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

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TLDR
In this paper, the authors present seventeen articles dealing with social, economic and institutional dynamics of precision farming, digital agriculture, smart farming or agriculture 4.0, and reveal 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.
Abstract
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.

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Minimum temperature mapping augments Australian grain farmers’ knowledge of frost

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Care in dairy farming with automatic milking systems, identified using an Activity Theory lens

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Blockchain technologies for sustainability in the agrifood sector: A literature review of academic research and business perspectives

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Computational Thinking and STEM in Agriculture Vocational Training: A Case Study in a Greek Vocational Education Institution.

TL;DR: The present case study aims to explore the relation between CT, STEM and agricultural education training (AET) in a Greek vocational training institute (IEk), the Agriculture IEK of Metamorfosis city (IEKMC), which is active in agriculture education.
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Can Digitalization Levels Affect Agricultural Total Factor Productivity? Evidence From China

TL;DR: Wang et al. as mentioned in this paper used digital technology as a keyword to construct a regional digitalization level indicator and found that digitalization can significantly raise agricultural total factor productivity in economically underdeveloped areas but not in economically developed areas.
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