Marine Fish Drying in Major Drying Yards: An Explorative Study in the Bay of Bengal of Bangladesh

The study investigated detailed drying yard infrastructures, processing conditions, raw materials quality, spot quality defect point, packaging, storage, marketing, profit margin and production of commercially important marine fish species in major drying hubs of Cox's Bazar district. In Moheshkhali, Thakurtala (0.81 ha), Ghotibhanga (47.5 ha), and Sonadia yards (250 ha) identified 19±4, 71±3, and 250±11 active processors respectively. Shaporirdip (28.25±6.13 ha) and Shamlapur yards (21±5 ha) had 38±2 and 45±2 active processors respectively from Teknaf, and Chowfalldandi drying yards covered 97.5±13.23 ha, with 143±10 active processors from Cox`s Bazar sadar area. The Nazirertek area included two drying yards: Nazirertek, the largest at 2259.26 ha with 1328±75 active processors, and Nunierchara, a smaller yard (0.340±09 ha) with 3±0 active processors used for processing of dry fish. For 1 kg of finished dried products, the average quantity of raw fish required were 3.25±0.3 kg for pomfret, 3.7±0.25 kg for jewfish/croaker, 2.8±0.02 kg for mackerel, 4.5±0.2 kg for sardine, 4.01±0.2 kg for anchovy, 5.5±0.3 kg for Bombay duck, 3.9±0.2 kg for shrimp, 4.04±0.3 kg for skipjack tuna, 3.7±0.3 kg for sea catfish, 3.7±0.3 kg for shark, and 3.6±0.1 kg for other small pelagic species. The percentage of salt used ranged from 3% to 16%, and the average freshness quality defect point of raw material fish ranged between 1.38 to 3.3 depending on species. Dried fish processors used mostly traditional methods for raw material handling, processing, packaging, storage, and marketing of dried fish products. A total of 42,566 metric tons (MT) of marine dried fish production was recorded in the surveyed Cox’s Bazar region. The average profit margins (%) of major sun-dried fish species were as follows: for pomfret 26 ±3, jewfish/croaker 25±1, mackerel 26±2, sardine 24±2, anchovy 25±5, bombay duck 28±3, ribbon fish 33±13, shrimp 14±0.3, shark 12±4 and for other species 11±6. The government and policymakers may find the results useful in planning and implementing the subsequent phases required for development and for the stakeholders in improving the quality, processing, storage, marketing and export of dried fish. Furthermore, this research may contribute to understanding the dynamics of Bangladesh's fish drying industry and its potential for sustainable development.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.15188754
Primary Topic
Fisheries and Aquaculture Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Marine Fish Drying in Major Drying Yards: An Explorative Study in the Bay of Bengal of Bangladesh

Zenodo (CERN European Organization for Nuclear Research)
Fisheries and Aquaculture Studies
article

Marine Fish Drying in Major Drying Yards: An Explorative Study in the Bay of Bengal of Bangladesh

article en

Abstract

The study investigated detailed drying yard infrastructures, processing conditions, raw materials quality, spot quality defect point, packaging, storage, marketing, profit margin and production of commercially important marine fish species in major drying hubs of Cox's Bazar district. In Moheshkhali, Thakurtala (0.81 ha), Ghotibhanga (47.5 ha), and Sonadia yards (250 ha) identified 19±4, 71±3, and 250±11 active processors respectively. Shaporirdip (28.25±6.13 ha) and Shamlapur yards (21±5 ha) had 38±2 and 45±2 active processors respectively from Teknaf, and Chowfalldandi drying yards covered 97.5±13.23 ha, with 143±10 active processors from Cox`s Bazar sadar area. The Nazirertek area included two drying yards: Nazirertek, the largest at 2259.26 ha with 1328±75 active processors, and Nunierchara, a smaller yard (0.340±09 ha) with 3±0 active processors used for processing of dry fish. For 1 kg of finished dried products, the average quantity of raw fish required were 3.25±0.3 kg for pomfret, 3.7±0.25 kg for jewfish/croaker, 2.8±0.02 kg for mackerel, 4.5±0.2 kg for sardine, 4.01±0.2 kg for anchovy, 5.5±0.3 kg for Bombay duck, 3.9±0.2 kg for shrimp, 4.04±0.3 kg for skipjack tuna, 3.7±0.3 kg for sea catfish, 3.7±0.3 kg for shark, and 3.6±0.1 kg for other small pelagic species. The percentage of salt used ranged from 3% to 16%, and the average freshness quality defect point of raw material fish ranged between 1.38 to 3.3 depending on species. Dried fish processors used mostly traditional methods for raw material handling, processing, packaging, storage, and marketing of dried fish products. A total of 42,566 metric tons (MT) of marine dried fish production was recorded in the surveyed Cox’s Bazar region. The average profit margins (%) of major sun-dried fish species were as follows: for pomfret 26 ±3, jewfish/croaker 25±1, mackerel 26±2, sardine 24±2, anchovy 25±5, bombay duck 28±3, ribbon fish 33±13, shrimp 14±0.3, shark 12±4 and for other species 11±6. The government and policymakers may find the results useful in planning and implementing the subsequent phases required for development and for the stakeholders in improving the quality, processing, storage, marketing and export of dried fish. Furthermore, this research may contribute to understanding the dynamics of Bangladesh's fish drying industry and its potential for sustainable development.

Zenodo (CERN European Organization for Nuclear Research)
World University of Bangladesh (BD)
Life below water
Openalex Percentile: Top 43%
Fisheries and Aquaculture Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.