Skip to main content Accessibility help

Prediction of metabolisable energy concentrations of fresh-cut grass using digestibility data measured with non-pregnant non-lactating cows

  • Sokratis Stergiadis (a1), Michelle Allen (a2), Xianjiang Chen (a1) (a3), David Wills (a1) and Tianhai Yan (a1)...


Pasture-based ruminant production systems are common in certain areas of the world, but energy evaluation in grazing cattle is performed with equations developed, in their majority, with sheep or cattle fed total mixed rations. The aim of the current study was to develop predictions of metabolisable energy (ME) concentrations in fresh-cut grass offered to non-pregnant non-lactating cows at maintenance energy level, which may be more suitable for grazing cattle. Data were collected from three digestibility trials performed over consecutive grazing seasons. In order to cover a range of commercial conditions and data availability in pasture-based systems, thirty-eight equations for the prediction of energy concentrations and ratios were developed. An internal validation was performed for all equations and also for existing predictions of grass ME. Prediction error for ME using nutrient digestibility was lowest when gross energy (GE) or organic matter digestibilities were used as sole predictors, while the addition of grass nutrient contents reduced the difference between predicted and actual values, and explained more variation. Addition of N, GE and diethyl ether extract (EE) contents improved accuracy when digestible organic matter in DM was the primary predictor. When digestible energy was the primary explanatory variable, prediction error was relatively low, but addition of water-soluble carbohydrates, EE and acid-detergent fibre contents of grass decreased prediction error. Equations developed in the current study showed lower prediction errors when compared with those of existing equations, and may thus allow for an improved prediction of ME in practice, which is critical for the sustainability of pasture-based systems.


Corresponding author

* Corresponding author: T. Yan, fax +44 2892689594, email


Hide All
1 O'Donovan, M, Lewis, E & O'Kiely, P (2011) Requirements of future grass-based ruminant production systems in Ireland. Irish J Agr Food Res 50, 121.
2 Ferris, C (2007) Sustainable pasture-based dairy systems – meeting the challenges. Can J Plant Sci 87, 723738.
3 Clark, DA, Caradus, JR, Monaghan, RM, et al. (2007) Issues and options for future dairy farming in New Zealand. New Zeal J Agr Res 50, 203221.
4 Dijkstra, J, Kebreab, E, Bannink, A, et al. (2008) Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh-grass based diets. Anim Feed Sci Technol 143, 203219.
5 National Research Council (2001) Nutrient Requirements of Dairy Cattle. Washington, DC: National Academy Press.
6 Agricultural and Food Research Council (1993) Energy and Protein Requirements of Ruminants. An Advisory Manual Prepared by the AFRC Technical Committee on Responses to Nutrients. Wallingford: CAB International.
7 Yan, T & Agnew, RE (2004) Prediction of metabolisable energy concentrations from nutrient digestibility and chemical composition in grass silages offered to sheep at maintenance. Anim Feed Sci Technol 117, 197213.
8 Jarrige, R (1989) Ruminant Nutrition: Recommended Allowances and Feed Tables. Paris: Institut National de la Recherche Agronomique & John Libbey Eurotext.
9 Bruinenberg, MH, Zom, RLG & Valk, H (2002) Energy evaluation of fresh grass in the diets of lactating dairy cows. Neth J Agr Sci 50, 6781.
10 Home Office (1986) Animal (Scientific Procedures) Act 1986. London: Her Majesty's Stationery Office.
11 Stergiadis, S, Cheng, XJ, Allen, M, et al. (2015) Evaluating nitrogen utilization efficiency of nonpregnant dry cows offered solely fresh cut grass at maintenance levels. J Anim Sci 93, 709720.
12 Stergiadis, S, Allen, M, Chen, XJ, et al. (2015) Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition. J Dairy Sci 98, 32573273.
13 Yan, T & Mayne, CS (2008) Prediction of methane emission of dairy cows offered fresh grass at maintenance level. In Multifunctional Grasslands in a Changing World, p. 143 [Organising Committee of 2008 IGC/IRC Conference, editor]. Guangzhou: Guangdong People's Publishing House.
14 Agnew, RE, Park, RS & Mayne, CS (2000) The potential of near infrared spectroscopy to predict the chemical and biological characteristics of grazed grass. In Grazing Management: The Principles and Practice of Grazing, for Profit and Environmental Gain, Within Temperate Grassland Systems. Proceedings of the British Grassland Society Conference, 29 February–2 March 2000, Harrogate , pp. 5152 [Rook, A and Penning, P, editors]. Kenilworth: British Grassland Society.
15 Agnew, RE, Yan, T, France, J, et al. (2004) Energy requirement and supply. In Feed into Milk: A New Applied Feeding System for Dairy Cows, pp. 1120 [Thomas, C, editor]. Nottingham: Nottingham University Press.
16 International, VSN (2013) GenStat for Windows, 16th ed. Hemel Hempstead: VSN International.
17 Robinson, DL (1987) Estimation and use of variance components. The Statistician 36, 314.
18 Searle, SR, Casella, G & McCulloch, CE (1992) Variance Components. New York: John Wiley & Sons.
19 Yan, T, Frost, JP, Agnew, RE, et al. (2006) Relationships among manure nitrogen output and dietary and animal factors in lactating dairy cows. J Dairy Sci 89, 39813991.
20 Givens, DI, Everington, JM & Adamson, AH (1990) The nutritive value of spring-grown herbage produced on farms throughout England and Wales over four years. III. The prediction of energy values from various laboratory measurements. Anim Feed Sci Technol 27, 185196.
21 Terry, RA, Osbourn, DF, Cammell, SB, et al. (1974) In vitro digestibility and the estimation of energy in herbage. Vaxtodling 28, 1925.
22 Australian Agricultural Council (1990) Feeding Standards for Australian Livestock: Ruminants. Melbourne: CSIRO.
23 Yan, T, Agnew, RE & Gordon, FJ (2002) The combined effects of animal species (sheep versus cattle) and level of feeding on digestible and metabolizable energy concentrations in grass-based diets of cattle. Anim Sci 75, 141151.
24 Waghorn, GC & Clark, DA (2004) Feeding value of pastures for ruminants. New Zeal Vet J 52, 320331.
25 Wims, CM, McEvoy, M, Delaby, L, et al. (2013) Effect of perennial ryegrass (Lolium perenne L.) cultivars on the milk yield of grazing dairy cows. Animal 7, 410421.
26 Fanchone, A, Noziere, P, Portelli, J, et al. (2013) Effects of nitrogen underfeeding and energy source on nitrogen ruminal metabolism, digestion, and nitrogen partitioning in dairy cows. J Anim Sci 91, 895906.
27 Hoekstra, NJ, Schulte, RPO, Struik, PC, et al. (2007) Pathways to improving the N efficiency of grazing bovines. Eur J Agron 26, 363374.
28 Van Es, AJH (1978) Feed evaluation for ruminants. I. The systems in use from May 1977 onwards in the Netherlands. Livest Prod Sci 5, 331345.
29 Tas, B (2006) Nitrogen utilization of perennial ryegrass in dairy cows. In Fresh Herbage for Dairy Cattle, pp. 125140 [Elgersma, A, Dijkstra, J and Tamminga, S, editors]. Wageningen: Springer.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

British Journal of Nutrition
  • ISSN: 0007-1145
  • EISSN: 1475-2662
  • URL: /core/journals/british-journal-of-nutrition
Please enter your name
Please enter a valid email address
Who would you like to send this to? *


Type Description Title
Supplementary materials

Stergiadis supplementary material
Figure S1

 Word (658 KB)
658 KB


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed