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Sjaak Wolfert

Bio: Sjaak Wolfert is an academic researcher from Wageningen University and Research Centre. The author has contributed to research in topics: The Internet & Supply chain. The author has an hindex of 12, co-authored 19 publications receiving 1507 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors present a review of the state-of-the-art of Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed.

1,477 citations

Journal ArticleDOI
TL;DR: This work has specified a farm management system that takes advantage of the new characteristics that ''Future Internet'' offers in terms of generic software modules that can be used to build farming related specialized modules.

203 citations

Journal ArticleDOI
TL;DR: The concept of Digital Twin is defined, a typology of different types of Digital Twins is developed, and a conceptual framework for designing and implementing Digital Twin systems based on the Internet of Things—Architecture (IoT-A), a reference architecture for IoT systems are proposed.

179 citations

Journal ArticleDOI
TL;DR: The implementation of an innovative cloud based Farm Management System that provides a framework that allows the interconnection among services developed by different service providers is provided, based on a set of domain independent software tools called "generic enablers" that have been developed in the context of the FI-WARE project.

132 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a review of the literature that concerns the ethical challenges that smart farming raises and suggest that future research should focus first on the content of these goals, especially on the contents of societal and commercial goals and whether and how they can be combined in differing contexts.
Abstract: Sensors, drones, weather satellites and robots are examples of technologies that make farming ‘smart’. In this article we present the results of our review of the literature that concerns the ethical challenges that smart farming raises. Our reading suggests that current ethical discussion about smart farming circles around three themes: (1) data ownership and access, (2) distribution of power and (3) impacts on human life and society. Discussions that fall under these themes have however not yet reached a satisfying conclusion, as there seem to be different ideas at work in the background regarding the purpose and function of digital farms in society. The pros and cons of these rivalling ideas are rarely foregrounded in the discussion. We suggest that future research should focus first on the content of these goals, especially on the content of societal and commercial goals and whether and how they can be combined in differing contexts. This will offer a lead to think about what data ought to be shared with whom, to set preconditions for trust between stakeholders and –eventually- develop appropriate guidelines and codes of conduct for future farming digitalization trajectories.

95 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, the authors present a review of the state-of-the-art of Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed.

1,477 citations

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.

814 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present the agronomical variables and plant traits that can be estimated by remote sensing, and describe the empirical and deterministic approaches to retrieve them, and 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.

631 citations

Journal ArticleDOI
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.

573 citations

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.

547 citations