Morphometric Analysis of Tor tambroides by Stepwise Discriminant and Neural Network Analysis
The population structure of the Tor tambroides was
investigated with morphometric data (i.e. morphormetric
measurement and truss measurement). A morphometric analysis was
conducted to compare specimens from three waterfalls: Sunanta, Nan
Chong Fa and Wang Muang waterfalls at Khao Nan National Park,
Nakhon Si Thammarat, Southern Thailand. The results of stepwise
discriminant analysis on seven morphometric variables and 21 truss
variables per individual were the same as from a neural network. Fish
from three waterfalls were separated into three groups based on their
morphometric measurements. The morphometric data shows that the
nerual network model performed better than the stepwise
discriminant analysis.
[1] N. Poulet, Y. Reyjol, H. Collier, and S. Lek, "Does fish scale
morphology allow the identification of populatio leuciscus burdigalensis
in river Viaur (SW France)," Aquat. Sci., vol. 67, pp. 122-127, 2005.
[2] S. H. Cardin and K. D. Friedland, "The utility of image processing
techniques for morphometric analysis and stock identification," Fisher.
Research, vol. 43, pp. 129-139, 1999.
[3] K. M. Bailey, "Structural dynamics and ecology of flatfish populations,"
J. Sea Research, vol. 37, pp. 269-280, 1997.
[4] A. G. Murta, "Morphological variation of horse mackerel (Trachuvus
trachurus) in the Iberian and North African Atlantic: implications for
stock identification," J. Mar. Sci., vol. 57, 1240-1248, 2002.
[5] A. Pinheiro, C. M. Teixeira, A. L. Rego, J.F. Marques, H.N.Cabral,
"Genetic and morphological variation of Solea lascaris (Risso, 1810)
along the Portuguese coast," Fisheries research, vol. 73, pp. 67-78,
2005.
[6] A. Silva, "Morphometric variation among sardine (Sardina pilchardus)
populations from the northestern Allantic and the Western
Mediterranean," J. Mar. Sci., vol. 60, pp. 1352-1360, 2003.
[7] F. Saborido-Rey and K. J. Nedreaas, "Geographic variation of Sebastes
mentella in the Northeast Arctic derived from a morphological
approach," J. Mar. Sci., vol. 57, pp. 965-975, 2000.
[8] J. Palma and J. P. Andrade, "Morphological study of Diplodus sargus,
Diplodus puntazo, and Lithognathus mornurus (Sparidae) in the Eastern
Atlantic and Mediterranean Sea," Fisher. Research, vol. 57, pp.1-8,
2002.
[9] J. P. Salani, D. A. Milton, M. J. Rahman, and M. G. Hussian, "Allozyme
and morphological variation throughout the geographic range of the
tropical shad, hila Tenualosa ilisha," Fisher. Research, vol. 66, pp. 53-
69, 2004.
[10] K. Vidalis, "Discrimination between population of picarel (Spicara
smaris L., 1758) in the Aegean Sea, using multivariate analysis of
phonetic characters," Fisher. Research, vol. 30, pp.191-197, 1997.
[11] W. R. Bowering, "An analysis of morphometric characters northwest
Atlantic using a multivariate analysis of covariance," Can. J. Fisher.
Aquat. Sci., vol. 45, pp. 580-585, 1998.
[12] K. A. Smith, "A simple multivariate technique to improve the design of
a sampling strategy for age-based fishery monitoring," Fisher. Research,
vol. 64, pp. 79-85, 2003.
[13] I. Pulido-Calvo and M. M Portela, "Application of neural approaches to
one-step daily flow forecasting in Portuguese watersheds," J. Hydrol., to
be published.
[14] G. Winterer, M. Ziller, B. Kloppel, A. Heinz, L. G. Schmidt, and W. M.
Herrmann, "Analysis of quantitative EEG with Artificial neural
networks and discriminant analysis - A methodological comparison,"
Neuropsychobiol., vol. 37, pp. 41-48, 1998.
[15] G. P. Zhang, "Time series forecasting using a hybrid ARIMA and neural
network model," Neurocomputing, vol. 50, pp. 159-175, 2003.
[16] J. F. Hair, E. A. Rolph, L. T. Roland, and C. B. William, "Multivariate
data analysis," New Jersersy: Prentice Hall, 1995, ch. 5.
[17] Z. Ramadan, S. Xin-Hua, K. H. Philip, J. J. Mara, and M. S. Kate,
"Variable selection in classification of environmental soil samples for
partial least square and neural network models," Anal. Chem. Acta, vol.
446, pp. 233-244, 2001.
[18] D. P. Swain and C. J. Foote, "Stocks and chameleons: the use of
phenotypic variation in stock identification," Fisher. research, vol. 47,
pp. 113-128, 1999..
[19] Guide to Using Neural Tools, Palisade Corporation, New York, 2005.
[1] N. Poulet, Y. Reyjol, H. Collier, and S. Lek, "Does fish scale
morphology allow the identification of populatio leuciscus burdigalensis
in river Viaur (SW France)," Aquat. Sci., vol. 67, pp. 122-127, 2005.
[2] S. H. Cardin and K. D. Friedland, "The utility of image processing
techniques for morphometric analysis and stock identification," Fisher.
Research, vol. 43, pp. 129-139, 1999.
[3] K. M. Bailey, "Structural dynamics and ecology of flatfish populations,"
J. Sea Research, vol. 37, pp. 269-280, 1997.
[4] A. G. Murta, "Morphological variation of horse mackerel (Trachuvus
trachurus) in the Iberian and North African Atlantic: implications for
stock identification," J. Mar. Sci., vol. 57, 1240-1248, 2002.
[5] A. Pinheiro, C. M. Teixeira, A. L. Rego, J.F. Marques, H.N.Cabral,
"Genetic and morphological variation of Solea lascaris (Risso, 1810)
along the Portuguese coast," Fisheries research, vol. 73, pp. 67-78,
2005.
[6] A. Silva, "Morphometric variation among sardine (Sardina pilchardus)
populations from the northestern Allantic and the Western
Mediterranean," J. Mar. Sci., vol. 60, pp. 1352-1360, 2003.
[7] F. Saborido-Rey and K. J. Nedreaas, "Geographic variation of Sebastes
mentella in the Northeast Arctic derived from a morphological
approach," J. Mar. Sci., vol. 57, pp. 965-975, 2000.
[8] J. Palma and J. P. Andrade, "Morphological study of Diplodus sargus,
Diplodus puntazo, and Lithognathus mornurus (Sparidae) in the Eastern
Atlantic and Mediterranean Sea," Fisher. Research, vol. 57, pp.1-8,
2002.
[9] J. P. Salani, D. A. Milton, M. J. Rahman, and M. G. Hussian, "Allozyme
and morphological variation throughout the geographic range of the
tropical shad, hila Tenualosa ilisha," Fisher. Research, vol. 66, pp. 53-
69, 2004.
[10] K. Vidalis, "Discrimination between population of picarel (Spicara
smaris L., 1758) in the Aegean Sea, using multivariate analysis of
phonetic characters," Fisher. Research, vol. 30, pp.191-197, 1997.
[11] W. R. Bowering, "An analysis of morphometric characters northwest
Atlantic using a multivariate analysis of covariance," Can. J. Fisher.
Aquat. Sci., vol. 45, pp. 580-585, 1998.
[12] K. A. Smith, "A simple multivariate technique to improve the design of
a sampling strategy for age-based fishery monitoring," Fisher. Research,
vol. 64, pp. 79-85, 2003.
[13] I. Pulido-Calvo and M. M Portela, "Application of neural approaches to
one-step daily flow forecasting in Portuguese watersheds," J. Hydrol., to
be published.
[14] G. Winterer, M. Ziller, B. Kloppel, A. Heinz, L. G. Schmidt, and W. M.
Herrmann, "Analysis of quantitative EEG with Artificial neural
networks and discriminant analysis - A methodological comparison,"
Neuropsychobiol., vol. 37, pp. 41-48, 1998.
[15] G. P. Zhang, "Time series forecasting using a hybrid ARIMA and neural
network model," Neurocomputing, vol. 50, pp. 159-175, 2003.
[16] J. F. Hair, E. A. Rolph, L. T. Roland, and C. B. William, "Multivariate
data analysis," New Jersersy: Prentice Hall, 1995, ch. 5.
[17] Z. Ramadan, S. Xin-Hua, K. H. Philip, J. J. Mara, and M. S. Kate,
"Variable selection in classification of environmental soil samples for
partial least square and neural network models," Anal. Chem. Acta, vol.
446, pp. 233-244, 2001.
[18] D. P. Swain and C. J. Foote, "Stocks and chameleons: the use of
phenotypic variation in stock identification," Fisher. research, vol. 47,
pp. 113-128, 1999..
[19] Guide to Using Neural Tools, Palisade Corporation, New York, 2005.
@article{"International Journal of Biological, Life and Agricultural Sciences:56611", author = "M. Pollar and M. Jaroensutasinee and K. Jaroensutasinee", title = "Morphometric Analysis of Tor tambroides by Stepwise Discriminant and Neural Network Analysis", abstract = "The population structure of the Tor tambroides was
investigated with morphometric data (i.e. morphormetric
measurement and truss measurement). A morphometric analysis was
conducted to compare specimens from three waterfalls: Sunanta, Nan
Chong Fa and Wang Muang waterfalls at Khao Nan National Park,
Nakhon Si Thammarat, Southern Thailand. The results of stepwise
discriminant analysis on seven morphometric variables and 21 truss
variables per individual were the same as from a neural network. Fish
from three waterfalls were separated into three groups based on their
morphometric measurements. The morphometric data shows that the
nerual network model performed better than the stepwise
discriminant analysis.", keywords = "Morphometric, Tor tambroides, Stepwise
Discriminant Analysis , Neural Network Analysis.", volume = "1", number = "9", pages = "106-5", }
