Regular estimates of herbage mass can improve profitability of pasture-based dairy systems
P. C. Beukes A B , S. McCarthy A , C. M. Wims A , P. Gregorini A and A. J. Romera AA DairyNZ Ltd, Private Bag 3221, Hamilton 3240, New Zealand.
B Corresponding author. Email: pierre.beukes@dairynz.co.nz
Animal Production Science 59(2) 359-367 https://doi.org/10.1071/AN17166
Submitted: 20 March 2017 Accepted: 15 November 2017 Published: 5 January 2018
Abstract
Paddock selection is an important component of grazing management and is based on either an estimate of herbage mass, or the interval since last grazing for each paddock. Obtaining estimates of herbage mass to guide grazing management can be a time consuming task. A value proposition could therefore assist farmers in deciding whether to invest resources in obtaining such information. A farm-scale simulation exercise was designed to estimate the effect of three levels of knowledge of individual paddock herbage mass on profitability of two typical pasture-based dairy systems in New Zealand; a medium input system stocked at 3.2 Friesian-Jersey cross bred cows/ha with ~15% imported feed, and a high input system stocked at 4.5 Friesian cows/ha with ~40% imported feed. The three levels of knowledge were: (1) ‘perfect knowledge’, where herbage mass per paddock is known with perfect accuracy, (2) ‘imperfect knowledge’, where herbage mass per paddock is estimated with an average error of 15%, (3) ‘low knowledge’, where herbage mass is not known, and paddocks are selected based on longest time since last grazing. In both systems, grazing management based on imperfect knowledge increased farm operating profit by ~NZ$385/ha at a milk price of NZ$6.33/kg milksolids (fat + protein) compared with low knowledge. Perfect knowledge added a further NZ$155/ha to profit. The main driver of these results is the level of accuracy in daily feed allocation, which increases with improved knowledge of herbage availability. This allows feed supply and demand to be better matched, resulting in less incidence of under- and over-feeding, higher milk production, and more optimal post-grazing residual herbage mass to maximise herbage regrowth.
Additional keywords: grazing management, herbage allowance, modelling, monitoring, paddock selection, value proposition.
References
Beukes PC, Palliser CC, Macdonald KA, Lancaster JAS, Levy G, Thorrold BS, Wastney ME (2008) Evaluation of a whole-farm model for pasture-based dairy systems. Journal of Dairy Science 91, 2353–2360.| Evaluation of a whole-farm model for pasture-based dairy systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXmsVWmtLc%3D&md5=7bdf72d4cec857a7a7c33c78eeeb01efCAS |
Chapman DF (2016) Using ecophysiology to improve farm efficiency: application in temperate dairy grazing systems. Agriculture 6,
| Using ecophysiology to improve farm efficiency: application in temperate dairy grazing systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC28XktlKisbk%3D&md5=bf61eea28892c610f2a68e1d33a45165CAS |
Chapman D, McCarthy S, Kay J (2014) Hidden dollars in grazing management: getting the most profit from your pastures. In ‘Proceedings of the South Island Dairy Event, Invercargill, New Zealand’. pp. 21–36. (SIDE Secretariat, Lincoln University: Christchurch, New Zealand)
Clark DA, Caradus JR, Monaghan RM, Sharp P, Thorrold BS (2007) Issues and options for future dairy farming in New Zealand. New Zealand Journal of Agricultural Research 50, 203–221.
| Issues and options for future dairy farming in New Zealand.Crossref | GoogleScholarGoogle Scholar |
Clark CEF, Romera A, Macdonald KA, Clark DA (2010) Inter-paddock annual dry matter yield variability on dairy farms. New Zealand Journal of Agricultural Research 53, 187–191.
| Inter-paddock annual dry matter yield variability on dairy farms.Crossref | GoogleScholarGoogle Scholar |
Crawford B, Crawford J, Butcher G, Martin D (2015) Grass factory New Zealand: weekly pasture dry matter measurement. Available at www.beeflambnz.com [Verified 25 April 2015]
DairyNZ (2010) ‘Facts and figures for New Zealand dairy farmers.’ (DairyNZ Limited: Hamilton, New Zealand)
DairyNZ (2014) Global production and price volatility. Available athttps://www.dairynz.co.nz/news/latest-news/global-production-and-price- volatility/ [Verified 15 September 2017]
DairyNZ Limited (2014) DairyNZ Economic Survey 2012–13. DairyNZ Limited, Hamilton, New Zealand.
Dalley DE, Roche JR, Moate PJ (1999) Dry matter intake, nutrient selection and milk production of dairy cows grazing rainfed perennial pastures at different herbage allowances in spring. Australian Journal of Experimental Agriculture 39, 923–931.
| Dry matter intake, nutrient selection and milk production of dairy cows grazing rainfed perennial pastures at different herbage allowances in spring.Crossref | GoogleScholarGoogle Scholar |
Eastwood CR, Nettle RM, Crawford AE (2010) Aligning objective data with grazing management decision making. In ‘Proceedings of the 4th Australasian dairy science symposium, Lincoln, New Zealand’. (Eds GR Edwards, RH Bryant) pp. 210–214. (Lincoln University: Christchurch, New Zealand)
Fulkerson WJ, McKean K, Nandra KS, Barchia IM (2005) Benefits of accurately allocating feed on a daily basis to dairy cows grazing pasture. Australian Journal of Experimental Agriculture 45, 331–336.
| Benefits of accurately allocating feed on a daily basis to dairy cows grazing pasture.Crossref | GoogleScholarGoogle Scholar |
Gregorini P, Galli J, Romera AJ, Levy G, Macdonald KA, Fernandez HH, Beukes PC (2014) Incorporating a prediction of postgrazing herbage mass into a whole farm model for pasture-based dairy systems. Journal of Dairy Science 97, 4354–4366.
| Incorporating a prediction of postgrazing herbage mass into a whole farm model for pasture-based dairy systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXhtVCju7nL&md5=0e763eb8889d89ba5e4d797bff40b46aCAS |
Holmes CW, Brookes IM, Garrick DJ, Mackenzie DDS, Parkinson TJ, Wilson GF (2002) ‘Milk production from pasture. Principles and practices.’ (Massey University: Palmerston North, New Zealand)
King WMcG, Rennie GM, Dalley DE, Dynes RA, Upsdell MP (2010) Pasture mass estimation by the C-DAX pasture meter: regional calibrations for New Zealand. In ‘Proceedings of the 4th Australasian dairy science symposium, Lincoln, New Zealand’. (Eds GR Edwards, RH Bryant) pp. 233–238. (Lincoln University: Christchurch, New Zealand)
Lee J, Donaghy D, Roche J (2007) The effect of grazing severity and fertilizer application during winter on herbage regrowth and quality of perennial ryegrass (Lolium perenne L.). Animal Production Science 47, 825–832.
| The effect of grazing severity and fertilizer application during winter on herbage regrowth and quality of perennial ryegrass (Lolium perenne L.).Crossref | GoogleScholarGoogle Scholar |
Lee J, Donaghy D, Roche J (2008) Effect of defoliation severity on regrowth and nutritive value of perennial ryegrass dominant swards. Agronomy Journal 100, 308–314.
| Effect of defoliation severity on regrowth and nutritive value of perennial ryegrass dominant swards.Crossref | GoogleScholarGoogle Scholar |
Macdonald KA, Penno JW, Lancaster JAS, Roche JR (2008) Effect of stocking rate on pasture production, milk production, and reproduction of dairy cows in pasture-based systems. Journal of Dairy Science 91, 2151–2163.
| Effect of stocking rate on pasture production, milk production, and reproduction of dairy cows in pasture-based systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXltlWlsr4%3D&md5=a9c3f14598e07f43cc5b17b97f28c4a7CAS |
Macdonald KA, Glassey CB, Rawnsley RP (2010) The emergence, development and effectiveness of decision rules for pasture-based dairy systems. In ‘Proceedings of the 4th Australasian dairy science symposium, Lincoln, New Zealand’. (Eds GR Edwards, RH Bryant) pp. 199–209. (Lincoln University: Christchurch, New Zealand)
McCarthy S, Hirst C, Donaghy D, Gray D, Wood B (2014) Opportunities to improve grazing management. Proceedings of the New Zealand Grassland Association 76, 75–80.
O’Donovan M, Dillon P, Rath M, Stakelum G (2002) A comparison of four methods of herbage mass estimation. Irish Journal of Agricultural and Food Research 41, 17–27.
Parsons AJ, Johnson IR, Harvey A (1988) Use of a model to optimize the interaction between frequency and severity of intermittent defoliation and to provide a fundamental comparison of the continuous and intermittent defoliation of grass. Grass and Forage Science 43, 49–59.
| Use of a model to optimize the interaction between frequency and severity of intermittent defoliation and to provide a fundamental comparison of the continuous and intermittent defoliation of grass.Crossref | GoogleScholarGoogle Scholar |
Romera AJ, Doole GJ (2015) Optimising the interrelationship between intake per cow and intake per hectare. Animal Production Science 55, 384–396.
| Optimising the interrelationship between intake per cow and intake per hectare.Crossref | GoogleScholarGoogle Scholar |
Romera AJ, Beukes P, Clark C, Clark D, Levy H, Tait A (2010) Use of a pasture growth model to estimate herbage mass at a paddock scale and assist management on dairy farms. Computers and Electronics in Agriculture 74, 66–72.
| Use of a pasture growth model to estimate herbage mass at a paddock scale and assist management on dairy farms.Crossref | GoogleScholarGoogle Scholar |
