A Decision Support System for Sustainable Agriculture: The Case Study of Coconut Oil Extraction Process

• Published in: Agronomy (Basel) 2022-01, Vol.12 (1), p.177
• Main Authors: Gagliardi, Gianfranco, Cosma, Antonio Igor Maria, Marasco, Francesco
• Format: Article
• Language: English
• Subjects: Agricultural economics; Agriculture; Agriculture 4.0; Artificial intelligence; Automation; Case studies; Coconut oil; Decision analysis; Decision making; decision support system; Decision support systems; Digital agriculture; Energy conservation; Fermentation; Industrial applications; Information systems; Integer programming; Internet of Things; Linear programming; Mixed integer; mixed integer linear programming; Reliability analysis; smart farming; Sustainable agriculture; sustainable farm
• ISSN: 2073-4395; 2073-4395
• DOI: 10.3390/agronomy12010177

The high demand of information and communication technology (ICT) in agriculture applications has led to the introduction of the concept of smart farming. In this respect, moving from the main features of the Fourth Industrial Revolution (Industry 4.0) promoted by the European Community, new approaches have been suggested and adopted in agriculture, giving rise to the so-called Agriculture 4.0. Improvements in automation, advanced information systems and Internet technologies allow for farmers to increase the productivity and to allocate the resources reasonably. For these reasons, agricultural decision support systems (DSS) for Agriculture 4.0 have become a very interesting research topic. DSS are interactive tools that enable users to make informed decisions about unstructured problems, and can be either fully computerized, human or a combination of both. In general, a DSS analyzes and synthesizes large amounts of data to assist in decision making. This paper presents an innovative decision support system solution to address the issues faced by coconut oil producers in making strategic decisions, particularly in the comparison of different methods of oil extraction. In more detail, the adopted methodology describes how to address the problems of coconut oil extraction in order to minimize the processing time and processing cost and to obtain energy savings. To this end, the coconut oil extraction process of the Leão São Tomé and Principe Company is presented as a case study: a DSS instance that analyzes the problem of the optimal selection between two different oil coconut extraction methods (fermentation-based and standard extraction processes) is developed as a meta-heuristics with a mixed integer linear programming problem. The obtained results show that there is clearly a trade-off between the increase in cost and reliability that the decision-maker may be willing to evaluate. In this respect, the proposed model provides a tool to support the decision-maker in choosing the best combination between the two different coconut oil extraction methods. The proposed DSS has been tested in a real application context through an experimental campaign.