Science communication and engagement in adaptive farm-systems research: a case study of flexible milking research in New Zealand

C. R. Eastwood; J. P. Edwards; V. Bates

doi:10.1071/an22358

journal article Dec 05, 2022

Science communication and engagement in adaptive farm-systems research: a case study of flexible milking research in New Zealand

C. R. Eastwood

J. P. Edwards V. Bates

Animal Production Science Vol. 64 No. 1 · CSIRO Publishing

View at Publisher Save 10.1071/an22358

Abstract

Context 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. Aims 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. Methods 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. Key results 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. Conclusion 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. Implications 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.

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References

37

[1]

"Farming systems research: issues in research strategy and technology design." American Journal of Agricultural Economics (1982) 10.2307/1240753

[2]

"Is participatory research a scientific practice?" Journal of Rural Studies (2011) 10.1016/j.jrurstud.2011.10.004

[3]

"Uncertainty, learning, and technology adoption in agriculture." Applied Economic Perspectives and Policy (2020) 10.1002/aepp.13003

[4]

"Videos and podcasts for delivering agricultural extension: achieving credibility, relevance, legitimacy and accessibility." The Journal of Agricultural Education and Extension (2021) 10.1080/1389224x.2021.1997771

[5]

"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 (2007) 10.1080/13892240701427573

[6]

DairyNZ (2022) ‘Great futures in dairying.’ (DairyNZ, Hamilton, New Zealand). Available at

[7]

Darnhofer I, Gibbon D, Dedieu B (2012) ‘Farming systems research into the 21st century: the new dynamic.’ (Springer Netherlands: Dordrecht, Netherlands) 10.1007/978-94-007-4503-2

[8]

"Does farming systems research have a future?" Agricultural Administration and Extension (1987) 10.1016/0269-7475(87)90071-7

[9]

"The changing face of science communication, technology, extension and improved decision-making at the farm-water quality interface." Marine Pollution Bulletin (2021) 10.1016/j.marpolbul.2021.112534

[10]

"New Zealand dairy farmers preference investments in automation technology over decision-support technology." Animal Production Science (2020) 10.1071/an18566

[11]

"Innovation uncertainty impacts the adoption of smarter farming approaches." Frontiers in Sustainable Food Systems (2020) 10.3389/fsufs.2020.00024

[12]

"Networks of practice for co-construction of agricultural decision support systems: case studies of precision dairy farms in Australia." Agricultural Systems (2012) 10.1016/j.agsy.2011.12.005

[13]

"Identifying current challenges and research priorities to guide the design of more attractive dairy-farm workplaces in New Zealand." Animal Production Science (2020) 10.1071/an18568

[14]

Farmer-centred design: An affordances-based framework for identifying processes that facilitate farmers as co-designers in addressing complex agricultural challenges

C.R. Eastwood, F.J. Turner, A.J. Romera

Agricultural Systems 2022 10.1016/j.agsy.2021.103314

[15]

Edwards JP (2021) Making milking times work for you. In ‘Inside Dairy’. (Ed. B Chapman-Smith) pp. 22–25. (DairyNZ Ltd). Available at

[16]

"Opportunities for improving the safety of dairy parlor workers." Journal of Dairy Science (2021) 10.3168/jds.2020-18954

[17]

"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 (2022) 10.3168/jds.2022-21847

[18]

"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 (2022) 10.3168/jds.2021-21242

[19]

"Hitting the bullseye: learning to become a reflexive monitor in New Zealand." Outlook on Agriculture (2017) 10.1177/0030727017708490

[20]

Jones JR, Wallace BJ, Booth R, Rhoades RE (2019) ‘Social sciences and farming systems research: methodological perspectives on agricultural development.’ (CRC Press) 10.1201/9780429306389

[21]

"Design process outputs as boundary objects in agricultural innovation projects: functions and limitations." Agricultural Systems (2012) 10.1016/j.agsy.2012.07.006

[22]

"Reshaping a farming culture through participatory extension: an institutional logics perspective." Journal of Rural Studies (2020) 10.1016/j.jrurstud.2020.06.037

[23]

"Predicting farmer uptake of new agricultural practices: a tool for research, extension and policy." Agricultural Systems (2017) 10.1016/j.agsy.2017.06.007

[24]

"How does research address the design of innovative agricultural production systems at the farm level? A review." Agricultural Systems (2011) 10.1016/j.agsy.2011.07.007

[25]

"Whole farm systems research: an integrated crop and livestock systems comparison study." American Journal of Alternative Agriculture (1994) 10.1017/s0889189300005580

[26]

"Mapping the research domains on work in agriculture. A bibliometric review from Scopus database." Journal of Rural Studies (2021) 10.1016/j.jrurstud.2020.10.050

[27]

Adoption pathway analysis: Representing the dynamics and diversity of adoption for agricultural practices

Oscar Montes de Oca Munguia, David J. Pannell, Rick Llewellyn et al.

Agricultural Systems 2021 10.1016/j.agsy.2021.103173

[28]

"A participatory, farmer-led approach to changing practices around antimicrobial use on UK farms." Journal of Dairy Science (2021) 10.3168/jds.2020-18874

[29]

"The evolving extension environment: implications for dairy scientists." Animal Production Science (2013) 10.1071/an12347

[30]

"Context, participation and discourse: the role of the communities of practice concept in understanding farmer decision-making." The Journal of Agricultural Education and Extension (2008) 10.1080/13892240802320388

[31]

Packham R (2011) The farming systems approach. In ‘Shaping change: natural resource management, agriculture and the role of extension’. (Eds JR Jennings, RG Packham, D Woodside) pp. 32–51. (Australasia Pacific Extension Network (APEN): Australia)

[32]

"Farming systems research: relevance to Australia." Australian Journal of Experimental Agriculture (1998) 10.1071/ea96055

[33]

Rose DC, Keating C, Morris C (2018) ‘Understand how to influence farmers’ decision-making behaviour: a social science literature review.’ (Agriculture and Horticulture Development Board (AHDB))

[34]

"Planning for whole-farm systems research at a credible scale: subdividing land into farmlets with equivalent initial conditions." Animal Production Science (2013) 10.1071/an11176

[35]

Stevens D, Casey M, Cousins K (2016) Farming systems research: purpose, history and impact in New Zealand hill country. In ‘Grassland research and practice series. Rotorua, NZ. Vol. 16’. (New Zealand Grassland Association (NZGA)) 10.33584/rps.16.2016.3261

[36]

"Integrated crop/livestock systems research: practical research considerations." Renewable Agriculture and Food Systems (2008) 10.1017/s1742170507002165

[37]

"Design as a source of renewal in the production of scientific knowledge in crop science." Agricultural Systems (2020) 10.1016/j.agsy.2020.102939

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Published: Dec 05, 2022
Vol/Issue: 64(1)

Authors

Cite This Article

C. R. Eastwood, J. P. Edwards, V. Bates (2022). Science communication and engagement in adaptive farm-systems research: a case study of flexible milking research in New Zealand. Animal Production Science, 64(1). https://doi.org/10.1071/an22358

Science communication and engagement in adaptive farm-systems research: a case study of flexible milking research in New Zealand

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