Impact Factor: 0.738
​5-Year Impact Factor: ​0.938
Journal Citation Reports® 2018
Upcoming Event
Related Journals
Related Journals
Turkish Journal of Fisheries and Aquatic Sciences 2020, Vol 20, Num, 2     (Pages: 103-111)

Deciphering the Stock Structure of Chanos chanos (Forsskål, 1775) in Indian Waters by Truss Network and Otolith Shape Analysis

Murugesan Sri Hari 1 ,Ayyathurai Kathrivelpandian 2 ,Sreekanth Giri Bhavan 3 ,Aliyamintakath Muhammadali Sajina 4 ,Shardul Sham Gangan 5 ,Zeba Jaffer Abidi 1

1 Fisheries Resource Harvest and Post-Harvest Management Division, ICAR-Central Institute of Fisheries Education, Mumbai, Maharashtra, India
2 Peninsular Marine Fish Genetic Resources, ICAR-National Bureau of Fish Genetic Resources, Cochin, Kerala, India
3 ICAR-Central Coastal Agricultural Research Institute, Old-Goa, Goa, India
4 Fisheries Resource and Environment Management Division, ICAR-Central Inland of Fisheries Research Institute, Barrackpore, Kolkata, West Bengal, India
5 Taraporewala Marine Biological Research Station, Mumbai, Maharastra, India
DOI : 10.4194/1303-2712-v20_2_03 Viewed : 433 - Downloaded : 700 Chanos chanos is one of the Indo-West Pacific fish species normally found along the Indian coast. Because the breeding protocol for milkfish has been standardized in India, there is an urgent need to study the stock structure of the species to select the best traits for future breeding programs and to conserve the species. A total of 246 fish samples were collected from four locations, Chilika Lake and Mandapam lagoon, in the East coast and Cochin Backwaters and Mandovi - Zuari Estuary, in the West coast of India to delineate the stocks of Milkfish along the Indian coast. A total of 21 truss distances and five otolith shape indices were measured. Principal component analysis was conducted for truss and otolith data. Mid-body depth and caudal peduncle depth measurements were highly useful in discriminating the stocks. All shape indices differed significantly between the sampling locations. Cross-validation by discriminant analysis of morphometric traits revealed that 87.6% of the individuals were correctly classified into their respective locations, while otolith shape data classified 59.6% of the fish samples correctly to their sampling sites. This study revealed that there is the existence of different populations of this species at the respective sampling locations. Future studies should focus on delineating the populations from all the geographical locations along the Indian coast. Keywords : Milkfish, Population, Morphology, Otolith, Cross-validation