Stong case for grass analysis improvement
BEING able to analyse fresh grass in the same way and as quickly as silage would benefit producers and plant breeders.
Rosemary Agnew, researcher at the Agricultural and Research Institute of Northern Ireland, says predicting fresh grass energy content and D-value lacks accuracy using NIR. Although NIR can accurately predict dry matter, crude protein, sugars and fibre, a fresh grass samples metabolisable energy (ME) content has to be predicted from the fibre content.
But if digestibility could be measured, as it is with grass silage, the prediction of ME would be more accurate, she says. This would be useful for assessing ME pre-ensiling or for grazing because grass swards vary in energy content.
A cheap and fast test for plant digestibility would also benefit grass breeders, says David Johnston of the Department of Agriculture and Rural Develop-ments plant breeding station.
"To make progress in improving digestibility and intakes, we have to be able to select plants on that basis. Currently, we do this by selecting against re-heading in July and August." But NIR would allow frequent sampling of digestibility, improving accuracy when selecting varieties for high energy content, he adds.
Work to develop a robust NIR calibration set for fresh grass digestibility begun two years ago, adds Dr Agnew. For the project ARINI is collaborating with Ian Givens of ADAS to collect enough data on fresh grass digestibility by feeding 200 samples to sheep.
These samples of known digestibility will allow an ME equation to be set for use by the NIR equipment. Then it will be possible to know the energy content of fresh grass five minutes after it reaches the lab. *