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Journal ArticleDOI

Big Data in Smart Farming – A review

01 May 2017-Agricultural Systems (Elsevier)-Vol. 153, pp 69-80

Abstract: Smart Farming is a development that emphasizes the use of information and communication technology in the cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing are expected to leverage this development and introduce more robots and artificial intelligence in farming. This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Following a structured approach, a conceptual framework for analysis was developed that can also be used for future studies on this topic. The review shows that the scope of Big Data applications in Smart Farming goes beyond primary production; it is influencing the entire food supply chain. Big data are being used to provide predictive insights in farming operations, drive real-time operational decisions, and redesign business processes for game-changing business models. Several authors therefore suggest that Big Data will cause major shifts in roles and power relations among different players in current food supply chain networks. The landscape of stakeholders exhibits an interesting game between powerful tech companies, venture capitalists and often small start-ups and new entrants. At the same time there are several public institutions that publish open data, under the condition that the privacy of persons must be guaranteed. The future of Smart Farming may unravel in a continuum of two extreme scenarios: 1) closed, proprietary systems in which the farmer is part of a highly integrated food supply chain or 2) open, collaborative systems in which the farmer and every other stakeholder in the chain network is flexible in choosing business partners as well for the technology as for the food production side. The further development of data and application infrastructures (platforms and standards) and their institutional embedment will play a crucial role in the battle between these scenarios. From a socio-economic perspective, the authors propose to give research priority to organizational issues concerning governance issues and suitable business models for data sharing in different supply chain scenarios.
Topics: Big data (58%), Supply chain (57%), Business model (55%), Business process (53%), Data sharing (53%)
Citations
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Journal ArticleDOI
TL;DR: The IoT ecosystem is presented and how the combination of IoT and DA is enabling smart agriculture, and future trends and opportunities are provided which are categorized into technological innovations, application scenarios, business, and marketability.
Abstract: The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of Internet of Things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the agriculture sector. There is a paradigm shift from use of wireless sensor network (WSN) as a major driver of smart agriculture to the use of IoT and DA. The IoT integrates several existing technologies, such as WSN, radio frequency identification, cloud computing, middleware systems, and end-user applications. In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. Furthermore, we provide future trends and opportunities which are categorized into technological innovations, application scenarios, business, and marketability.

420 citations


Cites background from "Big Data in Smart Farming – A revie..."

  • ...The complexity of the data can range from structured to nonstructured data [11], [34] which can be in the form of text, images, audio, and video....

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  • ...The use of IoT and DA will enable smart agriculture which is expected to deliver high operational efficiency and high yield [11], [12]....

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Journal ArticleDOI
TL;DR: A review of current studies and research works in agriculture which employ the recent practice of big data analysis, showing that the availability of hardware and software, techniques and methods for big dataAnalysis, as well as the increasing openness ofbig data sources, shall encourage more academic research, public sector initiatives and business ventures in the agricultural sector.
Abstract: Survey on the practice of big data analysis in agriculture.Detailed review of 34 high-impact relevant research studies.Discussion on the status and potential of big data analysis in agriculture.Open problems and challenges, barriers for wider adoption and use.Ways to overcome barriers and potential future applications in agriculture. To tackle the increasing challenges of agricultural production, the complex agricultural ecosystems need to be better understood. This can happen by means of modern digital technologies that monitor continuously the physical environment, producing large quantities of data in an unprecedented pace. The analysis of this (big) data would enable farmers and companies to extract value from it, improving their productivity. Although big data analysis is leading to advances in various industries, it has not yet been widely applied in agriculture. The objective of this paper is to perform a review on current studies and research works in agriculture which employ the recent practice of big data analysis, in order to solve various relevant problems. Thirty-four different studies are presented, examining the problem they address, the proposed solution, tools, algorithms and data used, nature and dimensions of big data employed, scale of use as well as overall impact. Concluding, our review highlights the large opportunities of big data analysis in agriculture towards smarter farming, showing that the availability of hardware and software, techniques and methods for big data analysis, as well as the increasing openness of big data sources, shall encourage more academic research, public sector initiatives and business ventures in the agricultural sector. This practice is still at an early development stage and many barriers need to be overcome.

335 citations


Journal ArticleDOI
TL;DR: This editorial reviews key insights from the literature on digital infrastructures and platforms, present emerging research themes, highlight the contributions developed from each of the six articles in this special issue, and conclude with suggestions for further research.
Abstract: In the last few years, leading-edge research from information systems, strategic management, and economics have separately informed our understanding of platforms and infrastructures in the digital age. Our motivation for undertaking this special issue rests in the conviction that it is significant to discuss platforms and infrastructures concomitantly, while enabling knowledge from diverse disciplines to cross-pollinate to address critical, pressing policy challenges and inform strategic thinking across both social and business spheres. In this editorial, we review key insights from the literature on digital infrastructures and platforms, present emerging research themes, highlight the contributions developed from each of the six articles in this special issue, and conclude with suggestions for further research.

248 citations


Cites background from "Big Data in Smart Farming – A revie..."

  • ...markets, to selling insurance, and even informing commodities trading decisions (Wolfert et al. 2017)....

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  • ...Uses range from powering seasonal labor markets, to selling insurance, and even informing commodities trading decisions (Wolfert et al. 2017)....

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Journal ArticleDOI
Abstract: Agriculture provides humanity with food, fibers, fuel, and raw materials that are paramount for human livelihood. Today, this role must be satisfied within a context of environmental sustainability and climate change, combined with an unprecedented and still-expanding human population size, while maintaining the viability of agricultural activities to ensure both subsistence and livelihoods. Remote sensing has the capacity to assist the adaptive evolution of agricultural practices in order to face this major challenge, by providing repetitive information on crop status throughout the season at different scales and for different actors. We start this review by making an overview of the current remote sensing techniques relevant for the agricultural context. We present the agronomical variables and plant traits that can be estimated by remote sensing, and we describe the empirical and deterministic approaches to retrieve them. A second part of this review illustrates recent research developments that permit to strengthen applicative capabilities in remote sensing according to specific requirements for different types of stakeholders. Such agricultural applications include crop breeding, agricultural land use monitoring, crop yield forecasting, as well as ecosystem services in relation to soil and water resources or biodiversity loss. Finally, we provide a synthesis of the emerging opportunities that should strengthen the role of remote sensing in providing operational, efficient and long-term services for agricultural applications.

231 citations


Journal ArticleDOI
Samiran Banerjee, Florian Walder, Lucie Büchi1, Marcel Meyer  +6 moreInstitutions (5)
08 Mar 2019-The ISME Journal
TL;DR: It is demonstrated that agricultural intensification reduces network complexity and the abundance of keystone taxa in the root microbiome, and this is the first study to report mycorrhizal keystoneTaxa for agroecosystems.
Abstract: Root-associated microbes play a key role in plant performance and productivity, making them important players in agroecosystems. So far, very few studies have assessed the impact of different farming systems on the root microbiota and it is still unclear whether agricultural intensification influences the structure and complexity of microbial communities. We investigated the impact of conventional, no-till, and organic farming on wheat root fungal communities using PacBio SMRT sequencing on samples collected from 60 farmlands in Switzerland. Organic farming harbored a much more complex fungal network with significantly higher connectivity than conventional and no-till farming systems. The abundance of keystone taxa was the highest under organic farming where agricultural intensification was the lowest. We also found a strong negative association (R2 = 0.366; P < 0.0001) between agricultural intensification and root fungal network connectivity. The occurrence of keystone taxa was best explained by soil phosphorus levels, bulk density, pH, and mycorrhizal colonization. The majority of keystone taxa are known to form arbuscular mycorrhizal associations with plants and belong to the orders Glomerales, Paraglomerales, and Diversisporales. Supporting this, the abundance of mycorrhizal fungi in roots and soils was also significantly higher under organic farming. To our knowledge, this is the first study to report mycorrhizal keystone taxa for agroecosystems, and we demonstrate that agricultural intensification reduces network complexity and the abundance of keystone taxa in the root microbiome.

229 citations


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Posted Content
Abstract: This book brings together in one place the work of one of our most respected economic theorists, on a field which he has played a large part in originating: the New Institutional Economics. Transaction cost economics, which studies the governance of contractual relations, is the branch of the New Institutional Economics with which Oliver Williamson is especially associated. Transaction cost economics takes issue with one of the fundamental building blocks in microeconomics: the theory of the firm. Whereas orthodox economics describes the firm in technological terms, as a production function, transaction cost economics describes the firm in organizational terms, as a governance structure. Alternative feasible forms of organization--firms, markets, hybrids, bureaus--are examined comparatively. The analytical action resides in the details of transactions and the mechanisms of governance. Transaction cost economics has had a pervasive influence on current economic thought about how and why institutions function as they do, and it has become a practical framework for research in organizations by representatives of a variety of disciplines. Through a transaction cost analysis, The Mechanisms of Governance shows how and why simple contracts give way to complex contracts and internal organization as the hazards of contracting build up. That complicates the study of economic organization, but a richer and more relevant theory of organization is the result. Many testable implications and lessons for public policy accrue to this framework. Applications of both kinds are numerous and growing. Written by one of the leading economic theorists of our time, The Mechanisms of Governance is sure to be an important work for years to come. It will be of interest to scholars and students of economics, organization, management, and law.

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Performance
Metrics
No. of citations received by the Paper in previous years
YearCitations
202218
2021297
2020269
2019218
2018118
201724