Indian Journal of Animal Research

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Research Article

Indian Journal of Animal Research, volume 52 issue 3 (march 2018) : 347-352

Application of multiple regression analysis to morphometric characters obtained from Serranus cabrilla (linnaeus, 1758) by using stepwise method
 

Levent Sangün, O. Ýnanç Güney
1University of Cukurova, Vocational School of Adana, P.O. Box 01160, Çukurova, Adana, Turkey
Cite article:- Sangün Levent, Güney Ýnanç O. (2017). Application of multiple regression analysis to morphometric characters obtained from Serranus cabrilla (linnaeus, 1758) by using stepwise method. Indian Journal of Animal Research. 52(3): 347-352. doi: DOI:10.18805/ijar.v0iOF.9147.

ABSTRACT

In fisheries science, high number of morphometric measures (independent variables) taken from different parts of the fish complicates the estimation of the body weight (dependent variable). Therefore, the researchers are seeking for a solution facilitating the interpretation of the equations of correlation between the characteristics. One way to deal with this challenge is the dimension reduction by means of stepwise multiple regression analysis. The aim of this study is to explain total variation with the same accuracy by using fewer independent variables. To accomplish this, 12 morphometric measures from 210 individuals of Serranus cabrilla were measured to estimate the body weight. Firstly, the 95% of the variation was explained by means of multiple regression analysis by using all variables. Then, by step-wise method, the same results were achieved with fewer independent variables. Finally, the variables with inter-multicollinearity eliminated and with two remaining independent variables determination coefficients resulted as 95%.  The result showed that using more variables does not create significant distinction for accuracy to estimate the body weight although; the total length and body dept was the most effective features for weight. 

REFERENCES

  1. Akar, M., Sangün, L. and Baylan, M. (2001). A study about some quantitative traits for specie of Serranus hepatus. XI. Aquaculture Symposium, 1: 360-367. 
  2. Almatar, S.M., Lone, K.P., Abu-Rezg, T.S. and Yousef A.A. (2004). Spawning frequency, fecundity, egg weight and spawning pampus argenteus (euphrasen) (stromateidae) in Kuwait. J. Appl. Ichthyol., 20: 176–188. 
  3. Çankaya, S., Kayaalp, G.T., Sangun, L., Tahtali, Y. and Akar, M. (2006). A comparative study of estimation methods for parameters in multiple linear regression model. J. Appl. Anim. Res., 29: 43-47. 
  4. Çankaya, S. and Abacý, S. H. (2012). Path analysis for determination of relationships between some body measurements and live weight of german fawn x hair crossbred kids. Kafkas Univ Vet Fak Dergisi, 18: 769-773
  5. Choi, U-K., Kwon, O-J., Lee, E-J., Yang, S-H., Son, D-H., Cho, Y-J., Im, M-H. and Chung, Y-G. (2000). Evaluation of sigumjang taste by multiple regression analysis. Food Sci. Biotechnol., 9: 209-213. 
  6. Draper, N.R. and Smith, H. (1981). Applied Regression Analysis. Wiley Series in Probability and Mathematical Statistics, 709 pp.
  7. Gunst, R.F. and Mason, R.L. (1980). Regression Analysis and Its Application: A Data - Oriented Approach. Marcel Dekker. New York, 402 pp. 
  8. Gupta N, Gill K.K. and Babuta R. (2015). Development of regression models in ber genotypes under the agroclimatic conditions of south-western region of Punjab, India. Indian J. Agric. Res., 49: 260-264.
  9. Harish G., Nataraja M.V., Jasrotia J., Holajjer P., Savaliya S.D. and Gajera M. (2014). Impact of weather on the occurrence pattern of insect pests on groundnut. Legume Research, 38: 524-535.
  10. Kayaalp,G.T. and Polat, S. (2001). Estimation of clorophyll-a for full completed and incompleted regression model. E.U. Journal of Fisheries and Aquatic Sciences, 18: 529-535. 
  11. Kleinbaum, D.G., Kupper, L.L., Muller, K.E. and Nizam, A. (1998). Applied regression analysis and other multivariable methods. Brooks/Cole Publishing Company, Pacific Grove, California.
  12. Kokate, L.S., Singh, A., Banu, R., Gandhi, R.S., Chakravarty, A.K., Gupta, A.K. and Sachdeva, G.K. (2014). Predýctýon of 305-day lactatýon mýlk yýeld based on býmonthly test day values ýn karan frýes cattle. Indian J. Anim. Res., 48: 103-105.
  13. Lantry, F., B., Steward, D., J. (1999). Evaluation of total-body electrical conductivity to estimate whole-body water content of yellow perch, Perca flavescens, and alewife, Alosa pseudoharengus. Fish. Bull, 97: 71-79. 
  14. Mcintyre, C.L and, Adams, L.G. (1999). Reproduction characteristics of migratory golden eagles in Denali National park, Alaska. The Cooper Ornithological Society, 101: 115-123. 
  15. Montgomery, D.C., Peck, E.A. and Vining, G.G. (2001). Introduction to Linear Regression Analysis. John Willey and Sons INC. NewYork 641 pp.
  16. Naha, B.C., Chakravarty A.K., Mir M.A. and Bhakat M. (2016). Optimizing age at first use of semen for higher fertility in Sahiwal breeding bulls. Indian J. Anim. Res., 50:(6) 1000-1004.
  17. Özcan, H., Aydýn, H. and Bayramoðlu, H.O. (2005). Ekmeklik buðdayda verim stabilitesi ve stabilite parametreleri arasýndaki korelasyon. Tarým Bilimleri Dergisi, 11: 21-25.
  18. Palacios, D.M. (2002). Factors influencing the island-mass effect of the galapagos archipelago. Geophysical Research Letters, 29: 2134. 
  19. Sezgin, A. (2010). Çiftçilerin tarýmsal yayýmýn finansmanýna katýlma isteklerini etkileyen faktörlerin analizi: Erzurum ili örneði. Agricultural Sciences, 16:116-122.
  20. Schoeman, S. J., Aziz, M.A. and Jordaan, G. F. (2002). The influence of multicollinearity on
  21. crossbreeding parameter estimates for weaning weight in beef cattle. South African Journal of Animal Science, 32: 239-246.
  22. Stevens, M., Maes, J. and Ollevier, F. (2006). A bioenergetics model for juvenile flounder Platichthys flesus. J. Appl. Ichthyol, 22: 79–84. 
  23. Takma, Ç., Atýl, H. and Aksakal, V. (2012). Çoklu doðrusal regresyon ve yapay sinir aðý modellerinin laktasyon süt verimlerine uyum yeteneklerinin karþýlaþtýrýlmasý. Kafkas Univ. Vet. Fak. Dergisi, 18: 941-944. 
  24. Tortonese, E. (1964). The main biogeographical features and problems of Mediterranean fish fauna. Copeia, 1: 97-107. 
  25. Wheeler, A. (1969). The fishes of the British Isles and North-West Europe. Michigan State University Press. East. Laressing, 780 pp.
  26. Whitehead, P.J.P., Bauchot, M.L., Hureau, J.C., Nielsen, J. and, Tortonese, E. (1986). Fishes of the Nort-Easten Atlantic and the Mediterranean. The Chaucer Press, Bungay, Vol:II, 1007 pp. 
  27. Yu, S.L. and Lee, T.W. (2002). Habitat preference of the stream fish, Sinogastromyzon puliensis (Homalopteridae). Zoological Studies, 41: 182-187. 
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