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Food, fibre and pharmaceuticals from animals
REVIEW

Precision dairy farming in Australasia: adoption, risks and opportunities

J. Jago A E , C. Eastwood B , K. Kerrisk C and I. Yule D
+ Author Affiliations
- Author Affiliations

A DairyNZ, Corner of Ruakura and Morrinsville Roads, Private Bag 3221, Hamilton, New Zealand.

B Melbourne School of Land and Environment, The University of Melbourne, Vic. 3010, Australia.

C MC Franklin Laboratory (CO4) The University of Sydney, Private Mailbag 4003, Narellan, NSW 2567, Australia.

D New Zealand Centre for Precision Agriculture, Massey University, Palmerston North, New Zealand.

E Corresponding author. Email: jenny.jago@dairynz.co.nz

Animal Production Science 53(9) 907-916 https://doi.org/10.1071/AN12330
Submitted: 19 September 2012  Accepted: 22 March 2013   Published: 28 May 2013

Abstract

Dairy farm management has historically been based on the experiential learning and intuitive decision-making skills of the owner-operator. Larger herds and increasingly complex farming systems, combined with the availability of new information technologies, are prompting an evolution to an increasingly data-driven ‘precision dairy’ (PD) management approach. Automation and the collection of fine-scale data on animals and farm resources via precision technologies can facilitate enhanced efficiency and decision making on dairy farms. The proportion of dairy farmers using this approach is relatively small (between 10 and 20% of farmers); however, industry trends suggest a continual increase in the use of precision technologies. Australasian PD farms have reported both positive and negative stories regarding the approach but to date there has been little industry attention or co-ordination in Australia or New Zealand. A series of workshops was held in late 2011 between industry-good representatives, researchers and farmers, from Australia and New Zealand, to discuss the opportunities and risks associated with PD. To take advantage of the emerging PD opportunity the trans-Tasman workshop group suggested five focus areas including: industry-good co-ordination and leadership in precision dairy; working to define the on- and off-farm value of PD; improving the technology available to farmers; integration of PD within farming systems for improved management; and developing learning and training initiatives for farmers and service providers. Action in these focus areas will enable future dairy farmers to implement the PD approach with enhanced confidence and effectiveness.

Additional keywords: dairy system evolution, farm management, information technology.


References

Ashby JA, Sperling L (1995) Institutionalizing participatory, client-driven research and technology development in agriculture. Development and Change 26, 753–770.
Institutionalizing participatory, client-driven research and technology development in agriculture.Crossref | GoogleScholarGoogle Scholar |

Banhazi TM, Black JL (2009) Precision livestock farming: a suite of electronic systems to ensure the application of best practice management on livestock farms. (Technical report). Australian Journal of Multi-disciplinary Engineering 7, 1–14.

Betteridge K, Carter ML, Costall DA (2009) Urine sensors for sheep and cattle. In ‘Precision livestock farming. Papers presented at the 4th European conference on precision livestock farming, Wageningen, The Netherlands, 6–8 July 2009’. (Eds C Lokhorst, PWG Groot Koerkamp) pp. 169–174. (Wageningen Academic Publishers: Wageningen, The Netherlands)

Bewley J (2010) Precision dairy farming: advanced analysis solutions for future profitability. In ‘Proceedings of the first North American conference on precision dairy management, Toronto, Canada, 2–5 March 2010’. Available at http://www.precisiondairy2010.com/proceedings/s1bewley.pdf [Verified 20 April 2013]

Bewley JM, Russell A (2010) Reasons for slow adoption rates of precision dairy farming technologies: evidence from a producer survey. In ‘Proceedings of the first North American conference on precision dairy management, Toronto, Canada, 2–5 March 2010’. pp. 30–31. Available at http://www.precisiondairy2010.com/proceedings/s1bewley2.pdf [Verified 20 April 2013]

Bewley JM, Boehlje MD, Gray AW, Hogeveen H, Kenyon SJ, Eicher SD, Schutz MM (2010) Assessing the potential value for an automated dairy cattle body condition scoring system through stochastic simulation. Agricultural Finance Review 70, 126–150.
Assessing the potential value for an automated dairy cattle body condition scoring system through stochastic simulation.Crossref | GoogleScholarGoogle Scholar |

Blake J, Forrester D, Garren Knell G, McConnell G, Patabendige D, Rossere T, Shepherd D, Burt E (2003) Evaluating the impact of farming systems change using precision agriculture within innovative farmer groups. In ‘Proceedings of the 1st Australian farming systems conference, Toowoomba, Queensland, 7–11 September’. (Eds R Brett, C King)

Bootle BW (2002) Precision agriculture: Final Report to the Australian Nuffield Farming [Online]. Available at http://www.nuffield.com.au/report_f/2000/bootle.pdf [Verified 9 September 2012]

Bramley RGV (2009) Lessons from nearly 20 years of Precision Agriculture research, development, and adoption as a guide to its appropriate application. Crop and Pasture Science 60, 197–217.
Lessons from nearly 20 years of Precision Agriculture research, development, and adoption as a guide to its appropriate application.Crossref | GoogleScholarGoogle Scholar |

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 |

Cuthbert S (2008) DairyNZ milking practices and technology use survey. Report prepared for DairyNZ, Hamilton. 40 pp.

DairyNZ (2012) DairyNZ economic farm survey 2010–11 [Online]. Available at http://www.dairynz.co.nz/page/pageid/2145866853/Dairy_Industry#719 [Verified 9 September 2012]

de Koning K (2010) Automatic milking – common practice on dairy farms. In ‘Proceedings of the first North American conference on precision dairy management, Toronto, Canada, 2–5 March 2010’. Available at http://www.precisiondairy2010.com/proceedings/s3dekoning.pdf [Verified 20 April 2013]

Dharma S, Shafron W, Oliver M (2012) ‘Australian dairy farm technology and management practices 2010–11.’ (ABARES: Canberra)

Draganova I, Yule IJ, Betteridge K, Hedley M, Stevenson M, Stafford K (2010) Activity patterns and nutrient redistribution in intensively managed dairy herd. In ‘Farming’s Future: Minimising Footprints and Maximising Margins. Occasional Report No. 23’. (Eds LD Currie, C Christensen) pp. 398–404. (Fertiliser and Lime Research Centre, Massey University: Palmerston North)

Eastwood CR (2008) Innovative precision dairy systems: a case study of farmer learning and technology codevelopment. PhD thesis, The University of Melbourne.

Eastwood CR (2011) Applying innovation systems thinking to high challenge technologies: Dairy ICT and precision dairy as a case study’ UM13556 – Milestone Report 1 for Dairy Australia. Rural Innovation Research Group, The University of Melbourne, Melbourne.

Eastwood C, Jago J (2012) Precision dairy farming in New Zealand and Australia: a discussion document for trans-Tasman collaboration between DairyNZ and Dairy Australia. Report produced for DairyNZ and Dairy Australia. Rural Innovation Research Group, The University of Melbourne, Melbourne.

Eastwood C, Kenny S (2009) Art or science? Heuristic versus data driven grazing management on dairy farms. Extension Farming Systems Journal 5, 95–102.

Eastwood CR, Chapman DF, Paine MS (2012) Networks of practice for co-construction of agricultural decision support systems: case studies of precision dairy farms in Australia. Agricultural Systems 108, 10–18.
Networks of practice for co-construction of agricultural decision support systems: case studies of precision dairy farms in Australia.Crossref | GoogleScholarGoogle Scholar |

Fountas S, Wulfsohn D, Blackmore BS, Jacobsen HL, Pedersen SM (2006) A model of decision-making and information flows for information-intensive agriculture. Agricultural Systems 87, 192–210.
A model of decision-making and information flows for information-intensive agriculture.Crossref | GoogleScholarGoogle Scholar |

García SC, Fulkerson WJ (2005) Opportunities for future Australian dairy systems: a review. Australian Journal of Experimental Agriculture 45, 1041–1055.
Opportunities for future Australian dairy systems: a review.Crossref | GoogleScholarGoogle Scholar |

Grafton MCE, Yule IJ, Rendle B (2011) A review of technologies for improved of fertiliser application accuracy. In ‘Adding to the knowledge base for the nutrient manager’. Occasional Report No. 24. (Eds LD Currie, CL Christensen) (Fertilizer and Lime Research Centre, Massey University: Palmerston North, New Zealand) Available at http://flrc.massey.ac.nz/publications.html [Verified 26 March 2013]

Hedley CB, Yule IJ (2009) Soil water status mapping and two variable-rate irrigation scenarios. Precision Agriculture 10, 342–355.
Soil water status mapping and two variable-rate irrigation scenarios.Crossref | GoogleScholarGoogle Scholar |

Hedley CB, Yule IJ (2012) Farmer uptake of variable rate irrigation technologies in New Zealand. In ‘10th international conference on precision agriculture, 15–18 July, Indianapolis, Indiana, USA’. (Ed. J Stafford) Available at https://www.ispag.org/catalog/category/487/ [Verified 26 April 2013]

Hedley P, Kolver ES, Glassey CB, Thorrold BS, van Bysterveldt A, Roche JR, Macdonald KA (2006) Achieving high performance from a range of farm systems. Proceedings of the Dairy3 Conference 4, 147–165.

Hedley CB, Yule IJ, Tuohy MP, Vogeler I (2009) Key performance indicators for simulated variable rate irrigation of variable soils in humid regions. Transactions of the American Society of Agricultural and Biological Engineers 52, 1575–1584.

Jago J, Davis KL, Jensen R (2007) Future innovative dairy technologies to address constraints of labour, information collection and decision-making on farms. In ‘Proceedings of the Australasian dairy science symposium, 18–20 September, Melbourne’. (Eds DF Chapman, DA Clark, KL Macmillian, DP Nation) pp. 492–507. (National Dairy Alliance: Melbourne)

Jago J, Edwards P, Scott S (2011) Milking effectively in rotary dairies. In ‘Proceedings of the South Island Dairy Event (SIDE), 27–29 June, Lincoln University’. (Eds N Gow, K Doig) pp. 288–298. (The Caxton Press: Christchurch, New Zealand)

Kamphuis C, Dela Rue B, Mein G, Jago J (2011) Requirements of mastitis detection systems for high throughput New Zealand dairies. In ‘Proceedings of the 3rd international symposium on mastitis and milk quality’. pp. 100–104. (National Mastitis Council: St Louis, MO)

Kamphuis C, Dela Rue B, Burke CR, Jago J (2012) Evaluation of two collar-mounted activity meters for detecting cows in estrus on a large pasture-grazed dairy farm. Journal of Dairy Science 95, 3045–3056.
Evaluation of two collar-mounted activity meters for detecting cows in estrus on a large pasture-grazed dairy farm.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38Xntlymtbg%3D&md5=acffe39b876a53aac2329e0c4e9d14e1CAS | 22612940PubMed |

Katz G, Arazi A, Pinsky N, Halachmi I, Schmilovitch Z, Aizinbud E, Maltz E (2007) Current and near term technologies for automated recording of animal data for precision dairy farming. Journal of Animal Science 85, 377

Klerkx L, Leeuwis C (2008) Institutionalizing end-user demand steering in agricultural R&D: farmer levy funding of R&D in The Netherlands. Research Policy 37, 460–472.
Institutionalizing end-user demand steering in agricultural R&D: farmer levy funding of R&D in The Netherlands.Crossref | GoogleScholarGoogle Scholar |

Klindworth K, Greenhall R (2004) Industry performance survey, CowTime Project. Department of Primary Industries, Ellinbank.

Laca EA (2009) Precision livestock production: tools and concepts. Revista Brasileira de Zootecnia 38, 123–132.
Precision livestock production: tools and concepts.Crossref | GoogleScholarGoogle Scholar |

Lawrence H (2012) A farming philosophy to avoid wasted energy on a New Zealand dairy farm. In ‘Dairy Research Foundation: current topics in dairy production. Conference Proceedings. Vol. 17’. (Ed. M Heward) pp. 27–34. (The University of Sydney: Camden, NSW)

Lawrence HG, Yule IJ (2007) Estimation of the in-field variation in fertiliser application. New Zealand Journal of Agricultural Research 50, 25–32.
Estimation of the in-field variation in fertiliser application.Crossref | GoogleScholarGoogle Scholar |

Little S (2011) ‘Performance, profit and risk in pasture-based dairy feeding systems – findings from the TasMilk60 study.’ (Dairy Australia: Melbourne)

Mackinnon D, Oliver M, Ashton D (2010) Australian dairy industry: technology and management practices, 2008–09. ABARE-BRS research report 10.11, Canberra.

Morris JE, Cronin GM, Bush RD (2012) Improving sheep production and welfare in extensive systems through precision sheep management. Animal Production Science 52, 665–670.

Nuthall PL (2012) The intuitive world of farmers – the case of grazing management systems and experts. Agricultural Systems 107, 65–73.
The intuitive world of farmers – the case of grazing management systems and experts.Crossref | GoogleScholarGoogle Scholar |

Pierce FJ, Nowak P (1999) Aspects of precision agriculture. Advances in Agronomy 67, 1–85.
Aspects of precision agriculture.Crossref | GoogleScholarGoogle Scholar |

Pullanagari RR, Yule IJ, Tuohy MJ, Hedley MJ, Dynes R, King WM (2012a) Multispectral radiometry to estimate pasture quality components. Precision Agriculture 13, 442–456.
Multispectral radiometry to estimate pasture quality components.Crossref | GoogleScholarGoogle Scholar |

Pullanagari RR, Yule IJ, Tuohy MP, Hedley MJ, Dynes RA, King WM (2012b) In-field hyperspectral proximal sensing for estimating quality parameters of mixed pasture. Precision Agriculture 13, 351–369.
In-field hyperspectral proximal sensing for estimating quality parameters of mixed pasture.Crossref | GoogleScholarGoogle Scholar |

Pullanagari RR, Yule IJ, Tuohy MP, Hedley MJ, Dynes RA, King WM (2013) Proximal sensing of the seasonal variability of pasture nutritive value using multispectral radiometry. Grass and Forage Science 68, 110–119.
Proximal sensing of the seasonal variability of pasture nutritive value using multispectral radiometry.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXitVOitr8%3D&md5=4d4547ba3828b889f5a50dd3382a9bd1CAS |

Schellberg J, Hill MJ, Gerhards R, Rothmund M, Braun M (2008) Precision agriculture on grassland: applications, perspectives and constraints. European Journal of Agronomy 29, 59–71.
Precision agriculture on grassland: applications, perspectives and constraints.Crossref | GoogleScholarGoogle Scholar |

Schulze C, Spilke J, Lehner W (2007) Data modeling for Precision Dairy Farming within the competitive field of operational and analytical tasks. Computers and Electronics in Agriculture 59, 39–55.
Data modeling for Precision Dairy Farming within the competitive field of operational and analytical tasks.Crossref | GoogleScholarGoogle Scholar |

Smith IG (Ed.) (2011) ‘Multi-disciplinary approach to practical and acceptable precision livestock farming for SMEs in Europe and worldwide.’ (Platinum: Halifax, UK)

Trotter M (2012) Establishing and testing a Taggle® real-time autonomous spatial livestock monitoring system. In ‘Australian and New Zealand spatially enabled livestock management symposium, Lincoln University 6 July 2012’. (Ed. K Betteridge) (AgResearch Grasslands: Palmerston North, New Zealand) Available at http://www.agresearch.co.nz/our-science/land-environment/soils-land-use/docs/SELM%20Abstracts%202012%20(4MB).pdf [Verified 20 April 2013]

Uzmay C, Kaya I, Tomek B (2010) Precision dairy herd management applications. Hayvansal Uretim 51, 50–58. [Journal of Animal Production]

Watson P (2009) CowTime Tracking Survey 2009. Report Prepared for the Department of Primary Industries Victoria [Online]. Available at http://www.cowtime.com.au/edit/Reports/COWTIME_TRACKING_SURVEY_2009_REPORT_FINAL.PDF [Verified 8 September 2012]

Wendl G, Schön H (2002) Precision livestock farming on the example of dairying farming - state of the art and perspectives for the future. In ‘Proceedings 8th international congress on mechanization and energy in agriculture, 15–17 October 2002, Bornova-Izmir, Turkey’.

Yule IJ, Eastwood CR (2011) Challenges and opportunities for precision dairy farming in New Zealand: developing a research agenda to enhance farm management benefits from precision dairy use. Report prepared for DairyNZ, Hamilton.

Yule IJ, Eastwood CR (2012) Challenges and opportunities for precision dairy farming in New Zealand. In ‘Proceedings of the 11th international conference on precision Agriculture, Indianapolis, Indiana, USA, 15–18 July 2012’. (Ed. J Stafford) Available at https://www.ispag.org/catalog/category/487/ [Verified 30 April 2013]

Yule IJ, Grafton MCE (2010) Factors affecting fertiliser application uniformity. Occasional Report No. 23. (Eds LD Currie, CL Christensen) pp. 413–420. (Fertiliser and Lime Research Centre, Massey University: Palmerston North, New Zealand)

Yule IJ, Lawrence HG, Jago J (2008) Precision management for dairy farming and automation. In ‘Proceedings of the 9th international conference on precision agriculture, Denver, Colorado, USA, 20–23 July, 2008’. (Ed. J Stafford) Available at https://www.ispag.org/catalog/category/487/ [Verified 30 April 2013]