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.

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

Economic, environmental and social sustainability is increasingly gaining the attention of academia and commitment in the policies of national economies. Global warming and climate change, weather disasters and disruptions are just some of the challenges that can drastically disrupt stable business models, and thus jeopardize sustainability. Agriculture, as an activity at the center of the value chain, is facing these problems, and, at the same time, contributes to feeding the growing world population and is responsible for conserving resources and ensuring sustainability. Process automation, data analysis and processing, control and management of agricultural operations have transformed the agricultural business and contributed to sustainability, survival and development within supply chains. This article analyzes the literature in the field of sustainability and agriculture led by digital technologies of Industry 4.0. The analysis of the research field showed the high importance of the topic in academic and national circles, given the number of published articles. Secondly, the concepts of sustainable agriculture and sustainability driven agriculture in the context of digital transformation were analyzed and it was shown that transformed agriculture can successfully cope with today’s challenges. Finally, guidelines for sustainable development driven by agriculture through the determinants of digital transformation are defined.

https://www.mdpi.com/2071-1050/12/20/8596/pdf

Sustainability Driven by Agriculture through Digital Transformation

A trans-theoretical model for the adoption of drones by large-scale German farmers

Exploring actors, their constellations, and roles in digital agricultural innovations

Most sub-Saharan Africa smallholder farming systems are highly heterogeneous Direct quantification of greenhouse gas emissions from these farming systems is hampered by diversity at farm-level Each farm contributes differently to greenhouse gas (GHG) emissions and consequently GHG inventories Typologies can be used as a mechanism of addressing farming systems’ heterogeneity by grouping them into specific farm types With the GHG quantification simplification initiatives in mind, we developed smallholder farm typologies based on soil fertility inputs We assessed nitrogen application rate, soil fertility management technologies and the socio-economic factors diversity among the farm typologies in the central highlands of Kenya We used data from a cross-sectional household survey with a sample size of 300 smallholder farmers We characterized the farm types using principal component analysis (PCA) To develop farm typologies, we subjected the PCA-derived typologies related factors to cluster analysis (CA) The results showed six farm types: Type 1, comprising cash crop and hybrid cattle farmers; Type 2, comprising food crop farmers; Type 3, composed of coffee-maize farmers; Type 4, comprising millet-livestock farmers; Type 5, comprising highly diversified farmers, and Type 6, comprising tobacco farmers Land size owned, total tropical livestock unit, the proportion of land and nitrogen applied to different cropping systems were significant in the construction of farm typologies Univariate analysis showed the household head's level of education, hired labour, group membership, access to extension services, and proportion of income from cropping activities as critical factors influencing farm typologies in the study area This study demonstrates the importance of smallholder farm typologies in identifying greenhouse gas emissions hotspots, designing quantification experiment and policy framing We concluded that policies and intervention measures targeting climate-smart agriculture at smallholder farms should consider not only farm-level soil fertility management technologies but also socio-economic characteristics that influence their adoption

Farming systems’ typologies analysis to inform agricultural greenhouse gas emissions potential from smallholder rain-fed farms in Kenya

Digitalisation in agriculture is considered the fourth revolution in farming, which is expressed by a broad range of available digital technologies and data applications. Politicians and experts assume that smart farming technologies (SFT) have a strong potential to enhance economic performance of farming and will contribute to agricultural sustainability as they may increase precision of inputs to crops and soils based on site-specific needs, and link these aspects to farm management systems. This paper explores farmers' and other stakeholders’ perceptions and attitudes towards SFT in Germany with a multi-actor approach. Quantitative and qualitative data show that while there are generally positive attitudes, farmers are less enthusiastic with regard to expected positive effects of SFT for the environment. Also, there is still a number of adoption barriers on the technology level as well as due to an unfavorable institutional and infrastructural environment. Although a multi-actor approach was practiced, close cooperation of practitioners with developers were not frequently observed nor could they be easily supported through action-research. Notwithstanding, through the multi-actor approach, a comprehensive situational picture of SFT appraisal was composed and, a general raise of awareness among the respective AKIS actors generated.

Klaus Erdle

Papers

Smart farming technology innovations – Insights and reflections from the German Smart-AKIS hub