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ONDRUŠKA, V. HOW, B. NETOLICKÝ, M. MÁŠA, V. TENG, S.
Original Title
Resource optimisation in aquaponics facility via process monitoring and graph-theoretical approach
Type
journal article in Scopus
Language
English
Original Abstract
Energy efficiency and economic viability are the often-quoted issues in aquaponic farming. This work aims to (i) identify process technologies and technical measures which would enhance the profitability of aquaponics business while conserving energy and other resources, and (ii) to validate the determined optimal measures on the testing aquaponics farm. The process network synthesis technique was used to search for an optimal process pathway while the image processing technique was applied to automatically monitor the growth rate of produce since it is the main revenue stream in aquaponics. With the aid of P-graph method, the optimal feasible structure has 9 times higher annual net income than that of the existing process. This optimal solution includes the integration of electrical heat pump, biogas system, and utilizes black solider fly (BSF) facility to produce fish feed. Additional light energy savings were achieved by practical installation of reflective foils which improved 16.88% of Photosynthetic photon flux density (PPFD) on growth beds. These measures can help the aquaponics farms to become more competitive and to decrease their ecological footprint.
Keywords
Aquaponics, Energy savings, P-graph, Process monitoring, Process optimization
Authors
ONDRUŠKA, V.; HOW, B.; NETOLICKÝ, M.; MÁŠA, V.; TENG, S.
Released
5. 12. 2022
Publisher
KeAi Publishing
Location
Beijing, China
ISBN
2588-9133
Periodical
Carbon Resources Conversion
Year of study
5
Number
4
State
People's Republic of China
Pages from
255
Pages to
270
Pages count
15
URL
https://www.sciencedirect.com/science/article/pii/S2588913322000187
BibTex
@article{BUT178613, author="Vojtěch {Ondruška} and Bing Shen {How} and Michal {Netolický} and Vítězslav {Máša} and Sin Yong {Teng}", title="Resource optimisation in aquaponics facility via process monitoring and graph-theoretical approach", journal="Carbon Resources Conversion", year="2022", volume="5", number="4", pages="255--270", doi="10.1016/j.crcon.2022.04.003", issn="2588-9133", url="https://www.sciencedirect.com/science/article/pii/S2588913322000187" }