Assessment of relationship between body weight and body measurement traits of indigenous Chinese Dagu chickens using path analysis

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1 Indian J. Anim. Res., 51 (3) 2017 : Print ISSN: / Online ISSN: AGRICULTURAL RESEARCH COMMUNICATION CENTRE Assessment of relationship between body weight and body measurement traits of indigenous Chinese Dagu chickens using path analysis Thobela Louis Tyasi 1#, Ning Qin 1#, Yang Jing 1, Fang Mu 1, HongYan Zhu 1, Dehui Liu 1, Shuguo Yuan 2 and Rifu Xu 1* Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Jilin Agricultural University, Changchun , Jilin, China. Received: Accepted: DOI: /ijar.v0iOF.6990 ABSTRACT The objectives of this study were to establish the direct and indirect effects of the relationship between body weight and body measurements on both sexes of the indigenous Chinese Dagu chicken and to develop a functional model for predicting body weight using different body measurements. The path analysis in female chickens revealed that shank length has the highest direct effect (path coefficient=0.233) on body weight and pelvis width showed higher indirect effect on body weight via shank length. In male chickens, the path analysis showed that body slope length has the highest direct effect (path coefficient=0.120) on the body weight of indigenous Chinese Dagu chickens, while fossil bone length has the highest indirect effect on body weight via body slope length. The equations could serve as a useful practical tool for livestock farmers, researchers and rural development workers for body weight estimation in the field and for selection purposes. Key words: Body measurements, Body weight, Dagu chicken, Indirect effect, Path analysis. INTRODUCTION Body weight is one of the most important economical traits in meat industry, whereby breeders want to select the best animals as parents for the next generation (Dekhili and Aggoun, 2013). However, in order to achieve the selection of particular traits depends on method of selection. During the selection of traits for breeding purposes, some traits may be affected directly while others may be affected indirectly (Keskin et al., 2005). Therefore, according to Ogah et al (2009), simple correlation between independent traits and dependent trait may not be suitable for explaining. Many researchers use path coefficient analysis as an alternative of simple correlation to explain the relationship between independent and dependent variables. Path coefficient analysis which was developed by Wright (1921) is an extension of multiple regression models. It allows for the determination of the explanatory variables that mostly affect the response variables (Gueye et al., 1998). Path analysis measures the direct and indirect effects of one trait on another (Mendes et al., 2005). A direct effect is a directional relationship between two traits, while an indirect effect is the effect of an independent trait on a dependent trait through one or more dominant trait (Norris et al., 2015). China has a wide variety of indigenous chicken resources (Qu et al., 2006; Guan et al., 2013; Mu et al., 2016). Ji et al (2005) explained that Chinese Dagu chicken is one of the local Chinese chicken that is genetically heterogeneous with a diverse phenotype and genotype to select from. Dagu chicken can survive in cold weather conditions, and yellow reddish in color (Qu et al., 2006). This chicken is a dual purpose breed which produces both meat and egg production (Qin et al., 2015). However, there is virtually no documented evidence of the relationships between their body weight and body measurements using a classical statistical tool such a path analysis. The main objectives of this study were to establish the direct and indirect effects of the relationship between body weight and body measurement traits on both male and female indigenous Chinese Dagu chickens and to develop a functional model for predicting body weight using different body measurements. MATERIALS AND METHODS Study area: The study was conducted at the experimental unit of the Animal Science and Technology College of Jilin Agricultural University, Changchun city, Jilin Province of China. Jilin province is located at latitude N and longitude E (Figure 1),while Changchun city is located at latitude 43º 882 N and longitude 125º 352 E. The annual rainfall is about 570.3mm during the rainy season between March and August, while the dry season runs from September to February. Experimental animals: One hundred and sixty indigenous Chinese Dagu chickens of both sexes (30 females and 130 males) were randomly selected at the age of 120 day old. *Corresponding author s poultryjlau@163.com 1 Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Jilin Agricultural University, Changchun , Jilin, China. 2 Jilin Grain Groups of Agriculture and Livestock Co., Ltd., Changchun , Jilin, China.

2 Volume 51 Issue 3 (2017) 589 Fig 1: Map of China showing the study area at Changchun City in the Jilin Province of China (Wikipedia, 2016) Animal management: The Chinese Dagu chickens were reared on deep litter in an intensive system where they were kept in poultry house. The chickens were fed grower ration and clean potable water was freely available. Routine vaccination and other management practices were done. Some of the management practices included cleaning the feeders and water containers daily and the addition of fresh feed to the stale feed in the feeders after the litter and droppings had been removed. The birds were fed the same feed throughout the experimental period. Clean water was supplied ad-libitium throughout the experimental period. The foot bath was also changed regularly. Dead chickens were removed promptly to prevent the contamination of the other chickens. Traits measured: Body weight was measured and seven linear body measurements were taken for each chicken. The anatomical reference points were according to the standard zoometrical procedures (Gueye et al., 1998; Teguia et al., 2008; Yakubu, 2011). The weight of each bird was measured individually using a sensitive weighing balance. The body measurement traits were measured using measuring tape calibrated in centimeters (cm) for body slope length and shank circumference and calibrated in millimeters (mm) for other body measurement traits. Measurements were carried out using the method described by the Agricultural Ministry of China (NY/T ). The traits were measured as follows: Body weight (BWT): Measured with the use of a sensitive weighing balance with a capacity of three decimal digits. Body slope length (BSL): Measured as the distance from shoulder joint to ischial tuberosity and measured from body surface. Breast width (BW): Measured as the width between two shoulder joints and measured outside the body. Breast depth (BD): Measured as the depth from the first thoracic vertebra to keel and measured outside the body. Fossil bone length (FBL): Measured as the length from the front end of the keel to the end of the keel and measured outside the body. Pelvis width (PW): Measured as the width of two pseudohorns. Shank length (SL): Measured as the length of the tars-metatarsus from the hock joint to the metatarsal pad. Shank circumference (SC): Measured as the circumference of the middle shank. All the measurements were taken by the same person in order to avoid individual variations in measurements. Statistical analysis: Means, standard deviation (SD) and coefficients of variation (CV) of body weight and linear body measurement traits of each sex were calculated as descriptive statistics. Pair-wise correlations between body weight and linear body measurement traits were also computed. Standardized partial regression coefficients, called path coefficients (beta weights), were also calculated. This was to allow direct comparison of values to reflect the relative importance of independent variables in explaining variation of the dependent variable. The path coefficient from an explanatory variable (X) to a response variable (Y) as described by Mendes et al (2005) is outlined below: Where, P Y.Xi = path coefficient from Xi to Y (i= BSL, BW, BD, FBL, PW, SL, SC) bi = partial regression coefficient S Xi = standard deviation of Xi = standard deviation of Y S Y The multiple linear regression model adopted was: Y= a+ b 1 X 1 +b 2 X 2 +b 3 X 3 +b 4 X 4 +b 5 X 5 +b 6 X6+b 7 X 7

3 590 INDIAN JOURNAL OF ANIMAL RESEARCH Where: Y = dependent or endogenous variable (BWT) a = intercept b s = regression coefficients X s = independent or exogenous variables (BSL, BW, BD, FBL, PW, SL, SC). The significance of each path coefficient in the multiple linear regression models was tested by t-statistic. The indirect effects of X i on Y through X j were calculated as follows: IE YXi = rxixj P Y.Xj Where, IE YXi = direct effect of X i via X j on Y = correlation coefficient between ith and jth independent rxixj variables P Y.Xj = path coefficient that indicates the direct effect of jth independent variable on the dependent variable. All the statistical analyses were done using SPSS (2010). RESULTS AND DISCUSSION Body weight and body measurement traits: Means (±SD) and coefficients of variation of the body weight and body measurement traits of indigenous Chinese Dagu chickens based on sex are presented in Table 1. Sexes had significant effect (P<0.05) on all body measurement traits, with higher values recorded for males, while no significant effect on body weight was recorded. Differences might be attributed to the different sex hormones present during the growth period of chickens. These findings are consistent with the findings on sexual differences in chickens of Youssao et al (2010); Yakubu and Salako (2009); Zaky and Amin (2007). In a related study, Deeb and Cahaner (2001) attribute the difference between male and female indigenous chickens to sexual dimorphism. The high variation observed for breast depth, pelvis width and shank length means that these body measurement traits can be selected for genetic improvement. Egena et al (2014) reported that the average body weight for indigenous chickens falls within the range of kg. However, the current study shows that the average body weight for indigenous Chinese Dagu chickens is kg, respectively. Pair-wise correlations: The phenotypic correlations between body weight and body measurement traits of Table 1: Descriptive statistics of body weight and body measurement traits of indigenous Chinese Dagu chickens based on sex Variable Female animals (n=30) Male animals (n=130) Mean±SD CV Mean±SD CV BWT(kg) 2.02± ± BSL(cm) 22.74± ± BW (mm) 81.46± ± BD (mm) 1.00± ± FBL(mm) 13.21± ± PW (mm) 96.31± ± SL (mm) 87.16± ± SC(cm) 4.38± ± Means in the same row bearing different superscript differ significantly (P<0.05), SD: Standard deviation, CV: Coefficient of variation. BWT: Body weight; BSL: Body slope length; BW: Breast width; BD: Breast depth; FBL: Fossil bone length; PW: Pelvis width; SL: Shank length; SC: Shank circumference. indigenous Chinese Dagu chickens of both sexes are presented on Table 2. The results showed no significant (P>0.01) association exists between body weight and body measurement traits. In cocks, phenotypic correlation ranges between , while in hens it ranges between The highest correlations were between breast width and pelvis width in males (r=0.351), and between shank length and pelvis width in females (r=0.718). The phenotypic correlation results of this current study are similar to the early results reported in various studies of indigenous chickens (Gueye et al., 1998; Yang et al., 2006; Mancha et al., 2008; Yakubu and Salako, 2009; Sri Rachma et al., 2013; Egena et al., 2014). It is very important to consider the relationship between body weight and body measurement traits as this could be useful as a selection criterion to improve the body weight. Although correlation analysis measures the relationship between body weight (dependent) and body measurement (independent) traits, it does not provide exact information about how much a independent traits contribute on dependent trait (Yakubu et al., 2015). Lorentz et al. (2011) point out that correlation coefficient analysis has limitations as it only indicates the magnitude relationships without revealing the cause-effect relationship. However, Norris et al. (2015) claim that path analysis is helpful in the Table 2: Phenotypic correlations among traits, male above diagonal and female below diagonal** Traits BWT BSL BW BD FBL PW SL SC BWT ns ns ns ns ns ns ns BSL ns * ** ns ** ** ** BW ns ns ** ns ** ** BD ns ns ns ns ** ns ns FBL ns ns ns * ns ns * PW ns ns ns ** ** ** * SL ns ns ns ** ** ** ** SC ns ns ns ns ns * * **, significant at p<0.01 for all correlation coefficients except otherwise stated; *, significant at p<0.05); ns, not significant.

4 Volume 51 Issue 3 (2017) 591 resolution of correlation into components of direct and indirect traits. Direct and indirect effects: Direct (path coefficient) and indirect effects of body measurements on body weight in female and male indigenous Chinese Dagu chickens are presented in Table 3 and Table 4. All the body measurement traits in females were significant. However, shank length made the greatest direct contribution to the body weight of female indigenous Chinese Dagu chickens (0.233). The findings of the present study contradict those of Egena et al (2014), who reported that shank length made the smallest direct contribution to the body weight of indigenous Nigerian chickens. Pelvis width showed the highest indirect effect on body weight via shank length in female indigenous Chinese Dagu chickens. Thus, body weight can be estimated in female Chinese Dagu chickens using shank length and pelvis width. In the male chickens (Table 4), all the body measurement traits were significant and body slope length made the greatest direct contribution to body weight (0.120). The fossil bone length showed the highest indirect effect on body weight via body slope length in male Chinese indigenous Dagu chickens. The fact that the larger indirect effect was obtained via body slope length indicates that the significant correlation observed between body weight and fossil bone length was principally via body slope length. Therefore, the body weight of male Chinese Dagu chickens could be estimated using body slope length and fossil bone length. The results of the present study contradict the findings of Yakubu and Salako (2009) who reported that thigh circumference (male) and comb height (female) had the highest direct effect on indigenous Nigerian chickens. Path analysis provides a complete means of determining factors affecting body weight in livestock. The results obtained from the path analysis provide information that could be used for the selection of livestock for improvement purposes. Establishment of preliminary regression equations: Preliminary equations with their coefficients of determinations (R 2 ) obtained from simple regression between body weight and body measurements of indigenous Chinese Dagu chickens are shown in Table 5. In hens, the highest single contribution to the variation in body weight was by shank length followed by breast depth and pelvis width (0.233, 0.120, 0.030) with R 2 = In cocks, however, the highest contribution to body weight was by body slope length followed by shank length, fossil bone length and shank circumference (0.120, 0.109, and 0.072) with R 2 =0.064.Similar results were reported by Egena et al (2014) on indigenous Nigerian chickens. Deletion of less significant variables in the establishment of body weight: In female chickens, the path coefficients of body slope length, breast width, fossil bone length and shank circumference were statistically non-significant, while the shank length, breast depth and pelvic width were statistically significant on the body weight of indigenous Chinese Dagu chickens. However, in male chickens, breast width, breast depth and pelvic width were statistically nonsignificant, while body slope length, shank length, fossil bone length and shank circumference were statistically significant. All the body measurement traits that were non-significant on the body weight of indigenous Chinese Dagu chickens were removed from the regression model. The removal of non-significant factors did not change the value of the coefficient of determination on either regression equation. The removal of non-significant variables in order to obtain Table 3: Direct and indirect effects of body measurement traits on body weight of female chickens Traits Correlation coefficient Directeffect Indirect effect with body weight BSL BW BD FBL PW SL SC BSL BW BD FBL PW SL SC Table 4: Direct and indirect effects of body measurement traits on body weight of male chickens Traits Correlation coefficient Directeffect Indirect effect with body weight BSL BW BD FBL PW SL SC BSL BW BD FBL PW SL SC

5 592 INDIAN JOURNAL OF ANIMAL RESEARCH Table 5: Preliminary regression models for estimation of body weight from body measurement traits of indigenous Chinese Dagu chickens Sex Model SE R 2 Female BWT= BSL 0.361BW BD 0.099FBL PW SL 0.316SC Male BWT= BSL 0.124BW BD FBL 0.116PW SL SC SE: standard error; R 2 : coefficient of determination Table 6: Optimum regression models for estimation of body weight from body measurement traits of indigenous Chinese Dagu chickens Sex Model SE R 2 Female BWT= BD PW SL Male BWT= BSL FBL SL SC SE: standard error; R 2 : coefficient of determination optimized equations is a method used by Yakubu and Salako (2009). Establishment of optimum regression models for prediction of body weight in indigenous Chinese Dagu chickens: Optimum regression models for the estimation of body weight from body measurement traits of Chinese Dagu chickens are shown in Table 6. For hens, after the deletion of four predictor variables (body slope length, breast width, fossil bone length and shank circumference), the remaining predictor variables (shank length, body depth and pelvic width) were written again to make a regression model for predicting the body weight of female indigenous Chinese Dagu chickens. In cocks, the remaining four predictor variables (body slope length, shank length, fossil bone length and shank circumference) make the optimum regression model for male chickens after the deletion of three predictor variables (breast width, breast depth and pelvic width). The findings of the current study are consistent with the findings reported by Peters et al (2006); Ajayi et al (2008); Yakubu and Salako (2009); Egena et al (2014). CONCLUSION It is well concluded that in female chickens, the path analysis revealed that shank length had the highest direct effect on body weight and pelvic width showed a higher indirect effect on body weight via shank length respectively. In male chickens, the path analysis showed that body slope length had the highest direct effect on the body weight of indigenous Chinese Dagu chickens, while fossil bone length had the highest indirect effect on body weight via body slope length. These equations could serve as a useful practical tool for livestock farmers, researchers and rural development workers for body weight estimation in the field and for selection purposes. Selecting and improving these traits will impact positively on the body weight of indigenous Chinese Dagu chickens. REFERENCES Agricultural ministry of china, (2004). Terminology of poultry production performance and methods of measurement with calculations. Agricultural Ministry of China (NY/T ), Beijing (in Chinese). Ajayi, F.O., Ejiofor, O. and Ironke, M.O. (2008). Estimation of body weight from linear body measurements in two commercial meat-type chickens. Global J. Agric. Sci., 7: Deeb, N. and Cahaner, A. (2001). Genotype-by-environment interaction with broiler genotypes differing in growth rate, the effects of high ambient temperature and naked-neck genotype on lines differing in genetic background. Poult. Sci., 80: Dekhili, T. and Aggoun, L. (2013). Path coefficient analysis of body weight and biometric traits in Ouled-Djellal breed of Nigeria. Revue Agric., 06: Egena, S.S.A., Ijaiya, A.T. and Kolawole, R. (2014). An assessment of the relationship between body weight and body measurements of indigenous Nigeria chickens (Gallus gallusdomesticus) using path coefficient analysis. Liv. Res. Rur. Dev., 26: Fajemilehin, O.K.S. and Salako, A.E. (2008). Body measurement characteristics of the West African dwarf goat in deciduous forest zone of South Western Nigeria. African J. Biotech., 7: Guan, R., Lyu, F., Chen, X., Ma, J., Jiang, H. and Xiao, C. (2013). Meat quality traits of four Chinese indigenous chickenbreeds and one commercial broiler stock. J. Zhejiang Univ., 14: Gueye, E.F., Ndiaye, A. and Branckaert, R.D.S. (1998). Prediction of body weight on the basis of body measurements in mature indigenous chickens in Senegal. Liv. Res. Rur. Dev., 10: Ji, C.L., Chen, G.H., Wang, M.Q. and WEIGEND, S. (2005). Genetic structure and diversity of 12 chinese indigenous chicken breeds. The Role Biotech., 3:

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