In pigs the quantification of breakdown and synthesis by powers of body protein led to the estimation of turn-over related protein retention efficiency by the equation kP = {1 + [1 − (P/α) (2/9)Q]−1/6}−1, with α the limit value of whole body protein (P) maturity, so that 0 ≤(P/α)≤1. The factor 2/9 is derived from diffusion attributes indicated by cell and nucleus geometries α and Q represents a scaled transformation of intake, 0 ≤ Q ≤ 1, such that a value of Q = 1 may represent ad libitum intake and Q = 0 the intake at the maintenance requirement. Published observations on finishing steers provide estimates of whole body protein synthesis and breakdown at pre-determined levels of intake in confirmation of the theoretical (2/9)Q power associated with (P/α) in kP. Further confirmation of the (2/9)Q power in cattle follows from satisfactory agreement between an estimate of conventional multiple regression retention efficiency and the turn-over related retention efficiency calculated at the given level of intake, for the mid point of the body mass interval covered by the regression estimate. In addition, a simulation experiment on cattle from the literature gives power estimates of protein breakdown and synthesis in general agreement with those accepted for pigs. Examples on both fine and coarse diets are employed to suggest a general rule for prediction on diets causing submaximal efficiency due to suboptimal intakes.

In sheep, evidence derived from estimates of conventional multiple regression efficiencies suggests that the rule (a-b) = (2/9) Q for the calculation of kP should be reserved for the description of compensatory growth. Protein retention efficiency for ordinary growth should be described by an adaptation of the rule derived for suboptimal intakes.

The magnitude of the discrepancy between conventional regression estimates of protein retention efficiency and theoretical estimates of synthesis efficiency indicates a major contribution ascribable to protein turn-over in the generally accepted estimates. As protein turn-over is known to be influenced by diet, feeding level and degree of maturity, this suggests the development of an estimator of protein efficiency that can be adapted for such differences. Therefore, based on generally accepted formulas for growth description, a method of estimating protein retention efficiency was developed which is flexible enough to accommodate different diets, feeding levels and degrees of maturity. Moreover, a formula was derived to convert one type of estimate to the other by regarding constant efficiency as equivalent to variable efficiency at the mid point of the estimation interval. Increase in scientific depth to this descriptive approach is provided by a theoretical consideration of a possible mechanism of hormonal control of protein synthesis and breakdown, ultimately expressed as proportionalities to powers of whole body protein (P). Molecular considerations on cellular synthesis and breakdown indicate a difference between breakdown and synthesis powers equal to (2/9)Q. The factor (2/9) is indicated by an argument based on insulinlike growth factor derived activator diffusion attributes by nucleus and body tissue geometries, while Q is equal to the proportion of nuclei activated by insulin-like growth factor. This proportion is likely to be a function of the concentration of growth factor in the blood. Hence, a linear relationship between intake and blood insulin-like growth factor concentration suggests that Q can be represented by a scaled transformation of intake, 0 ≤ Q ≤ 1, such that a value of Q = 1 represents ad libitum intake on a suitable diet and Q = 0 intake at the maintenance requirement. The quantification of breakdown and synthesis power differences by (2/9)Q leads to kP = {1 + [1 − (P/α)(2/9)Q]−1/6}−1, for turn-over related protein retention efficiency (kP), with α the limit value of P at maturity, so that 0 ≤ (P/α) ≤ 1. Experimental estimates, derived from direct estimates of whole body protein synthesis and breakdown at predetermined levels of intake, are in excellent agreement with the theoretical (2/9)Q in the power associated with (P/α) in kP. Furthermore, conventional multiple regression retention efficiencies satisfactorily approximate the turn-over related retention efficiency that can be calculated at a given level of intake for the mid point of the interval covered by the regression estimates.

A dynamic model for simulation of growth in pigs, extended to describe thermoregulatory processes, was made stochastic to simulate groups of pigs with between-animal variation in mature body protein (Pα) and lipid mass (Lα), in the potential rate at which mature mass is attained (B⋆), and in the distribution of body protein and lipid over pools and depots. The resulting variation in body composition leads to variation in energy requirements for protein turn-over and thermoregulation, causing between-animal variation in maintenance requirements (MEmaint).

Simulated population means for Pα, Lα /Pα and B⋆ were varied in three steps each. Excluding unrealistic parameter combinations this led to 33 – 6 = 21 simulated genotypes. Simulated within-population coefficients of variation (CV) were 7, 15 and 3%. Random replicates of each genotype were simulated five times, in climatic conditions that were in turn severely cold, mildly cold (about 5 and 1ºC below lower critical temperature), thermoneutral, mildly hot and severely hot (about 1 and 5ºC above upper critical temperature), during the entire growth period of 23 to 100 kg live weight. Simulated food intake was ad libitum.

Simulated thermoneutral within-population standard deviations of body protein and lipid content were 0·21 to 0·46 kg and 0·78 to 2·14 kg at 100 kg body weight. On average, the corresponding values in cold and hot conditions were slightly higher.

MEmaint showed a protein-turn-over-related within-population CV of 1·5% at thermoneutrality. Thermoregulatory action contributed about 4% extra variance in cold and hot conditions but CV values were not affected. A genetic increase in the maximum protein deposition rate from 100 to 250 g/day would increase MEmaint as related to protein turn-over and thermoregulation by 11% at thermoneutrality, and by 6 to 11% in cold or hot conditions. Two relevant groups of genotypes could be distinguished based on the within-population regression coefficients of MEmaint on daily or cumulative protein deposition (bdailyPdep, bcumPdep). These ranged from 0·250 to 0·428 kJ/kg0·75 per day per g/day and from 2·77 to 5·45 kJ/kg0·75 per day per kg, respectively, in 12 ‘conventional’ genotypes at thermoneutrality. On average, bdailyPdep was increased by 48%, 20%, –11% and –36% in the other climatic conditions mentioned above, respectively. The corresponding increase of bcumPdep was 32%, 14%, 8% and 48%. Three fast-growing lean genotypes showed similar bdailyPdep and bcumPdep at thermoneutrality, but much more pronounced increases in cold and hot conditions: 137%, 49%, –12% and + 88% for bdailyPdep and 248%, 108%, 17% and 196% for bcumPdep.

It is concluded that differences in body composition traits between pig genotypes do not cause important between-genotype differences in thermoregulatory MEmaint, and that thermoregulatory processes contribute little body-composition-related variation to hot or cold MEmaint within most genotypes.

The inferences to be made from this with regard to experimental design are discussed. The verification of the above predictions will require a very elaborate and large-scale experiment.