AFBI research provides new tools to predict grass feeding value

Date published: 03 June 2015

Grass-based dairy production is common in Northern Ireland because of the cool and moist climate which allows for long grazing seasons.

Grazed grass is our cheapest feed, but how do we estimate its energy content?

Grass Based Systems – Positive Attributes

Grass-based dairy production is common in Northern Ireland because of the cool and moist climate which allows for long grazing seasons. Grass-based systems reduce milk production costs and increase the contents of omega-3 fatty acids, conjugated linoleic acid, vitamins and antioxidants in milk which are beneficial for human health, when compared with year-round indoor housing systems feeding silage and concentrates. Pasture-based systems also sustain rural landscapes and habitats and improve the image of the dairy industry to consumers.

                                                                                                                                                                                                                             

Feeding Value of Grass

Fresh grass may provide from 50% (intensive systems) to 100% (low-input systems) of the total dry matter intake of cows during the grazing season. Accurate prediction of the feeding value of grass, coupled with reliable estimates of grass intake, is essential in planning feeding strategies for grazing dairy cows. Metabolisable energy (ME), which represents the energy value in grass, may be accurately measured under controlled research conditions but it is difficult to assess at farm-level. The importance of a rapid assessment of the ME content of grass on farm highlights the necessity of developing prediction equations which use commonly available data at farm level, such as grass nutrient content. For example, leafy grass with more crude protein and less fibre contains more ME, than mature grass with higher fibre content. These relationships are shown in Figure 1 and were developed using the extensive research data from a 3-year experiment in AFBI Hillsborough.

 

Relationships between grass nutrients, showing how grass metabolisable energy (ME) content changes as crude protein (CP), acid-detergent-fiber (ADF) and neutral-detergent fibre (NDF) rise and fall.
Relationships between grass nutrients, showing how grass metabolisable energy (ME) content changes as crude protein (CP), acid-detergent-fiber (ADF) and neutral-detergent fibre (NDF) rise and fall.
Predicting Grass ME Content

Recent research in AFBI Hillsborough measured the ME content of grass through dairy cows, which were fed fresh-cut grass during the grazing season over 3 consecutive years. Experimental facilities in AFBI Hillsborough include ruminant metabolism units and calorimetric chambers. These allow the accurate measurement of dry matter intake, faeces and urine excretions and methane emissions, which are necessary to calculate the ME contents of grass within the digestive tract. Using this approach, it was possible to derive equations to predict nutrient digestibility and energy concentrations of grass. These studies showed that grass ME content can be predicted from its protein, oil, fibre and ash content. These are very useful tools for dairy producers and advisers providing more accurate information on the feeding value of fresh grass. This information is essential in providing confidence in the value of grass as a high quality feed for dairy cows.

This work does not end with this achievement, as ME content can be even more accurately determined when nutrient digestibility parameters are included in the calculations. Further work on this aspect will be completed this year. The ultimate objective of this work will be to produce methods whereby a sample of grass can be tested in the field and an instant prediction obtained for intake, feeding value and potential milk yield from grass. Through AFBI research, this vision is much closer to reality than most people realise, with the potential to transform traditional grazing management.

 

Acknowledgements

The study was supported by the Department of Agriculture, Food and the Marine of the Republic of Ireland through the Research Stimulus Fund (project No 11/S/105) and the Department of Agriculture and Rural Development of Northern Ireland (DARD project No 0099).

 

Notes to editors: 

The full article that presents this work in more detail can be found in Journal of Dairy Science, 2015, volume 98, pages 3257-3273

 

All studies at AFBI Hillsborough are encompassed within the overriding objective of Advancing Animal Science, Improving Livestock Farming

 

AFBI carries out high quality technology research and development, statutory, analytical, and diagnostic testing functions for DARD and other Government departments, public bodies and commercial companies.

 AFBI's Vision is “Scientific excellence in Northern Ireland … serving the world”.

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