INTERNATIONAL JOURNAL OF AGRICULTURE & BIOLOGY ISSN Print: 1560–8530; ISSN Online: 1814–9596 10–583/EET/2011/13–3–419–422 http://www.fspublishers.org Full Length Article To cite this paper: Erat, S., 2011. Application of linear, quadratic and cubic regression models to predict body weight from different body measurements in domestic cats. Int. J. Agric. Biol., 13: 419–422 Application of Linear, Quadratic and Cubic Regression Models to Predict Body Weight from Different Body Measurements in Domestic Cats SERKAN ERAT 1 Department of Animal Breeding and Husbandry, Faculty of Veterinary Medicine, Kirikkale University, Yahsihan, Kirikkale, Turkey 1 Corresponding author’s e-mail: serkanerat@yahoo.com ABSTRACT The aims of this study were to predict body weight (BW) from different body measurements and to determine the best regression model for domestic cats. For this aims, a total of 48 adult Turkish cats (20 females & 8 males Turkish Angora; 13 females & 7 males Turkish Van) were used. In the study, wither height (WH), body length (BL) and head circumference (HC) were assumed as independent variables, whereas body weight was used as dependent variable. Linear, quadratic and cubic effects of the independent variables were included in the assumed model as Y= b 0 + b 1 X + b 2 X 2 + b 3 X 3 + e. Where Y = body weight; b 0 = the intercept; X = independent variables, (WH, BL, or HC); b 1 , b 2 and b 3 = regression coefficients and e = random error. Conceptual predictive (Cp) and Akaike information criterion (AIC) were used to determine the most suitable model among the assumed models. The model that has the smallest Cp and AIC values is the best model. The R 2 values from the regression indicate the BL (R 2 = 0.50) to be moderately related to the BW. Neither the quadratic term nor the cubic term was significant for all body traits, whereas the linear term was highly significant (p < 0.001) for all independent variables. Since the maximum number of independent variables is three, there were seven possible different models. It can be concluded that cat body weight was explained with the following model. (BW) = - 4.53 + 0.11 WH + 0.13 BL with p- values, <0.001, 0.0083, and <0.001 for the intercept, b 1 and b 2 , respectively with R 2 = 0.57. © 2011 Friends Science Publishers Key Words: Cat; Regression analysis; Body weight estimation INTRODUCTION In a domestic cat population, body weight is an important trait that is used in evaluating body condition (Erat & Arikan, 2010) and health status (Lund et al., 2005) of cats, in computing dosages and in prescribing drugs. Body weight and condition score are also often used for assessing nutritional condition of dog and cat (Laflamme, 1997; Esfandiari & Youssefi, 2010). A lot of techniques, which are simple or sophisticated and expensive or inexpensive, are available to get information on animal’s body traits. The easiest way to assess an animal’s body mass is to weigh the animal. However, under some situations scale may not be available and prediction of body weight from body measurements could be preferred practically (Latshaw & Bishop, 2001). Multiple regression analysis has been used widely to describe quantitative association between dependent (body weight) and independent variables (hearth girth, body length & wither height etc.) in animal studies (Cankaya, 2009). Several studies on cattle, sheep and goat (Mohammed & Amin, 1997; Wilson et al., 1997; Atta & El khidir, 2004; Topal & Macit, 2004; Adeyinka & Mohammed, 2006; Bagui & Valdez, 2007), dog and cat (Pendergrass et al., 1983; Valdez & Recuenco, 2003), horse and donkey (Pearson & Ouassat, 1996; Marante et al., 2007) and poultry (Latshaw & Bishop, 2001; Grona et al., 2009) have been conducted to predict body weight from body measurements. The body weight estimation from using external body measurements on domestic cats is scarce. Valdez and Recuenco (2003) estimated the body weight of Philippine domestic cats using some external body measurements. Therefore, the present study was designed to predict body weight of Turkish cats (Felis catus) from wither height, body length and head circumference and to choose the most appropriate regression model. MATERIALS AND METHODS Source of data: A total of 48 adult Turkish cats (20 females & 8 males Turkish Angora; 13 females & 7 males Turkish Van) were used (Fig. 1). All cats were solid white in color and sexually intact. Averages of weight and age for these cats were 3.39 kg and 2.71 years, respectively. Measurements: Live body weight (BW), wither height