**1. Introduction**

320 A Bird's-Eye View of Veterinary Medicine

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> Agriculture is Uganda's most important sector, contributing 48% of gross domestic product (GPD) and directly supporting 85% of the population in rural areas. Livestock which is concentrated along 'the cattle corridor' runs southwest to northeast across Uganda, encompassing 29 districts represents 7.5% of the GDP and 17% of the agricultural GDP. The south-western agro-ecological zone (SWAEZ) of Uganda, comprising of the districts of Bushenyi, Ibanda, Isingiro, Kiruhura, Lyantonde, Mbarara, Ntungamo, Rakai and Sembabule lies within the corridor with a population of 3,085,900 people (UBOS 2006).

> The cattle population in the SWAEZ number to 1,689,605 (UBOS and MAAIF, 2009). There are a number of different cattle breeds on farms in the south western agro-ecological zone (SWAEZ) which include the following: Friesian and Friesian crosses 50% (F1) and 75%(F2), Boran and Boran crosses and the Ankole cattle. The Ankole cattle used to be the most predominant breed of cattle but they have been extensively crossed with the Friesian cattle.

> There are generally no guidelines on the optimum productivity and cost-effective level at which to stop cross-breeding. It is known that the more one up-grades the more susceptible the crossbred animals become to common diseases requiring extra cost on feeding and disease control. Studies by Kiwuwa *et al* 1983; Kugonza (2005) and Ndumu (2007) indicate similar findings about the production and husbandry constraints affecting other local breeds, the Ankole cattle in addition to extensive nature of cross breeding of the Ankole cattle. But these evaluations have been limited in scope and approaches while covering limited agro-ecological environments and unique production systems and furthermore, there have been a lot of changes in the grazing systems, feed resources availability and supply as a result of continued adverse changes in climatic conditions which impacts on the overall performance of the animals. It is, therefore, necessary that up-to date information is constantly generated to guide farmers in the best practices with regards to adoption of

The Growth Performance Evaluation of Cattle

were entered in Excel worksheet

**2.1 Description of on-station data** 

station site focussing on breed differences.

different time intervals of 30 day means.

breed, sex of calf and season of birth (model i) below.

*µ* = the common parameter (konstant) **B***i* = the fixed effect of breed of cattle (i = 1, 2)

**2.1.1 Analysis models** 

(Table 1).

Where:

season of birth.

Breeds in the South Western Agro-Ecological Zone (SWAEZ) of Uganda 323

The heart girth tape was placed around the girth for reading off the weights. Weights of cattle were immediately recorded in data sheets and transferred for entry into Excel programme as back up and for further collation for analysis; all weights in kilograms (kg)

On-station data involved only two cattle breeds i.e., the pure (100%) Friesian and the pure (100%) Ankole cattle. The weights were taken immediately after birth. The sample sizes were 30 Ankole cattle and 35 Friesian cattle. Continuous recording of heart girth and body weight measurements was done every two weeks for a period of 3 years. The data was, however entered in Excel at interval of 30 days i.e. monthly 1 for period 1-30 days, period 2 for 31-60 days, etc. All calves were managed under similar conditions allowing suckling up to 6 months while their dams were on open free range grazing management under the care a herdsman. Comparison was based on fixed effects under a single management of one on-

Prior to the analysis of variance (ANOVA), a simple descriptive statistical analysis was done to examine the distribution of weight data structured at 30-day intervals for distribution of the means. Those values showing gross errors and outlying were excluded from the data set to avoid adversely affecting the means and hence, standard deviations, variances and standard errors. This was achieved using VIEWTABLE, GPLOT and MEANS procedures of SAS, version 9 (2002). The GPLOT showed the distribution of observations against the

ANOVA using General Linear Model (GLM) (SAS, 2000) for calf body weight was performed to determine the fixed effects of various factors on body weight at 30-day intervals from the first month of birth to 12th months of age (360 days of age ). The data was classified according to the experimental variables covering the twelve periods 1-30, 31-60, 61-90, 91-120, 121-150, 151-180, 181-210, 211-241, 241-270, 271-300, 301-330 and 331-360 days

Various analyses were run for different combination of the fixed effects and effects with non-significance levels of P>0.05 dropped from the next test model until the final model was developed. After final adjustments for the various differences and exclusions of nonsignificant effects such as year of birth and multiple births and interaction of cattle breed with season of birth, the final model (i) below was arrived at. This includes only the effect of

Y*ijkl* = *µ* + **B***i* + **X***<sup>j</sup>* + **S***k* + e*ijkl* (i)

Y*ijklm* = the live weight of the lth calf born under ith calf cattle breed, jth sex of calf and kth

appropriate breeding and production technologies for improving production and productivity of various cattle breeds in Uganda.

The overall objective of the study was to evaluate and document the performance of existing breeds of cattle in the south western agro-ecological zone (SWAEZ) for improved livestock productivity. The specific objectives include: (i) to evaluate the growth performance of existing cattle breed under on-station and on-farm conditions.

The study is meant to generate up to-date and accurate information on performance of selected cattle populations in the SWAEZ in terms of their growth, maturity and production parameters. This would help in packaging of appropriate information on better management practices to guide farmers in partnership with National Agriculture Advisory Services (NAADS) and extension workers as conduits for effective uptake pathways for technology adoption.
