Table of Contents Author Guidelines Submit a Manuscript
Journal of Marine Biology
Volume 2015, Article ID 948053, 11 pages
Research Article

Estimating the Potential Production of the Brown Mussel Perna perna (Linnaeus, 1758) Reared in Three Tropical Bays by Different Methods of Condition Indices

1Programa de Pós Graduação do Instituto Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, 21941-900 Rio de Janeiro, RJ, Brazil
2Laboratório de Radioisótopos Eduardo Penna-Franca, Universidade Federal do Rio de Janeiro, 21941-900 Rio de Janeiro, RJ, Brazil

Received 16 June 2014; Revised 25 November 2014; Accepted 15 December 2014

Academic Editor: Tracy K. Collier

Copyright © 2015 Petrus Galvao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Perna perna (Linnaeus, 1758) is the main marine bivalve mussel yielded commercially in Brazil. In spite of this, scientific data is very scarce regarding its productivity in tropical shallow waters. The Condition Index (CI) is used worldwide in mariculture to assess animal health, harvest time, and yield. In this study, the authors used CI results from nine different methods to assess the season effect on the mussel CI and also to evaluate the potential yield of three southern Brazilian bays. The results from nine CI methods were used for the comparison of the seasonality and yield of mussels reared in three marine bays. Sampling was carried out monthly within two 4-month periods, from December 2008 to August 2009. The results show a trend for seasonal effects on the CI results. The winter months showed the highest and the lowest values. Between bays, higher CI values were detected in animals reared at Sepetiba Bay, followed by Guanabara Bay and Ilha Grande Bay. We suggest that the CI (that considers the ratio between bivalve soft tissue wet weight and total length) should be used by fishermen, since this formula was able to detect differences between sites and is more easily applied.