Morphometric Analysis Of Tor Tambroides By Stepwise Discriminant And Neural Network Analysis

• Main Authors: M. Pollar, M. Jaroensutasinee, K. Jaroensutasinee
• Format: Text
• Language: English
• Published: Zenodo 2007
• Subjects: Morphometric; Tor tambroides; Stepwise Discriminant Analysis; Neural Network Analysis.; Arctic; Collier; Foote; Mara; Milton; Nakhon; Roland; Saborido
• Online Access: https://dx.doi.org/10.5281/zenodo.1326597; https://zenodo.org/record/1326597

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. : {"references": ["N. Poulet, Y. Reyjol, H. Collier, and S. Lek, \"Does fish scale\nmorphology allow the identification of populatio leuciscus burdigalensis\nin river Viaur (SW France),\" Aquat. Sci., vol. 67, pp. 122-127, 2005.", "S. H. Cardin and K. D. Friedland, \"The utility of image processing\ntechniques for morphometric analysis and stock identification,\" Fisher.\nResearch, vol. 43, pp. 129-139, 1999.", "K. M. Bailey, \"Structural dynamics and ecology of flatfish populations,\"\nJ. Sea Research, vol. 37, pp. 269-280, 1997.", "A. G. Murta, \"Morphological variation of horse mackerel (Trachuvus\ntrachurus) in the Iberian and North African Atlantic: implications for\nstock identification,\" J. Mar. Sci., vol. 57, 1240-1248, 2002.", "A. Pinheiro, C. M. Teixeira, A. L. Rego, J.F. Marques, H.N.Cabral,\n\"Genetic and morphological variation of Solea lascaris (Risso, 1810)\nalong the Portuguese coast,\" Fisheries research, vol. 73, pp. 67-78,\n2005.", "A. Silva, \"Morphometric variation among sardine (Sardina pilchardus)\npopulations from the northestern Allantic and the Western\nMediterranean,\" J. Mar. Sci., vol. 60, pp. 1352-1360, 2003.", "F. Saborido-Rey and K. J. Nedreaas, \"Geographic variation of Sebastes\nmentella in the Northeast Arctic derived from a morphological\napproach,\" J. Mar. Sci., vol. 57, pp. 965-975, 2000.", "J. Palma and J. P. Andrade, \"Morphological study of Diplodus sargus,\nDiplodus puntazo, and Lithognathus mornurus (Sparidae) in the Eastern\nAtlantic and Mediterranean Sea,\" Fisher. Research, vol. 57, pp.1-8,\n2002.", "J. P. Salani, D. A. Milton, M. J. Rahman, and M. G. Hussian, \"Allozyme\nand morphological variation throughout the geographic range of the\ntropical shad, hila Tenualosa ilisha,\" Fisher. Research, vol. 66, pp. 53-\n69, 2004.\n[10] K. Vidalis, \"Discrimination between population of picarel (Spicara\nsmaris L., 1758) in the Aegean Sea, using multivariate analysis of\nphonetic characters,\" Fisher. Research, vol. 30, pp.191-197, 1997.\n[11] W. R. Bowering, \"An analysis of morphometric characters northwest\nAtlantic using a multivariate analysis of covariance,\" Can. J. Fisher.\nAquat. Sci., vol. 45, pp. 580-585, 1998.\n[12] K. A. Smith, \"A simple multivariate technique to improve the design of\na sampling strategy for age-based fishery monitoring,\" Fisher. Research,\nvol. 64, pp. 79-85, 2003.\n[13] I. Pulido-Calvo and M. M Portela, \"Application of neural approaches to\none-step daily flow forecasting in Portuguese watersheds,\" J. Hydrol., to\nbe published.\n[14] G. Winterer, M. Ziller, B. Kloppel, A. Heinz, L. G. Schmidt, and W. M.\nHerrmann, \"Analysis of quantitative EEG with Artificial neural\nnetworks and discriminant analysis - A methodological comparison,\"\nNeuropsychobiol., vol. 37, pp. 41-48, 1998.\n[15] G. P. Zhang, \"Time series forecasting using a hybrid ARIMA and neural\nnetwork model,\" Neurocomputing, vol. 50, pp. 159-175, 2003.\n[16] J. F. Hair, E. A. Rolph, L. T. Roland, and C. B. William, \"Multivariate\ndata analysis,\" New Jersersy: Prentice Hall, 1995, ch. 5.\n[17] Z. Ramadan, S. Xin-Hua, K. H. Philip, J. J. Mara, and M. S. Kate,\n\"Variable selection in classification of environmental soil samples for\npartial least square and neural network models,\" Anal. Chem. Acta, vol.\n446, pp. 233-244, 2001.\n[18] D. P. Swain and C. J. Foote, \"Stocks and chameleons: the use of\nphenotypic variation in stock identification,\" Fisher. research, vol. 47,\npp. 113-128, 1999..\n[19] Guide to Using Neural Tools, Palisade Corporation, New York, 2005."]}