Evaluation of genotype-environment interactions in beef cattle production systems using a computer simulation model

Abstract

A biotechnical model that simulates the life cycle of beef cattle was validated and used to examine effects of different genetic potentials for mature size (WMA), milk production (PMA) and maturing rate (MATR) on biological efficiency and to evaluate the interaction of genetic potentials with nutritional regimen. The model was validated using data from a cooperating ranch in the Gulf Coastal Plains region of Texas. The validation was accomplished by comparison of simulated performance variables to actual cattle performance records. Production was simulated for various combinations of genetic potentials (WMA, PMA and MATR) and management systems (nutritional regimen and age at first calving). The results of the different simulations were compared to examine effects on biological efficiency. Biological efficiency of a herd was defined as the ratio of the total weight sold to the total weight of digestible nutrients consumed (WT/TDN) and also as the ratio of the total weight sold to the number of breeding cows (WT/C). The simulations of herds with alternative potentials for mature size indicated that efficiency was higher for the smaller mature size when measured by WT/TDN. The larger females weaned heavier calves and WT/C was higher for the larger mature size. The nutritional regimens restricted the growth of the potentially larger females and caused pregnancy rates to be lower than for the smaller females. The earlier maturing genotype was more efficient than the slower maturing genotype. The WT/TDN, WT/C and pregnancy rates were higher for the early maturing genotype. The earlier maturing genotype had a greater capability to respond to improved nutrition than the slower maturing genotype. There was no simulated advantage for a higher milk production potential and no interaction was indicated between this potential and nutritional regimen. The simulation model used in this study was designed to account for trade-offs among the effects of different genetic potentials and the production environment. The simulations illustrated the tendency for these effects to be compensatory but unequally so for different genotype-environment combinations, and, consequently, the results indicate the importance of considering the management program when setting breed and individual selection goals.