New Zealand dairy farmers preference investments in automation technology over decision-support technology
B. T. Dela Rue A C , C. R. Eastwood A , J. P. Edwards A and S. Cuthbert BA DairyNZ Ltd, Private Bag 3221, Hamilton 3240, New Zealand.
B Cuthbert & Associates, Hamilton, New Zealand.
C Corresponding author. Email: brian.delarue@dairynz.co.nz
Animal Production Science 60(1) 133-137 https://doi.org/10.1071/AN18566
Submitted: 6 September 2018 Accepted: 1 March 2019 Published: 24 April 2019
Abstract
Dairy farmers are adopting precision technologies to assist with milking and managing their cows due to increased herd sizes and a desire to improve labour efficiency, productivity and sustainability. In the present study, we evaluated the adoption of technologies installed at or near the dairy, and milking practices, on New Zealand dairy farms. These data quantify current use of technology for milking and labour efficiency, and decision-making, and provide insight into future technology adoption. A telephone survey of 500 farmers, randomly selected from a database of New Zealand dairy farms, was conducted in 2018. Adoption for all farms is indicated for six automation technologies, including automatic cup removers (39%), automatic drafting (24%), automatic teat spraying (29%), computer-controlled in-shed feeding (29%), automatic plant wash (18%) and automatic yard wash systems (27%). Five data-capture technologies also included in the survey were electronic milk meters (8%), automatic animal weighing (7%), in-line mastitis detection (7%), automatic heat detection (3%) and electronic animal-identification readers (23%). Analysis by dairy type indicated an adoption level for the automation technologies in rotary dairies of 36–77%, and 7–49% for data-capture technologies, with 10% having none of these 11 technologies installed. This compares with herringbone dairies at 4–21% and 2–11% for automation and data-capture technologies respectively, with 56% having none of these technologies. Rotary dairies, with a combination of automatic cup removers, automatic teat spraying, and automatic drafting, were associated with 43% higher labour efficiency (cows milked/h.person) and 14% higher milking efficiency (cows milked/h) than were rotary dairies without all three technologies. Dairy farmers will increasingly use technologies that deliver value, and the present study has provided information to guide investment decisions, product development and research in areas such as applying technology in new workplaces.
Additional keywords: labour efficiency, milking practices, pasture-based dairy farming, precision farming, technology adoption.
References
Borchers MR, Bewley JM (2015) An assessment of producer precision dairy farming technology use, prepurchase considerations, and usefulness. Journal of Dairy Science 98, 4198–4205.| An assessment of producer precision dairy farming technology use, prepurchase considerations, and usefulness.Crossref | GoogleScholarGoogle Scholar | 25892693PubMed |
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 |
Eastwood C, Jago J, Edwards J, Burke J (2016) Getting the most out of advanced farm management technologies: roles of technology suppliers and dairy industry organisations in supporting precision dairy farmers. Animal Production Science 56, 1752–1760.
| Getting the most out of advanced farm management technologies: roles of technology suppliers and dairy industry organisations in supporting precision dairy farmers.Crossref | GoogleScholarGoogle Scholar |
Eastwood CR, Greer J, Schmidt D, Muir J, Sargeant K (2018) Identifying current challenges and research priorities to guide the design of more attractive dairy-farm workplaces in New Zealand. Animal Production Science.
| Identifying current challenges and research priorities to guide the design of more attractive dairy-farm workplaces in New Zealand.Crossref | GoogleScholarGoogle Scholar |
Edwards JP, Dela Rue BT, Jago JG (2015) Evaluating rates of technology adoption and milking practices on New Zealand dairy farms. Animal Production Science 55, 702–709.
| Evaluating rates of technology adoption and milking practices on New Zealand dairy farms.Crossref | GoogleScholarGoogle Scholar |
Gargiulo JI, Eastwood CR, Garcia SC, Lyons NA (2018) Dairy farmers with larger herd sizes adopt more precision dairy technologies. Journal of Dairy Science 101, 5466–5473.
| Dairy farmers with larger herd sizes adopt more precision dairy technologies.Crossref | GoogleScholarGoogle Scholar | 29525319PubMed |
Jago J, Eastwood C, Kerrisk K, Yule I (2013) Precision dairy farming in Australasia: adoption, risks and opportunities. Animal Production Science 53, 907–916.
| Precision dairy farming in Australasia: adoption, risks and opportunities.Crossref | GoogleScholarGoogle Scholar |
Kamphuis C, Dela Rue BT, Eastwood CR (2016) Field validation of protocols developed to evaluate in-line mastitis detection systems. Journal of Dairy Science 99, 1619–1631.
| Field validation of protocols developed to evaluate in-line mastitis detection systems.Crossref | GoogleScholarGoogle Scholar | 26686708PubMed |
Rutten CJ, Velthuis AGJ, Steeneveld W, Hogeveen H (2013) Invited review: sensors to support health management on dairy farms. Journal of Dairy Science 96, 1928–1952.
| Invited review: sensors to support health management on dairy farms.Crossref | GoogleScholarGoogle Scholar | 23462176PubMed |