A study of operator effects on ultrasonic measures of fat depth and longissimus muscle area in cattle, sheep and pigs.

Abstract

Use of real-time ultrasonography in meat animal improvement programs has increased largely as a result of the perceived accuracy of such instruments in measuring longissimus muscle area (LMA) and fat depth (BF). The objective of this study was to examine operator effects for ultrasonic determination of BF and LMA in market-weight cattle, sheep and pigs. The day prior to slaughter, five persons scanned 45 pigs, 32 sheep and 18 cattle at the last rib using an A-mode Ithaco Model 731AM101 body composition meter (ABF) and a Johnson and Johnson Ultrasound 210DX B-mode scanner fitted with a 3.0 MHz probe. All operators measured their own B-mode recordings (OBF, OLMA); an independent, experienced technician also obtained measurements from all recordings (TBF, TLMA). Species x machine x operator interaction effects were detected (P less than .001) for ultrasonic BF. Within-species analyses also revealed that the machine x operator interaction was important (P less than .001) for all species. Analyses of ABF, OBF, TBF, OLMA and TLMA detected species x operator interactions (P less than .001) for all traits except TLMA (P less than .20). Assuming a random model with animal, operator and residual effects, variance components were estimated by maximum likelihood for each species. Repeatabilities, calculated as the intraclass correlation among animals for BF and LMA scanned and interpreted by different operators, were .13, .21 and .51 (OBF) and .28, .15 and .29 (OLMA) for cattle, sheep and pigs, respectively, indicating the importance of operator effects. Repeatabilities of TBF were .90, .42 and .68 and of TLMA were .19, .55 and .65 for cattle, sheep and pigs, respectively, indicating the importance of image interpretation in determining operator effects associated with use of the 210DX B-mode scanner. Technical training standards must, therefore, be established for operators of such equipment.

Prediction of carcass lean content by real-time ultrasound in Pietrain and negative stress Pietrain

“…The carcass lean content is calculated from backfat thickness and longissimus muscle depth between the third and fourth last ribs, and these measurements are then converted into an estimate value of lean meat content by the respective equipment (Ministère des Classes Moyennes et de l 'Agricultur e , 1999). The correlation between backfat thickness, longissimus muscle depth and longissimus muscle area measured on carcasses, and those corresponding to live animal measurements done by real-time ultrasound, are high with good repeatability (McLaren et al, 1991;Fischer, 1997;Szabo et al, 1999). Ultrasonic techniques therefore offer the possibility of predicting carcass composition when animals are scanned in vivo (Sather et al, 1996 ;Szabo et al, 1999;Hulsegge et al, 1999).…”

In vivo estimation of lamb carcass composition by real-time ultrasonography

“…The use of ultrasound technology to estimate carcass composition in sheep saw the early studies with several authors (Edwards et al, 1989;Fortin & Shrestha, 1986;Hamby, Stouffer, & Smith, 1986;Jones, Walton, Wilton, & Szkotnicki, 1982& McLaren et al, 1991 with little expectation. The initial cost-effective of the equipment, the small size of fat thickness comparing with other species, the lack of variation in subcutaneous tissue, and the presence of wool were the main limitations of the utility of ultrasound in sheep.…”

Use of dual-energy x-ray absorptiometry in non-ruminant nutrition research

“…Many of these measurements are obviously related to total body weight or carcass wholesale cut weight, but they are of limited value for determining compositional patterns (Pomar et al, 2001;Pomar et al, 2009). Ultrasonic measurements of backfat and loin depth are taken on the assumption that these depths are closely related to body (or carcass) lean and fat masses (McLaren et al, 1991). These ultrasonic measurements have to be taken at specific body locations by experienced operators (McLaren et al, 1991;Oviedo-Rondón et al, 2007;Case et al, 2012).…”