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.

You can access and play with the graphs:

Discover all records
Home page

Title

Estimation of neural network parameters for wheat yield prediction

en
Abstract

Precision agriculture (PA) and information technology (IT) are closely interwoven. The former usually refers to the application of nowadays' technology to agriculture. Due to the use of sensors and GPS technology, in today's agriculture many data are collected. Making use of those data via IT often leads to dramatic improvements in efficiency. For this purpose, the challenge is to change these raw data into useful information. This paper deals with suitable modeling techniques for those agricultural data where the objective is to uncover the existing, patterns. In particular, the use of feed-forward backpropagation neural networks will be evaluated and suitable parameters will be estimated. In consequence, yield prediction is enabled based oil cheaply available site data. Based on this prediction, economic or environmental optimization of, e.g., fertilization call be carried out.

en
Year
2008
en
Country
  • DE
Organization
  • Univ_Halle_Wittenberg (DE)
  • Otto_Von_Guericke_Univ_Magdeburg (DE)
Data keywords
  • information technology
en
Agriculture keywords
  • agriculture
en
Data topic
  • modeling
  • sensors
en
SO
ARTIFICIAL INTELLIGENCE IN THEORY AND PRACTICE II
Document type

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

Institutions 10 co-publis
    uid:/JTXRV0H3
    Powered by Lodex 8.20.3
    logo commission europeenne
    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.