A Conceptual Framework for Guiding the Participatory Development of Agricultural Decision Support Systems

Scientists develop decision support systems (DSSs) to make agricultural science more accessible for farmers and extension officers. Despite the growing use of participatory approaches in agricultural DSS development, reflection on this endeavour is largely focused on the ‘doing’ of participation or the ‘problem of implementation’, with little reference to relevant theoretical approaches within the field of science and technology studies (STS). However, if DSS development is to reach its full potential, a more conceptually informed understanding of how stakeholders collaborate in the participatory development of DSSs is required. To contribute to this gap, we developed a conceptual framework based on three concepts drawn from STS that can add value to understanding agricultural DSSs: interpretative flexibility, technological frames, and boundary objects. A DSS becomes a boundary object when it enables the various parties involved in its development to collaborate and learn together despite diverse perceptions of the DSS or the issues that the DSS is being used to address. When combined, these three concepts highlight the importance of social learning for participatory DSS development, particularly the need to begin by exploring the parties’ different perspectives and facilitating co-learning. Our framework leads to a re-definition of success for participatory DSS development, by identifying social learning as a valuable outcome that can occur when farmers, extension officers and scientists collaborate. A case study of stakeholder collaboration to develop an irrigation scheduling DSS for the Australian sugarcane industry is used to illustrate the analytical strength of this conceptual framework.social learning, interpretative flexibility, technological frames, boundary objects, irrigation, climate variability

Understanding power, social capital and trust alongside near real-time water quality monitoring and technological development collaboration

We report on qualitative social research conducted with stakeholders in a local agricultural knowledge and advice network associated with a collaborative water quality monitoring project. These farmers, advisors and researchers allude to existing social dynamics, technological developments, and (more general) social evolution which is analysed against a novel analytical framework. This framework considers notions of power, social capital, and trust as related and dynamic, forming the basis of our contribution to knowledge. We then probe the data to understand perceived impacts of the collaborative project and social interaction associated with this research project, which involved cutting edge automated and frequent water quality monitoring that allowed for near real-time access to data visualisation displayed via a bespoke mobile or web ‘app’ (1622WQ). Our findings indicate that a multi-faceted approach to assessing and intervening based on consideration of multiple social dimensions holds promise in terms of creating conditions that allow for individual and group learning to encourage changes in thinking required to result in improved land management practice

Grasping at digitalisation: turning imagination into fact in the sugarcane farming community

Nutrient runoff from catchments that drain into the Great Barrier Reef (GBR) is a significant source of stress for this World Heritage Area. An alliance of collaborative on-ground water quality monitoring (Project 25) and technologically driven digital application development (Digiscape GBR) projects were formulated to provide data that highlighted the contribution of a network of Australian sugar cane farmers, amongst other sources, to nutrient runoff. This environmental data and subsequent information were extended to the farming community through scientist-led feedback sessions and the development of specialised digital technology (1622 (TM) WQ) that help build an understanding of the nutrient movements, in this case nitrogen, such that farmers might think about and eventually act to alter their fertilizer application practices. This paper reflects on a socio-environmental sustainability challenge that emerged during this case study, by utilising the nascent concept of digi-grasping. We highlight the importance of the entire agricultural knowledge and advice network being part of an innovation journey to increase the utility of digital agricultural technologies developed to increase overall sustainability. We develop the digi-MAST analytical framework, which explores modes of being and doing in the digital world, ranging from 'the everyday mystery of the digital world (M)', through digital 'awareness (A)', digitally 'sparked' being/s (S), and finally the ability of individuals and/or groups to 'transform (T)' utilising digital technologies and human imaginations. Our digi-MAST framework allows us to compare agricultural actors, in this case, to understand present modes of digi-grasping to help determine the resources and actions likely to be required to achieve impact from the development of various forms of digital technological research outputs

Australian Consumers’ Preferences for Food Attributes: A Latent Profile Analysis

Understanding consumer food preferences can provide agribusinesses with a competitive advantage through meeting consumers’ needs. Consumers’ preferences for food attributes have been extensively examined, focusing on specific aspects of attributes with specific food products. It is less clear how consumers evaluate the relative importance of the key food attributes in general. Applying the commonly adopted classification of food attributes into endogenous attributes (i.e., safety and freshness) and exogenous attributes (i.e., genetically modified (GM)-free and organic), the relative importance of these attributes for consumers was investigated. Furthermore, the heterogeneity of preferences was explored to identify distinct subgroups of consumers who may differ in valuing various food attributes. An online survey of 489 city dwellers in Australia revealed that the endogenous attributes were regarded as the most important in an order of safety and freshness. The exogenous attributes were rated as much less important. Three profiles with distinctive preferences for food attributes were identified: Not Fussy (12% of participants), Quality First (49%) and Choosy (39%). The findings suggest that consumers value the importance of various food attributes in a hierarchical order, and there is significant heterogeneity in consumers’ food preference. The implications of these findings are discussed in the context of food policy and agribusiness decision-making

A review of social science on digital agriculture, smart farming and agriculture 4.0 : New contributions and a future research agenda

While there is a lot of literature from a natural or technical sciences perspective on different forms of digitalization in agriculture (big data, internet of things, augmented reality, robotics, sensors, 3D printing, system integration, ubiquitous connectivity, artificial intelligence, digital twins, and blockchain among others), social science researchers have recently started investigating different aspects of digital agriculture in relation to farm production systems, value chains and food systems. This has led to a burgeoning but scattered social science body of literature. There is hence lack of overview of how this field of study is developing, and what are established, emerging, and new themes and topics. This is where this article aims to make a contribution, beyond introducing this special issue which presents seventeen articles dealing with social, economic and institutional dynamics of precision farming, digital agriculture, smart farming or agriculture 4.0. An exploratory literature review shows that five thematic clusters of extant social science literature on digitalization in agriculture can be identified: 1) Adoption, uses and adaptation of digital technologies on farm; 2) Effects of digitalization on farmer identity, farmer skills, and farm work; 3) Power, ownership, privacy and ethics in digitalizing agricultural production systems and value chains; 4) Digitalization and agricultural knowledge and innovation systems (AKIS); and 5) Economics and management of digitalized agricultural production systems and value chains. The main contributions of the special issue articles are mapped against these thematic clusters, revealing new insights on the link between digital agriculture and farm diversity, new economic, business and institutional arrangements both on-farm, in the value chain and food system, and in the innovation system, and emerging ways to ethically govern digital agriculture. Emerging lines of social science enquiry within these thematic clusters are identified and new lines are suggested to create a future research agenda on digital agriculture, smart farming and agriculture 4.0. Also, four potential new thematic social science clusters are also identified, which so far seem weakly developed: 1) Digital agriculture socio-cyber-physical-ecological systems conceptualizations; 2) Digital agriculture policy processes; 3) Digitally enabled agricultural transition pathways; and 4) Global geography of digital agriculture development. This future research agenda provides ample scope for future interdisciplinary and transdisciplinary science on precision farming, digital agriculture, smart farming and agriculture 4.0.</p

Comparing established practice for short-term forecasts and emerging use of climate projections to identify opportunities for climate services in Australian agriculture

The use of climate services in agriculture to improve both tactical and strategic management decisions on farm is an area of increasing societal interest and technological development in Australia, as climate change increases climate variability and risk. Yet the focus of most uses of climate services remains on weather and seasonal forecasts and tactical farm responses, with longer term climate projections less often empirically examined. In this paper we analyse 25 interviews with farmers in Australia and use social practice theory to compare farm risk management decisions utilising short-term weather forecasting and longer-term climate projection planning. We identify different elements of climate risk management as a social practice, looking particularly at materials (objects and tools), meanings (beliefs and thinking) and competencies (skills and knowledge) associated with climate services. We find that there are significant differences in how decisions are made using different temporal data scales and furthermore, that there are large gaps in the materials, meaning and competencies for the use of longer-term climate projections. This analysis allows us to clearly identify opportunities for the agricultural sector in Australia, and globally, to better support decisions in both weather and climate timeframes by treating these as distinctly different capabilities and addressing the different elements of social practice outlined here

The sugar industry’s impact on the landscape of the Australian wet tropical coast

The cultivation of sugarcane transformed the landscape and ecology of the Wet Tropics region of Australia over the last 140 years. In parallel, government policies shaped the\ud unique structure and culture of the sugar industry throughout Queensland, directly and indirectly affecting sugarcane cultivation practices. Despite government environmental policies and strategies, the nutrient run-off from sugarcane cultivation continues to impact on the coastal landscape and health of the Great Barrier Reef. Sugarcane growers in the area and stakeholders\ud from within and outside the industry were interviewed to determine why growers adopt many of the recommended practices that increase productivity, but not environmental practices such as reduced fertilizer application rates. This paper identifies how sugarcane growers are distinct from other farmers in Australia and suggests reasons why government environmental policy has failed.\ud We conclude that a new policy approach based on Ecological Modernization Theory is recommended to achieve desired ecological outcomes and, at the same time, maintain productivity levels

Improving the participatory development of decision support systems for the sugar industry

Sugar production systems are characterized by complex interactions between a range of economic, environmental and social factors. This complexity has lead to a search for ways in which scientific knowledge can be incorporated into forms that industry stakeholders can use to assist their management decisions. Decision support systems (DSSs) are one of the ways in which scientists have attempted to make agricultural systems science more accessible and useful for industry stakeholders. Recently, there has been a shift towards more participatory research and development of DSSs. We have analysed the participatory development of DSSs using concepts from the sociology of science and technology, as part of a study examining the adoption of knowledge intensive technologies in the Australian sugar industry. In this paper, we develop a framework for describing the phases of the participatory process, and the likely outcomes of the process. Understanding these phases allows those involved to be more confident that the participatory process will result in the beneficial relationships and greater mutual understanding that are desired from these processes. This work also highlights that the subsequent use of the DSS is not a guaranteed outcome of participatory development. We identify two likely outcomes of participatory DSS development: DSSs may lead to practice change even if they are used only to build capacity, or DSSs may be used directly to improve practice on an ongoing basis. Our analysis so far suggests that successful DSS development should be viewed as a participatory process leading to practice change, which results in improved farm or agricultural supply chain management, irrespective of whether or not this involves ongoing DSS use. We illustrate this framework with case studies of DSSs for irrigation management and climate forecasting

“If they don't tell us what they do with it, why would we trust them?” Trust, transparency and benefit-sharing in Smart Farming

Advances in Smart Farming and Big Data applications have the potential to help agricultural industries meet productivity and sustainability challenges. However, these benefits are unlikely to be realised if the social implications of these technological innovations are not adequately considered by those who promote them. Big Data applications are intrinsically socio-technical; their development and deployment are a product of social interactions between people, institutional and regulatory settings, as well as the technology itself. This paper explores the socio-technical factors and conditions that influence the development of Smart Farming and Big Data applications, using a multi-level perspective on transitions combined with social practice theory. We conducted semi-structured interviews with 26 Australian grain farmers and industry stakeholders to elicit their perspectives on benefits and risks of these changes. The analysis shows that issues related to trust are central concerns for many participants. These include procedural concerns about transparency and distributional concerns about who will benefit from access to and use of “farmers’ data”. These concerns create scepticism about the value of ‘smart’ technologies amongst some industry stakeholders, especially farmers. It also points to a divergence of expectations and norms between actors and institutions at the regime and niche levels in the emerging transition towards Smart Farming. Bridging this divide will require niche level interventions to enhance the agency of farmers and their local networks in these transactions, and, the cooperative design of new institutions at regime level to facilitate the fair and transparent allocation of risk and benefit in farming data information chains