25-27 September, 2019, Valparaíso, Chile (http://www.bigdssagro2019.usm.cl)

Important dates:
Submission start: April 1, 2019.
Submission deadline: May 20, 2019.
Author acceptance/rejection notification: July 15, 2019.
Camera-ready Extended Abstract deadlines: August 15, 2019.

We are very happy to communicate that extended and revised papers of accepted contributions will be invited for submission in a special issue of International Transactions in Operational Research, to be announced soon.
The BigDSSAgro2019 conference is the third conference in the series devoted to decision support systems in agriculture, which combine Operational Research methods and Big Data techniques to support many real-world decision-making problems in small scale farming, industrial agriculture, smart farms, agri-business supply chains, land use and environmental protection, among others. In BigDSSAgro 2019, the scope will be extended to focus on decisions, technologies and innovation for the 2030 agriculture.

Authors are invited to submit extended abstracts of their recent work by May 20, 2019. See the submissions guidelines for more information in the conference web page. The Program Committee will select the papers to be presented on the basis of the submitted extended abstracts. It is expected that revised and extended versions will subsequently be submitted for publication in a post-conference special issue to be announced. The list of topics in which we invite submissions include, but are not limited to the following main areas:
-Operational research methods relevant to agriculture, forestry and environment.
-Sustainability indicators in agriculture and environment.
-Modelling sensor based data to get useful information.
-Big Data techniques with potential applications in agriculture.
-Optimization and simulation models, including agent based simulation.
-Decision support tools based on Big Data and Operational research techniques.
-Decision support tools based on GIS and their implications with Big Data.
-Economic aspects of adoption of Big Data analytics.
-Machine learning.
-Support Vector machine.
-Precision agriculture, digital agriculture.
-Industrial agriculture.
-Small scale farming.
-Agri-business supply chain.
-Forestry.
-Land Use.
-Environment studies and environmental protection.