The current review focuses on characterization and conservation efforts vital for the development of breeding programmes for indigenous beef cattle genetic resources in Southern Africa. Indigenous African cattle breeds were identified and characterized using information from refereed journals, conference papers and research reports. Results of this current review reviewed that smallholder beef cattle production in Southern Africa is extensive and dominated by indigenous beef cattle strains adaptable to the local environment. The breeds include Nguni, Mashona, Tuli, Malawi Zebu, Bovino de Tete, Angoni, Landim, Barotse, Twsana and Ankole. These breeds have important functions ranging from provision of food and income to socio-economic, cultural and ecological roles. They also have adaptive traits ranging from drought tolerant, resistance to ticks and tick borne diseases, heat tolerance and resistance to trypanosomosis. Stakeholders in the conservation of beef cattle were also identified and they included farmers, national government, research institutes and universities as well as breeding companies and societies in Southern Africa. Research efforts made to evaluate threats and opportunities of indigenous beef cattle production systems, assess the contribution of indigenous cattle to household food security and income, genetically and phenotypically characterize and conserve indigenous breeds, and develop breeding programs for smallholder beef production are highlighted. Although smallholder beef cattle production in the smallholder farming systems contributes substantially to household food security and income, their productivity is hindered by several constraints that include high prevalence of diseases and parasites, limited feed availability and poor marketing. The majority of the African cattle populations remain largely uncharacterized although most of the indigenous cattle breeds have been identified.

A study was carried out to evaluate non genetic factors affecting milk yield and milk composition in Zimbabwean Red Dane and Jersey cattle cattle. A total of 1004 and 10 986 unedited Red Dane and Jersey 305-day lactation records respectively, were obtained from Livestock Identification Trust (LIT) containing 22 herds (1 Red Dane herd and 21 Jersey herds), with Red Dane calving in the period 2004 to 2009 (giving year of birth from 1998 to 2007) and Jersey cows calving in the period 1996 to 2008 (giving year of birth from 1994 to 2005). The General Linear Model (GLM) procedure of the Statistical Analysis System (SAS, 2004) version 9.1.3 was used to determine the genetic parameters and environmental factors. Calving interval, month of calving, parity and quadratic effects of age at calving fitted as covariates significantly (P < 0.0001) affected the milk, fat and protein yields. Milk, fat and protein yields obtained increased with an increase in calving interval. There was a linear and quadratic relationship between the production traits and age at calving of the Jersey cattle implying that milk, fat and protein yields increase with age of the animal. It is thus important to preadjust data for these environmental factors when carrying out genetic evaluations of production traits in dairy cattle.

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Body measurements are important criteria in the selection of elite animals for breeding. The objective of this study was to determine the relationship, accuracy of prediction of body weight from body measurements, and identifying multicollinearity from three beef breeds.  Four classes of stock (bull, cows, steers, and heifers) were considered. Correlation, simple, and multiple linear regression models were fitted with body weight (BW) as the dependent variable and body length (BL), heart girth (HG), height at wither (HW), muzzle circumference (MC), and shank circumference (SC) as the independent variables. The BW of the animals ranged from 218 to 630 kg, the least being heifers and bulls were the heaviest. The pairwise phenotypic correlations showed a high and significant positive relationship between BW and body dimensions (r = 0.751- 0.96; P<0.01). However, negative correlations were observed between BW with BL and MC of r = -0.733 and -0.703 and -0.660, -0.650, for cows and heifers, respectively. Regressing BW on BL, HG, and HW measurements gave statistically significant (P<0.01) equations with R2 ranging from 0.60 to 0.79. Collinearity, as portrayed by high variance inflation factors (VIFs), tolerance values, and low eigenvalues, was evident in four of the variables. It was concluded that the regression model was useful in BW prediction for smallholder farms and the relationship between BW and other body measurements was influenced by breed and class of stock. It is recommended that ridge regression or principal component regression be used in cases where multicollinearity exisists.

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