The world is running out of healthy food where we are in need of nutritional security which is an existing threat with enormous climate change, land and water constraints, increase in urbanization, environmental degradation, changing income and diets where everyone is in need of positive health outcomes. Big data analytics has made such a widespread impact in the agriculture industry that it’s hard to pinpoint all its effects, and harder still to predict what changes it might bring. Big Data represents the information assets characterized by a high volume, velocity and variety to require specific technology and analytical methods for its transformation into value. 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.

We transform the huge amount of data into useful information to decision-makers. Applications can range from very different areas like food production to sustainability or climate change impact and it is expected to increase in future. Many treatments of this subject fail to describe why and how the concerned OR methods works effectively in the context of practice.

The scope of this special issue is to provide an overview of real applications of agro-Big Data in Agriculture or in the Agri-food industry supporting effectively decision-making processes. The issue is intended to capture findings on established and new methods - considering the fundamentals of the methodology as well as details achieved in applications.

The motivation behind this Agriculture Special Issue is to identify the key challenges that are faced by big data analysts trying to solve problems for agriculture communities, discuss potential solutions, and identify the opportunities emerging from cross-domain interactions among agriculture experts, hydrologists, dairy experts, aquaculture experts, and big data analytics experts. Therefore, we expect to gain from the domain experts an explanation of how they can apply big data analytics, semantic web standards, machine learning techniques, and linked data standards into their scientific research via high impact publications in this Special Issue.

Topics:

This Special Issue expects original and high quality submissions related (but not limited) to one or more of the following topics:

  • Modelling sensor data to get useful information
  • BigData techniques with potential application in agriculture
  • Sensor farms
  • Quality/Process control using sensors as indicator of produce quality
  • Successful application of DSS based on Big Data
  • Decision support tools based on GIS and their implications with BigData
  • Economic aspects of adoption of BigData analytics
  • Architecture for big data innovation in Agriculture
  • Big data innovation in agriculture
  • Performance evaluation of big data principles;
  • Environmental big data integration;
  • Smart farm and its application in big data;
  • Environmental big data
  • Data Analytics in Agriculture
  • Agricultural Data Visualization
  • Big data in agricultural disaster management;
  • Cloud based decision support system for plant diseases;
  • Environmental big data and knowledge management;
  • Real time and big data.

Important dates:

  • Submission: June 30, 2020
  • Author notification: July 30, 2020 
  • Revised papers: September 30, 2020 
  • Final decision: October 15, 2020 
  • Camera Ready papers due: November 30, 2020 
  • Publication: December 15, 2020 

Submission guidelines:

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found at: 

http://www.scpe.org/index.php/scpe/about/submissions#authorGuidelines

Special issue editors:

  • Rajasekaran Rajkumar, Vellore Institute of Technology, India
  • Jolly Masih, Erasmus School of Economics, Rotterdam, Netherlands