Average daily gain in lambs grazing mixed annual forage species compared with single species and relationship to feed on offer

E. H. Clayton; H. Fahey; P. Tyndall; R. Lowrie; B. Xu; F. Ataollahi; M. R. Norton

doi:10.1071/AN24102

RESEARCH ARTICLE (Open Access)

Next Contents Vol 64(14)

Average daily gain in lambs grazing mixed annual forage species compared with single species and relationship to feed on offer

E. H. Clayton

^A ^* , H. Fahey ^A , P. Tyndall ^A , R. Lowrie ^A , B. Xu ^A , F. Ataollahi

^A and M. R. Norton

^A

+ Author Affiliations

- Author Affiliations

^A NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia.

^* Correspondence to: Edward.Clayton@dpi.nsw.gov.au

Handling Editor: Andy Greer

Animal Production Science 64, AN24102 https://doi.org/10.1071/AN24102

Submitted: 26 March 2024 Accepted: 25 August 2024 Published: 18 September 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

Annual forage crops provide high-quality fodder for livestock during typical autumn and winter feed-gaps in the south-east of Australia and benefits through rotations in cropping systems. While benefits from intercropping with cereals and pasture or mixing canola and peas have been studied in Australia, the potential animal-production benefits of grazing mixed annual species forage crops have not been examined.

Aims

To determine average daily gain (ADG) and rumen fluid parameters when sheep graze mixtures of annual fodder crops compared with a single species.

Methods

Ninety six Dorset × Border Leicester × Merino lambs (mean = 44.3 ± 0.55 kg) were allocated to one of the following four treatment groups (n = 24/treatment) on the basis of sex and liveweight; a single species brassica control (canola) (Br) or annual forage species mixes containing brassica (canola, turnip, radish) and cereal (wheat, cereal rye) (B + C), brassica and legume (vetch, arrowleaf clove) (B + L) or brassica, cereal and legume (B + C + L). Liveweight and rumen fluid parameters were assessed prior to grazing and again 21 and 35 days after the commencement of grazing.

Key results

Mean ADG from Day 0 to Day 21 was lower for female, but not male, lambs grazing the Br control (231 ± 23 g head⁻¹ day⁻¹) than for those grazing any forage mix (B + C = 292 ± 23 g head⁻¹ day⁻¹, B + L = 296 ± 23 g head⁻¹ day⁻¹, B + C + L = 310 ± 22 g head⁻¹ day⁻¹). Liveweight change over 35 days of grazing was not different between any forage mixtures. Rumen fluid pH was higher (P < 0.001) for sheep grazing forages containing cereals (B + C = 6.97 ± 0.06, B + C + L = 6.86 ± 0.06) than for those grazing brassica or legume (Br = 6.59 ± 0.06, B + L = 6.68 ± 0.06). Total volatile fatty acid concentration was lower and rumen pH was higher when sheep grazed B + C than when they grazed any other forage mix.

Conclusions

The higher ADG in females grazing mixtures than in those grazing the Br was related to higher dry matter on offer. Further research should determine whether the lower pH observed when sheep grazed brassica and legume than when grazing mixes containing cereals is associated with subacute rumen acidosis and reduced fibre degradation and forage energy utilisation.

Implications

Mixed forage species can provide higher DM on offer and ADG. Improved rumen efficiency could be related to improved growth.

Keywords: annual fodder crops, dry matter, efficiency, methane, production, rumen parameters, weight gain.

References

AFIA (2006) ‘Laboratory methods manual.’ (Australian Fodder Industry Association: Balwyn Vic., Australia)

Barry TN (2013) The feeding value of forage brassica plants for grazing ruminant livestock. Animal Feed Science and Technology 181, 15-25.
| Crossref | Google Scholar |

Black JL, Kenney PA (1984) Factors affecting diet selection by sheep 2. Height and density of pasture. Australian Journal of Agricultural Research 35, 565-578.
| Crossref | Google Scholar |

Bramley E, Lean IJ, Fulkerson WJ, Stevenson MA, Rabiee AR, Costa ND (2008) The definition of acidosis in dairy herds predominantly fed on pasture and concentrates. Journal of Dairy Science 91, 308-321.
| Crossref | Google Scholar | PubMed |

Bujňák L, Maskaľová I, Vajda V (2011) Determination of buffering capacity of selected fermented feedstuffs and the effect of dietary acid–base status on ruminal fluid pH. Acta Veterinaria Brunensis 80, 269-273.
| Crossref | Google Scholar |

Chateil C, Gondringer I, Tarallo L, Kerbiriou C, Le Viol I, Ponge J-F, Salmon S, Gachet S, Porcher E (2013) Crop genetic diversity benefits farmland biodiversity in cultivated fields. Agriculture, Ecosystems & Environment 171, 25-32.
| Crossref | Google Scholar |

Clayton EH, Lean IJ, Rowe JB, Cox WJ (1999) Effects of feeding virginiamycin and sodium bicarbonate to grazing lactating dairy cows. Journal of Dairy Science 82, 1545-1554.
| Crossref | Google Scholar | PubMed |

Craig PR, Coventry D, Edwards JH (2013) Productivity advantage of crop–perennial pasture intercropping in southeastern Australia. Agronomy Journal 105, 1588-1596.
| Crossref | Google Scholar |

de Veth MJ, Kolver ES (2001) Digestion of ryegrass pasture in response to change in pH in continuous culture. Journal of Dairy Science 84, 1449-1457.
| Crossref | Google Scholar | PubMed |

Dove H, Kelman WM, Kirkegaard JA, Sprague SJ (2012) Impact of magnesium–sodium supplementation on liveweight gains of young sheep grazing dual-purpose cereal or canola crops. Animal Production Science 52, 1027-1035.
| Crossref | Google Scholar |

Enemark JMD, Jørgensen RJ, Kristensen NB (2004) An evaluation of parameters for the detection of subclinical rumen acidosis in dairy herds. Veterinary Research Communications 28, 687-709.
| Crossref | Google Scholar | PubMed |

Fletcher AL, Kirkegaard JA, Peoples MB, Robertson MJ, Whish JPM, Swan AD (2016) Prospects to utilise intercrops and crop variety mixtures in mechanised, rain-fed, temperate cropping systems. Crop & Pasture Science 67, 1252-1267.
| Crossref | Google Scholar |

Florence AM, McGuire AM (2020) Do diverse cover crop mixtures perform better than monocultures? A systematic review. Agronomy Journal 112, 3513-3534.
| Crossref | Google Scholar |

Fogarty NM, Ingham VM, Gilmour AR, Cummins LJ, Gaunt GM, Stafford J, Edwards JEH, Banks RG (2005) Genetic evaluation of crossbred lamb production. 1. Breed and fixed effects for birth and weaning weight of first-cross lambs, gestation length, and reproduction of base ewes. Australian Journal of Agricultural Research 56, 443-453.
| Crossref | Google Scholar |

Freer M, Moore AD, Donnelly JR (2012) The GRAZPLAN animal biology model for sheep and cattle and the GrazFeed decision support tool. CSIRO Plant Industry Technical Paper May 2012, 1–47.

Graham NM (1962) Energy expenditure of grazing sheep. Nature 196, 289.
| Crossref | Google Scholar |

Haydock KP, Shaw NH (1975) The comparative yield method for estimating dry matter yield of pasture. Australian Journal of Experimental Agriculture and Animal Husbandry 15, 663-670.
| Crossref | Google Scholar |

Hayes RC, Li GD, Norton MR, Culvenor RA (2018) Effects of contrasting seasonal growth patterns on composition and persistence of mixed grass–legume pastures over 5 years in a semi-arid Australian cropping environment. Journal of Agronomy and Crop Science 204, 228-242.
| Crossref | Google Scholar |

Hector A, Schmid B, Beierkuhnlein C, Caldeira MC, Diemer M, Dimitrakopoulos PG, Finn JA, Freitas H, Giller PS, Good J, Harris R, Hogberg P, Huss-Danell K, Joshi J, Jumpponen A, Korner C, Leadley PW, Loreau M, Minns A, Mulder CPH, O’Donovan G, Otway SJ, Pereira JS, Prinz A, Read DJ, Scherer-Lorenzen M, Schulze ED, Siamantziouras ASD, Spehn EM, Terry AC, Troumbis AY, Woodward FI, Yachi S, Lawton JH (1999) Plant diversity and productivity experiments in European grasslands. Science 286, 1123-1127.
| Crossref | Google Scholar | PubMed |

Howieson JG, O’Hara GW, Carr SJ (2000) Changing roles for legumes in Mediterranean agriculture: developments from an Australian perspective. Field Crops Research 65, 107-122.
| Crossref | Google Scholar |

Kirkegaard JA, Sprague SJ, Dove H, Kelman WM, Marcroft SJ, Lieschke A, Howe GN, Graham JM (2008) Dual-purpose canola: a new opportunity in mixed farming systems. Australian Journal of Agricultural Research 59, 291-302.
| Crossref | Google Scholar |

Laudert SB, Matshushima JK (1982) Limestone effects on digestion and gastrointestinal pH of finishing steers. Journal of Animal Science 55(Suppl 1), 427.
| Google Scholar |

Lithourgidis AS, Dordas CA, Damalas CA, Vlachostergios DN (2011) Annual intercrops: an alternative pathway for sustainable agriculture. Australian Journal of Crop Science 5, 396-410.
| Google Scholar |

Littell RC, Henry PR, Ammerman CB (1998) Statistical analysis of repeated measures data using SAS procedures. Journal of Animal Science 76, 1216-1231.
| Crossref | Google Scholar | PubMed |

Malézieux E, Crozat Y, Dupraz C, Laurans M, Makowski D, Ozier-Lafontaine H, Rapidel B, de Tourdonnet S, Valantin-Morison M (2009) Mixing plant species in cropping systems: concepts, tools and models. A review. Agronomy for Sustainable Development 29, 43-62.
| Google Scholar |

Masters DG (2015) Mineral nutrition of sheep: new insights into interactions when grazing vegetative crops. Animal Production Science 55, 1215-1216.
| Crossref | Google Scholar |

McGrath SR, Pinares-Patino CS, McDonald SE, Simpson RJ, Moore AD (2021a) Utilising dual-purpose crops in an Australian high-rainfall livestock production system to increase meat and wool production. 2. Production from breeding-ewe flocks. Animal Production Science 61, 1074-1088.
| Crossref | Google Scholar |

McGrath SR, Sandral GA, Holman BWB, Friend MA (2021b) Lamb growth rates and carcass characteristics of White Dorper and crossbred lambs grazing traditional and novel pastures during spring in southern Australia. Animal Production Science 61, 1160-1169.
| Crossref | Google Scholar |

Moore AD, Bell LW, Revell DK (2009) Feed gaps in mixed-farming systems: insights from the Grain & Graze program. Animal Production Science 49, 736-748.
| Crossref | Google Scholar |

Moss A, Jouany J-P, Newbold J (2000) Methane production by ruminants: its contribution to global warming. Annales de Zootechnie 49, 231-253.
| Crossref | Google Scholar |

Nelson AG, Pswarayi A, Quideau S, Frick B, Spaner D (2012) Yield and weed suppression of crop mixtures in organic and conventional systems of the Western Canadian Prairie. Agronomy Journal 104, 756-762.
| Crossref | Google Scholar |

NHMRC (2013) ‘Australian Code for the Care and Use of Animals for Scientific Purposes’, 8th edn. (Australian Government: Canberra, ACT, Australia)

NRC (2001) ‘Nutrient requirements of dairy cattle’, 7th edn. (National Academy Press: Washington, DC, USA)

Packer EJ, Clayton EH, Cusack PMV (2011) Rumen fermentation and liveweight gain in beef cattle treated with monensin and grazing lush forage. Australian Veterinary Journal 89, 338-345.
| Crossref | Google Scholar | PubMed |

Provenza FD, Balph DF (1990) Applicability of five diet-selection models to various foraging challenges ruminants encounter. In ‘Behavioural mechanisms of food selection’. NATO ASI Series (Series G: Ecological Sciences Vol. 20)’. (Ed. RN Hughes) pp. 423–460. (Springer: Heidelberg, Germany)

Rogers JA, Davis CL, Clark JH (1982) Alteration of rumen fermentation, milk fat synthesis and nutrient utilization with mineral salts in dairy cows. Journal of Dairy Science 65, 577-586.
| Crossref | Google Scholar | PubMed |

Russo VM, Leury BJ, Kennedy E, Hannah MC, Auldist MJ, Wales WJ (2018) Forage type influences milk yield and ruminal responses to wheat adaptation in late-lactation dairy cows. Journal of Dairy Science 101, 9901-9914.
| Crossref | Google Scholar | PubMed |

Russo VM, Leury BJ, Kennedy E, Hannah MC, Auldist MJ, Morris GL, Wales WJ (2021) Prior forage type influences ruminal responses to a wheat grain challenge in lactating dairy cows. Animals 11, 3188.
| Crossref | Google Scholar | PubMed |

SAS Institute Inc. (1997) ‘SAS/STAT Software: Changes and Enhancements Through Release 6.12.’ (SAS Institute Inc.: Carey, NC, USA).

Shriver BJ, Hoover WH, Sargent JP, Crawford RJ, Jr, Thayne WV (1986) Fermentation of a high concentrate diet as affected by ruminal pH and digesta flow. Journal of Dairy Science 69, 413-419.
| Crossref | Google Scholar |

Smith WB, Galyean ML, Kallenbach RL, Greenwood PL, Scholljegerdes EJ (2021) Understanding intake on pastures: how, why and a way forward. Journal of Animal Science 99, skab062.
| Crossref | Google Scholar |

Sun XZ, Waghorn GC, Hoskin SO, Harrison SJ, Muetzela S, Pacheco D (2012) Methane emissions from sheep fed fresh brassicas (Brassica spp.) compared to perennial ryegrass (Lolium perenne). Animal Feed Science and Technology 176, 107-116.
| Crossref | Google Scholar |

Sun X, Henderson G, Cox F, Molano G, Harrison SJ, Luo D, Janssen PH, Pacheco D (2015) Lambs fed fresh winter forage rape (Brassica napus L.) emit less methane than those fed perennial ryegrass (Lolium perenne L.), and possible mechanisms behind the difference. PLoS ONE 10, e0119697.
| Crossref | Google Scholar | PubMed |

t’Mannetje L, Haydock KP (1963) The dry-weight-rank method for the botanical analysis of pasture. Journal of the British Grassland Society 18, 268-275.
| Crossref | Google Scholar |

Thornton JH, Owens FN (1981) Monensin supplementation and in vivo methane production by steers. Journal of Animal Science 52, 628-634.
| Crossref | Google Scholar | PubMed |

Tothill, JC, Hargreaves, JNG, Jones, RM, McDonald, RM (1992) Botanal – a comprehensive sampling and computing procedure for estimating pasture yield and composition. 1. Field sampling. In ‘Tropical Agronomy Technical Memorandum Vol. 78’. (CSIRO: Brisbane, Qld, Australia)

Wang Z, Goonewardene LA (2004) The use of MIXED models in the analysis of animal experiments with repeated measures. Canadian Journal of Animal Science 84, 1-11.
| Crossref | Google Scholar |

White A, Holst P (2006) Fat scoring sheep and lambs. NSW Department of Primary Industries Primefact 302, 1-2.
| Google Scholar |

Williams SRO, Hannah MC, Jacobs JL, Wales WJ, Moate PJ (2019) Volatile fatty acids in ruminal fluid can be used to predict methane yield of dairy cows. Animals 9, 1006.
| Crossref | Google Scholar | PubMed |