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Field Monitoring of Tritia mutabilis (Linnaeus, 1758) Egg Capsule Deposition and Intracapsular Embryonic Patterns Using Artificial Substrates and Machine Learning-Based Approaches
by
Palermo, Francesco Alessandro
, Troli, Emanuele
, Cocci, Paolo
, Angeletti, Mauro
in
Adriatic Sea
/ Animal embryos
/ Animal reproduction
/ Artificial substrata
/ artificial substrate
/ biomonitoring
/ Coastal waters
/ Coastal zone
/ Coasts
/ Data collection
/ Developmental stages
/ Eggs
/ Embryos
/ Environmental factors
/ Fisheries
/ Fishing
/ Habitat loss
/ Learning algorithms
/ Machine learning
/ Marine molluscs
/ Morphology
/ Neural networks
/ Oviposition
/ Small-scale fisheries
/ Substrates
/ Tritia mutabilis
2021
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Field Monitoring of Tritia mutabilis (Linnaeus, 1758) Egg Capsule Deposition and Intracapsular Embryonic Patterns Using Artificial Substrates and Machine Learning-Based Approaches
by
Palermo, Francesco Alessandro
, Troli, Emanuele
, Cocci, Paolo
, Angeletti, Mauro
in
Adriatic Sea
/ Animal embryos
/ Animal reproduction
/ Artificial substrata
/ artificial substrate
/ biomonitoring
/ Coastal waters
/ Coastal zone
/ Coasts
/ Data collection
/ Developmental stages
/ Eggs
/ Embryos
/ Environmental factors
/ Fisheries
/ Fishing
/ Habitat loss
/ Learning algorithms
/ Machine learning
/ Marine molluscs
/ Morphology
/ Neural networks
/ Oviposition
/ Small-scale fisheries
/ Substrates
/ Tritia mutabilis
2021
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Do you wish to request the book?
Field Monitoring of Tritia mutabilis (Linnaeus, 1758) Egg Capsule Deposition and Intracapsular Embryonic Patterns Using Artificial Substrates and Machine Learning-Based Approaches
by
Palermo, Francesco Alessandro
, Troli, Emanuele
, Cocci, Paolo
, Angeletti, Mauro
in
Adriatic Sea
/ Animal embryos
/ Animal reproduction
/ Artificial substrata
/ artificial substrate
/ biomonitoring
/ Coastal waters
/ Coastal zone
/ Coasts
/ Data collection
/ Developmental stages
/ Eggs
/ Embryos
/ Environmental factors
/ Fisheries
/ Fishing
/ Habitat loss
/ Learning algorithms
/ Machine learning
/ Marine molluscs
/ Morphology
/ Neural networks
/ Oviposition
/ Small-scale fisheries
/ Substrates
/ Tritia mutabilis
2021
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Field Monitoring of Tritia mutabilis (Linnaeus, 1758) Egg Capsule Deposition and Intracapsular Embryonic Patterns Using Artificial Substrates and Machine Learning-Based Approaches
Journal Article
Field Monitoring of Tritia mutabilis (Linnaeus, 1758) Egg Capsule Deposition and Intracapsular Embryonic Patterns Using Artificial Substrates and Machine Learning-Based Approaches
2021
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Overview
Tritia mutabilis (Linnaeus, 1758) represents a marine gastropod species of ecological and economical importance especially in coastal areas of the central Adriatic Sea (Italy). T. mutabilis encloses its fertilized eggs within capsules which play a protective role in the embryo defense against adverse environmental factors. Egg capsules are attached to any hard substrates and the availability of adequate substrates for oviposition represents therefore a major determinant of reproductive output of this species. The aim of the present study was to provide the first comprehensive monitoring of T. mutabilis egg capsule deposition and intracapsular embryonic patterns using specific artificial substrates and innovative analytical approaches. Square-based pyramid structures were placed within an area subjected to small-scale fishing activity along the Italian coastal waters of the central Adriatic Sea and monitored from March to June 2019. In addition, a machine learning-based approach was developed in order to speed up and automate time-consuming counting procedures of egg capsules attached on each pyramid. Overall, egg capsules were deposited on the almost totality of the artificial substrates reaching values of the surface coverage per site ranging from 31 to 97%. These findings lead to a quantitative estimation of egg number per site included between 27,060 and 62,940 capsules. Our results demonstrate that using these artificial substrates together with monitoring of both egg capsule deposition patterns and intracapsular developmental stages may be useful to improve the T. mutabilis stock management.
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