Njas-Wageningen Journal of Life Sciences最新文献

As research and innovation around Smart Farming further advances, there is a need to consider the impact of these technologies including the socio-economic, behavioural and cultural issues that may arise from their adoption. The current study explores the perceived risks and benefits arising from the development of Smart Farming in Ireland and in particular focuses on the different interpretations ascribed to risk issues by different actors. Semi-structured interviews were carried out with 21 actors who through their professional positions have some level of responsibility for the growth of Smart Farming in Ireland. Although the participants in the current study were largely in agreement about the benefits presented by Smart Farming for Irish agriculture and society, they held different interpretations and opinions when discussing identified risks. The main concerns related to consumer rejection of technologies, inequitable distribution of risks and benefits within the farming community, adverse socio-economic impacts of increased farmer-technology interactions, and ethical threats presented by the collection and sharing of farmers’ data. The current study reinforces how ambiguity can surround the discussion of risks as individuals form perceptions based on divergent value judgements. The findings reinforce the call for discourse-based management of risks and the embedding of frameworks such as Responsible Research and Innovation within Smart Farming.

Digital agriculture is likely to transform productive processes both on- and off- farm, as well as the broader social and institutional context using digital technologies. It is largely unknown how agricultural knowledge providing organisations, such as advisors and science organisations, understand and respond to digital agriculture. The concept of ‘organisational identity’ is used to describe both initial understandings of, and emerging responses, to digital agriculture, which together show how organisations ‘digi-grasp’, i.e. make sense of and enact digitalisation in their organisations. The understanding is described using aspects of identity change (i.e. the nature, pace, source and context of digital agriculture), while the responses are outlined through the various attributes of organisational identity (i.e. capabilities, practices, services, clients, partners, purpose and values). We explore this question in the context of New Zealand through 29 semi-structured interviews with different types of agricultural knowledge providers, including farm advisors, science organisations, as well as technology providers. The findings show that digitalisation is often understood as farm-centric, despite being considered disruptive both on- and off-farm. These understandings influence an organisation’s digitalisation responses to digital agriculture. The responses were often ad-hoc, starting with adapting organisational capabilities, practices and services as their clients and partners require, rather than a strategic approach allowing for more flexibility of roles and processes and changing business models. The ad-hoc approach appears to be a response to uncertainty as digital agriculture is in early stages of development. This indicates that agricultural knowledge and innovation system should better support agricultural knowledge providers in digi-grasping and developing a digitalisation strategy, by anticipating possible futures and reflecting on the consequences of these for value propositions, business models and organisational identities of agricultural knowledge providers.

The promise of technology development in agriculture is well publicised with some claiming that digital disruption will transform the way farming and food production is done in the future. For farm advisers, engaging in smart farming involves managing the proliferation of new forms of information, new knowledge and networks and new technical devices that produce digitised representations of farm performance. The nature and effects of digital practices in particular poses challenges for farm advisers as they seek to understand how digital tools and services can be integrated into their service delivery for improved farm decision making. In this paper we present insights from a co-design process with private farm advisers and ask: What enables farm advisers to engage with digital innovation? And, how can digital innovation be supported and practiced in smart farming contexts? Digital innovation presents challenges for farmers and advisers due to the new relationships, skills, arrangements, techniques and devices required to realise value for farm production and profitability from digital tools and services. We show how a co-design process supported farm advisers to adapt their routine advisory practices through recognising and engaging with the social, material and symbolic practices of digiware in smart farming. We demonstrate the need to recognise ‘digiware as constituted in and by heterogeneous practices from which possibilities for digital innovation emerge. These possibilities include the increased capacity of farm advisers to identify the value proposition of smart farming tools and services for theirs and their clients’ businesses, and the adaptation of advisory services in ways that harnass and mobilise diverse skills, knowledge/s, materials and representations for translating digital data, digital infrastructure and digital capacities into better decisions for farm management.

The work described here has sought to define the role of the Internet in knowledge acquisition among Polish farmers, as well as the diversity characterising their professional activity conducted online. Relevant discussion is in this way broadened to reflect the conditioning underpinning smart agriculture, most especially in the context of states emerging from a period of economic transition. Particular attention is here paid to the factor of choice of source of information assisting with the running of a farm. Analyses relating to this matter are founded upon questionnaires supplied by almost 2500 farmers. The results show that the Internet does not constitute the most important information source for Polish farmers, though there is a close link between use of the Internet and their basic social characteristics, as also associated with structural features of Polish agriculture. On that basis, it can be considered that Polish farming still finds itself at the preliminary phase of entry into smart agriculture. The Polish case shows that we cannot assume that there is a readiness for smart farming in all places.

Although precision livestock farming (PLF) technologies ensure various dimensions of more precise information, the question arises to what extent additional preciseness provides more value. Literature gives insufficient anchor points to estimate the value of information (VOI) obtained with PLF technologies. This study proposes a conceptual framework with building blocks to determine the VOI. Next, the framework is used to describe factors and existing gaps in the VOI assessment. This, finally, leads to reflections and recommendations about how to assess and improve the VOI of PLF. Literature reveals that the VOI surpasses the mere use of more precise information to take decisions, but encompasses a path from data collection to decisions with particular outcomes. The framework interlinks three building blocks: (i) data processing, (ii) decision making and (iii) impact analysis with factors influencing the VOI such as the process to transform data into information, level of precision, decision rules, social influences, the accuracy of information, herd size and prevalence of the condition measured. Besides profitability, outcomes from decisions include the impact on animal welfare, environment, food safety, and food security. The data-to-value framework allows for a better assessment of VOI and its potentials, and provides anchor points to design useful and valuable PLF technologies. The framework also helps to determine the role of advisors in interpreting the more precise information and in formulating farmer-tailored advice to apply the most optimal practices. Both technology design and advisors’ role may enhance the VOI of future PLF developments and applications.

As agriculture meets digital technologies, a new frontier of innovation is emerging and creating multiple pathways to a smart farming future. This paper presents a case study of a smart farming innovation originating from a small-to-medium sized enterprise (SME) that designs and manufactures machinery used in broadacre, conservation tillage farming. The innovation, known as DOT™, is an entrepreneur’s response to problems in the agriculture industry. Applying the innovation opportunity space (IOS) conceptual framework, this study identified the process of innovation was based on synthesis of tacit knowledge (experience-based knowledge of farming and agribusiness) and codified knowledge (drawing on computer programming). The innovation offers a solution for farming problems, and other firms are incorporating the autonomous functionality into their short-line manufacturing operations through licensing agreements, and early farmer adoption is positive. However, this smart farming IOS is presently an Unstable IOS and there remain some gaps: public policy for safe deployment of autonomous agriculture vehicles is lagging behind the invention and commercialization; the new business models for manufacture and commercialization of high-tech equipment are just emerging, and data ownership and control remain unresolved; and evidence of the value of smart farming technologies to farmers and the larger social system and biosphere remains scant.

Increased use of data from smart farming technologies presents an opportunity for farmers to better understand their farm systems, and thereby improve outcomes for productivity, sustainability, and animal care. A research gap exists regarding the impact of data-driven smart farming on the relationship between advisors and farmers, and advisors and farm data/technology. Therefore, we asked: how are farmers and advisors interacting with data-driven smart farming, and what are the implications for farm advisor capability and roles in a future where farmers use more data-driven smart farming? We studied advisory roles, advisor-farmer interactions, and new technologies in the context of three case studies: i) automated cow body condition scoring in New Zealand; ii) precision grazing management in New Zealand; and iii) the Soil Water Outlook tool in the Australian grains and lamb sectors. We propose a conceptual framework involving on-farm adaptation, learning, capability development and organizational roles. The findings show that smart technologies exhibit potentially disruptive features for farm management, necessitating greater input from a farmer’s advisory network to facilitate optimal farm system adaptation. This has implications for the nature of the advisory relationship, where advisory capabilities evolve to include skills on determining technology value propositions alongside farmers and new skills are built for linking data to better decision-making on farm. This paper contributes to improved understanding of how back-office advisory roles may move from information gathering, to remote data interpretation due to data-driven smart farming. We identify the advisor’s role in acting as a sensemaker in the smart farming innovation system, rather than a promoter or barrier to technology uptake. Further adaptation of advisory practices is required to enable greater value from data-driven smart farming to be captured by farmers.

Big data represent a pioneering development in the field of agriculture. By producing intuition, intelligence, and insights, these data have the potential to recast conventional process-driven agriculture, plotting the course for a smarter, data-driven farming. However, many open issues about the use of big data in agriculture remain unanswered. In this work, conceptualizing smart agricultural systems as cyber-physical-social systems, and building upon activity theory, we aim at highlighting some key questions that need to be addressed. To our view, big data constitute a tool reciprocally produced by all the actors involved in the agrifood supply chains. The constant flux of this tool and the intricate nature of the interactions among the actors who share it complicate the translation of big data into value. Moreover, farmers’ limited capacity to deal with data complexity, along with their dual role as producers and users of big data, impedes the institutionalization of this tool at the farm level. Although the approach used left us with more questions than answers, we suggest that unraveling the institutional arrangements that govern value co-creation, capturing the motivations of farmers and other actors, and detailing the direct and indirect effects that big data (and the technologies used to generate them) have in farms are important preconditions for setting forth rules that facilitate the extraction and equal exchange of value from big data.

A key challenge in agriculture, as in other disciplines, is taking a large body of research-based knowledge and making it meaningful to the user-audience. Computer aided search engines potentially can offer widespread access to large repositories with relevant reports and publications, however the usefulness of such systems for the practitioners who are dealing with multi-faceted and context-related issues is often limited. Building search engines with user-centered ontologies offer a means of resolving this as it provides a vocabulary common to different stakeholders and can optimise the interaction between practitioner users and the expert system.

The paper critically reflects on the methodology used to construct a user-centered ontology in the development of a search engine designed to help agricultural practitioners (farmers and advisers) find useful research outputs. This involved the iterative participation of domain experts, adviser practitioners and stakeholder communities in ten diverse case studies across Europe. Specifically it analyses the design, validation and evaluation phases of the ontology development drawing on qualitative data (reports, observations, interviews) from four case studies and asks: How effective is the process of co-constructing an ontology with experts, practitioners and other stakeholders in enabling the search for useful and meaningful knowledge? In doing this, it contributes to a deeper theoretical understanding of shared concepts and meanings in the context of digital communications in the agricultural arena by adapting Carlile’s (2004) framework of syntactic, semantic and pragmatic capacities.

Digital technologies are working to transform the global agricultural system. Farmers and firms are creating, adapting and adopting a range of new hardware, software, mobile apps, sensor technologies and big data applications, which is working to disrupt established structures within the farm machinery and associated data sectors. Focusing just on the extension of precision technologies to agriculture, this paper maps the competitive landscape using a 2 × 2 typology that situates entities operating in Canada based on their strategies, distinguishing between top-down and bottom-up networks of competitors and collaborators and the degree of interoperability of their digital applications. We examine the emergence of four specific cases in western Canadian agriculture. The typology and the cases suggest global agri-food firms, industry collectives and a host of entrepreneurial start-ups and small and medium-sized enterprises are competing to both organize and disrupt the global agri-food value chain. It is not yet clear which strategy, if any, will prevail and provide the model for broad acre agriculture in Canada and around the world.