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Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics
Chitala chitala (Hamilton, 1822) is an economically important food fish species occurring throughout Indian rivers, which also has ornamental value. This study focuses on morphological variations in C. chitala from seven river basins across India namely; Son, Tons, Ken, Brahmaputra, Ganga, Gomti and...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022642/ https://www.ncbi.nlm.nih.gov/pubmed/35462771 http://dx.doi.org/10.7717/peerj.13290 |
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author | Chandran, Rejani Singh, Achal Singh, Rajeev K. Mandal, Sangeeta Ganesan, Kantharajan Sah, Priyanka Paul, Pradipta Pathak, Abhinav Dutta, Nimisha Sah, Ramashankar Lal, Kuldeep K. Mohindra, Vindhya |
author_facet | Chandran, Rejani Singh, Achal Singh, Rajeev K. Mandal, Sangeeta Ganesan, Kantharajan Sah, Priyanka Paul, Pradipta Pathak, Abhinav Dutta, Nimisha Sah, Ramashankar Lal, Kuldeep K. Mohindra, Vindhya |
author_sort | Chandran, Rejani |
collection | PubMed |
description | Chitala chitala (Hamilton, 1822) is an economically important food fish species occurring throughout Indian rivers, which also has ornamental value. This study focuses on morphological variations in C. chitala from seven river basins across India namely; Son, Tons, Ken, Brahmaputra, Ganga, Gomti and Gandak. A truss network was constructed by interconnecting nine landmarks to generate 36 morphometric variables extracted from digital images of specimens sampled from the study locations. Transformed truss measurements were subjected to principal component analysis (PCA), canonical discriminant function analysis (CDFA) and discriminant analyses of principal components (DAPC). DAPC function coefficients performed much better in capturing the variation pattern and discrimination between the rivers which was not achieved using CDFA. Eight truss variables were identified with significant and highest loading for truss variables on principal components and coefficients on discriminant function from DAPC contributing to maximum variation between the rivers. Performance graph and functional distribution of identified truss variables clearly indicated distinction between the rivers. Thin plate spline analysis and procrustes shape analysis further showed the variation in morphology between specimens across the rivers. The significant parameters differentiating specimens from different rivers were linked to dorsal fin origin, the base of the pectoral fin and the perpendicular point on the anal fin from the dorsal fin origin. Variation in the hydrodynamics of the rivers studied might be possibly affecting the fin kinematics and consequently leading to adaption seen as phenotypic variation in C. chitala. The results showcased in the present study shall help in better understanding of intra-specific diversity which is significant for management and conservation of a species. |
format | Online Article Text |
id | pubmed-9022642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90226422022-04-22 Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics Chandran, Rejani Singh, Achal Singh, Rajeev K. Mandal, Sangeeta Ganesan, Kantharajan Sah, Priyanka Paul, Pradipta Pathak, Abhinav Dutta, Nimisha Sah, Ramashankar Lal, Kuldeep K. Mohindra, Vindhya PeerJ Aquaculture, Fisheries and Fish Science Chitala chitala (Hamilton, 1822) is an economically important food fish species occurring throughout Indian rivers, which also has ornamental value. This study focuses on morphological variations in C. chitala from seven river basins across India namely; Son, Tons, Ken, Brahmaputra, Ganga, Gomti and Gandak. A truss network was constructed by interconnecting nine landmarks to generate 36 morphometric variables extracted from digital images of specimens sampled from the study locations. Transformed truss measurements were subjected to principal component analysis (PCA), canonical discriminant function analysis (CDFA) and discriminant analyses of principal components (DAPC). DAPC function coefficients performed much better in capturing the variation pattern and discrimination between the rivers which was not achieved using CDFA. Eight truss variables were identified with significant and highest loading for truss variables on principal components and coefficients on discriminant function from DAPC contributing to maximum variation between the rivers. Performance graph and functional distribution of identified truss variables clearly indicated distinction between the rivers. Thin plate spline analysis and procrustes shape analysis further showed the variation in morphology between specimens across the rivers. The significant parameters differentiating specimens from different rivers were linked to dorsal fin origin, the base of the pectoral fin and the perpendicular point on the anal fin from the dorsal fin origin. Variation in the hydrodynamics of the rivers studied might be possibly affecting the fin kinematics and consequently leading to adaption seen as phenotypic variation in C. chitala. The results showcased in the present study shall help in better understanding of intra-specific diversity which is significant for management and conservation of a species. PeerJ Inc. 2022-04-18 /pmc/articles/PMC9022642/ /pubmed/35462771 http://dx.doi.org/10.7717/peerj.13290 Text en ©2022 Chandran et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Aquaculture, Fisheries and Fish Science Chandran, Rejani Singh, Achal Singh, Rajeev K. Mandal, Sangeeta Ganesan, Kantharajan Sah, Priyanka Paul, Pradipta Pathak, Abhinav Dutta, Nimisha Sah, Ramashankar Lal, Kuldeep K. Mohindra, Vindhya Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics |
title | Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics |
title_full | Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics |
title_fullStr | Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics |
title_full_unstemmed | Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics |
title_short | Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics |
title_sort | phenotypic variation of chitala chitala (hamilton, 1822) from indian rivers using truss network and geometric morphometrics |
topic | Aquaculture, Fisheries and Fish Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022642/ https://www.ncbi.nlm.nih.gov/pubmed/35462771 http://dx.doi.org/10.7717/peerj.13290 |
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