Science communication and engagement in adaptive farm-systems research: a case study of flexible milking research in New Zealand
C. R. Eastwood
A * , J. P. Edwards A and V. Bates A
A DairyNZ Ltd, PO Box 85066, Lincoln 7647, New Zealand.
Abstract
The aim of farm-systems research is to test concepts in a holistic context that enables results to be as applicable as possible to commercial farmers. A downside of such research has been that it can take several seasons to be confident in the consistency of the outcomes and interpretation of the results. Scientists are often reluctant to communicate outcomes until they have clear conclusions, which conflicts with farmers’ desire to see rapid answers and engage with research.
This paper reviews a 3-year farm-systems research project investigating flexible milking strategies for New Zealand dairy farmers. The aims of this paper are to (1) examine the impact of real-time science communication in achieving farm system change, and (2) develop a framework for science communication and engagement in adaptive farm-systems research.
The project involved farmer interviews, a farmlet experiment, a component experiment, partner farms, modelling, and a farmer reference group. We use data from sources such as e-newsletter engagement, webinar participation, web-page engagement, presentation attendance, and farmer feedback to collect insights on the impact of the project.
The analysis highlighted that farmers do not always seek complete information and will follow a project as it evolves, particularly when it is highly topical. We propose a framework for delivering adaptive farm systems research and communication. The framework includes the critical aspects for real-time farm-systems research: credible evidence, rapid results, inclusion of farmer voices, meaningful outcomes, flexible communication channels, iterative feedback loops, and adaptable research design.
Farm-systems research can be designed to communicate results to farmers as a project develops, while simultaneously using the engagement with farmers to refine the direction of the research.
This framework can guide scientists leading multi-year farm systems projects to design, implement, and communicate the project outcomes to improve farmer engagement and adoption.
Keywords: co-development, communication, email, engagement, learning, podcast, project design, social media, webinar.
References
Byerlee D, Harrington L, Winkelmann DL (1982) Farming systems research: issues in research strategy and technology design. American Journal of Agricultural Economics 64, 897-904.
| Crossref | Google Scholar |
Cerf M (2011) Is participatory research a scientific practice? Journal of Rural Studies 27, 414-418.
| Crossref | Google Scholar |
Chavas J-P, Nauges C (2020) Uncertainty, learning, and technology adoption in agriculture. Applied Economic Perspectives and Policy 42, 42-53.
| Crossref | Google Scholar |
Chivers C-A, Bliss K, de Boon A, Lishman L, Schillings J, Smith R, Rose DC (2021) Videos and podcasts for delivering agricultural extension: achieving credibility, relevance, legitimacy and accessibility. The Journal of Agricultural Education and Extension 1-25.
| Crossref | Google Scholar |
Crawford A, Nettle R, Paine M, Kabore C (2007) Farms and learning partnerships in farming systems projects: a response to the challenges of complexity in agricultural innovation. The Journal of Agricultural Education and Extension 13, 191-207.
| Crossref | Google Scholar |
DairyNZ (2022) ‘Great futures in dairying.’ (DairyNZ, Hamilton, New Zealand). Available at https://www.dairynz.co.nz/media/5795487/dnz_great_futures_in_dairying_a4-booklet_web_june2022.pdf
Davidson AP (1987) Does farming systems research have a future? Agricultural Administration and Extension 24, 69-77.
| Crossref | Google Scholar |
Davis AM, Webster AJ, Fitch P, Fielke S, Taylor BM, Morris S, Thorburn PJ (2021) The changing face of science communication, technology, extension and improved decision-making at the farm-water quality interface. Marine Pollution Bulletin 169, 112534.
| Crossref | Google Scholar |
Dela Rue BT, Eastwood CR, Edwards JP, Cuthbert S (2020) New Zealand dairy farmers preference investments in automation technology over decision-support technology. Animal Production Science 60, 133-137.
| Crossref | Google Scholar |
Eastwood CR, Renwick A (2020) Innovation uncertainty impacts the adoption of smarter farming approaches. Frontiers in Sustainable Food Systems 4, 24.
| Crossref | Google Scholar |
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.
| Crossref | Google Scholar |
Eastwood CR, Greer J, Schmidt D, Muir J, Sargeant K (2020) Identifying current challenges and research priorities to guide the design of more attractive dairy-farm workplaces in New Zealand. Animal Production Science 60, 84-88.
| Crossref | Google Scholar |
Eastwood CR, Turner FJ, Romera AJ (2022) Farmer-centred design: an affordances-based framework for identifying processes that facilitate farmers as co-designers in addressing complex agricultural challenges. Agricultural Systems 195, 103314.
| Crossref | Google Scholar |
Edwards JP (2021) Making milking times work for you. In ‘Inside Dairy’. (Ed. B Chapman-Smith) pp. 22–25. (DairyNZ Ltd). Available at https://online.flippingbook.com/view/484738483/24/
Edwards JP, Kuhn-Sherlock B (2021) Opportunities for improving the safety of dairy parlor workers. Journal of Dairy Science 104, 419-430.
| Crossref | Google Scholar |
Edwards JP, Williamson JH, Kuhn-Sherlock B (2022a) Improving parlor efficiency in block calving pasture-based dairy systems through the application of a fixed milking time determined by daily milk yield and milking frequency. Journal of Dairy Science 105, 7513-7524.
| Crossref | Google Scholar |
Edwards JP, McMillan N, Bryant RH, Kuhn-Sherlock B (2022b) Reducing milking frequency from twice each day to three times each two days affected protein but not fat yield in a pasture-based dairy system. Journal of Dairy Science 105, 4206-4217.
| Crossref | Google Scholar |
Fielke S, Nelson T, Blackett P, Bewsell D, Bayne K, Park N, Rijswijk K, Small B (2017) Hitting the bullseye: learning to become a reflexive monitor in New Zealand. Outlook on Agriculture 46, 117-124.
| Crossref | Google Scholar |
Klerkx L, van Bommel S, Bos B, Holster H, Zwartkruis JV, Aarts N (2012) Design process outputs as boundary objects in agricultural innovation projects: functions and limitations. Agricultural Systems 113, 39-49.
| Crossref | Google Scholar |
Knook J, Turner JA (2020) Reshaping a farming culture through participatory extension: an institutional logics perspective. Journal of Rural Studies 78, 411-425.
| Crossref | Google Scholar |
Kuehne G, Llewellyn R, Pannell DJ, Wilkinson R, Dolling P, Ouzman J, Ewing M (2017) Predicting farmer uptake of new agricultural practices: a tool for research, extension and policy. Agricultural Systems 156, 115-125.
| Crossref | Google Scholar |
Le Gal P-Y, Dugué P, Faure G, Novak S (2011) How does research address the design of innovative agricultural production systems at the farm level? A review. Agricultural Systems 104, 714-728.
| Crossref | Google Scholar |
Luna J, Allen V, Fontenot J, Daniels L, Vaughan D, Hagood S, Taylor D, Laub C (1994) Whole farm systems research: an integrated crop and livestock systems comparison study. American Journal of Alternative Agriculture 9, 57-63.
| Crossref | Google Scholar |
Malanski PD, Dedieu B, Schiavi S (2021) Mapping the research domains on work in agriculture. A bibliometric review from Scopus database. Journal of Rural Studies 81, 305-314.
| Crossref | Google Scholar |
Montes de Oca Munguia O, Pannell DJ, Llewellyn R, Stahlmann-Brown P (2021) Adoption pathway analysis: representing the dynamics and diversity of adoption for agricultural practices. Agricultural Systems 191, 103173.
| Crossref | Google Scholar |
Morgans LC, Bolt S, Bruno-McClung E, van Dijk L, Escobar MP, Buller HJ, Main DCJ, Reyher KK (2021) A participatory, farmer-led approach to changing practices around antimicrobial use on UK farms. Journal of Dairy Science 104, 2212-2230.
| Crossref | Google Scholar |
Murphy C, Nettle R, Paine M (2013) The evolving extension environment: implications for dairy scientists. Animal Production Science 53, 917-923.
| Crossref | Google Scholar |
O’Kane MP, Paine MS, King BJ (2008) Context, participation and discourse: the role of the communities of practice concept in understanding farmer decision-making. The Journal of Agricultural Education and Extension 14, 187-201.
| Crossref | Google Scholar |
Petheram RJ, Clark RA (1998) Farming systems research: relevance to Australia. Australian Journal of Experimental Agriculture 38, 101-115.
| Crossref | Google Scholar |
Scott JM, Munro M, Rollings N, Browne W, Vickery PJ, Macgregor C, Donald GE, Sutherland H (2013) Planning for whole-farm systems research at a credible scale: subdividing land into farmlets with equivalent initial conditions. Animal Production Science 53, 618-627.
| Crossref | Google Scholar |
Tanaka DL, Karn JF, Scholljegerdes EJ (2008) Integrated crop/livestock systems research: practical research considerations. Renewable Agriculture and Food Systems 23, 80-86.
| Crossref | Google Scholar |
Toffolini Q, Jeuffroy M-H, Meynard J-M, Borg J, Enjalbert J, Gauffreteau A, Goldringer I, Lefèvre A, Loyce C, Martin P, Salembier C, Souchère V, Valantin-Morison M, van Frank G, Prost L (2020) Design as a source of renewal in the production of scientific knowledge in crop science. Agricultural Systems 185, 102939.
| Crossref | Google Scholar |
