content of the grass in a grazing context with different mineral nitrogen fertilisation levels and different weather conditions.

Materials and methods

The MGGm is a dynamic model developed in C++ describing the grass growth and the N fluxes of a paddock at a 2 m ² level. The model is run with a daily time step simulating soil N mineralisation/

immobilisation and water fluxes, grass growth, N uptake and grass N content. The model is driven by a daily potential growth depending on the radiation and the total green biomass. To calculate the actual daily growth, this potential growth is then multiplied by parameters depending on environmental conditions (temperature, water in the soil and radiation) and a parameter depending on the availability of the mineral N in the soil compared to the demand in N associated with the potential grass growth.

The availability of the N in the soil depends on the mineral N in the soil, the proportion of the N usable

by the plant (depending on the time of the year and the heading date) and the N demand to grow one kg

of biomass (depending on the N dilution curve and the actual biomass over 4 cm; Gastal and Lemaire,

2002). The N dilution curve represents the decrease of the N needed for one kg of dry matter (DM)

growth with the increase of the accumulated biomass (Gastal and Lemaire, 2002). Animal deposition of

nitrogen is simulated through a one day-grazing sequence, with the number of animals adapted by the

410 Grassland Science in Europe, Vol. 21 – The multiple roles of grassland in the European bioeconomy model depending on the pre grazing mass (calculated by the model) based on a daily intake of the animal which was assumed to be 16 kg DM ha ^-1 .

Different simulations have been run to simulate the impact of mineral N fertilisation in grazing conditions. These simulations have been tested on 2 different weather conditions (Table 1) in Ireland (Co. Cork) and in France (Normandy). The initial mineral N in the soil was defined at 80 and the organic N at 14,400 kg N ha ^-1 (6% of organic matter content). Four different mineral N applications were tested 0, 100, 200 or 300 kg of N ha ^-1 per year in Ireland. Due to the lack of rain and high temperature in summer in Normandy, the annual mineral N fertilization has been reduced by 25% without applications in autumn. The size of the paddock is 1 ha and a total of seven (France) or eight (Ireland) grazing events has been conducted.

Results and discussion

The results are presented in Table 2 and Figure 1. The model is capable of reacting to different weather conditions and is highly sensitive to different levels of mineral N fertilisation (Figure 1). The lack in rainfall in France in 2008 led to a poor growth in summer and autumn. The response to N mineral level of fertilisation conforms with the literature (Whitehead, 1995) with a higher response at low mineral N levels than at higher applied levels (20.2 and 14.8 kg DM kg ^-1 N applied between 0 to100 or 75 kg N and 13.1 and 8.9 kg DM kg ^-1 N mineral applied between 200 and 300 or 150 and 225 kg mineral N respectively in Ireland and in France).

The N content of the grass offered evolves in accordance with the season and increases with the mineral N fertilisation levels. This higher concentration has been previously described in the literature (Whitehead, 1995). When there is higher mineral N available in the soil there is higher N uptake. This is in accordance with the principle of the dilution curve described by Gastal and Lemaire (2002). Due to the weather conditions in France, the annual average N content of the grass offered is a little bit higher than in Ireland.

This is because in autumn, the high level of soil N mineralisation is accompanied by a lower grass growth than in Ireland. Consequently the relative N uptake is higher leading to a higher N concentration in the plant.

Table 1. Description of the two annual weathers applied in the simulations.

Location Annual average temperature (°C)

Monthly rainfall (mm) Annual total

rainfall (mm)

J F M A M J J A S O N D

France Normandie 10.2 61 32 136 68 64 12 35 72 42 80 102 41 743

Ireland Co. Cork 8.7 107 39 88 59 38 53 143 23 102 83 98 37 869

Table 2. Impact of the weather conditions and the mineral N fertilisation on the total grass grazed and average grass N content offered at grazing. ¹

Mineral N fertilisation (France / Ireland) 0 75 / 100 150 / 200 225 / 300

Total grass grazed (kg DM ha

) France, Normandie 6,014 7,151 8,023 8,710

Ireland, Co. Cork 8,388 10,446 12,120 13,452

Average grass N content offered (g kg

DM)

France, Normandie 2.52 2.73 2.94 3.14

Ireland, Co. Cork 2.30 2.56 2.81 3.04

1

DM = dry matter.

Grassland Science in Europe, Vol. 21 – The multiple roles of grassland in the European bioeconomy 411

Conclusions and further work

The MGGm is a user friendly model with basic and simple inputs. The model has been capable of reacting in a sensible manner to different weather and mineral N fertilisation events. The future of the MGGm is to be included in a whole farm dairy model (the Pasture Base Herd Dynamic Milk model (Ruelle et al., 2015)), permitting the prediction of the impact of different climatic conditions, grazing management and fertilisation practices on the milk production of the animals and the economics of the farm.

Acknowledgments

The authors acknowledge the funding from the Research Stimulus Fund 2011 administered by the Department of Agriculture, Fisheries and Food (Project 11/S/132).

References

Dillon P., Roche J.R., Shalloo L. and Horan B. (2005) Optimising financial return from grazing in temperate pastures. In: Murphy J.J. (ed) Utilisation of grazed grass in temperate animal systems, Cork, Ireland, pp. 131-147.

Gastal F. and Lemaire G. (2002) N uptake and distribution in crops: an agronomical and ecophysiological perspective. Journal of Experimental Botany 53, 789-799.

Ruelle E., Shalloo L., Wallace M. and Delaby L. (2015) Development and evaluation of the pasture-based herd dynamic milk (PBHDM) model for dairy systems. European Journal of Agronomy 71, 106-114.

Whitehead D.C. (1995) Grassland nitrogen. CAB International, Wallingford, UK, 416 pp.

0 10 20 30 40 50

020406080100

Week

G ro w th (kg D M)

0 10 20 30 40 50

1.52.02.53.03.54.04.5

Week

Gr as s N c on te nt ( % )

A B

Figure 1. Net growth and grass N content for the French 2008 weather (black) and the Irish 2009 weather (grey) at the level 0 (dotted line) and

300 (continuous line) of mineral N fertilisation.