Socio-economic assessment of dry fish processors in Cuddalore District, Tamil Nadu, India

Sharmitha Saravanan; Balaji Radhakrishnan; Moghana Lavanya Sengodan; Gangai Selvi Ramalingam; Keisar Lourdusamy D

doi:10.17017/j.fish.1230

Sharmitha Saravanan Department of Agricultural and Rural Management, Tamil Nadu Agricultural University (TNAU), Coimbatore – 641 003, Tamil Nadu, India
Balaji Radhakrishnan Department of Agricultural and Rural Management, Tamil Nadu Agricultural University (TNAU), Coimbatore – 641 003, Tamil Nadu, India
Moghana Lavanya Sengodan Department of Agricultural and Rural Management, Tamil Nadu Agricultural University (TNAU), Coimbatore – 641 003, Tamil Nadu, India
Gangai Selvi Ramalingam Department of Physical Science & IT, Agricultural Engineering College & Research Institute (AEC&RI), Tamil Nadu Agricultural University, Coimbatore – 641 003, Tamil Nadu, India
Keisar Lourdusamy D Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore – 641 003, Tamil Nadu, India

DOI: https://doi.org/10.17017/j.fish.1230

Keywords: Cuddalore, dry fish processing, livelihood resilience, socio-economic profile, Tamil Nadu, women processors

Abstract

The present study focuses on the socio-economic characteristics and occupational structure of dry fish processors in the Cuddalore District of Tamil Nadu, India. The primary data was collected from 100 dry fish processors in Cuddalore (50%) and Parangipettai (50%) blocks of the district in 2025 using a structured interview schedule. It was found that the sector was mostly women-dominated (87%) and 66% of respondents were above 45 years. Dry fish processing was the main occupation for 82% of the respondents. Most of the respondents belonged to nuclear families (74%) with 3–5 members. Raw fish procurement was mostly dependent on landing centers (67%), and traditional cement floor drying (54%) was predominant. Credit dependence was reported by 61% of the respondents, mostly from non-institutional sources (62%). Garrett ranking revealed that raw fish scarcity (Garrett mean score: 71.69) and weather uncertainty (Garrett mean score: 67.80) were the key constraints. A statistically significant association was observed between village location and production quality preference (χ² = 15.458; p < 0.05). The study concluded that the dry fish processing sector was an economically important but structurally vulnerable component of the marine fisheries value chain, which requires better institutional support and technological assistance to improve livelihood stability.

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