Our Organisation Search
Quick Links
Toggle: Topics

Measuring the value of plants with DNA

Photo of technician with a Near-Infrared Reflectance spectroscopy machine

Teagasc researchers are using DNA technologies to improve the efficiency of plant selection and deliver highly digestible cultivars.

Improving perennial ryegrass cultivars in order to support pastoral-based production systems for milk and meat is critically important. Specifically, better digestibility of the forage is an important target trait for forage breeders, as it leads to an increase in animal performance. It also has the potential to reduce methane emissions within agriculture.

Disappointingly, genetic gains for important forage quality traits have been modest over recent decades. However, an increased focus on trait evaluation during breeding and the adoption of genomic evaluations can address this, and researchers at Teagasc have been studying the use of breeding technologies that can help.

One such technology is genomic selection (GS), which uses genome-wide DNA markers to estimate breeding values on selection candidates. GS can assist traditional breeding programmes and increase genetic gain by shortening the selection cycle, increasing the accuracy of selection and increasing the number of selection candidates that can be evaluated.

Measuring forage quality

A prerequisite to developing GS approaches is the establishment of a reference population that is a) evaluated for the target trait in field trials, and b) characterised for differences in DNA profiles among the population.    

Near-Infrared Reflectance (NIR) spectroscopy is an indirect approach that can be used to measure forage quality. It illuminates a forage sample with light and measures the near-infrared region of light reflected back. The absorbance of light at different wavelengths is plotted to provide a spectrum for each sample (Figure 1). The resulting shape is a unique fingerprint of the sample that is influenced by its composition.

Agnieszka Konkolewska, Marie Skłodowska-Curie Fellow and project researcher, says: “We used NIR spectra on a reference population of more than 15,000 samples, then selected a subset of these samples for chemical analysis based on scan diversity.

“Doing this enabled us to develop calibration models for a number of forage quality traits – including organic matter digestibility, crude protein and neutral detergent fibre – that can now be used for the routine evaluation of breeding material during selection. It also proved that NIR spectra is a reliable method for measuring forage quality, removing the need for expensive chemical analysis.

“Furthermore, working with over 15,000 samples enabled us to collect forage quality data on a large reference population of breeding material, for use in our development of GS models.”

Chart showing NIR spectra of calibration samples

Figure 1. NIR spectra of calibration samples, coloured by the respective high (red) and low (blue) neutral detergent fibre (NDF) values.

DNA and genomic selection

In forage breeding, the goal is to use the best plants as parents to produce a new generation, where the new generation will be on average superior to the previous generation. Finding the best parents can be achieved using field evaluations or by studying DNA through genomic selection.

Teagasc Research Officer Stephen Byrne worked closely with Agnieszka in building models to enable GS. Describing how they did this, he says: “We combined the evaluations of forage quality on the reference population with genomic evaluations of the same plants. This enabled us to build predictive models for genomic selection, which can now be used to predict the value of a plant to a breeding programme, based only on DNA information.”

Forage quality is just one trait of importance to forage breeders. With this in mind, the researchers are also developing genomic selection models for other traits measured in national list trials.

“Our vision is to employ multi-trait GS, using index selection with weights from the Pasture Profit Index (PPI),” says Stephen. “This will enable the selection of the best plants within the best families, which has already been shown to be an effective way to increase genetic gain in forage breeding.

“When combined with inexpensive approaches to evaluate DNA, this will be a powerful tool. It will support forage breeders in selecting the best plants to combine to produce new cultivars, and help them to identify the best plants to use as parents to start a new round of selection. At Teagasc, work is already underway to validate and quantify genetic gain using this approach.” 

Photo of a gloved hand holding a clump of grass


This work is supported by the European Union’s Horizon 2020 research and innovation programme, under the Marie Skłowdowska-Curie grant agreement number 841882. It also received support from Science Foundation Ireland and the Department of Agriculture, Food and the Marine on behalf of the Government of Ireland – grant 16/RC/3835 (VistaMilk).


We would like to thank Aonghus Lawlor (UCD) and Teagasc’s Michael Dineen, Patrick Conaghan, Rachel Keirse, Dan Milbourne and Susanne Barth for their collaboration on this project.

[pic cap 1] Near-Infrared Reflectance (NIR) spectroscopy is a reliable method for measuring forage quality

[pic cap 2] In forage breeding, the goal is to use the best plants as parents to produce a new generation

[pic credit] Photography: Andrew Downes