Last update: November 22, 2010 12:27:19 PM E-mail Print

 

Description of a model for the calculation of breeding values for profitability

 

M. J. Herselman


Grootfontein Agricultural Development Institute, Private Bag X529, Middelburg, EC, 5900, South Africa.

E-mail: Tino Herselman

 


Currently, the selection of breeding animals through the National Small Stock Improvement Scheme (NSSIS) in South Africa is based on indices and estimated breeding values for different production traits. The net result of such selection is an increase in production or income per head and not necessarily per unit of available resource. The income from an individual sheep is directly related to the level of production of that animal, whereas the income from a sheep farming enterprise is determined by the efficiency of converting available grazing material into products. For the farm enterprise, the available grazing material is the primary limiting factor. In the South African context, where vast areas of land are of relative low potential and where too much pressure is already placed on the natural resource, it is of particular importance that livestock is bred to increase income per unit of available resource and not per head. Continuously breeding bigger animals with higher nutritional requirements will inevitably result in more pressure being placed on the veld if animal numbers are not decreased accordingly. Currently, body weight is the most important trait considered during selection in the stud and commercial sheep and goat industries and it can therefore be expected that these animals will have ever-increasing nutritional requirements. The purpose of this paper is to propose a concept for incorporation into the NSSIS, which will enable breeders to select wool sheep for their potential to generate income within the limitation of the primary resource. A database was created consisting of ewe body weight (BW), clean fleece weight (CFW), clean wool price (CWP), number of Iambs born per ewe per year (LB), meat price (MP) and farm profit (PROFIT). Different combinations (243) of the first five variables were taken arbitrary and farm profit (R/SSU) was calculated for each of the 243 records with the SM2000 model of Herselman (2002). Amongst others, the following aspects are already built into SM2000 or were specifically included before the calculations were performed: generation of a growth curve for Iambs from adult ewe body weight; a 2 kg increase in body weight results in lambs to be marketed one month earlier; meat price of cull ewes (adult) is taken as 85% of that of lambs; the wool production of lambs is calculated from that of adult ewes; the small stock unit equivalents (SSU) are calculated from ME intake which in turn is calculated from the production data using the formulas of the ARC (1980). Subsequently, a multiple linear regression was fitted on the data (243 records) with PROFIT as dependent variable and BW, CFW, CWP, LB and MP as independent variables (Equation 1).

 

Equation 1

PROFIT (R/SSU) = -200.02 - 1.47BW + 28CFW + 2.8CWP + 67LB + 8.45MP             (R2 = 0.97)

Equation 1 can be used in this format for the calculation of profit of a wool sheep farming enterprise from the average production data of the farm and relevant wool and meat prices. Subsequently, CWP in Equation ! was substituted with a prediction equation whereby CWP is calculated from fibre diameter (FD), FD2 and staple length (SL). The wool prices for different micron and staple length categories for this equation were obtained from Cape Wools SA for the production seasons of 1997/98 to 2002/03. Likewise, MP in Equation 1 was substituted with the average meat price of the same period. The equation was further expanded to obtain an equation for the calculation of a breeding value for Farm Profit from estimated breeding values (ebv's) of the other production traits (Equation 2).

 

Equation 2

PROFITebv(R/SSU) =  -998.16 - 1.47BWebv + 28CFWebv + 0.25SLebv - 106.23FDebv + 2.2634(21 + FDebv)2 + 67LBebv

The model for the calculation of breeding values for profitability has been computerized in a spreadsheet format, which enables easy re-calculation with other baseline values. The application of PROFITebv as a selection criterion will be evaluated in practice before implementation in the NSSIS.