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Genetic Study of Gudali and Wakwa Beef Cattle Breeds of Adamawa Region, Cameroon

Abstract:

The present study was carried out to evaluate genetically the growth performance of the Gudali and Wakwa beef cattle. Data utilized for this study was obtained from the Institute of Agricultural Research for Development (IARD), Wakwa Station, Cameroon. The data used consisted of pedigree information of 3788 animals and 2276 performance records for the Gudali and Wakwa cattle respectively, ranging from birth to 36-months weight collected from 1968 and 1988. The data were collected from compiled herd books (calf record sheet, bull progeny record sheet and cow record sheet) consisting of pedigree information and performance records from birth to 36-months weight for both the Gudali and Wakwa breeds. The raw data were edited such that the utilized records gave complete information on calf identity, sire identity, dam identity, sex of animal, dates of birth, season of birth, herd and weights at birth, 3- month weight (3MWT), 4- month weight (4MWT), 6-month weight (6MWT), weaning weight (WWT), 12-month weight (12MWT), yearling weight (YWT), 18-month weight (18MWT), 24-month weight (24MWT), 30-month weight (30MWT) and 36-month weight (36MWT). In order to determine the fixed effects that were included in the model, a preliminary analysis was performed using the general linear models procedure as implemented in the statistical package, Statistical Analysis System 8.2. Inbreeding coefficient was calculated using the Multiple Trait Derivative Free Numerator Relationship Matrix (MTDFNRM) programme of the Multiple Trait Derivative Free Restricted Maximum Likelihood (MTDFREML) package. Genetic parameters of the growth traits were analyzed using MDTFREML package. From these, the additive genetic variance (σ2a), maternal variance (σ2m), error variances (σ2e), phenotypic variance (σ2p), covariance between additive genetic and maternal variance (σam), correlation between additive genetic and maternal variance (ram), and heritabilities were derived at convergence. Genetic correlation (rG) between growth traits was also calculated. Preliminary analyses showed that all fixed effects of calf month and year of birth, season, sex, herd and herd-year-season had a highly significant (p < 0.0001) effects on all the growth traits studied while year of birth of sire was significant (p < 0.05) for all the traits studied except for 30- and 36-MWT. In the Gudali breed, cow age group was not significant (p > 0.05) for all traits except BWT, 3MWT, 4MWT, and 24MWT, which had highly significant (p < 0.01) effects. Also, in the Wakwa breed, cow age group was not significant (p > 0.05) for all traits except BWT, 3MWT, 4MWT, and WWT. The average inbreeding coefficient obtained in this study ranged from 0 to 8%. Maternal variances for all traits studied were consistently lower than additive genetic variance in both breeds of cattle. The covariance between direct and maternal components was antagonistic in all traits studied. The direct heritability (h2a) estimates for BWT, 3MWT, 4MWT 6MWT, WWT, YWT, 18MWT, 24MWT, 30MWT, and 36MWT were 0.39, 0.24, 0.22, 0.10, 0.25, 0.21, 0.18, 0.25, 0.18 and 0.18 respectively for the Gudali cattle. On the other hand, the direct heritability (h2a) estimates of BWT, 3MWT, 4MWT 6MWT, WWT, YWT, 18MWT, 24MWT, 30MWT, and 36MWT were 0.41, 0.22, 0.17, 0.25, 0.21, 0.16, 0.15, 0.22, 0.34 and 0.33 respectively were obtained for the Wakwa cattle. The direct heritability estimate of birth weight in Wakwa was high (0.41). Moderate additive genetic heritability (h2a) estimates were obtained for BWT (0.39), 3MWT (0.24), 4MWT (0.22), WWT (0.24), YWT (0.21), 24MWT (0.25) in the Gudali cattle. Medium h2a were obtained for 3MWT (0.22), 6MWT (0.25), WWT (0.21), 24MWT (0.22), 30MWT (0.34), and 36MWT (0.33) in the Wakwa cattle. The lowly heritable traits included 6MWT (0.10), 18MWT (0.18), 30 MWT (0.18) and 36MWT (0.18) for the Gudali cattle, while for the Wakwa, they included 4MWT (0.17), YWT (0.16) and 18MWT (0.15). The maternal heritability (h2m) estimates were BWT (0.05), 3MWT (0.13), 4MWT (0.15), 6MWT (0.07) WWT (0.11), YWT (0.10) 18MWT (0.05), 24MWT (0.09), 30MWT (0.03), 36MWT (0.07) for Gudali cattle. Also, the maternal heritability for the Wakwa cattle include: BWT (0.16), 3MWT (0.16), 4MWT (0.14), 6MWT (0.18) WWT (0.18), YWT (0.13), 18MWT (0.14), 24MWT (0.03), 30MWT (0.05) and 36MWT (0.10). The maternal heritability for performance traits in both breeds falls between lowly heritable and medium heritable traits. The moderate to high values of heritabilities indicated that selection for growth traits was effective in spite of the antagonism association between direct and maternal effects. The additive direct genetic correlations between some of the growth parameters were positive and high (0.50 - 0.99). The same pattern was observed for maternal genetic correlations among traits (0.53 - 0.99), though some had negative genetic correlations (BWT and EMWT (-0.80); BWT and 36MWT (-0.79). Direct genetic correlations between BWT and WWT; BWT and YWT; BWT and 18MWT; BWT and 36MWT; WWT and YWT; WWT and 18MWT; WWT and 36MWT; YWT and 18MWT; YWT and 36MWT and 18MWT and 36MWT were 0.53, 0.39, -0.66, -0.21, 0.88, 0.87, 0.70, 0.70, 0.60 and 0.50 for the Gudali cattle. The direct genetic correlations between the same traits in the Wakwa cattle were 0.79, 0.52, -0.50, -0.31, 0.95, 0.79, 0.69, 0.93, 0.60, and 0.49 respectively. The maternal genetic correlations between the same traits for Gudali cattle were 0.72, 0.39, -0.81, -0.89, 1.00, 0.99, 0.97, 0.60, 0.70; and 0.50; 0.62, 0.32, -0.80, -0.79, 0.75, 0.99, 0.99, 0.50, 0.60 and 0.53 for Wakwa cattle. The positive and high values reported for the additive genetic and maternal correlations between the growth parameters indicate that selection for one trait would result in genetic improvement in the other trait. On the whole, the level of performance of the two breeds of cattle comes close to that reported in literature for beef cattle. The estimates of genetic parameters as well as information obtained on effects of the various factors should be of use in designing breeding programmes for the herds studied.

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