Optimizing Mussel Production Systems: The Role of
Technological Tools Against Unpredictable External Conditions -
Abstract
Athanasios Ragkos 1, Dimitrios Skordos 1, Georgios Delis 2, Georgia Koutouzidou 3 and
Alexandros Theodoridis 2
1
  Agricultural Economics Research Institute, ELGO-DIMITRA, Kourtidou 56-58, 111 45 Athens, Greece
2
  School of Veterinary Medicine, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
3
  Institute of Plant Breeding and Genetic Resources, ELGO-DIMITRA, 570 01 Thessaloniki, Greece


                Summary 1
                Mussel production is an activity of specific importance of mainland coastal areas of Greece, as
                it is the source of supplementary (or main) incomes for fishermen. Previous research showed
                that the system involves a relatively small number of heterogeneous farms and producers, with
                different levels of entrepreneurial organization and production practices, which have an impact
                on their economic performance. However, a common external threat for mussel farms relates
                to unpredicted changes in environmental conditions. Since mussels are able to feed by
                absorbing nutrients from sea water, they also accumulate other substances in high
                concentrations, while they are also vulnerable to physiochemical changes (e.g. temperature and
                oxygen) in water. The presence of toxins in aquatic ecosystems, therefore, generates important
                threats for the viability of mussel production as well as for public health. Indeed, mussels are
                distributed for human consumption of after costly processing in sanitation facilities, while also
                they can be discarded – or even the production area can be put out of operation - if toxins are
                found in high concentrations. These destructive implications can be avoided if adverse
                environmental conditions are detected at a very early stage and mussels can thus be moved to
                another part of the sea rea, where conditions are better. SmartMussel project proposes a model
                of automated, remote-controlled management system for mussel farms, which uses probes of
                temperature, dissolved oxygen and conductivity associated with prediction software to
                demonstrate the potential need for mussel movement between marine areas. As part of
                SmartMussel project, this paper examines the potential socioeconomic effects of introducing
                and operation this automated system. In particular, the analysis is based on the development of
                a linear programming model, where three types of mussel farms (large size farms (LSF),
                medium size farms (MSF) and small size farms (SSF) according to the occupied surface area)
                are included as separate blocks of variables and constraints. Data for the analysis are derived
                from an on-site questionnaire survey of mussel farmers in the study area of Vistonikos Gulf
                (Eastern Macedonia, Greece), which were refined and calibrated based on additional survey
                data from Thermaikos Gulf (Central Macedonia, Greece). The results of the model indicate the
                optimal structure of the sector, which highlight how each farm type can be viable compared to
                other types. The optimized objective function (i.e., the total gross margin of mussel farms) is
                then used within a cost-benefit analysis framework, which is related to the number of possible
                outbreaks of adverse conditions that can lead to the destruction of production. Through this
                analysis, the mid-and long-term effects of using the automated systems are approached, thus
                demonstrating the necessity of introducing it and its usability in terms of risk management.
                Among other findings of the analysis, the contribution of the sector to employment and specific
                proposals for increasing the viability of each farm type are revealed.


Proceedings of HAICTA 2022, September 22–25, 2022, Athens, Greece
EMAIL: ragkos@agreri.gr (A. 1); dimitrisskor@gmail.com (A. 2); delis@vet.auth.gr (A. 3); koutouzidoug@gmail.com (A 4);
alextheod@vet.auth.gr (A. 5)
ORCID: 0000-0002-7247-6118 (A. 1); 0000-0001-7355-2074 (A. 2); 0000-0003-4900-8911 (A. 3); 0000-0002-6077-0504 (A. 4); 0000-
0001-8524-6218 (A. 5)
             ©️ 2022 Copyright for this paper by its authors.
             Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
             CEUR Workshop Proceedings (CEUR-WS.org)




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Keywords
Linear programming, cost-benefit analysis, risk management




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