Browsing by Author "Mujibi, Fidalis D. N."

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    Frontiers | Milk Composition for Admixed Dairy Cattle in Tanzania
    (Frontiers Media, 2018-04-24) Cheruiyot, Evans K.; Bett, Rawlynce C.; Amimo, Joshua O.; Mujibi, Fidalis D. N.
    It is well established that milk composition is affected by the breed and genotype of a cow. The present study investigated the relationship between the proportion of exotic genes and milk composition in Tanzanian crossbred dairy cows. Milk samples were collected from 209 animals kept under smallholder production systems in Rungwe and Lushoto districts of Tanzania. The milk samples were analyzed for the content of components including fat, protein, casein, lactose, solids-not-fat (SNF), and the total solids (TS) through infrared spectroscopy using Milko-Scan FT1 analyzer (Foss Electric, Denmark). Hair samples for DNA analysis were collected from individual cows and breed composition determined using 150,000 single nucleotide polymorphism (SNP) markers. Cows were grouped into four genetic classes based on the proportion of exotic genes present: 25–49, 50–74, 75–84, and >84%, to mimic a backcross to indigenous zebu breed, F1, F2, and F3 crosses, respectively. The breed types were defined based on international commercial dairy breeds as follows: RG (Norwegian Red X Friesian, Norwegian Red X Guernsey, and Norwegian Red X Jersey crosses); RH (Norwegian Red X Holstein crosses); RZ (Norwegian Red X Zebu and Norwegian Red X N’Dama crosses); and ZR (Zebu X GIR, Zebu X Norwegian Red, and Zebu X Holstein crosses). Results obtained indicate low variation in milk composition traits between genetic groups and breed types. For all the milk traits except milk total protein and casein content, no significant differences (p < 0.05) were observed among genetic groups. Protein content was significantly (p < 0.05) higher for genetic group 75–84% at 3.4 ± 0.08% compared to 3.18 ± 0.07% for genetic group >84%. Casein content was significantly lower for genetic group >84% (2.98 ± 0.05%) compared to 3.18 ± 0.09 and 3.16 ± 0.06% for genetic group 25–49 and 75–84%, respectively (p < 0.05). There was no significant difference (p < 0.05) between breed types with respect to milk composition traits. These results suggest that selection of breed types to be used in smallholder systems need not pay much emphasis on milk quality differences as most admixed animals would have similar milk composition profiles. However, a larger sample size would be required to quantify any meaningful differences between groups.
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    Genetic parameters for production and feeding behaviour traits in crossbred steers fed a finishing diet at different ages
    (NRC Research Press, 2013-03) Durunna, Obioha N.; Mujibi, Fidalis D. N.; Nkrumah, Donald J.; Basarab, John A.; Okine, Erasmus K.; Moore, Stephen S.; Wang, Zhiquan
    Durunna, O. N., Mujibi, F. D. N., Nkrumah, D. J., Basarab, J. A., Okine, E. K., Moore, S. S. and Wang, Z. 2013. Genetic parameters for production and feeding behaviour traits in crossbred steers fed a finishing diet at different ages. Can. J. Anim. Sci. 93: 79–87. Because cattle can be raised postweaning under several feeding regimes, this study examined the consistency of phenotypic and genetic parameters of some production and feeding behaviour traits between two feeding periods that beef cattle received a finisher diet. Crossbred steers (n=851) were used for feeding trials from 2002 to 2009 where the steers received a finisher diet either during the fall–winter season (FP1) or during the winter–spring season (FP2). The steers evaluated in FP2 received a backgrounding diet in FP1. Traits examined include dry matter intake (DMI), average daily gain (ADG), gain: feed ratio (G:F), residual feed intake (RFI), and ultrasound measures of backfat thickness (UBF), rib-eye area (UREA) and marbling (UMB). Others include feeding duration (FD), headdown time (HDT) and feeding frequency (FF). As expected, there was no difference (P=0.90) between the RFI measured in the two periods. The two periods were similar for UBF (P=0.87) and UREA (P=0.25),while DMI, ADG and UMB were greater (P<0.04) in FP2 than in FP1. The FD, HDT and FF were greater (P<0.0001) in FP1 compared with FP2. Heritability estimates were calculated in FP1 and FP2, respectively, for ADG (0.38, 0.28), DMI (0.52, 0.42), RFI (0.16, 0.27), G:F (0.18, 0.33), HDT (0.35, 0.18) and FF (0.26, 0.46). More importantly, genetic correlations between FP1 and FP2 were estimated for DMI (0.61), RFI (0.65) and G:F (0.60). The results may indicate the influence of age or feeding period or both on these traits, which may suggest the need for multi-environment genetic evaluations to identify superior animals.