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Extended abstract
Introduction (and purpose): A high genetic improvement in growth rate and feed efficiency of broilers has been recorded in the last five decades due to genetic selection. However, the increase in global human population, increasing demand for affordable animal protein, increasing feed costs and continuing global environmental issues continue to push the broiler industry to produce broiler chickens that grow quickly and efficiently. In order to further improve the growth rate and feed efficiency of broiler chickens, it is necessary to understand the genetic background of growth rate (body weight) and feed efficiency in broiler chickens. Therefore, this study was conducted with the objectives of simultaneous estimation of genetic parameters of body weight (BW), feed intake (FI), body weight gain (Gain) in broiler chickens, and calculation of residual feed (RFI) and estimation of its genetic parameters.
Materials and Methods: The data of 45 generations for growth rate in commercial broilers form Arta Sablan Poultry Company of Ardabil province were used for analysis to estimate genetic parameters for body weight (BW) in males and females at three different ages. Body weight data were measured at three different ages (day t, day t-4 and day t-7) of both sexes. The first BW was recorded on day t for 25 generations, however, as the selection continued, the birds began to grow faster and reach the desired body weight earlier, therefore, the age of weighing changed and BW was recorded at t-4 and t-7. Body weight in males and females as well as body weight at two ages were considered as separate traits in each of the three traits. This led to the creation of a 12-trait model for BW, FI and Gain in two sexes and three age groups. The phenotypic RFI trait (RFIP) was estimated from the conditional distribution of FI given BW and Gain using partial phenotypic regression coefficients. Similarly, genetic RFI (RFIG) was estimated from the conditional distribution of FI given BW and Gain using partial genetic regression coefficients. Genetic parameters of body weight and feed efficiency were estimated using multi-trait REML analysis, hence, gender by genotype interaction and age by genotype interaction were examined for all traits BW, FI, Gain and RFI. Correlation between production traits and feed yield traits were also estimated.
Results: In males, the estimated heritability of BW was 0.38, 0.34, and 0.29 on days t-7, t-4, and t of age, respectively, while, in females, the estimated heritability of BW on days t-7, t-4 and t were 0.41, 0.38 and 0.38 respectively. The genetic correlation of BW between males and females on day’s t-7, t-4, and t was 0.95, 0.89, and 0.89, respectively, and the genetic correlation of BW was significantly different between ages. The average heritability of FI and Gain was moderate and the estimates were significantly different in males and females at the same age for all traits. In addition, the genetic correlation between males and females at the same age was significantly different, indicating a genotype-by-sex interaction for BW and FI traits. The mean heritability estimates of RFIP were significantly higher than RFIG in both sexes and three different age groups. In addition, the genetic correlation between RFIP and RFIG was significantly different at the age of t days, but no significant difference was observed at the age of t-7 days. Estimates of the heritability of production traits and feed efficiency were obtained at an average level and therefore it can be modified by genetic selection.
Conclusion: The results of multivariate REML analysis in this study show that the genetic evaluation for production traits BW and Gain and feed efficiency traits FI, RFIP and RFIG should consider gender and age differences in order to improve selection accuracy and genetic gain. Genetic correlations between phenotypic and genetic RFI were close at younger ages and significantly different at older ages, indicating that selection using either at that particular younger age would lead to the same genetic response. These results are important for the continuous development of strategies to improve feed efficiency in broiler breeding and production. In general, statistical models and methods have been used and the results reported in this study can be generalized to other poultry species with slight changes, because chicken is the main model for all bird species.
Introduction (and purpose): A high genetic improvement in growth rate and feed efficiency of broilers has been recorded in the last five decades due to genetic selection. However, the increase in global human population, increasing demand for affordable animal protein, increasing feed costs and continuing global environmental issues continue to push the broiler industry to produce broiler chickens that grow quickly and efficiently. In order to further improve the growth rate and feed efficiency of broiler chickens, it is necessary to understand the genetic background of growth rate (body weight) and feed efficiency in broiler chickens. Therefore, this study was conducted with the objectives of simultaneous estimation of genetic parameters of body weight (BW), feed intake (FI), body weight gain (Gain) in broiler chickens, and calculation of residual feed (RFI) and estimation of its genetic parameters.
Materials and Methods: The data of 45 generations for growth rate in commercial broilers form Arta Sablan Poultry Company of Ardabil province were used for analysis to estimate genetic parameters for body weight (BW) in males and females at three different ages. Body weight data were measured at three different ages (day t, day t-4 and day t-7) of both sexes. The first BW was recorded on day t for 25 generations, however, as the selection continued, the birds began to grow faster and reach the desired body weight earlier, therefore, the age of weighing changed and BW was recorded at t-4 and t-7. Body weight in males and females as well as body weight at two ages were considered as separate traits in each of the three traits. This led to the creation of a 12-trait model for BW, FI and Gain in two sexes and three age groups. The phenotypic RFI trait (RFIP) was estimated from the conditional distribution of FI given BW and Gain using partial phenotypic regression coefficients. Similarly, genetic RFI (RFIG) was estimated from the conditional distribution of FI given BW and Gain using partial genetic regression coefficients. Genetic parameters of body weight and feed efficiency were estimated using multi-trait REML analysis, hence, gender by genotype interaction and age by genotype interaction were examined for all traits BW, FI, Gain and RFI. Correlation between production traits and feed yield traits were also estimated.
Results: In males, the estimated heritability of BW was 0.38, 0.34, and 0.29 on days t-7, t-4, and t of age, respectively, while, in females, the estimated heritability of BW on days t-7, t-4 and t were 0.41, 0.38 and 0.38 respectively. The genetic correlation of BW between males and females on day’s t-7, t-4, and t was 0.95, 0.89, and 0.89, respectively, and the genetic correlation of BW was significantly different between ages. The average heritability of FI and Gain was moderate and the estimates were significantly different in males and females at the same age for all traits. In addition, the genetic correlation between males and females at the same age was significantly different, indicating a genotype-by-sex interaction for BW and FI traits. The mean heritability estimates of RFIP were significantly higher than RFIG in both sexes and three different age groups. In addition, the genetic correlation between RFIP and RFIG was significantly different at the age of t days, but no significant difference was observed at the age of t-7 days. Estimates of the heritability of production traits and feed efficiency were obtained at an average level and therefore it can be modified by genetic selection.
Conclusion: The results of multivariate REML analysis in this study show that the genetic evaluation for production traits BW and Gain and feed efficiency traits FI, RFIP and RFIG should consider gender and age differences in order to improve selection accuracy and genetic gain. Genetic correlations between phenotypic and genetic RFI were close at younger ages and significantly different at older ages, indicating that selection using either at that particular younger age would lead to the same genetic response. These results are important for the continuous development of strategies to improve feed efficiency in broiler breeding and production. In general, statistical models and methods have been used and the results reported in this study can be generalized to other poultry species with slight changes, because chicken is the main model for all bird species.
Keywords: Broiler chickens, Feed intake, Residual feed intake, Heritability, Body weight, Genetic correlation.
Type of Study: Research |
Subject:
ژنتیک و اصلاح نژاد دام
Received: 2024/07/8 | Accepted: 2024/09/28
Received: 2024/07/8 | Accepted: 2024/09/28
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