e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application


Field experiments using precision farming technology and Geographic Information Systems, following a so-called Precision Experimental Design, were conducted in maize, winter barley and winter wheat and compared with two randomised plot experiments in maize to quantify yield effects attributed to weed competition and weed control. Fields were divided into cells, and weed densities for all weed species, soil conductivity and grain yield were measured in each cell. Untreated plots and herbicide treatments against grass weeds or broad-leaved weeds were included in all three experiments. Chenopodium album, Polygonum spp. and Echinochloa crus-galli were the dominating weed species in maize. Stellaria media, Veronica hederifolia, Matricaria chamomilla, Alopecurus myosuroides and Galium aparine were the most abundant weed species in the winter barley and winter wheat fields. All species were distributed heterogeneously within the fields with densities ranging from 0 to more than 200 plants m-2. In the Precision Experimental Design, it was found that grass-weed competition and herbicide application had a significant effect on grain yield, using a linear mixed model with spatial correlation structure to determine the effects of groups of weed species, soil variability and herbicide application on grain yield separately. When a conventional plot experiment was set up in the same field, no statistically significant grain yield difference between the treatments was found. The results highlight the benefits of Precision Experimental Design for studying weedcrop competition. Data can be used to calculate yield loss functions for groups of weed species and to create a decision_support system for site-specific weed control.

  • DE
  • Univ_Hohenheim (DE)
Data keywords
  • information system
Agriculture keywords
  • farming
Data topic
  • information systems
  • modeling
  • sensors
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Univ_Hohenheim (DE)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.