Submitted to: Journal of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: 3/11/2002
Publication Date: 7/22/2002
Citation: Williams, C.B. 2002. Application of the richard's function to characterize growth potential for different biological types of cattle [abstract]. Journal of Animal Science. 80(Suppl. 1):213.
Technical Abstract: Different patterns of growth in cattle result mostly from different patterns of nutrient intake and most of the observed variation in nutrient intake is due to diet quality, physical capacity, and nutrient requirements of the animal. Nutrient intake of animals given ad libitum access to a nutrient dense diet is largely controlled by nutrient requirements. To predict growth response for different nutrient intakes, the nutrient requirements for growth should be based on the full growth potential of the animal. On high quality diets, nutrient intake would support potential growth, and on low quality diets, physical capacity would limit nutrient intake, resulting in a lower than potential growth response. The Richard's function was used to characterize the growth potential of 21 biological types of cattle evaluated at MARC. Parameters for this function are 1) asymptotic value for empty body weight (EBW) at maturity (A), 2) scaling parameter (b), 3) maturing index (k), and 4) inflection parameter (M). Standard reference EBW (SREBW) was defined as EBW of mature cattle that contained 25% fat, and stage of maturity was defined as EBW/SREBW. The value of M was set to 5.8 for all breeds, so that the mean stage of maturity for steers and females was .5 at the point of inflection. Breed values for A were set at 1.6 and 1.4 times published values of SREBW for steers and cows, respectively. These values were based on data that showed steers and cows on high quality diets attained mature EBW that were 1.6 and 1.4 times SREBW, respectively. Time at birth was set to zero, and breed values for b were calculated from birth weight, A, and M. Breed values for k were estimated by using the first derivative of the Richard=s function to predict observed growth with values of k that varied from .002 to .004 in increments of .0001. The k value that minimized the sum of squared deviations between observed and predicted values was selected. Evaluation using independent data sets showed a close agreement between predicted and observed growth curves.