Big Data Analytics and Decision Support for Sustainable Agriculture and Food Safety
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Agriculture".
Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 1669
Special Issue Editors
Interests: big data; agreement measures between evaluators; generalized linear models in health economics; structural equation models; generalized propensity scores for impact assessments
Special Issues, Collections and Topics in MDPI journals
Interests: blockchain technology; innovation; agriculture; supply chain; food and beverage; sustainability
Special Issues, Collections and Topics in MDPI journals
Interests: statistical learning; text mining; natural language processing; machine learning; opinion mining; learning analytics; deep learning; big data
Special Issues, Collections and Topics in MDPI journals
Interests: blockchain technology; network security; artificial intelligence; machine learning; data management; data processing; big data systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Big data is currently of great interest in data science, involving a wide range of disciplines, particularly those focused on new technologies (Kambatla et al., 2014). In this Special Issue, therefore, we would like to address not only the issues concerning the collection, analysis and dissemination of large amounts of data but also their organization, storage, dissemination, protection and non-manipulation. It is also of great scientific interest to know what the most effective strategies are for making this incredible amount of information work for the benefit of society, the economy, academia and political governments. In particular, documents concerning sustainability and agriculture, amongst others, will be taken into consideration (Columbus, 2018).
Indeed, sustainable development is the main concern of modern society (Van Gorp & van der Goot, 2012) and is significantly affected by the goal of agriculture in seeking to guarantee food security for the ever increasing population (Galati et al., 2022; Delgado et al., 2019). In this scenario, the adoption of emerging technologies plays a crucial role (Adamashvili et al., 2020). Particularly, digital innovations that help farmers to make informed decisions by collecting huge amount of data and transforming them into useful information will allow facing global challenges such as climate change, resource depletion, landscape problems and, consequently, a loss of productivity (Delgado et al., 2019).
Therefore, this Special Issue aims to collect articles regarding the latest developments in big data analysis tools. Particular attention will be given to scientific research regarding digital innovations; decision support systems in agricultural practices; how to solve the problems of sustainable agriculture and food production; studying the application of big data analysis tools, decision support systems and other emerging technologies in agricultural practices for obtaining maximum process efficiency; high accessibility to vast data and their practical use toward achieving transparency of the value chain.
Suitable topics include, but are not limited to, the following:
- Artificial intelligence applied in agriculture
- Big data processing techniques
- Visualization and design principles of big data infrastructures
- Blockchain technology in agriculture
- Data acquisition, cleaning, distribution and best practices for big data
- Data mining in agriculture
- Data protection, privacy and policy
- Evaluation of metrics and decision-making processes
- New technologies developed specifically for big data
- New algorithms for decision support systems
- Big data opportunities and how companies can use them to their advantage
- Physical and robotic interfaces
- Food traceability system
- Food additives, pesticide residues and food contamination
- Food marketing
- Food processing
- Post-harvest management
- Loss and waste of food
- Supply of quality food
- Soil and water management
- Sustainable agriculture and interactions with the environment
- Sustainable business model
- Climate change and sustainable agriculture
- Culture, society and sustainable agriculture
- Adamashvili, N., Fiore, M., Contò, F., & La Sala, P. (2020). Ecosystem for successful agriculture. collaborative approach as a driver for agricultural development. European Countryside, 12(2), 242-256. doi:10.2478/euco-2020-0014.
- Columbus, L. (2018, May 23). 10 charts that will change your perspective of big data’s growth. Forbes.
- Delgado, J.A., Short, N.M. Jr., Roberts, D.P., & Vandenberg, B. (2019). Big Data Analysis for Sustainable Agriculture on a Geospatial Cloud Framework. Front. Sustain. Food Syst. 3(54). doi: 10.3389/fsufs.2019.00054
- Galati, A., Migliore, G., Thrassou, A., Schifani, G., Rizzo, G., Adamashvili, N., & Crescimanno, M. (2022). Consumers’ willingness to pay for agri-food products delivered with electric vehicles in the short supply chains. FIIB Business Review, doi:10.1177/23197145221112743
- Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014, February 2). Trends in big data anaylytics. Software Engineering Research Group| supervised by Dr. Jeff Lei.
- Van Gorp, B. van der Goot, M.J. (2012). Sustainable Food and Agriculture: Stakeholder's Frames. Communication, Culture and Critique 5(2), 127–148, https://doi.org/10.1111/j.1753-9137.2012.01135.x
Dr. Alessia Spada
Dr. Nino Adamashvili
Dr. Emiliano Del Gobbo
Prof. Dr. Radu State
Guest Editors
Manuscript Submission Information
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Keywords
- algorithm
- Big Table
- cloud
- Distributed File System
- data scientist
- MapReduce
- Natural Language Processing NoSQL
- predictive analytics
- structured vs unstructured data
- emerging technologies
- big data analytics
- decision support systems
- sustainable development
- sustainable agriculture
- climate change
- resource depletion
- resource management
- environmental degradation
- food security and safety
