Application of ultrasound for feeding and finishing animals: a review

The ability to evaluate carcass traits in live animals is of value to research, educational, and industry personnel. Ultrasonic technology has been tested since the early 1950s and continues to be under investigation as a means of accomplishing this task. The accuracy of ultrasound in predicting carcass traits is variable and is dependent on species, ultrasonic instrumentation, and(or) the skill of the technician. Based on this review, the ranges of correlation coefficients (r) for carcass traits as predicted by ultrasound to the respective carcass measurement are as follows: swine (fat .20 to .94; longissimus muscle .27 to .93), sheep (fat .42 to .95; longissimus muscle .36 to .79) and beef (fat .45 to .96; longissimus muscle .20 to .94; marbling .20 to .91). Although these correlation coefficients give an indication of the accuracy of ultrasound, it should be noted that these statistics do not reflect population variation or bias. Applications of ultrasound in swine finishing programs include the successful prediction of market weight carcass characteristics and the prediction of percentage of lean cuts before slaughter. In contrast, the application of ultrasound in lamb finishing programs has met with limited success. Most data indicate that weight and(or) visual estimations of fat are at least as accurate as ultrasound predictions of carcass composition. In beef finishing programs, ultrasound has, at times, been used successfully to predict fat and muscle traits before slaughter and beef carcass chemical composition. The ability to predict marbling, however, remains unclear and requires further investigation. Ultrasound has also been used in beef finishing programs to predict days on feed to a constant body compositional end point. When summarized, these data indicate that a single ultrasonic measurement of fat can be helpful in predicting days on feed in yearling cattle. When used alone, however, a single backfat measurement does not provide adequate accuracy. Therefore, factors such as age, sex, breed type, weight, and hip height are needed to help predict days on feed more accurately.