Ewe whole body composition predicted in vivo by real-time ultrasonography and image analysis

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ContentslistsavailableatScienceDirect

Small

Ruminant

Research

j o u r n a l ho me p ag e :w w w . e l s e v i e r . c o m / l o c a t e / s m a l l r u m r e s

Short

communication

Ewe

whole

body

composition

predicted

in

vivo

by

real-time

ultrasonography

and

image

analysis

S.R.

Silva

a,∗

_,

_J.

_Afonso

b

_,

_C.M.

_Guedes

a

_,

_M.J.

_Gomes

a

_,

_V.A.

_Santos

a

_,

_J.M.T.

_Azevedo

a

_,

A. Dias-da-Silva

a

a_CECAV,_Universidade_de_{Trás-os-Montes}_e_Alto_Douro,_5001-801_Vila_Real,_Portugal b_CIISA,_FMV,_ULisboa,_Avenida_da_Universidade_Técnica,_1300-477_Lisboa,_Portugal

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Received26June2015

Receivedinrevisedform12January2016 Accepted29January2016

Availableonline1February2016 Keywords:

Matureewes

Chemicalbodycomposition Real-timeultrasound

a

b

s

t

r

a

c

t

Therelationshipbetweenultrasoundmeasurementsandtheemptybodychemicalcompositionofmature eweswasstudiedintwobreeds.Thebreedswereamilk-producingbreedChurradaTerraQuente—CTQ (n=33;liveweight42.0±7.3kg,mean±SD),andameatbreedIledeFrance—IF(n=23;liveweight 60.7±9.1kg,mean±SD).Fatandmuscledepthsweremeasuredintheliveanimalsbyreal-time ultra-soundscanning(RTU;7.5MHzprobe)overthe13ththoracic,andbetweenthe3rdand4thlumbar vertebrae,andtotaltissuedepthoverthe11thrib.Followingslaughter,thecarcassandnon-carcass componentsoftheemptybodywerecombinedandsubjectedtochemicalanalysisandassessmentof energyvalue.DataobtainedbyRTUafterimageanalysiswasusedtodevelopsimpleandmultiple regres-sionmodelsforeachbreed.ThetraitsmostaccuratelyestimatedfromsingleRTUmeasurementswere theabsolutevaluesforfatcontentandenergyvalueoftheemptybody.Therespectivecoefficientsof determination(R2₎_for_IF_and_CTQ_ewes_using_subcutaneous_fat_depth_over_the_13th_thoracic_vertebra were0.768and0.908forfat,0.821and0.900forenergy;andformeasurementsbetweenthe3rdand4th lumbarvertebraewere0.845and0.911forfat,0.852and0.906forenergy.Allthesecoefficientswere sig-nificant(P<0.01).ThebestpredictionmodelsincludedonetothreeRTUmeasurementsandwerebetter forCTQewes,whereadjustedR2_values_ranged_from_0.923_(P_<_0.001)_for_water_to_0.969_(P_<_0.001)_for protein,thanforIFewes,wheretherangewas0.394(P<0.01)forproteinto0.940(P<0.001)forfat.The resultsrevealedgoodestimatesofthefatandenergycontentoftheemptybodyofbothbreedsandalso goodestimatesofproteincontentforCTQewes,butpoorestimatesofproteincontentforIFewes,with thebestpredictionmodelsforeachbodycomponentbeingdifferentfromeachbreed.Consequently,itis concludedthatpredictivemodelsthatarespecifictothebreedandcircumstancesofthestudyinwhich theyaretobeusedwillhavetobeestablishedtohaveapracticalapplication.

1. Introduction

Theknowledgeofchemicalbodycompositionisfundamentalto studytheeffectofnutritionalandgeneticfactorsonlivestock pro-duction.Bodycompositionstudiesinmeatanimalshavefocused primarilyonthosechangesthatoccurduringthegrowthofthe ani-malupto“marketweight”,butalsoonchangesthatoccurduring pregnancyandlactation(Mitchell,2007).Eventoday,dissection and chemical analysis representthe standard for body compo-sitiondeterminationoffarmanimals.However,suchtechniques raiseseveralproblems(e.g.,ethicalproblems,theimpossibilityof

∗ Correspondingauthor.Fax:+351259350482. E-mailaddress:ssilva@utad.pt(S.R.Silva).

withinanimalcomparisonsandneedoflargenumbersofanimals, veryintensivelaborandhighcost).Toovercometheseconstraints severalinvivoimagemethodologieshave beenproposedtoget accurateestimatesofchemicalbody composition,suchas com-putertomography(CT),magneticresonanceimaging,dual-energy X-rayabsorptiometryorreal-timeultrasound(RTU).These tech-niqueshavebeenreviewedbyseveralauthors(SilvaandCadavez, 2012; Scholz et al.,2015).The RTUscanning is already largely usedinanimalproductionandisconsiderablylessexpensivethan otherimagingtechniques.Concerningtheestimationofdissectible carcasscomponents,manystudieshavebeenmadebasedon ultra-sonicmeasurementsandtheeffectivenessofregressionmodelsfor predictionofcarcasscompositionisnowwellestablished, partic-ularlyforgrowinganimals(Ripolletal.,2009;Grilletal.,2015). Concerningthepredictionofchemicalbodycompositionthedata http://dx.doi.org/10.1016/j.smallrumres.2016.01.024

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availableare scarcer, although someresults have already been availableforsows(Kingetal.,1986),lactatingcows(Wrightand Russel,1984)andsheep(Leymasteretal.,1985).Besides,thereis notmuchinformationaboutthecomparisonofpredictionmodels obtainedfordifferentbreedskeptinsimilarconditions,using ultra-sonicmeasurements.Thepresentstudyaimstoestimateinvivo wholeemptybodychemical compositionforewesofChurrada TerraQuente(CTQ)andIledeFrance(IF)breeds usingRTUand imageanalysis.

2. Materialsandmethods

2.1. Animals

Experimentalanimalswerecaredandhandledinaccordance withtheguidelines ofEUdirective number2010/63/EUand all RTUexaminationsweredonebyanexperiencedtechnicianwith accreditationbyFELASACategoryC.Theexperimentalanimals con-sistedof56mature,non-pregnantandnon-lactatingewesofthe nativemilkproducingbreedCTQ(n=33;liveweight42.0±7.3kg, mean±SD),andthemeatproducingbreedIF(n=23;liveweight 60.7±9.1kg,mean±SD).

2.2. Ultrasoundimagecaptureandanalysis

Beforeultrasoundscanning,theanimalswereshorn,deprived offoodfor24handweighed.Thewoolateachscanninglocation wasclippedclosetotheskin,anda gelwasusedasacoupling medium.TheanimalswerescannedwithanAlokaSSD500V scan-ner(Tokyo,Japan)usingalinearprobeof7.5MHz(UST-5512U-7.5, 38mm,Tokyo,Japan).Theprobewasplacedperpendiculartothe backbone,overthe13ththoracicvertebraandbetweenthe3rdand the4thlumbarvertebrae.Subcutaneousfatdepth(SF)was mea-suredatbothlocations(SF13andSF34,respectively),aswellasthe longissimusthoracisetlumborummuscledepth(MD13andMD34, respectively).Also,atissuedepthmeasurement(TDtho)wasalso obtainedoverthe11thrib,16cmfromthedorsalmidline.Images werecapturedonadigitalvideocamera(DCR-HC96E,Sony,Tokyo, Japan).Then,imagesfromeachsiteweresavedinJPEGimage for-mat,andthemeasurementsabovementionedwereobtainedby imageanalysiswithImageJsoftware.

2.3. Slaughterprocedure,samplescollection,andchemical analysis

Afterslaughteringtheforeandhindlimbs(feet)wereseparated attheradio-carpaland tarso-metatarsaljoints,respectively.The pelt,head,andalltheinternalorganswereremovedand individ-uallyweighed.Thealimentary tractwasweighedfull,and then emptiedandreweighed.Allnon-carcassbodycomponents, includ-ingthepelt(whichwillbesubsequentlyreferredtoasoffal),were thencombinedandstoredin plasticbagsat−20◦_C_until grind-ing.Thecarcasswasstored at4◦C for24hours,reweighedand thensplitdownthevertebralcolumnwitha bandsaw.Theleft halfofthecarcasswasthenstoredinplasticbagsat−20◦_C._Frozen carcassesandoffalwerecutintosmallpiecesbyanelectricband sawandimmediatelygroundinamincer(RetschSM200,Haan, Germany)withasieveplatehaving8mmdiameterholes.The mix-tureswerethengroundthroughanothersieveplatewith4mm diameterholes.Thenthemixtures(carcassandoffal)were homog-enizedinanindustrialmixer(Stef,Rimini,Italy).Forcarcassand offalmixturesfourrandomsamplesofapproximately300gwere obtained,placedinasealedplasticboxandstoredat−20◦_C_for laterchemicalanalysis.

Sampleswere analyzedinduplicate formoisture,ash,crude protein(N×6.25)andfataccordingtoAOAC(1990).Theenergy

valuewasdeterminedbyadiabaticbombcalorimetry(Parr1241 calorimeter,Moline,IL).Carcassandoffalcomposition(kg)were calculatedfromtherespectiveweightsandchemicalcomposition. Theweightsoftheemptybodychemicalcomponentswere calcu-latedasthesumofcarcassandoffalcomponents.

2.4. Statisticalanalysis

ThechemicalcompositioncomponentsandRTUmeasurements forbothbreedswereanalyzedbyANOVAandmeandifferences wereperformedusingFisherLSDtestwithasignificancelevelof P<0.05.Toassesstheaccuracyofemptybodychemical composi-tionestimatedbyRTUsimpleregressionequationswereobtained. Alsomultipleregressionanalyzes wereperformedtodetermine whichcombinationsofRTUmeasurementsandLWbestpredicted emptybodychemicalcompositionandenergyvalue.Forboth sim-pleandmultipleregressionsthebestfittingwasevaluatedbythe coefficientofdetermination(R2₎_and_residual_standard_of devia-tions(RSD).AllstatisticalanalysiswasperformedbyJMP(Version 5.01;SASInstituteInc.,Cary,NC,USA).

3. Results

Churra daTerra Quenteewes showedsignificantly (P<0.05) lowerEBW(34.3vs.50.8kg)andemptybodycontentofwater(17.8 vs.28.6kg),ash(1.34vs.2.44kg)andprotein(5.51vs.9.33kg)than IFewes(Table1).Theabsoluteemptybodycontentoffat(8.66vs. 10.5kg)andenergyvalue(466vs.628MJ)werealsoconsiderably lowerinCTQewes,butthedifferencesbetweenthetwobreeds werenotstatisticallysignificant(P>0.05),duetothehighCVofthe data.Itmustbepointedoutthat,concerningfat,proteinandenergy value,CVvalueswerelargerforCTQewesthanforIFewes.When thecomponentswereexpressedasproportionsofEBW(Table1), alldifferencesbecamenotsignificant(P>0.05),againwiththehigh CVofthedataplayinganimportantrole.Forinstanceinthecaseof fatproportion,CTQewesshowconsiderablyhigherfatproportion thanIFewes(252vs.202g/kg),despitethelackofstatistical signif-icance.Expressingthedifferentbodycomponentsasproportions reducedtheEBWeffectonthebreedcomparisonsand,withthe exceptionofproteininIledeFranceewes,resultedinmuchlower CVvalues.

WhencomparingtheRTUmeasurementsatthethoracicand lumbarlocationswithinabreed,theresultsshowednosignificant differences(P>0.05;Table1)bothforsubcutaneousfatdepthand formuscledepth.TherewasnosignificanteffectofbreedonSF13, SF34orTDtho.However,muscledepthatbothsites(MD13and MD34)wasnearly50%greaterinIFthaninCTQewes(P<0.05). BothbreedsshowedconsiderablevariationforalltheRTU mea-surementsobtained,anditcanbepointedoutthat,exceptofTDtho (forwhichIFewesshowedhigherCV),thecoefficientsofvariation forCTQewesweremuchhigherthanthoseforIFewes.

Consideringtheamountof variationexplained byRTU mea-surementsfortotalemptybodycomponents(Table2),therewas atendencyforbetteraccuracy(basedonR2₎_of_estimates_in_the caseofCTQewes.Fatwasclearlythebodycomponentmore accu-ratelyestimatedusingRTUmeasurements.Thisisparticularlytrue forCTQewes,usingSF13,SF34andevenTDtho,whichexplained, respectively,90.8,91.1and85.1%ofthevariationintotalfat con-tent,and78.3, 81.1and72.2% ofthevariation infatproportion (Table2).ForIFewesfatwasalsothebetter-predictedbody com-ponent,butwithlessaccuracythanforCTQewesandwithMD13 andMD34RTUmeasurementsbecomingalmostasgood estima-torsoffatcontentasSF13,SF34,andTDtho(Table2).Still,RTU measurementsoffatdepthprovidedthebestestimates,withSF13 andSF34explaining,respectively,76.8and84.5%ofthevariation

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Table1

Means,standarddeviations(SD),rangesandcoefﬁcientsofvariation(CV)forliveweight(LW),emptybodyweight(EBW),chemicalcompositionandenergyvalueofthe emptybodyandinvivoreal-timeultrasonic(RTU)measurements†ofChurradaTerraQuente(CTQ)andIledeFrance(IF)ewes.

CTQ IF

Mean SD Range CV Mean SD Range CV

LW,kg 42.0a 7.28 30.9–60.4 17.32 60.7b 9.10 47.0–79.0 14.98

EBW,kg 34.3a 7.50 22.6–54.2 21.88 50.8b 6.85 40.48–63.76 13.48

Emptybody

Water,kg 17.8a 2.89 12.7–26.1 16.27 28.6b 2.97 23.3–33.6 10.38

Ash,kg 1.34a 0.19 0.96–1.81 14.32 2.44b 0.49 1.80–3.31 20.04

Fat,kg 8.66a 3.29 4.29–17.9 38.20 10.5a 3.28 4.31–15.9 31.28

Protein,kg 5.51a 0.95 3.76–7.95 17.26 9.33b 1.02 7.45–12.0 10.95

Energyvalue,MJ 465.8a 148.3 266.9–889.4 31.84 627.8a 141.7 375.9–887.7 22.60

Proportionsofemptybody

Water,g/kg 540.4a 37.6 485.0–611.7 6.96 565.1a 29.5 516.6–633.1 5.20

Ash,g/kg 41.0a 4.50 33.6–51.9 10.96 47.9a 7.25 32.7–62.3 15.13

Fat,g/kg 251.6a 50.1 153.1–333.7 19.91 201.7a 40.8 106.5–264.0 20.20

Protein,g/kg 167.0a 9.00 147.7–186.2 5.40 185.3a 21.0 150.6–220.9 11.40

Energyvalue,MJ/kg 13.8a 1.78 10.3–16.5 12.93 12.2a 1.28 9.29–14.3 10.52

RTUmeasurement(mm)

SF13 4.98aA 2.08 1.75–9.40 41.80 4.83aA 1.10 3.40–8.13 22.82

SF34 5.17aA 2.15 1.84–10.01 41.61 4.97aA 1.23 2.89–8.44 24.68

MD13 19.92aB 3.96 13.09–27.35 19.88 29.64bB 3.18 24.33–35.22 10.73

MD34 19.71aB 3.74 12.01–28.21 18.96 29.17bB 3.21 24.74–35.94 11.00

TDtho 12.79a 2.42 9.09–19.25 18.89 12.97a 3.31 8.36–18.59 25.52

a,b:Forbreedswithinarow,meanswithoutacommonsuperscriptaresigniﬁcantlydifferent(P<0.05).

A,B:ForeachbreedandforSFandMDmeasurementswithinacolumn,meanswithoutacommonsuperscriptaresigniﬁcantlydifferent(P<0.05).

†_RTU_measurements_of_subcutaneous_fat_depth_over_the_13th_thoracic_vertebra_(SF13);_subcutaneous_fat_depth_between_the_3rd_and_the_4th_lumbar_vertebrae_(SF34); longissimusthoracisetlumborummuscledepthoverthe13ththoracicvertebra(MD13);longissimusthoracisetlumborummuscledepthbetweenthe3rdandthe4thlumbar vertebrae(MD34)andtissuedepthoverthe11thrib,16cmfromthedorsalmidline(TDtho).

Table2

Coefﬁcientsofdetermination(R2₎_and_residual_standard_deviations_(RSD)_for_simple_regression_equations_between_the_amount_and_proportion_of_total_empty_body_components

andinvivoreal-timeultrasonic(RTU)measurements†_for_Churra_da_Terra_Quente_(CTQ)_and_Ile_de_France_(IF)_ewes‡_.

Wholebodycomponent RTUmeasurement(mm) Amount Proportion

CTQ IF CTQ IF R2 _RSD _R2 _RSD _R2 _RSD _R2 _RSD Water SF13 0.580 1.900 0.673 1.730 0.349 30.8 0.438 22.6 SF34 0.612 1.830 0.559 2.010 0.705 20.7 0.376 23.8 MD13 0.827 1.220 0.620 1.870 0.802 17.0 0.519 20.9 MD34 0.748 1.470 0.710 1.630 0.765 18.5 0.668 17.4 TDtho 0.517 2.040 0.818 1.290 0.311 31.7 0.527 20.8 Fat SF13 0.908 1.010 0.768 1.610 0.783 23.7 0.751 20.8 SF34 0.911 1.000 0.845 1.320 0.811 22.1 0.603 26.3 MD13 0.601 2.110 0.734 1.730 0.337 41.4 0.715 22.3 MD34 0.574 2.180 0.825 1.400 0.306 42.4 0.626 25.5 TDtho 0.851 1.290 0.842 1.330 0.722 26.8 0.718 22.2 Protein SF13 0.639 0.580 0.421 0.795 0.220 8.087 0.499 15.2 SF34 0.659 0.564 0.268* 0.894 0.686 5.134 0.556 14.3 MD13 0.861 0.360 0.331 0.855 0.717 4.875 0.245* 18.7 MD34 0.789 0.444 0.150ns 0.964 0.709 4.935 0.350 17.3 TDtho 0.557 0.643 0.145ns 0.966 0.200* 8.191 0.263* 18.4 Energy value SF13 0.900 47.5 0.821 61.3 0.778 0.851 0.737 0.674 SF34 0.906 46.1 0.852 55.7 0.809 0.790 0.613 0.818 MD13 0.662 87.6 0.767 70.0 0.347 1.460 0.623 0.807 MD34 0.627 92.0 0.794 65.7 0.315 1.495 0.631 0.798 TDtho 0.837 60.8 0.808 63.5 0.714 0.965 0.603 0.828

‡_All_correlation_{coefficients}_are_significant_(P_<_0.01)_except_those_marked_with_*_or_with_. ns_which_are_{respectively,}_significant_(P_<_0.05)_or_not_significant_(P_>_0.05).

inthetotalfatcontentand75.1and60.3%ofthevariationinfat

proportion(Table2).

Concerning the potential of RTU measurements to estimate water and proteincontentin thetotal empty body,the results showedalowerabilitytoexplainthevariationobservedthaninthe caseoffatcontentandenergyvalue(Table2).ForCTQewesMD13

explained thelargest amountof variation in total protein con-tent(R2₌_0.861;_P_<_0.01),_followed_by_MD34_(R2₌_0.789;_P_<_0.01) andinproteinproportion(R2₌_0.717;_P_<_0.01),_followed_by_MD34 (R2₌_0.709;_P_<_0.01)._However,_for_IF_ewes_most_RTU_measurements madeinthepresentstudyshowedtobepoorestimatorsofprotein

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Table3

Coefﬁcients(±SE)ofthebestmultiple-regressionmodelsforpredictionofweightsofwater,fatandprotein,andenergyvalue,intheemptybody,andforpredictionoftheir respectiveproportions,usingliveweight(LW)andinvivoreal-timeultrasonic(RTU)measurements†,forChurradaTerraQuenteandIledeFranceewes.

Constant LW SF13 SF34 TDtho MD13 MD34 AdjustedR2 _RSD _P

ChurradaTerraQuente Emptybody

Water(kg) 1.81±0.838 0.168±0.045 0.273±0.07 0.176±0.07 0.923 0.802 0.001

Fat(kg) −5.13±1.22 0.112±0.034 0.727±0.152 0.413±0.119 0.950 0.737 0.001

Protein(kg) 0.148±0.175 0.055±0.009 0.091±0.015 0.064±0.015 0.969 0.167 0.001

Energyvalue(MJ) −189.7±48.9 7.27±1.37 29.3±6.07 15.5±4.76 0.960 29.5 0.001

Water(g/kg) 589.2±15.6 −19.6±2.04 2.46±1.07 0.820 15.9 0.001 Fat(g/kg) 194.7±19.1 16.8±5.37 11.0±5.34 −4.22±1.34 0.851 19.4 0.001 Protein(g/kg) 171.2±3.79 −2.57±1.06 −2.78±1.06 1.15±0.267 0.819 3.83 0.001 Energyvalue(MJ/kg) 11.4±0.723 0.933±0.095 −0.116±0.05 0.827 0.739 0.001 IledeFrance Emptybody Water(kg) 10.41±1.74 0.299±0.028 0.834 1.21 0.001 Fat(kg) −7.51±2.233 1.207±0.245 8.36±3.42 0.271±0.122 0.940 0.80 0.001 Protein(kg) 6.42±0.762 0.602±0.154 0.394 0.795 0.008 EV(MJ) −155.3±100.5 59.60±11.42 11.53±5.129 0.928 38.04 0.001

Water(g/kg) 662.9±15.49 −19.66±3.029 0.652 17.44 0.001

Fat(g/kg) −43.3±41.28 17.55±5.27 5.406±2.016 0.798 18.344 0.001

Protein(g/kg) 246.8±12.35 −4.74±0.924 0.535 14.341 0.001

EV(MJ/kg) 5.06±1.395 0.631±0.167 0.135±0.065 0.763 0.625 0.001

contentandthebestresultwasforSF34asanestimatorofprotein

proportion(R2₌_0.556;_P_<_0.01).

Table3showsthemultipleregressionmodelsthatbetter esti-matedchemicalbodycompositionforCTQandIFewesfromLW andRTUmeasurements.Inlinewiththeresultsfromthesimple regressionanalysis,theinclusionofRTUmeasurementsin predic-tivemodelsprovedeffectivetoexplainmostofthevariation in bodycomposition.Infact,exceptforthepredictionofwaterofIF ewes,allﬁnalpredictionequationsforbodycomposition compo-nentsincluded1–3RTUmeasurements,withSF34beingthemost reliableindependentvariable,sinceitwasincludedin9outofthe 16equations.However,whilethebestmodelsprovidedgood esti-matesoffatcontentforbothbreeds(R2_≥_0.798;_P_<_0.001)_and_of proteincontentforCTQewes(R2_≥_0.819;_P_<_0.001),_even_the_best onlyexplain54%ofthevariationinproteinproportionforIFewes.

4. Discussion

TheabsenceofsigniﬁcantdifferencesbetweentheRTU mea-surementsatthethoracicandlumbarlocationswithinabreedis inagreementwiththeresultsofSilvaetal.(2006)andRipolletal. (2009,2010).Thériaultetal.(2009)reportedmoreprecise mea-surementsoffatdepthbetweenthe12thand13ththoracicthan betweenthe3rdand 4thlumbar vertebrae,but theyexplained thiswiththepresenceofathirdlayeroffatinthelatterlocation, inthefattestlambs,stressingtheneedofagoodmorphological knowledgeofthetissuesstudied—theidentiﬁcationofthatthird layeroffatwouldhaveimprovedtheprecisionoftheultrasonic measurements.Infact,thelayeringoffathasbeenintheorigin oferroneousestimatesofsubcutaneousfatbut,duetothe evolu-tioninRTUimagesacquisition,theuseofhighprobefrequency(i.e. 7.5MHz)andimageanalysis,theproblemraisedbylayeringoffat willbeovercome,asstatedbyseveralauthors(Silvaetal.,2006; Hopkinsetal.,2007).

Thevariation intheabsoluteweightoffat wasmuch better explainedthanthevariationinfatproportion.Thisisinagreement withpreviousstudiesusingRTU(Silvaetal.,2006;Grilletal.,2015) orRTUandCT(JunkuszewandRingdorfer,2005),whichshowed moreabilityofmeasurementsobtainedwithsuchtechnologiesto estimateabsolutevaluesofdifferentcarcassorbodycomponents thantoestimatetheproportionofthesamecomponents.A sim-ilarpatternappliestotheestimationofenergy value.However, forproteinestimates,therewasnoclearpatternconcerningthe estimationofabsolutevaluesversustheestimationofproportions. Whetherthiswaslargelyrelatedornottothelowercoefﬁcients ofvariationobservedforproteinthanforfatandenergyvaluewas notclear.Thefactisthat,asnoticedbyFortin(1980),removing mostofthevariationofbodycomponentsasproportionsturnthe explanationofthevariationobservedmoredifﬁcult.

Asalready noticedbySilvaet al.(2005),for growinglambs, theRTUmeasurementsofsubcutaneousfatinthepresentstudy explainedaverylargeamountofthevariationobservedintotal bodyfat.However,whileSilvaetal.(2005)showedSF13asa bet-terestimatoroffatcontentthanSF34,thepresentresultstendto showSF34asabetterestimatoroffatcontentthanSF13,namely regardingabsolutefatcontentforbothbreedsandintermsoffat proportionforCTQewes.Theonlyexceptiontothistrendwasthe amountofvariationexplainedbyfatproportioninIFewes.The explanationofthevariationinenergyvaluefollowedcloselythe samepatternsobservedforfat,justtendingtoprovideslightlyless accurateestimatesthanforfat,especiallyinthecaseofCTQewes (Table2).Thiscouldbeexpectedgiventhehighcontentofenergy infat.

Thesmalleramountofvariationinproteincontentexplainedby RTUmeasurementsofmuscledepthwhencomparedtotheamount ofvariationinfatcontentexplainedbyRTUmeasurementsoffat depthwasnotsurprising,consideringthatfatisthemostvariable tissueinmatureanimals.Fordissectiblecomponents,Ripolletal. (2010)noticedthat,infact,RTUmuscledepthwasmorecorrelated

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withleanthanfatmeasurements.Inthesameline,theirresults showedthatRTUfatthicknesswasmorecorrelatedwith subcuta-neousfatandintermuscularfat.However,Silvaetal.(2005)verified thatSF13 andSF34werethebestestimatorsoffat andprotein contentrespectively.Thepresentresultsforchemicalcomposition ofCTQewesareinlinewiththoseofRipolletal.(2010)for dis-sectiblecomponents,but theresultsnowobtainedforchemical compositionofIFewesalwaysshowaRTUmeasurementoffatas thebestestimatorofproteincontent(SF13forproteinweightand SF34forproteinproportion).Eventakingintoaccountthe differ-encesobservedinthecoefficientsofvariationforthedifferentbody componentsandthevariousRTUmeasurements,betweenCTQand IFewes,therewasnoclearpatternthatcouldexplainbreed dif-ferencesconcerningtherelationshipbetweenultrasonicandbody components(Table2).Still,thepresentresultsshow,acrossthe twobreedsstudied,thehighcontributionthatsingleRTU measure-mentsmayhavetoexplainchemicalbodycomposition,especially intermsoffatcontent,confirming,formatureanimals,asimilar conclusionisalreadytakenbySilvaetal.(2005)forgrowinglambs ofthesamebreeds.

BeingLWatraiteasytoevaluate,itisalsoatraitthat,inmost studiesofbodycomposition,tendstoaccountforalargeamount ofthevariationobservedinthedifferentbodycomponents.This hasbeenshownbyseveralauthorssuchasGreineretal.(2003), incattle,andSilvaetal.(2006),andRipolletal.(2010),insheep. Inthepresentstudyonlythebestmodelsobtainedforestimation ofchemicalcomponentsofCTQewesareinagreementwiththose studies.Anyway,onecanexpectthatinpopulationswith signiﬁ-cantvariationinLWthistraitcanexplainmorevariationinbody compositionthaninapopulationwithmorehomogeneousLW.On thesamebasis,itmustbenoticedthatthepredictivevalueofthe modelsdevelopedinthepresentstudywouldprobablybelower whenappliedtopopulationswithlowerCVforinitialLW.Still,the resultssuggestthattheinclusionoftwoorthreeRTU measure-mentsinthemodelisgenerallyenoughtopredicttheabsolute amountofthedifferentbodycomponentsandtheirproportions. Fromapracticalpointofview,theneedforjustareducednumber ofRTUmeasurementsiscrucialtomakethemethodology appli-cablebecausethecapturingofimagesandmeasurementscanbe speedupwithoutimpairingtheprecisionandaccuracyof predic-tions.Thishasbeendiscussednotonlyfortheultrasoundbutother imagetechniquessuchasCT(Scholzetal.,2015).

Overalltherewasaclearpatternshowingthatabsolutevalues ofbodycomponentsareestimatedwithhigheraccuracythantheir proportions.Forfat,thisisparticularlynoticeablebecausethe accu-racyofthebestmodelsexplainedmorethan94%ofthebodyfat variationinabsolutevaluewhereasforfatproportiontheyonly explainedupto85%(P<0.01).Thesevaluesareveryclosetothe onesobtainedbySilvaetal.(2005),butinthepresentstudy,the bestmodelsforestimationoffatcontentincludedoneRTU mea-surementofmuscledepthinadditiontooneRTUmeasurementof fatdepthexceptinthecasethemodelforfatweightinCTQewes.

WhiletheresultsfromsingleregressionanalysisforCTQewes hadalreadyshownthatsomeRTUmeasurementscanbeusefulfor estimationofproteincontent.Theresultsofmultipleregression analysisshowthatthecombinationofdifferentRTUmuscle mea-surements(MD13andMD34)andLWcanexplain97%(P<0.001) ofthevariationintheabsolutevalueofbodyprotein.However, eventhebestmodelofproteinestimationforIFewesshowedmuch loweraccuracy,explainingonly54%(P<0.001)ofthevariationin proteinproportion.Ifminorvariationsinproteincontentofmature animalsaretobeanalyzedbyRTUmeasurements,furtherstudies willbenecessarytoconﬁrm(ornot)thepotentialnowrevealed, especiallyforCTQewes.Incontrastwiththeresultsobtainedby Silvaetal.(2005),forlambsofbothbreedsconsideredasawhole, thebestmodelsforestimationoftheproteincontentofCTQewes

inthepresentstudyincluded,atleast,oneRTUmeasurementof muscledepth.

Teixeira(2009)pointedoutthat,whenchoosingbetweenthe differentmethodologiesavailableforassessmentofcarcass com-position,oneshouldconsiderseveralfactorssuchasthespecies concerned,thedifferentworkingconditions,theaccuracyofthe methodinmakingdifferentpredictionsandtheprecisionof pre-dictionmodels.Inreality,evenusingsimilarmethodologies,factors suchasthebreedstudiedand thestageofdevelopmentof the experimentalanimalsmayhaveanimportanteffectonthe rela-tionestablishedbetweentheultrasonicmeasurementstakenand thebodycomponentsestimated.Theformersituationcanbe illus-trated by the present study and the latter by the comparison betweenthepresentresultsandthosereportedbySilvaetal.(2005) withgrowinglambs.

5. Conclusion

Real-timeultrasoundmeasurementsinliveewesprovidedgood estimatesofthefatandenergycontentoftheemptybodyofboth breeds.Theyalsoprovidedgoodestimatesofproteincontentfor CTQewes,buttheestimatesofproteincontentforIFeweswere poor.Theresultsshowthatpredictivemodelsthatarespeciﬁcto thebreedandcircumstancesofthestudyinwhichtheyaretobe usedwillhavetobeestablishedtohaveapracticalapplication.

Conﬂictofinterest

None.

Acknowledgement

This work received ﬁnancial support from the FCT-PEst-OE/AGR/UI0772/2014whichwegratefullyacknowledge.

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