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Breeding for Improved Product Quality

22 March 2013
Teagasc

IRELAND - A new multidisciplinary research project involving Teagasc, UCC, UCD and ICBF is looking at breeding for improved product quality in dairy, beef and sheep in Ireland.

The world’s population currently consumes 37 million tonnes of dairy products, 65 million tonnes of beef, and 13 million tonnes of sheep meat annually. This is expected to grow in line with population expansion.

Food safety and the human health effects of food are currently high priority for consumers. Breeding for improved product quality, in combination with optimised production and processing regimes, is one approach that will help the Irish dairy and meat sectors ensure animal products of consistently high quality and nutritive value are available.

A recently awarded project, BreedQuality, will use state-of-the-art tools to develop phenotypic, genetic and genomic approaches for a national strategy to improve the quality and consistency of milk and meat products from Irish cattle and sheep.

Dr Donagh Berry, Teagasc Animal & Grassland Research and Innovation Centre, Moorepark, explains: “To achieve consistency in quality, the underlying meaning of quality to consumers must be described, understood and translated into technical specifications at each stage within the supply chain.

In other words, the determinants of superior quality must first be identified from a marketplace perspective and then explored from a technical standpoint. The first task of the BreedQuality project will be to document the relative importance of quality attributes in delivering consumer and customer satisfaction and this will help guide the focus of the ‘breeding for quality’ research.”

Current Status of Breeding for Quality in Ireland

Product quality is traditionally laborious and costly to measure, hindering the routine capture of such information. Therefore, product quality is one of the suites of traits largely neglected from the national breeding strategies in dairy, beef and sheep in Ireland.

The task on milk quality in the BreedQuality project builds on recently completed research by Teagasc in the EU-funded project, RobustMilk (http://www.robustmilk.eu). Several methods are currently being explored to develop rapid, low-cost, approaches to routinely assess milk quality. We envisage that within three years Ireland will have implemented a world-class and potentially world-first national breeding strategy for milk quality parameters.

Like milk quality, breeding for improved meat quality is hampered primarily by the challenges of routine low-cost measurements of meat quality. However, unlike for milk, individual meat samples are not currently subjected to technologies that can be readily exploited to measure detailed meat quality components.

“Research at Teagasc and elsewhere, nevertheless, suggests various secondary methods such as near infra-red spectroscopy could potentially be useful to predict meat quality characteristics, particularly colour, drip loss, fat content and fatty acid composition,” says Dr Berry.

Near infra-red spectroscopy exploits information generated in this region of the electromagnetic spectrum and is amenable to online measurement. Recent Teagasc, UCD and international research has also shown that other tools, such as image analysis, including hyperspectral imaging, computed tomography and Raman spectroscopy are also capable of predicting important aspects of fresh meat quality.

Combining Resources and Knowledge

Routine access to large quantities of low-cost, accurate phenotypes, irrespective of the trait, will remain of fundamental importance in animal breeding (and management) for at least many decades.

The BreedQuality project, involving animal scientists, milk and meat scientists, molecular and quantitative geneticists, market researchers and industry, will combine resources and knowledge to produce a set of close-to-implementation tools and algorithms that will result in the implementation of market-based national breeding strategies for improved milk and meat quality.

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