Artificial intelligence–based method for the rapid detection of fish parasites (Ichthyophthirius multifiliis, Gyrodactylus kobayashii, and Argulus japonicus)

Li, Jiadong; Lian, Zirui; Wu, Zhelin; Zeng, Lihua; Mu, Liangliang; Yuan, Y.; Bai, Hao; Guo, Zheng; Mai, Kangsen; Xiao, Tiaojun; Ye, Jianmin

doi:10.1016/j.aquaculture.2022.738790

Cited by 7 publications

(6 citation statements)

References 34 publications

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“…Such high accuracy means that we can identify the sex of fish using our model rather than dissection. Moreover, considering artificial intelligence has been applied to fish management and parasite detection in aquaculture [52][53][54], to improve the efficiency of practical applications, it is also necessary to introduce computer programs to calculate the values of Y 1 and Y 2 and to try to automatically measure the morphological traits of fish photos and automatically convert data through artificial intelligence, which will greatly improve the efficiency of our model.…”

Section: Discussionmentioning

confidence: 99%

Sexual Dimorphism and Discrimination of Barbel Steed (Hemibarbus labeo) in the Jinhe River, China: An Indicator of Habitat Status

Tuo

Xiao

et al. 2023

Sustainability

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Sex identification is linked to sexual dimorphism and is an important study issue in fish biology and aquaculture. However, owing to the unmarked sexual heteromorphism between adult Hemibarbus labeo, it is often difficult to distinguish their sex by visual observation. This study aimed to find a simple and reliable morphometric criterion for the sex identification of H. labeo using discriminant models. Forty-two morphometric traits of sixty-eight H. labeo individuals collected from the Jinhe River were measured, and 41 standardized features were calculated and analyzed. Eight trait variables from 41 standardized attributes were screened using stepwise discriminant analysis. The total classification accuracy of the model was 95.59%. Twelve standardized features significantly differed between male and female H. labeo individuals (p < 0.05). The condition factor, body height, dorsal fin coxal length, the distance between the pelvic and anal fins, and body length were significantly greater in females than in males (p < 0.05), suggesting that females of H. labeo in the Jinhe River were plumper than males, with a larger body size, but a smaller caudal peduncle. These results implied that the sex identification of H. labeo can be performed using the discriminant equation established in this study. This study provides a theoretical basis for endangered fish species protection and their artificial propagation.

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Section: Discussionmentioning

confidence: 99%

Sexual Dimorphism and Discrimination of Barbel Steed (Hemibarbus labeo) in the Jinhe River, China: An Indicator of Habitat Status

Tuo

Xiao

et al. 2023

Sustainability

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“…The SQLite database can be connected to standalone applications, as the PyQt GUI library is a tool for creating graphical interfaces with Python to use them beyond the world wide web. The latter is very popular and is applied in many research projects [14][15][16].…”

Section: Methodsmentioning

confidence: 99%

Natural Language Processing and Fiction Text: Basis for Corpus Research

Gorozhanov,

Guseynova,

Stepanova

2024

Vestn. Ross. univ. družby nar., Ser. Teor. âzyka semiot. semant

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The study deals with NLP procedures on the material of the fiction texts in German and in English, which are considered as strong cultural texts. The aim of the study is to develop a model of such a technical device to process, analyze and interpret a fiction text, which would reveal the full potential of popular NLP tools within the corpus approach. The general methods used in the study are analysis and synthesis. Special methods are additionally used to solve certain specific issues: descriptive method, modelling and qualitative and quantitative analysis. The scientific novelty lies in the fact that the authors apply the crucial principles of the classical theories of text interpretation according to the latest methods and tools of the applied linguistics. As a practical result, special software has been developed, which is able to process SQL based linguistic corpora, automatically built with spaCy NLP library and Python programming language. This software can be used for a fiction text interpretation, as well as for compiling learning materials in Home Reading. It is assumed that the development of special software for strong cultural texts stimulates the search for scientific solutions and at the same time allows one to understand the essential differences that exist between natural and artificial intelligence.

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“…deep learning) have been successfully used in various fields of parasitology including parasitic disease diagnostics as well as parasite and vector species identification (Dantas‐Torres, 2023 ). AI‐based algorithms in image or video processing are useful tools for parasite species identification and infection level assessment in parasitic disease examinations (Li et al., 2023 ; Wąsikowska et al., 2018 ; Wąsikowska & Linowska, 2021 ).…”

Section: Assessmentmentioning

confidence: 99%

Re‐evaluation of certain aspects of the EFSA Scientific Opinion of April 2010 on risk assessment of parasites in fishery products, based on new scientific data. Part 1: ToRs1–3

Koutsoumanis,

Allende,

Alvarez‐Ordóñez

et al. 2024

EFS2

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Surveillance data published since 2010, although limited, showed that there is no evidence of zoonotic parasite infection in market quality Atlantic salmon, marine rainbow trout, gilthead seabream, turbot, meagre, Atlantic halibut, common carp and European catfish. No studies were found for greater amberjack, brown trout, African catfish, European eel and pikeperch. Anisakis pegreffii, A. simplex (s. s.) and Cryptocotyle lingua were found in European seabass, Atlantic bluefin tuna and/or cod, and Pseudamphistomum truncatum and Paracoenogonimus ovatus in tench, produced in open offshore cages or flow-through ponds or tanks. It is almost certain that fish produced in closed recirculating aquaculture systems (RAS) or flowthrough facilities with filtered water intake and exclusively fed heat-treated feed are free of zoonotic parasites. Since the last EFSA opinion, the UV-press and artificial digestion methods have been developed into ISO standards to detect parasites in fish, while new UV-scanning, optical, molecular and OMICs technologies and methodologies have been developed for the detection, visualisation, isolation and/or identification of zoonotic parasites in fish. Freezing and heating continue to be the most efficient methods to kill parasites in fishery products. High-pressure processing may be suitable for some specific products. Pulsed electric field is a promising technology although further development is needed. Ultrasound treatments were not effective. Traditional dry salting of anchovies successfully inactivated Anisakis. Studies on other traditional processes -air-drying and double salting (brine salting plus dry salting) -suggest that anisakids are successfully inactivated, but more data covering these and other parasites in more fish species and products is required to determine if these processes are always effective. Marinade combinations with anchovies have not effectively inactivated anisakids. Natural products, essential oils and plant extracts, may kill parasites but safety and organoleptic data are lacking. Advanced processing techniques for intelligent gutting and trimming are being developed to remove parasites from fish.

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Artificial intelligence–based method for the rapid detection of fish parasites (Ichthyophthirius multifiliis, Gyrodactylus kobayashii, and Argulus japonicus)

Cited by 7 publications

References 34 publications

Sexual Dimorphism and Discrimination of Barbel Steed (Hemibarbus labeo) in the Jinhe River, China: An Indicator of Habitat Status

Sexual Dimorphism and Discrimination of Barbel Steed (Hemibarbus labeo) in the Jinhe River, China: An Indicator of Habitat Status

Natural Language Processing and Fiction Text: Basis for Corpus Research

Re‐evaluation of certain aspects of the EFSA Scientific Opinion of April 2010 on risk assessment of parasites in fishery products, based on new scientific data. Part 1: ToRs1–3

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