Submitted to: Archives of Animal Breeding
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 25, 2005
Publication Date: December 1, 2005
Citation: Mitchell, A.D., Scholz, A.M., Solomon, M.B. 2005. Estimation of body composition of pigs by a near-infrared interactance probe technique. Archive of Animal Breeding. 49(1):580-591.
Interpretive Summary: The absorbance or reflectance of light in the near infrared (NIR) range is the basis for methods used for evaluating the quality (i.e., fat, water and protein content) of a variety of agricultural products. The purpose of this study was to evaluate the possible application of NIR for estimating the composition of live pigs and their carcasses. NIR readings were made by placing a surface probe at three locations (ham, side or shoulder) on a total of 120 pigs and their carcasses. These readings were then compared to measurements of fat and protein content as determined by chemical analysis of the carcass. The NIR readings responded to differences in carcass composition, but failed to provide the accuracy needed to be used alone to predict the composition of either the live pig or carcass. However, it appears that NIR may be of value when used in conjunction with other measurements such as backfat depth and body weight. Further advances may be possible through refinement of the NIR technique
Near-infrared (NIR) interactance was evaluated as a potentially new method for estimating live body and carcass composition of pigs. Using a surface placed fiber optic probe, measurements of the live animal and carcass were made on a total of 120 pigs. These measurements were compared with lipid and protein content of soft tissue dissected from the pig carcass. NIR results were evaluated using multiple regression equations containing NIR readings at various locations on the body, combinations of wavelengths and with or without ultrasonic fat depth readings and body weight. NIR measurements made on the carcass predicted percent carcass fat (R=.71) better than did measurements made on the live animal (R=.66), however, both could be improved substantially by including live body weight in the prediction equation (R=.93 and .91). Spectral information indicated that the depth of tissue penetration and reflectance may be the primary limitation in this application of the current technology.