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Genomic Selection for Pasture Digestibility

Total Cost €


EC-Contrib. €






Project "GenSPaD" data sheet

The following table provides information about the project.


Organization address
address: Oak Park
city: Carlow
postcode: R93
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Ireland [IE]
 Total cost 196˙590 €
 EC max contribution 196˙590 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-CAR
 Starting year 2020
 Duration (year-month-day) from 2020-04-20   to  2022-04-19


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Breeding for improved perennial ryegrass (PRG) cultivars to support pastoral based production systems for milk and meat is a critically important goal. However, genetic gains for traits such as forage yield and quality have very much lagged behind genetic gain for agronomic traits in cereals. One reason for this is the long breeding cycle in a typical PRG breeding programme, where a single cycle of selection can take 5-6 years. Genomic selection (GS) is a form of marker assisted selection that simultaneously estimates all loci, haplotype, or marker effects across the entire genome to calculate Genomic Estimated Breeding Values (GEBVs). The main advantage that GS could offer PRG breeding is to enable multiple cycles of selection to be achieved in the same time it takes to do a single cycle of conventional selection, thereby increasing the rate of genetic gain. Improving digestibility of the forage leads to an increase in animal performance, and is therefore an important target trait for forage breeders. Furthermore, it has already been shown that increases in organic matter digestibility can reduce methane emissions. Reducing methane emissions is a key target of the EUs climate and energy policy. In this action I will focus on developing and validating GS equations for feed parameters that are being used as model inputs into the Cornell Net Carbohydrate and Protein System (CNCPS). This CNCPS is currently being adapted to predict nutritional value to the grazing animal in pasture based production systems, and it is envisaged that it will be able to identify feed parameters limiting milk-solid production and thereby direct future forage breeding efforts. The work of this action will lead to a novel and innovative forage breeding programme that can select for multiple feed parameters to develop the ideal forage cultivars for pasture production systems.

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The information about "GENSPAD" are provided by the European Opendata Portal: CORDIS opendata.

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