Dual energy X-ray absorptiometry (DXA) can be used to predict live animal and whole carcass composition of sheep

Small Ruminant Research 100 (2011) 143–152

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Dual energy X-ray absorptiometry (DXA) can be used to predict live animal and whole carcass composition of sheep T.E. Hunter a , D. Suster b , F.R. Dunshea a , L.J. Cummins c , A.R. Egan a , B.J. Leury a,∗ a b c

Melbourne School of Land and Environment, The University of Melbourne, Parkville, Vic. 3010, Australia Department of Primary Industries, Spring Street, Melbourne, VIC 3000, Australia ‘Ivanhoe’, Bulart Bridge Road, Cavendish, VIC 3314, Australia

a r t i c l e

i n f o

Article history: Received 4 March 2011 Received in revised form 30 June 2011 Accepted 1 July 2011 Available online 11 August 2011 Keywords: Sheep Body composition Carcass composition Dual energy X-ray absorptiometry

a b s t r a c t An Hologic QDR4500A dual energy X-ray absorptiometer (DXA) was used to measure live body composition in 15 second-cross wether lambs ((Border Leicester × Merino) × Poll Dorset) aged 6–8 months (17–50 kg) and 13 mature ewes (composite terminal sire line based largely on Poll Dorset, White Suffolk and Texel breeds) (44–71 kg). After slaughter, DXA scans were also performed on the whole carcasses. Values determined by DXA including total tissue mass (TTM), lean tissue mass (LTM), fat tissue mass (FTM) and bone mineral content (BMC) for the half carcass were evaluated by comparison with chemically determined composition. In the case of BMC the relationship was with chemically determined ash content. Live weight and chemically determined lean, fat and ash were strongly related to DXA-derived values for whole body TTM, LTM, FTM and BMC, respectively (R2 = 0.999, 0.988, 0.980 and 0.977, respectively). Carcass weight and chemically determined lean, fat and ash were strongly related to DXA-derived values for carcass TTM, LTM, FTM and BMC, respectively (R2 = 0.998, 0.984, 0.986 and 0.906, respectively). However, because DXA estimates were different from chemically determined values in this sample of carcasses, they needed to be adjusted with the use of appropriate regression equations to correct the inbuilt algorithms used to predict human body composition. These data demonstrate the efficacy of DXA as a non-destructive method for determining the composition of the whole body and carcasses of sheep. © 2011 Elsevier B.V. All rights reserved.

1. Introduction In Europe and Australasia there have been increasing changes in production systems and marketing of sheep meat, with consumers demanding larger and leaner lamb cuts (McLaughlin, 1992; Thatcher and Gaunt, 1992; Stanford et al., 1998; Pethick et al., 2010). Currently, the Australian lamb industry uses a number of traits such as weight, GR (‘Grade Rule’) fat depth (measured over the 12th rib, 110 mm from the midline) and m. longissimus lumborum depth as the basis of genetic improvement (Hopkins

∗ Corresponding author. Tel.: +61 3 83446341; fax: +61 3 83445037. E-mail address: [email protected] (B.J. Leury). 0921-4488/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2011.07.003

et al., 2004). While these measures may be used as indicators of lean meat yield, their usefulness is likely to diminish if selection pressure is placed on these single measures, as has been the case for the pig (Suster et al., 2003; D’Souza et al., 2004). In many parts of the world mature sheep are used for purposes other than meat production such as wool and milk. Body composition can vary considerably during the reproductive and seasonal cycles and to adequately manage animals in these systems there is a need to measure body composition in the live animal. Although liveweight is correlated with body composition (Searle, 1970; Ponnampalam et al., 2007), changes in live weight over time are difficult to interpret in the absence of more detailed information on body composition (Stanford et al., 1998). Also, increasingly sheep are being used as model

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animals to study obesity (Henry et al., 2001; Anukulkitch et al., 2007) and in order to do this, accurate measures of body composition are required. A method that has been used to determine fat, lean tissue and bone mineral composition in live pigs is dual energy X-ray absorptiometry (DXA) (Mitchell et al., 1998; Lukaski et al., 1999; Marcoux et al., 2002; Suster et al., 2003). There have been a few studies that have reported close relationships between DXA-predicted and chemically determined (Clarke et al., 1999; Dunshea et al., 2007) or dissected (Mercier et al., 2006) body composition in the half carcass of lambs. However, there has been only one that has related these measures in the live animal (Pearce et al., 2009) and the animals were not slaughtered until 11 days after scanning, sufficient time for changes in body composition and gut fill to occur. Therefore, the major aim of this study was to determine whether DXA could be used to predict chemical composition of the whole body and carcass of the sheep in vivo. 2. Materials and methods 2.1. Animals The DXA was used to determine body composition in 15 secondcross wether lambs ((Border Leicester × Merino) × Poll Dorset) aged 6–8 months (17–50 kg) and 13 mature ewes (composite terminal sire line based largely on Poll Dorset, White Suffolk and Texel breeds) (44–71 kg).

All animal procedures were approved by The University of Melbourne, Institute of Land and Food Resources Animal Ethics Committee. The animals were transported between 200 and 300 km to the Department of Primary Industries, Werribee, five days prior to the beginning of the experimental period and were housed in a shed in individual pens (0.90 m × 1.35 m) with constant access to fresh water. The animals were fed lucerne chaff to maintenance requirements (SCA, 1990). Sheep were shorn the day before DXA scanning to ensure that wool cover was as short as possible (1.5 cm) and even between all animals. Feed was removed 12 h before scanning to reduce variation in gastro-intestinal fill (Dunshea et al., 1988) while water was available until scanning.

2.2. Scanning Scanning was performed using an Hologic QDR4500A Fan Beam X-Ray Bone Densitometer (Hologic, Inc., Waltham, MA, USA) utilising the whole body scan mode (software V8.26a:3). Animals were anaesthetised using i.v. thiopentone sodium (10 mg/kg, Thiobarb, Jurox, Rutherford, NSW, Australia) prior to scanning with the DXA. Animals were positioned prone with back legs extended and front legs placed back along the side of the trunk. As the software is designed for human subjects, this position was chosen to most closely represent the position of a supine human. While humans are scanned supine, this is not possible for sheep due to the potential for ruminal regurgitation and fluid asphyxiation, the risk of which is reduced in prone sheep. Animals were closely monitored during scanning and recovery and were fed immediately after recovery 15–20 min later. Measurements made by DXA included total tissue mass (TTM), lean tissue mass (LTM), fat tissue mass (FTM) and bone mineral content (BMC). The Hologic QDR4500A DXA was equipped with a step phantom that is constructed of acrylic and aluminium. Acrylic attenuates X-ray beams in a manner similar to fatty tissue and the addition of aluminium produces materials that appear leaner (Kelly et al., 1998). This principle is exploited

Fig. 1. Dual energy X-ray absorptiometry regional analysis grid and a live animal scan image analysed with: (a) grid placement 1, the scan image was analysed as closely as possible to the human model as specified by the manufacturer except the front legs are placed in the trunk region (modified human mode); (b) grid placement 2, the body in the scan image was placed in the arm region and head in the head region.

T.E. Hunter et al. / Small Ruminant Research 100 (2011) 143–152 by the step phantom for unit calibration ensuring maintenance of accurate lean/fat composition results. The step phantom was scanned on a weekly basis. A spine phantom was also supplied by Hologic Inc. and consisted of a simulated lumbar spine, of a known bone mineral content, encased in an acrylic block. The spine phantom was scanned daily to ensure an accurate and repeatable BMC measurement. The DXA regional analysis software was used in determining body composition results. For soft tissue measurements of humans, the QDR4500 software allows the scanned image to be divided into head, arms, legs and trunk; the regional analysis grid used to do this is presented in Fig. 1a. In the first of the two positions used the entire scan was analysed as closely as possible to the human model (Fig. 1a). The pelvic region was set with the top in line with the top of the pelvis and the angled lines below the pelvis bisecting both femoral necks. The spinal region lines were placed immediately on either side of the spine and the mid-spine line placed at the level of the 13th thoracic vertebra. In the human model, arms are isolated from the trunk and leg regions but it is difficult to separate the front legs of live sheep sufficiently to enable similar positioning. Thus the position was altered to include the left and right front leg in the left and right ‘ribs’ or trunk region, respectively. This was done to enable consistency as variation in animal size affected the ability to clearly separate legs from the trunk region. In the human model, a line is set around the level of the chin to separate the head region. Since it is difficult to maintain a consistent straight head position for sheep, the 5th cervical vertebra was chosen as the demarcation point and the line consistently placed at this point. In the second position the scan was placed in the left arm region, leaving all other regions empty (Fig. 1b). The modified human mode was assessed as this was the manufacturer’s recommendation. The left arm mode was used as this regional analysis provided the most precise results in a previous in vivo study with pigs (Suster et al., 2003) and has been used in studies of half carcasses where the head has been removed (Dunshea et al., 2007). Also, the arm region provided in vivo scan data that were more repeatable than when other regions of the regional analysis grid were used in pigs (Suster et al., 2006). A single scan of a sheep was selected to further examine the effect of the horizontal line in the spinal region. This scan was reanalysed 14 times with the only difference being the position of this horizontal, which was moved approximately 1–2 vertebrae each time, from the bottom of the region (near the pelvis) to the top (near the first cervical vertebra).

2.3. Slaughter The following day, after 12 h without feed, animals were slaughtered using commercial practices. After exsanguination, the blood was collected, weighed and sampled. All organs and digestive tracts were removed and weighed and the digestive tract was emptied. The contents of the forestomach and abomasum (rumen, reticulum, omasum and abomasum together), small intestine and large intestine were weighed and sampled separately. The empty digestive tract and all organs were frozen and stored for further analysis. Feet and heads from three of each class of sheep were weighed, frozen and stored. Skins were weighed and three representative samples were taken from each skin – left foreleg, centre back and right hindleg. These were frozen and stored. All samples were frozen rapidly at −35 ◦ C to minimise moisture loss and then stored at −5 ◦ C.

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2.4. Carcass scanning The entire carcasses were hung by the Achilles and chilled overnight and cold carcass weights taken 24 h post slaughter prior to DXA scanning. As for live animals, the carcasses were scanned prone with the neck presented almost perpendicular to the carcass and DXA table which increases the height from the table to the top of the neck. To test whether height of the neck would impact on estimates of body composition the necks of carcasses of three wethers and four ewes were cut halfway through. The carcasses were then re-scanned with the neck lying parallel to the carcass and table to examine the effect of the height above the table. After scanning, carcasses were frozen rapidly at −35 ◦ C and stored at −5 ◦ C until further processing. Water loss during storage was determined by the difference between weight before and after storage and was insignificant. 2.5. Carcass and body composition Frozen carcass, skin, blood and viscera from all animals and head and feet from six representative animals were minced separately, homogenised and subsamples were collected for chemical analysis of dry matter, fat, protein and ash. Dry matter content was measured by weight loss after 24 h drying at 102 ◦ C, and water content was calculated by difference. Ash was determined by residue weight following combustion of oven dry samples for 2 h at 650 ◦ C in a muffle furnace. Additional samples were freeze-dried prior to chemical lipid and protein analyses. Freezedried samples were analysed for lipid content by soxhlet extraction with diethyl ether (Atkinson et al., 1972) and protein by the Kjeldahl method [Kjeldahl predicted N × 6.25, assuming protein is 16% N (AOAC, 2000)]. 2.6. Statistical analyses General linear regression analysis was used to obtain correlation equations between the indirect measurements from the DXA scans and the direct chemical measurements post-slaughter (Genstat; Version 11, release 11.1.0.1575). To increase the homogeneity of residuals and to improve interpretation, the response and independent variables were logarithmically transformed (to base 10) before conducting the regression analysis (Suster et al., 2003, 2006). The live animal scans were analysed using two different grids and these data are compared and contrasted whereas carcass scans were only analysed in the left arm mode Initially animal type (breed, sex and age) was included in the models but with very few exceptions (carcass composition) the effect was non-significant and even where it was significant the effect was negligible. Therefore, this term was dropped from the models reported in the tables. However, for completeness the individual regressions are reported for whole body and carcass composition in Fig. 2.

3. Results The DXA-derived TTM was lower (−3.8%, P < 0.001) than measured live weight regardless of the regional grid setting used to determine body composition (Table 1). DXA-derived LTM and FTM were not different from chemically determined tissue masses when the manufacturer’s settings for the supine human mode (Fig. 1a) were used to

Table 1 Summary statistics for whole body chemical composition (kg) and dual energy X-ray absorptiometry (DXA) values (kg) determined in the live animal (n = 28) in the modified human mode (MH) and left arm mode (LA).a Itemd

TTM LTM FTM BMC a b c d e

DXA-derived MHb

Chemical

DXA-derived LAc

P-value

Mean

SEMe

Mean

SEM

 (%)

Mean

SEM

 (%)

45.24x 32.51x 10.67x 1.44x

2.850 1.590 1.210 0.097

43.53y 32.15x 10.27x 1.09y

2.660 1.580 1.112 0.091

−3.8 −1.1 −3.7 −24.2

43.52y 33.51y 8.96y 1.05y

2.660 1.700 0.999 0.089

−3.8 3.1 −16.0 −26.7

Values with a different lower case superscript are significantly different (P < 0.05). Scanned image divided into head, arms, legs and trunk as described in Fig. 1a. Scanned image placed with the body in the left arm region and the head in the head region as described in Fig. 1b. TTM, total tissue mass; LTM, lean tissue mass; FTM, fat tissue mass; BMC, bone mineral content. SEM, standard error of the means.

<0.001 <0.001 <0.001 <0.001

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1.9 1.8

Log live weight

b

Y= -0.038 + 1.03 X (+ 0.0004 for ewes)

Log whole body lean weight

a

SED = 0.0047; R2= 0.999

1.7 1.6 1.5 1.4 1.3 1.2

1.7 Y= 0.072 + 0.943 X (+ 0.004 for ewes)

SED = 0.012; R2= 0.991

1.6 1.5 1.4 1.3 1.2 1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

1.1

1.2

Log DXA weight

c

d

Y=- 0.11 + 1.21 X (-0.039 for ewes) 0.971

Log whole body ash weight

Log whole body fat weight

SED = 0.0578;

R2=

1.4

1.5

1.6

1.7

Log DXA lean weight

1.5 1.3

1.3

1.1 0.9 0.7 0.5 0.3

Y= 0.14 + 0.70 X (+ 0.019 for ewes) SED = 0.0246; R2= 0.980

0.3

0.1

-0.6

-0.4

-0.2

0.0

0.2

-0.1

0.1 -0.1 0.2

0.4

0.6

0.8

1.0

1.2

1.4

Log DXA fat weight

-0.3

Log DXA bone mineral weight

Fig. 2. Relationships, in the live animal, between the log (base 10) of dual energy X-ray absorptiometry (DXA) derived and (a) total tissue mass, and chemically determined (b) lean tissue mass, (c) fat tissue mass and (d) ash (or bone mineral for DXA measures) content using the left arm region for scan placement for wether lambs () and ewes (). Dashed line is line of identity. Regression equations without inclusion of a term to differentiate animal type (breed/sex/age) are shown in Table 1. The P values for inclusion of the term to differentiate the breed/sex/age were 0.88, 0.53, 0.24 and 0.25 for equations shown in (a)–(d), respectively.

partition the sheep image (−1.1% and −3.7%, respectively, P > 0.20). However, when the body in the scan image was placed in the left arm region and the head placed in the head region, LTM was higher (+3.1%, P < 0.001) and FTM was lower (−16.1%, P < 0.001) than the chemically determined values. The ash content of the whole body of live animal was underestimated by DXA-derived BMC in both regional modes (−24.2% and −26.7%, respectively, P < 0.001). The DXA-derived TTM was strongly related to whole body, empty body and carcass weight (Table 2). The slope of the relationship between whole body scale weight and DXA-derived TTM was very close but significantly different than unity (1.03 ± 0.0055). DXA-derived TTM was progressively less precisely related to whole body, empty body and carcass weights. Inclusion of animal type in the model did not improve (P = 0.88) the model fit for whole body weight (Fig. 2a). Incorporating subregions into the scanned image did not alter the DXA-derived estimates of weight (Table 2). The DXA-derived LTM was highly correlated with whole body, empty body and carcass LTM (Table 2). The

relationship between DXA-derived LTM derived using the modified human mode and whole body LTM was close to unity (0.99 ± 0.021) with an intercept that was not different from zero (Table 2). The modified human mode resulted in lower DXA-derived LTM values than the left arm mode, although the latter were slightly more highly correlated with chemically determined values (Table 2). Inclusion of animal type in the model did not improve (P = 0.53) the model fit for whole body LTM (Fig. 2b). DXA-derived LTM was progressively less precisely related to whole body, empty body and carcass LTM. The DXA-derived FTM was highly correlated with whole body, empty body and carcass FTM (Table 2). The DXAderived FTM determined in the modified human mode underestimated chemically determined FTM as indicated by a slope greater than unity (1.12 ± 0.031) with an intercept that was less than zero. The modified human mode resulted in higher DXA-derived FTM values than the left arm mode with the former being slightly more highly correlated with chemically determined values. Inclusion of

T.E. Hunter et al. / Small Ruminant Research 100 (2011) 143–152

147

Table 2 Precision of models for log chemical composition (kg) from log dual energy X-ray absorptiometry (DXA) values (kg) determined in the live animal (n = 28) in the modified human (MH) and left arm (LA) mode. Body component Weight Whole body Empty body Whole carcass Lean tissue Whole body Empty body Whole carcass Fat tissue Whole body Empty body Whole carcass Ash Whole body Empty body Whole carcass

SEDa

R2

−0.040 (±0.0089) + 1.03 (±0.0055) log TTMMH or LA −0.176 (±0.0258) + 1.09 (±0.0159) log TTMMH or LA −0.533 (±0.0356) + 1.17 (±0.0219) log TTMMH or LA

0.0046 0.0133 0.0183

0.999 0.994 0.991

0.020 (±0.0316) + 0.990 (±0.0211) log LTMMH 0.056 (±0.0262) + 0.955 (±0.0173) log LTMLA −0.113 (±0.0488) + 1.047 (±0.0326) log LTMMH −0.076 (±0.0427) + 1.011 (±0.0282) log LTMLA −0.515 (±0.0549) + 1.146 (±0.0367) log LTMMH −0.474 (±0.0482) + 1.106 (±0.0319) log LTMLA

0.0140 0.0119 0.0216 0.0194 0.0243 0.0220

0.988 0.991 0.974 0.979 0.973 0.978

−0.110 (±0.0299) + 1.12 (±0.0308) log FTMMH −0.085 (±0.0356) + 1.16 (±0.0389) log FTMLA −0.112 (±0.0299) + 1.12 (±0.0307) log FTMMH −0.088 (±0.0355) + 1.16 (±0.0388) log FTMLA −0.264 (±0.0401) + 1.11 (±0.0412) log FTMMH −0.235 (±0.0481) + 1.15 (±0.0526) log FTMLA

0.0482 0.0583 0.0481 0.0582 0.0654 0.0788

0.980 0.978 0.980 0.971 0.964 0.946

0.139 (±0.0050) + 0.722 (±0.0213) log BMCMH 0.149 (±0.0047) + 0.731 (±0.0203) log BMCLA 0.124 (±0.0052) + 0.735 (±0.0222) log BMCMH 0.134 (±0.0049) + 0.745 (±0.0211) log BMCLA −0.0471 (±0.0081) + 0.647 (±0.0344) log BMCMH −0.0380 (±0.0076) + 0.658 (±0.0326) log BMCLA

0.0263 0.0248 0.0275 0.0258 0.0426 0.0399

0.977 0.980 0.976 0.979 0.929 0.938

SED, standard error of the differences.

animal type in the model did not improve (P = 0.24) the model fit for whole body FTM (Fig. 2c). DXA-derived FTM was less precisely related to whole body, empty body and carcass FTM as weight of FTM increased. The DXA-derived BMC was highly correlated with whole body, empty body and carcass ash (Table 2). When averaged over the full range of weights encountered, DXA-derived BMC underestimated whole body ash content. However, regression analyses revealed that this effect was not systematic and the degree of underestimation was less at greater live weights while inclusion of animal type in the model did not improve (P = 0.25) the model fit for whole body BMC (Fig. 2d). The modified human mode resulted in higher DXA-derived BMC values than the left arm mode although the latter were slightly more highly correlated with chemically determined values. DXA-derived BMC was less precisely related to whole body, empty body and carcass ash content as weight of BMC increased. Moving the horizontal line in the spine region from the bottom of the region (near the pelvis) to the top of the region (near the first cervical vertebra) had no effect on DXA derived TTM in the modified human mode. However DXA derived LTM increased while FTM and BMC decreased as the line was moved proximally (Fig. 3). The DXA-derived carcass TTM was lower (−9.3%, P < 0.001) than measured scale weight regardless of the regional grid setting used to determine body composition (Table 3). When the body in the scan image was placed in the modified human mode, carcass LTM was lower (−17.3%, P < 0.001) and FTM was higher (+9.4%, P < 0.001) than the chemically determined values (Table 3). However, when the carcass in the scan image was placed in the left arm region and the head placed in the head region, both LTM

(−4.4%, P < 0.001) and FTM (−17.9%, P < 0.001) were lower than the chemically determined values (Table 3). The ash content of carcass was underestimated by DXA-derived BMC in both regional modes (−12.9% and −27.9%, respectively, P < 0.001). The DXA-derived carcass TTM was strongly related to carcass weight (Table 4). The slope of the relationship between whole body scale weight and DXA-derived TTM was very close but significantly different than unity (1.04 ± 0.0078). Inclusion of animal type in the model TTM

LTM

FTM

BMC

120 110

% of Position

a

Best prediction model (values in parentheses are standard errors)

100 90 80 70 60 0

1

2

3

4

5

6

7

8

9 10 11 12 13 14

Position Fig. 3. DXA derived estimates of total tissue mass (TTM), lean tissue mass (LTM), fat tissue mass (FTM) and bone mineral content from a single scan of a sheep but where the position of the horizontal line in the spinal region was moved from the pelvis (Position 1) to the first cervical vertebrae (Position 14).

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Table 3 Summary statistics for whole carcass chemical composition (kg) and dual energy X-ray absorptiometry (DXA) values (kg) (n = 28) determined in the modified human mode (MH) and left arm mode (LA).a Itemd

TTM LTM FTM BMC a b c d e

DXA-derived MHb

Chemical

DXA-derived LAc

P-value

Mean

SEM

Mean

SEM

 (%)

Mean

SEM

 (%)

24.61x 16.42x 7.26x 0.93x

1.754 0.948 0.801 0.062

22.33y 13.58y 7.94y 0.81y

1.533 0.690 0.821 0.067

−9.3 −17.3 9.4 −12.9

22.33y 15.70z 5.96z 0.67z

1.533 0.893 0.622 0.057

−9.3 −4.4 −17.9 −27.9

e

<0.001 <0.001 <0.001 <0.001

Values with a different lower case superscript are significantly different (P < 0.05). Scanned image divided into head, arms, legs and trunk as described in Fig. 1a. Scanned image placed with the body in the left arm region and the head in the head region as described in Fig. 1b. TTM, total tissue mass; LTM, lean tissue mass; FTM, fat tissue mass; BMC, bone mineral content. SEM, standard error of the means.

resulted in a small but significant (P = 0.001) improvement in the model fit for carcass weight (Fig. 4a). Incorporating subregions into the scanned image did not alter the DXA-derived estimates of carcass weight (data not shown).

a

b 1.5

1.6 Y= 0.016 + 1.014 X (+ 0.012 for ewes)

Log carcass lean weight

sed = 0.0061; R2= 0.999

Log carcass weight

The DXA-derived carcass LTM was highly correlated with carcass LTM (Table 4). Carcass LTM was underestimated by DXA-derived LTM using the modified human mode as indicated by a slope greater than unity

1.4

1.2

1.0

Y= 0.088 + 0.931 X (+ 0.025 for ewes)

sed = 0.015; R2= 0.990

1.3

1.1

0.9

0.7

0.8 0.8

1.0

1.2

1.4

1.6

0.7

0.9

Log DXA weight

c

sed = 0.0417; R2= 0.932

Log carcass ash weight

Log carcass fat weight

Y= 0.049 + 0.56 X (+ 0.045 for ewes)

sed = 0.0367; R2= 0.988

0.7 0.5 0.3 0.1

-0.1

0.1

0.3

0.5

0.7

1.5

0.3

d

Y=- 0.066 + 1.22 X (-0.047 for ewes)

-0.3

1.3

Log DXA lean weight

1.1 0.9

1.1

0.9

0.1

-0.9

-0.7

-0.5

-0.3

-0.1 -0.1

0.1

-0.3

1.1 -0.5

-0.3

Log DXA fat weight

Log DXA bone mineral weight

Fig. 4. Relationships, in the carcass, between the log (base 10) of dual energy X-ray absorptiometry (DXA) derived and (a) total tissue mass, and chemically determined (b) lean tissue mass, (c) fat tissue mass and (d) ash (or bone mineral for DXA measures) content using the left arm region for scan placement for wether lambs () and ewes (). Dashed line is line of identity. Regression equations without inclusion of a term to differentiate animal type (breed/sex/age) are shown in Table 4. The P values for inclusion of the term to differentiate the breed/sex/age were 0.001, 0.004, 0.021 and 0.077 for equations shown in (a)–(d), respectively.

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Table 4 Precision of models for log carcass chemical composition (kg) from log dual energy X-ray absorptiometry (DXA) values (kg) determined in the full carcass (n = 28) placed in the modified human mode (MH) and left arm mode (LA). Body component

Best prediction model (values in parentheses are standard errors)

SEDa

R2

Carcass weight Lean tissue

−0.009 (±0.0103) + 1.04 (±0.00777) log TTM −0.088 (±0.0318) + 1.15 (±0.0283) log LTMMH 0.031 (±0.0265) + 0.990 (±0.0224) log LTMLA −0.102 (±0.0164) + 1.06 (±0.0189) log FTMMH −0.048 (±0.0200) + 1.16 (±0.0266) log FTMLA 0.032 (±0.0108) + 0.626 (±0.0386) log BMCMH 0.087 (±0.0114) + 0.637 (±0.0346) log BMCLA

0.0073 0.0189 0.0173 0.0312 0.0401 0.0489 0.0435

0.998 0.984 0.986 0.992 0.986 0.906 0.926

Fat tissue Ash a

SED, standard error of the differences.

(1.15 ± 0.0283) whereas the slope was close to unity when LTM was determined in the LA mode (0.990 ± 0.0224) (Table 4, Fig. 4b). Inclusion of animal type in the model resulted in a small but significant (P = 0.004) improvement in the model fit for carcass LTM (Fig. 3b). The DXA-derived carcass FTM was highly correlated with carcass FTM (Table 4). Carcass FTM was underestimated by DXA-derived FTM using both the modified human and the LA modes as indicated by slopes greater than unity (1.06 ± 0.0189 and 1.16 ± 0.0266) (Table 4, Fig. 4c). Inclusion of animal type in the model resulted in a small but significant (P = 0.021) improvement in the model fit for carcass FTM (Fig. 3c). The DXA-derived carcass ash content was highly correlated with carcass BMC (Table 4). When averaged over the full range of weights encountered, DXA-derived BMC underestimated whole body ash content. However, regression analyses revealed that this effect was not systematic and the degree of underestimation was less at greater live weights as indicated by a convergence of the model and the line of unity (Fig. 4d). Inclusion of animal type in the model did not significantly (P = 0.077) improve the model fit for carcass ash weight (Fig. 3c). Cutting through the neck reduced the total height of the carcass as well as reducing the depth of tissue around the neck area. Consequently, the DXA scans using this presentation increased TTM (P < 0.001), LTM (P = 0.017) and BMC (P = 0.016) compared with the carcasses presented with a perpendicular neck (Table 5). The FTM was not affected (P = 0.98) by the presentation of the neck. While the estimates of TTM, LTM and BMC were quantitatively more similar to chemical composition the differences were still

different (P < 0.001) and would require appropriate adjustment algorithms to predict carcass composition. 4. Discussion Importantly, the present data confirm that DXA-derived estimates of total and individual tissue masses are highly related to, and can be used to predict, chemical composition of live sheep as well as whole sheep carcasses. However, it is important to note that the regression coefficients generally differ from unity and therefore appropriate predictive equations need to be used to quantitatively predict body composition. Also, there do appear to be anomalies when compared to other species and spatial positioning, possibly because of elevation of the whole carcass above the DXA table, or the presence of wool in the case of the live animal (Hunter, 2000). For example, previous studies have shown that DXA-derived TTM was virtually identical to measured live weight for the live pig (Suster et al., 2003), pig full and half carcasses (Suster et al., 2003, 2004) and sheep half carcasses (Dunshea et al., 2007) whereas, in the present study whole body and carcass TTM were underestimated by 3.8% and 9.3%, respectively. The live sheep and carcass presents some spatial difficulties compared to other species such as humans and pigs when being scanned using DXA. Humans are normally scanned in a supine position with arms placed at their side (Anon., 1996) whereas pigs are scanned in a prone position with their fore- and hind-legs placed in similar position on the grid as the human (Suster et al., 2003). It is difficult to place a sheep in a supine position and so we scanned the sheep in the prone position with front

Table 5 Summary statistics for whole carcass chemical composition (kg) and dual energy X-ray absorptiometry (DXA) values (kg) (n = 7) determined in the left arm mode (LA) with neck extended or neck cut.a Itemd

TTM LTM FTM BMC a

DXA-derived LA neck extendedb

Chemical

DXA-derived LA neck cutc

P-value

Mean

SEMe

Mean

SEM

 (%)

Mean

SEM

 (%)

29.26x 18.70x 9.32x 1.23x

2.603 1.369 1.342 0.131

26.34y 18.09y 7.37y 0.78y

2.208 1.261 1.030 0.081

−10.0 −3.3 −20.9 −36.6

26.59z 18.14z 7.37y 0.80z

2.228 1.248 1.088 0.081

−9.1 −3.0 −20.9 −35.0

<0.001 <0.001 <0.001 <0.001

Values with a different lower case superscript are significantly different (P < 0.05). Scanned image placed with the body in the left arm region and the head in the head region as described in Fig. 1b but with the neck extended perpendicular as a result of hanging method. c Scanned image placed with the body in the left arm region and the head in the head region as described in Fig. 1b but with the neck cut half way down and placed on DXA table. d TTM, total tissue mass; LTM, lean tissue mass; FTM, fat tissue mass; BMC, bone mineral content. e SEM, standard error of the means. b

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legs placed back along the side of the trunk. The sheep carcass was also scanned prone but with the front legs outstretched due to positioning of the legs after hanging. Interestingly, Lambrinoudaki et al. (1998) found that DXA derived FTM and BMC were lower while DXA-derived LTM was higher when humans were scanned in the prone rather than supine position which may explain some of the findings discussed below. Regardless, the present data suggest that live sheep can be scanned in a prone position and excellent estimates of whole body, empty body and carcass composition can be obtained regardless of the scanning grid employed, provided appropriate correction algorithms are used. While the modified human mode appears to provide quantitatively more accurate estimates of chemical body and carcass composition, the positioning of the horizontal spinal line is critical and incorrect placement can introduce large errors. For this reason, and for consistency with previous applications with live pigs and half sheep and pig carcasses, it is proposed to use the LA mode in future studies. The DXA predictions of chemically determined LTM were more precise than those for lipid and ash. This is consistent with other studies with other species (Mitchell et al., 1996; Lukaski et al., 1999; Suster et al., 2003) and sheep (Pearce et al., 2009). Measurements made by DXA are based on the differential attenuation of high and low energy X-rays by bone, lean tissue and lipid with each of these components attenuating X-rays at different rates. However, X-ray attenuation coefficients for LTM are essentially derived from body water and estimated, by the QDR4500 software, with the assumption that the LTM of the subject is 73.2% water (Anon., 1996). Importantly, the water content in the gastrointestinal tract of live animals causes overestimation in the DXA-derived LTM because it is not included in the empty body measurement. While all animals had feed removed for a standard length of time (12 h) before scanning to reduce these effects, small ruminants such as sheep have a greater proportion of their live weight as gut water than monogastrics, possibly leading to an overestimation of LTM. In the present study whole body LTM was overestimated by 3% when assessed using the LA mode but not when using the MH mode possibly because of in-built algorithms that adjust for gut water in the regional analyses software (Suster et al., 2006). On the other hand, Pearce et al. (2009) found that whole body LTM was overestimated by 3-fold when using the Norland DXA in the LA mode. These authors did not attempt to reconcile this gross overestimation, which is surprising given that the relationships between DXA derived and actual chemical lean in the carcass were quantitatively much closer. Hunter (2000) found that DXA derived LTM was decreased (−4.5 kg) and FTM increased (+2.5 kg) after sheep were shorn and that estimated TTM decreased to a greater extent than the amount of wool removed. The sheep in the present study were recently shorn and had minimal wool cover while the amount of wool cover is not mentioned in the study of Pearce et al. (2009). It is possible that the Merinos used by Pearce et al. (2009) could have substantial wool coverage which could have at least partially contributed to the overestimation of LTM in the live sheep.

The DXA derived carcass LTM underestimated chemical carcass LTM composition whereas in previous studies carcass LTM has been overestimated by DXA in sheep (Clarke et al., 1999; Dunshea et al., 2007) and pig (Suster et al., 2003, 2004, 2005) half carcasses. In part this may be due to the considerable underestimation of carcass TTM in the present study (ca −9%). This is possibly because of the height of the top of the carcass above the table (up to 45 cm) as a result of the carcass shape after achilles hanging. In this context, Aloia et al. (1995) found that as tissue thickness increases the whole body soft tissue counted becomes less than actual body weight in humans. Furthermore, although FTM was not substantially affected, the fat-free mass (LTM and BMC) was decreased at high tissue depths. In the present study, lowering the height of the neck region by cutting the neck and laying it parallel to the carcass and DXA table increased TTM, LTM and BMC but not FTM. The present data have shown that carcass composition can be determined by scanning whole carcasses and using appropriate adjustment algorithms. However, it may be easier and more accurate to use half carcasses scanned side on in the LA mode (Dunshea et al., 2007) when this is possible. The DXA-derived estimates of whole body FTM were underestimated in the LA mode but not in the MH mode with the underestimation more pronounced at higher FTM (Fig. 2c). Likewise, Suster et al. (2003) found that the Hologic QDR 4500 underestimated whole FTM in pigs, particularly at higher FTM. Pearce et al. (2009) also found that FTM was underestimated by DXA in sheep. The DXA derived carcass FTM was also underestimated relative to chemical half carcass composition as was the case for the pig half carcass (Suster et al., 2003, 2005) or the sheep half carcass (Clarke et al., 1999; Dunshea et al., 2007). Similarly, DXA underestimated dissected fat in the half carcass of sheep (Mercier et al., 2006). Although FTM primarily consists of lipid, it is not totally anhydrous. To correct for this, the QDR4500 DXA software assumes FTM to be a combination of lipid (91.4%) and water (8.6%) (Anon., 1996). Importantly, the estimated water that is incorporated in the DXA-derived FTM value is not measured from water within body fat but rather from the whole body water pool. This being the case, alterations in body water will also affect the FTM prediction although the extent to which the body water component influences the fat measurement in live animals is unclear, particularly in small ruminants such as sheep that may contain a substantial amount of gut water. Because adipose tissue hydration decreases with increasing total body fat and animal age (DiGirolamo and Owens, 1976; Suster et al., 2004) the estimated FTM may also decrease if a constant water and lipid content is assumed. Alternatively, the increasing tissue thickness with animal size may provide some explanation for the underestimation. The degree of X-ray penetration of the body, and thus the subsequent signal for the DXA measurement, decreases with body thickness reducing the efficiency at which attenuation can be determined (Aloia et al., 1995; Kelly et al., 1998). In this context, the difference in chemical FTM and DXA derived carcass FTM increased with increasing height above the table (data not shown).

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The DXA procedure has been reported to provide a reliable measurement of BMC and is the clinical method of choice for measurement of bone density (Lukaski, 1993). In the present study, as with others (Suster et al., 2003; Dunshea et al., 2007; Pearce et al., 2009) the poorest correlation was found between BMC and chemical ash content. Differences between the measures may be related to the fact that non-osseous minerals are included in the measure of chemical ash. Also, the DXA technology is unable to determine the composition of non-mineral material within the bone, specifically brain and marrow (Tothill, 1995), because it is masked by surrounding bone tissue. Thus, the extent of the influence of non-mineral bone components on the DXA-derived BMC value is unknown and may explain some of the inaccuracy between DXA-derived and chemically determined values. The choice of analysis mode largely depends upon whether there is interest in regional body composition analysis as both modes provided excellent predictions of body and carcass composition. For the live animal scans the MH mode provides quantitatively the closest approximations to chemical composition, quite likely because of in built adjustment algorithms that account for the presence of water in the lumen of the gut (Suster et al., 2006). The MH mode also provides information about regional distribution of different tissues although the positioning of the horizontal spinal delineation line is critical. On the other hand, for the carcass scans the LA mode provides quantitatively the closest approximations to chemical composition, quite likely because there was no need to adjust for gut water. At least for the live pig, the most repeatable results were obtained by placing the entire body in the LA region and the head in the head region of the DXA regional analysis grid (Suster et al., 2006). 5. Conclusion Dual energy X-ray absorptiometry provided an accurate measurement of chemical composition of the whole body, the empty body and carcass of the sheep across a wide range of live and carcass weights. However, DXA estimates need to be adjusted with the use of appropriate regression equations to correct the in-built algorithms. For ease of measurement it is recommended that the scan image be positioned in the left arm region of the software regional analysis grid. DXA is a practical and accurate method for tracking changes in fat content in the live animal and will help in our understanding of some of the effects of management practices and genetic selection on lean, fat and bone mineral composition of sheep. DXA will also prove an invaluable tool in the study of obesity using sheep models. References Aloia, J.F., Vaswani, A., Ma, R., Raster, E., 1995. Comparative study of body composition by dual-energy X-ray absorptiometry. J. Nucl. Med. 36, 1392–1397. Anon., 1996. Hologic, I. QDR 4500 Fan Beam X-ray Densitometer, User’s Guide, Waltham, USA. Anukulkitch, C., Rao, A., Dunshea, F.R., Blache, D., Lincoln, G.A., Clarke, I.J., 2007. Influence of photoperiod and gonadal status on food intake, adiposity, and gene expression of hypothalamic appetite regulators in

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