Traceability system for quality monitoring in the fishery and aquaculture value chain

Oliveira, José Geraldo de; Lima, José Evaristo; Silva, Dimitri da; Kuprych, Volodymyr; Faria, Pedro Miguel; Teixeira, Cláudio; Cruz, Estrela Ferreira; Cruz, António Miguel Rosado da

doi:10.1016/j.jafr.2021.100169

Cited by 17 publications

(19 citation statements)

References 8 publications

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“…This study entails the development of an integrated information system that leverages contemporary software architecture, namely microservices architecture, which has been implemented in various types of systems, including land administration systems, 40 greenhouse systems, 41 aquaculture value chain traceability systems, 42 energy management systems, [43][44][45][46][47] smart distribution transformer area, 48 control system, 49 groundwater management system, 50 smart water usage, 51 F I G U R E A5 IoT application UI screenshots.…”

Section: Discussionmentioning

confidence: 99%

“…This study entails the development of an integrated information system that leverages contemporary software architecture, namely microservices architecture, which has been implemented in various types of systems, including land administration systems, 40 greenhouse systems, 41 aquaculture value chain traceability systems, 42 energy management systems, 43–47 smart distribution transformer area, 48 control system, 49 groundwater management system, 50 smart water usage, 51 by utilizing the semantic web and internet of things (IoT) technologies. The designed Hazelnut Classification System (HDS) addresses the categorization of 18 Turkish hazelnut cultivars, offering comprehensive information tailored to diverse stakeholder needs.…”

Section: Discussionmentioning

confidence: 99%

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Microservices‐based databank for Turkish hazelnut cultivars using IoT and semantic web technologies

Aydin,

Aldara

2024

Concurrency and Computation

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SummaryInformation and communication technologies (ICTs) can play a crucial role in facilitating access to comprehensive information on the quality standards of Turkish hazelnut cultivars. In this regard, this study introduces a Hazelnut Databank System (HDS) that utilizes the microservices architecture, an integrated software system supported by the Internet of Things (IoT) and semantic web, to categorize Turkish hazelnut cultivars. The study focuses on developing microservices using various programming languages and frameworks. Specifically, C# on the .NET Core Framework was used for both microservices and the web‐based application implemented through the ASP.NET Core MVC Framework. Mobile‐based software applications were created using Xamarin. Forms, and the IoT application was developed using the Python programming language. The data storage is facilitated through the MS SQL Server database. Additionally, the study incorporates the implementation of a hazelnut species classification system using the DNN + ResNet50 machine learning model, achieving an impressive accuracy rate of 95.77%. The overall usability of the system was evaluated, resulting in a score of 42 out of 50. By providing detailed information on Turkish hazelnut cultivars, the HDS has the potential to greatly improve hazelnut production quality in Turkey and increase awareness of hazelnut agriculture among relevant stakeholders.

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Section: Discussionmentioning

confidence: 99%

“…This study entails the development of an integrated information system that leverages contemporary software architecture, namely microservices architecture, which has been implemented in various types of systems, including land administration systems, 40 greenhouse systems, 41 aquaculture value chain traceability systems, 42 energy management systems, 43–47 smart distribution transformer area, 48 control system, 49 groundwater management system, 50 smart water usage, 51 by utilizing the semantic web and internet of things (IoT) technologies. The designed Hazelnut Classification System (HDS) addresses the categorization of 18 Turkish hazelnut cultivars, offering comprehensive information tailored to diverse stakeholder needs.…”

Section: Discussionmentioning

confidence: 99%

Microservices‐based databank for Turkish hazelnut cultivars using IoT and semantic web technologies

Aydin,

Aldara

2024

Concurrency and Computation

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“…A wider study of the Bangladesh shrimp FSC could seek to understand the roles these other actors play in internal and external traceability systems, even though they are not part of the formal value chain (i.e. not performing any activities that add value to the product) (ISO, 2011;Oliveira et al, 2021). Another important research scope would be to use the proposed method for different case studies e.g.…”

Section: Discussionmentioning

confidence: 99%

Systematic assessment of food traceability information loss: A case study of the Bangladesh export shrimp supply chain

2022

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“…Unfortunately, capture production from the wild has remained static for more than 40 years (Oliveira et al, 2021). An alternative means of production is therefore required to meet the demand.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Diluted Doses of GnRHa (Ovulin) Supplemented with Buserelin Acetate- GnRHa (Suprecur) on Final Ova Maturation and Breeding of the African Catfish (Clarias gariepinus)

Ataguba,

Kwala,

Abum

2023

Aquatic Science and Fish Resources (ASFR)

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Studies have shown that Ovulin® is a cost-effective hormone for inducing final oocyte maturation (FOM) in Clarias gariepinus, and further studies have shown that dilution of the hormone can also be effective. This study was designed to investigate the spawning response of C. gariepinus, with an average weight of 1110.0±91.2g, by the induction method utilising serially diluted Ovulin® combined with buserelin acetate (Suprecur®), a gonadotropin hormone-releasing hormone analogue (GnRHa). Treatments administered include 0.5ml/kg Ovulin® (T1), 0.4ml/kg Ovulin® + 32µg/kg Suprecur® (T2), 0.3ml/kg Ovulin + 32µg/kg Suprecur® (T3), 0.2ml/kg Ovulin® + 32µg/kg Suprecur® (T4) and 32µg/kg Suprecur® (T5) + 5mg/kg Domperidone®. We determined the fecundity (absolute egg numbers), latency period, fertilisation rate, hatching rates, and survival (post-yolk absorption stage) in eachtreatment. The results demonstrated that diluted Ovulin® + Suprecur® together successfully induced ovulation in the experimental C. gariepinus broodfish. There was no significant difference (p>0.05) in egg weights stripped from each treated group. The application of 0.5ml/kg Ovulin®, 0.3ml/kg Ovulin® + 32 µg/kg of Suprecur® and 0.2ml/kg Ovulin® + 32 µg/kg of Suprecur® resulted in a Latency period of 12 hours compared to 11 hours for the other treatments. Results of the fertilisation percentage indicated that hormone administration did not significantly affect the fertilisation rate (p>0.05). Similarly, the hatching rate was not dependent onhormone administration (p>0.05). Also, hormonal administration to female broodstock did not affect fry survival rate to first feeding (p>0.05).

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Traceability system for quality monitoring in the fishery and aquaculture value chain

Cited by 17 publications

References 8 publications

Microservices‐based databank for Turkish hazelnut cultivars using IoT and semantic web technologies

Microservices‐based databank for Turkish hazelnut cultivars using IoT and semantic web technologies

Systematic assessment of food traceability information loss: A case study of the Bangladesh export shrimp supply chain

The Effect of Diluted Doses of GnRHa (Ovulin) Supplemented with Buserelin Acetate- GnRHa (Suprecur) on Final Ova Maturation and Breeding of the African Catfish (Clarias gariepinus)

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