Genetic correlations between linear type traits, food intake, live weight and condition score in ...

164 Pages·2006·5.93 MB·English

Genetic correlations between linear type traits, food intake, live
weight and condition score in Holstein Friesian dairy cattle
R. F. Veerkamy' and S.B rotherstone'
Abstract
Vnrill~ctC' O I I I / I O I I C ~i~lJ~('YSC c s f i ~ n t c d f r o ~nilz i rizirr~nrl irodrl usir7;; n resfricft~cil~ rnsirrrtlrrl~ik c~lilrood/ )roe-rdlrrri oliic-/I
allozucdfi~ri lnt~qluald esign r~rirfricrsn ild rrlissirlg obsrrzlrrfioi7s (VCE). Dofir w f s (,otrfainir~,y(:i ) 15 275 rrcords c!f
linear fypr' clnssificntiom on heifers, (ii) 3399 livr illri:,.l~im rrd cor~difiotrs cortJs rrreaslirrd ilt c-alain~ir nif (iii) 1157
rccouds of yirld, ~ir~/-1/1rrliliffltf~nrk ~I,I ~ ~ I ~ Y lIiuI ~t, C~ uei~ynhrf~ iic orrdifion scorr dlirii~gf hr first 2b ~ L J ~ J ~o/fC lSil cfatioir;
werp irnalyscd joinfly.
Herifabilif!! esfiinntcs for dry-rnaffrr irztnke, /ir~rir lcighf lznd coi~~iifioSrCi O ~ P t/7e lar<yestd nflr S P i~i l t ~ (0~.4 4, 0.44
and 0.35 rrsprctivcly a n ~tfh c genefic corrrlnfiorl bctzclceri corldifior~s core (7i1~tih e ,~!irlift rnits n ~ n g r d f i o r-0~.2~9 to
-0.46. The genetic corr~lationb etzueei~r riilk yield nnd nzlr~rn~liiv~e ivrighf runs nc;\rative (-0.09) birf trfter nifjirstir~g
for thr gcnptic variation in coizdition score this ~ o r r ~ l ~ filJi17oS i[~~o s i t i i(l0~.~2 9). Grrzctic corn31afiorrsb efiort'r7 liilc
zoeight nnif s fnf~rrec,h rst iuidfh, body depth nnd runip suidth ill^^^ ~ ~ o i ~ s i s f1t1i~~yrh( ~0f.5l2~ f~o 0.64; 0.75 to 0.86; 0.59
to 0.81; 0.56 to 0.74, ri~spccfiuc/~C/)h.p st width and body drpfh zvcrt7 l i f f l rt o rr~oifrunfrlc?o~r rclafed silifh dr!/-rrlmftrr
intake (0.25 to 0.28 nud 0.20 to 0.34 respectively), nrrd nngulnrify (-0.47 fo 0 . 7 7 ) n r~dc llrsf irlidtli (0.32 to 0.733
appeared to be good pn~dicforso f coildition score. These coruelations shoiileii that ( i ) fhr relnfiz~eu n/z/e (~j-lii~ilt)'( 'icy/if
conzparrd with food ii~fnlcec npacify drtermincs the optimum iiirectiorz if sc~lectiolif or stnfz~rec, l ~ ~isllifd th, boil!/
depth and nnguluuity, and corzsrqurrzfly thr optilnirrrr size of the dmiry ccosu, 1711d fhnt (ii) 1i.r~w~e ight, condifio~slc ore
andfood infakc can be predictedfrorn tlir type trnifs il~ifllli tflc loss in ncczlrncy. A rrstricfed indr .~iv hich r11iririiair7s
conditiorr scarf nf i f s c ~rrrtwt1 e7~elz uos preiiicf~dt o r(~diucc~, ~tli~r((~rello 11011r~iec)r l r f ipci l l by 5%.
Keywords: dnlry ~ a f f / r , f o ordr ~fakr1,1 1zmrf ypr fn1rf5,l rz~tw, eight
Introduction (Dempfle, 1986, Groen, 1989, Vi\scher 1.1 ill 1991,
Most milk producers would agree thdt improving Groen ef (11, 1994) Increasing food intake, however,
the profitability of cows, consistent with their health could have a positive econonyic value in the situation
and welfare, is the most important breeding objective where additional concentrates are needed to
for dairy cattle. Clearly food costs are important supplement the energy from forage. In that situ,ltion,
components of profitability, because food costs relatively more forage can be given when intake
account proportionately for about 0.80 o f the total increases and the amount of concentrate in the diet at
variable costs associated with milk production (Milk a given milk yield can be reduced (Croen and Kor\,er,
Marketing Board, 1990). Generally, food is used for 1989). Considering that the economic weights of
the separate functions of maintenance, lactation and intake capacity ; ~ n dl ive, weight are in opposing
body tissue gain, or loss, and genetic improvement of directions, whereas the gcnctic correlation bct~vccn
food utilization h,ls to come from changing these these two traits is vositi\/e. it seems imvortant to
components. cons~ders lrnultaneoLsly both ~ntakea ncl I;\ e weight
111 the breeding goal (Vccrkanip, 1996)
Accounting for increased maintenance requirements
of a cow wit11 increased live weight, the economic It call be expected also that ~ntakec apac~tva nd bodb
value of live weight is reported to be negative condition score are likely to become more ~mportant
%h Veerkarnp and Brotherstone
In the ~ L tlI l l.c3,r cy,~ildles0i1 tlli, tec>cli~l\g, i t e m . This is elcc t lon~cg d t t ~th e exlcl~dctl~ n c l o op~e t ~ o d;1 1lo\1c ~ l
l ~ e c , i i~c,~lc~c-elio~n for !i csld i ~ i c r e ~ ~thi ic. g ,lp het\\ crn m e < ~ \ uc.lm cTnt of tood ottcrcd to, and I ?tu\ed h\,
c%nt.rg\.i ntxll ,ind O L I ~ ~dL~rI r~in ge ,irl! I,lci,ltion: the> ~ncli1\ d~1,llc o\\ i to1 4 d , i \~/ L \ cck, t~o m cal\ lng to 3'
correl;~lcdr cSspol\sc~i l l looci intc~l\cf~ro, m sclclction on t.rilnlmLlm ot 26 n e e k i and 1113 to 38 \ \ eck i ,ittc3t
\ ield, c,ili CO\ er oi11! 40 to 4SU0 cif the. extra ccd\l ng (dcpt tnd~ngo n t l ~ vc< i l \ Ing d i t e ot eClchc ob\)
~ . c ~ c l ~ ~ ~ r c(~\ .nxiw A" tric ~ndonki.1 i l l . , 190 1; l ' c ~ ~ h ~ i ~ i iTph,e . d'1ta I rported helc a r t tot pel to1 m~lnceo \ c.1 they
IeJe)4). \\"liil\t tlic~rc~is no c,\ idcncc, cif a large h l i t 2h \%t\rko\ f l , ~ c t ~ i t ~~oenc,o lcleclo \ er c o l i i c ~ ~ ~c%t r \
1xotx)rtion of gcsnc~tic\ ,,iri,ltio~lI n p'lrtial etticiencics \(.a15t toni lCJSO/XI to 1994/05
(Gl,ll\c ,111ci C ~ ~ s t o d i o19, 84; Vcscsrk,lmp ,ind b:mm,ms,
lC195)1, 11osto t tlic>r c \~~i ' i i~ci i>~~iigc >rrge\c~l ~ ~ i r e ~ ~foire ~ ~ tI\'l ie complete mixed diels wcrc dispcnstd into
\icld h,ls to comc From h o d \ tisst~cm ohilir,itio~l. indi\.id~l,il food bins, once dail!-. Wcigl~tso f frc~sli
~ c l c c . t i n ~ for a lolver ii\,c \veiglit ~ v l ~ i l s t dir t otfered ; ~ i i dr c'ti~sed were recorc i~~01l1 4 d ' i ~ s
s i rn i~ l taneo~~ssellyec ting tor i~icrrased! ,ield, or direct consecuti\.elq cach week. [>;lily s,lmples from the
sc.lc,ction tor gross c.tficienc\,, co~~lcinic re'ise the g ~ i p clitferent clieh ;111cl r c f ~ ~ s ~wi lesr e mi,llysed for dry
I~ct~vc't'nth e r,ite ot progress in vield and thc r,ltc ot rn~itter.C ows on tht. foocl int,ll<c trial MrCrc' ~ e i g h e c l
progress in int,il<c c,ipcicity, ,ind hence ,111 i l icrc~~sinc ~ ,ind condition scored once, ,l M ' C C ~ after milking.
tlie depenclenc!~ on body tissue mobilircition c l ~ ~ r i ~ i gC onclition scoring was b,~sc,d on tlie system
early I,ictatioi~.F or these re;1so1is, there is intcrest in de\,eloped by Tdowm,in ['t (71. (1976). Tliis system
inclu~ling1' cornhin<ition of dry-~nat ieri ntclkc, l i \ c. scores betcveen 0 and 5 ( lem to fat), and describes
tveiglit ,ind conclition scorr in the cl,lir? cattle eClch score in terms of the ;umount of tissue colrer
breeding go,il ancl therefore genetic p ~ ~ r ~ l i n c tfcorr\ ol'er the tr,~ns\,crsper ocesses of the lumbar vertebrae
tliese traits 'Ire' required. and '?round the tail heclcl. Halidling procedures of
tlie weekly data were described in more detail by
Mecisuremcnt ot ilidiviclual ccl~v's pcrtormancc. for Veerkamy 1.f nl. (1 994). Yield, d ry-matter intake, live
iveiglit, tood intake or condition scorc is not ~ V i g h td ncl co~idi t i ( l is~co re were calculated as the
comnlon pr;lCticc for 111e)st brceding progr'lmmes ,111d average of tlie weekly rccords accumulatecl over
therefore there is gre& interest in other trdits ~vliich weeks 3 to 26 of lact,ition, ,lnd 1157 lactations (on 527
m,iy liclp to prcdict tlicsc>p otential goal traits. I.inecir animals) were a\~~iilablfco r milk, fat aiid protein
t y ~ ctr aits dcscribc biological extremes for a I'irge yicld (milk, FY and PY, respectively), dry-iliattcr
number of \ , i s ~ ~caIlia r,icteristics, are measurecl on intake (IIMI), live weight (LW) and conclition scorc
rel,lti\,ely largc~s c.alc, international con\,ersions are (CS). Live weiglits cillcl conclition scores at calving or
a\.ail,lble ,lnd tr'lits like body depth, capacity and ~ ~ i t h 2i 4n h t1iel.eof (CLW and CCS) were av,lilable
sizc arc pt,rcei\,cd to he important by breeders for for 3399 IC1ctations( on 1046 animals).
m.lny rtdsnns. Tlierefore it seems appropri,lte to
e s t i n ~ ~ ~gttcn.e tic correlations b c > t ~ , e ety~pie traits and To increase the numbcr of records with type
dry-~iiattc~inr t'lkr, condition scorc, ancl li1.e ~\reigl~t cl~ssification,4 7 xlditional herds were includcd in
,incl then to e \ . c ~ l ~ ~ cthiet e use of these tr'lits as the analysis. Records (no. = 15 275) were selected
potential predictors in ,I selection inclex. Hencc, thc from the Holstein Friesian Society records on
first objecti\,e is to est i i~i~i\t.e;u -i,lnce components for pedigree heifcrs from 1983 to 1994 inclusi\~ea nd
vielcl, dry-111~itter int,~ke,l i1.e ~ r e i g h t, lnd condition preferellcc ~ ~ g1ivens t o herds with the) largest
score ,ind the seconcl ohjcctiire is to estiinlte genetic number of sircs in conimoii with L;uiighill to establish
corre1,itions htt\%,ccn tlic~sc tr<iits and lincar t).pe geiictic lilikagt'. l ' he pedigree file (no. = 28 547)
traits. consisted ot sirc,s, dams ,ind all g r a i ~ d p ~ ~ r eonft tsli ese
wit11 links to at least twro ,inirnCils\ vith a recorcl.
For oath o t the two clat'i sets, tlie total number o f
Material and methods rccords tor type and for the tr'lits lneasured ;it
n 1 7 i i 7 L;lngliill (during ccllving or during the first 26 ~veeks
Rc~corcls \\.ere ohtC1inrd from cows housed and of Idcta tion) ,Ire given in Tablc 1 . Of tlit, total number
tn,>~i,~gcxaI t the, Scottish A g r i c ~ ~ l t ~ ~Croalle ge/ of type records (15 275), 514 heifers were type
Uni\,t.rsit!. of Fdinburgh I.angliill L>,~iry C'attlc cl,issified at L.anghil1, dncl all of these aniinals had
I<esearcli Centre. In each yeal. c,~l\i ng beg,ln e x l y in CLW ,ind CCS recorcicd in tlie tirst lact'ition.
Septtmher ,ind ; ~ n i m ~ ijlosi ning tlie trial all ccil\,ed Howe\,er, only 314 of tlic~stt type c1,issifiecl I~eifers
hc~t\ \~t~Sce~pnte niht~ra nd J;in~~,lr)A.l.l co\vs in\,ol\.ed h'xl DMT, IdW and CS rccordcd. O\.er and aho\ c c~l l
in tlit. st~td! \vt,rt, Holsteiii-Friesi,i~ls.C ox\ s crc ot1it.r r e l~~t ions l~ iipnsc luded in tlie relationship
kept indoors in con\.entional cubicle housing krom mdtrix, link'ige betc\,ee~it he 'Tdanghill records' ,ind
c,ll\.ing to ] L I I ~r lild offered complete mixed diets 1711 the 'n,~tionalt ype r~c o r d sw' Tcisp rovided by 55 sirc1s
lil7it11iii. T l~rough tlie use of C;~l , i i~t 3roc~dbent vvliicli h , ~ d3 961 daughters with t \ ~ p er ec~rcisi n thc
Genetic correlatio1 1s i n dairy cattle 387
Table 1 2 ' i i i i i l~i~0i1 i i ~ ~ o i -t iil~~i i i / i~ l l I i~ tr'jits (clicbt \vicltli (C'W), h o r i ~J eptli (EL)), \t,rt~~rc>
(ST'A), angularit\. (AN(,), nbil, CS ,~ncl 1 \ V ) \ I - L T ~ .
kl,. o f rt~cl,rl l i ti ttc3d in a it>\tw h-ail ,ilicils~i s i i n ~ u l t ~ n ct~o ~gc~'t ~ ~ l \
more consistent c~stin1'1tc.so f thr, jic~~ic~ct.icc~ rrc,l,lt~on,.
I Ieiter\
' I lit. cttc.cts ti ttcd tor Lhc 1~~1ngIiiltlr ,ii t i L\ t.re ;I,
I IcltL~1.i i <.(l\\
clescrihed ,iLlo\,cs, ,111d 101- tlic lint.ar t!,pe tr;iil\
fixt3d efteel5 illcl~~cicId,~ ct~itiosnt, ige <it in5pection ( 1
T> 15275 15275
Lc1~~gktir~i'Ill ( h l ~ l lF~)', , P), Dbll, to 15), Ilerd-),c;ir-\ i a t (248 l<,\ cls, 48 herds), month of
I,W, C Sjt 410 1 l?, c,ll\ i ~ i g( 1 to 12) ,lnd ,1gcX'i t inspection and I-lolstcii~
Lc~~~gclellil\l l1 11(sC l L \ ' ~ 1 1 <Ci C 'S)$ 1' l 0 33LlC) pcrcc.ntclgc~'1 s lincclr CO\ ~iriatc~sIn. orcler to <icco~ull
tor ditfc~rcncci?n~ t he range of scoring utilircd h\ tht.
t Milk, FY ancl 1'Y AI-ern llk, t a t , ~ n t iP I-otcin irlcl, rlbll 15 tielcl ofticem, the t),pe tr'lits ~ 2 ~ e r'ied justcd h\ tlit'
drq-ni.itter lntakc., LL1: ,illcl CS ,ire l i \ tl ~\.t,lgli,ti nd col>clitioli
rdtic) ot thc3 st<i~ici'ir~dde \.iritioil of tlie field otficcxr to
score, ,111 ,~\c~r,lgecoI\ t>rt he. f i n t 26 \ \ t~-koht Id~t~itio~i.
the' rnc~~ilsit and,lrcl de\.i;ition of '111 ficsld ottiiclrs
CL\l\' md CC'S C I I C . 11\c n.e~glit~ n dco ndltioli \core, ,I[
(K~.otherstone1, '194).
cal\ ins .
~ ~ [ ~ / l 1 5 ~ 1 1 1 ~ ' 1 1 ~
Adjusting genetic ( ~ o - ) \ ~ l r i , ~ ~tiocr~ c,i~nost her trciit
m,ikes i~ i te rpre t~~t ic~(sno mctinics) c'lsicr; tor
example, li1.e weight ,idjustcd for difft~rc~nceins body
conclition scorc might lid\.t. ,~notlirr (biologic,il)
interprct,ltion th,ln l i \ c , wc>ight in its 0w.n right. The
A ~ ~ [ l / ! / s i s geiletic (co)\,;lrianccs for 'live. weight adjustecrl for
Multi\rariate c~ncilysews ere performed to estim,~te condition score' (IdWA) were cre<~terl sing thc
the variances and covari,lnces. Ail indi\.iclu,il '~nimdl gmetic regression of li\re iveigl~to il condition scorc:
model, mit11 the full numerator relationsl~ipm atrix 11 = ol /02,,, ~27liereo l,, ,L< is the genetic co\.,lriancc
included, was fitted using restricted rn,~ximurn between live \veiglIt ,111cl conditioi~s corc <111d o'~,i s
likelihood procedure (VCE) which allo\h,ed for the genetic \,ari,ince of conditioii scorc. Thc gcsncltic
~1nequad1e sign matrices and 11iissi1ig observations \,ariance of 1ix.e ~ v ~ i g rh~t c l j ~ f~ur~ cto~nddit ion score
and pro\,idcd the standard errors of the es t i~n~l tes (G',,,, ) is then:
(Groeneveld, 1996).
The first aildlysis irlcluded I~angliill data only,
separated into (i) heifers aild (ii) heifers plus cows. and thc covariancc bet~veena djusted 1iL.e \\,eight ,illcl
The model ~ ~ s e colil the latter data set included, a seconcl tr'iit (T):
besides the additive genetic randoni effect, ,I
permanent en\~ironment,il random effect to takc
,lccount o f tlie covariancc between lactations on tlic
same cow. Fixed effects included in the model for the Finally, using these adjusted (cc~- ) \~ i r i ,~ ic tch~cs ,
Idanghill traits were: year (1980 to 1995) by genetic genetic corre1,ltions ( r , , ) ~ ~ i t 'l~id j~is tcdli \,cl \ \right
line (selectioi~o r control) by dict (high or lo\v were calculcited, is: l . , , ='o,, ,,, ,/(Go,, ,,,,) .
concentrdte) with 50 le\,els; month of cal\.ing (12
levels); lactation number (1, 2, 3 and >0); Holstei i~
1-7ercentage of the cow as a covc~ric?te'i;n d age ,it
calving and age at calviiig s ~ l ~ l ~ ~'1s r ccd~ \ , ~ l r i a t e s Results
withi11 eC1c1il actdtion group. O\,erClll n ~ e ~ i ~ph~rsno, t ypic stand,ird de\,iations,
t~cri t~~bil i t iacnsd perm,inent en\,irc~nnientaIe tfc3cts
Secoi~dly,~ liai nalysis (on heifer ancl heifer plus zow 'Ire gi\ cn in l able 2. The I~cri t~~bil i t ifeosr the,
data) was performed to establish the genetic complete data set 'ire soine~vhatl cnvcr thdn thosc
~ o r r e l ~ ~ t i obentsw een the linedr t),pe trClits, ~ n dti vcs from thr chtri set including heifer records o11lb..I n thc
of the Ldnghill traits (correlations bctwccn I, icld and heifer cl,it,i set, hcrit,lbilitics tor tht. yittld traits agrrr
type traits arc available from a larger national data closely with those rcportcd by Krotlit~rstont(~1 '19-l-).
set (Rrotlicrstone, 1993)). Although a complete For CS the heritability is coniparablc \\.it11 the.
multi\.ari'~tcm odel might have bee11 preferable, this Iierit~bilityf or yield. MeC?suresf or C1.W 'ind CCS
was not feasible cornp~~tationallFyo. r this r c ~ i o nt,h e. Iicl\,rl oxver herit,ihility tli'>n the. ,l\ erage of se\.ercil
genetic correlations between type tr'lits a n d the tr'lits llieasures during cc~rI>la.c t'ition. ' lhe repe,ltabilit!- ( / I '
recorded at l.c~ngliilwl cre estimatecl by a iluinber of + C ' = 0.81) ,lnd licritahility tor I~,W;I re relc~ti\,elhyi gh
b i ~ ~ ~ r i,a~tiie,l lys~As. subset of the highly correlated coinp<~rec~Iv itlit hese \.alues for the ott1c.r tr'lits.
388 Veerkamp and Brotherstone
Table 2 h l ~ , i i i i > , I I I I I >/i i i i i i i i i . i l i i i ~ i ~ i i i l i r ~ i i i( D,+, Table 3 P l i ~ ~ i i o t , ~ i/ il i~i~~ ~ i i~iiiii:~:o iiiili i i i i i i ;<iJii iZti~- i i ~ c ~ l o i i ~
/ ~ , ~ ~ ~ l i i l ifh~ 'jl i i i~ii iii ~j~ii7 i . i i~iri i i7i~it~ ~ ~ ; ~ i ~ i ~ i i i ic~f if ~i iitii i i(lci ' ) f o i . i i ~ i / : : i ~ i ~ i iL/Oi I I i 2 / n l ~ o i ilil i , t i i l i ~ i ~tl~ii/' l r . ( / l l s t ~ ~ i i ' i i i i ( i . ( .irili L ~ i ~ i ; ~ l i i l l
li!111.-l I I I L ~ ~ I - ILI ?~ / , I / L ~ I J I ; : / I ~ / /
Heifers M11h r\ 1'Y LJMI 1,M CS C'I W C'CS
Hc.itc31.~ 2lcaaii 0 , 11 ' \ v .
Milk 11.74 0.') 1 0-41 -O.lL) 0.42 0.10 -0.0 1
hlllh FY 0-59 0-79 0-50 0 - 0 5 -0-28 0.30 0-09
( l , ~ , dcl\J 1 ' 1 0.86 l1 74 0 49 -0.07 --0-27 0-25 0.07
F!' [g, <{<1l \ LIMI 11-34 0.62 0-40 0.32 0-05 0.12 0-1 2
I l l (q/~i'l!) 1.W -0.30 41- l l -0.20 0-0I 0-h(, 0-711 0.40
13\11 CS O-4h 0 . 3 3 -0 2'1 0.23 0.66 0..31 0-58
(hg /da \ ) ['LW 0.08 11-20 0.07 0.26 0.80 0.27 0.40
I \/V (kg) CCS -0 18 -0.07 -0-(1h 0.18 0-41 0-67 0.36
C S (X100)
C L1Y (kg) 5.e. of thc gcnetic corrclations ranges trom (1-(12t o 0.13.
C C 5 (xloo)
Hei ters
t i.o\vs hlilk FY PY LIMI 1.W CS CLW CCS
Milk 0.74 0.90 0.40 0 . 2 0 0 . 3 6 0-06 0 . 1 1
Milk PY 0.55 0.78 11-5C1 -0.13 -0.27 0.12 -0.05
( k g / d d ~ ) 27-2 1 - 1 1 0.27 0.02 0.2h 0.02 I'Y 0.80 0.75 0.50 -0- l3 0 . 2 8 0.05 -0-1 2
FY (g/d,ly) 1 1 12 187 0-40 0.02 0-1 8 0.02 DMI 0.59 0.76 0.64 0.19 -0.12 0.11 -0.13
I'Y (g/d,ly) 861 110 0.35 0-02 0.22 0.02 LW 11-09 0.03 -0-02 0.27 0-63 0.76 0.40
rIM1 CS -0.46 -0.31 -0.35 0.00 0.67 0.48 0.72
(kg/&)) 16-L) I -H 0.44 0.02 0.23 0.02 CLW 0.03 O.O(? 0-05 0.18 0.85 0-41 0-56
l W (kg) 597 50 0.44 0.03 0.37 0.03 CCS -0.38 -0.38 -0.33 -0.08 0.64 0.88 0.51
CS (X 100) 248 38 0.35 0-03 0.21 0.02
CI.W(kg) h13 5.3 0-35 0.02 0-24 0.02 s.c. of the genctic correlations ranges from 0.01 to 0.05.
CCS [XlOO) 279 37 0.24 0.02 0.09 0.01 t Milk, FY and PY arc milk, tat and protein yield, DMI is
dry-matter intake, 1.W and CS are live weiglit and condition
t Milk, FY and I'Y are milk, fat and protein yield, DMI is score, all averaged over the first 26 wceks of lactation; CLW
drymatter intake, LW and CS are live weight and condition and CCS are live weight and condition score at c'llving.
score, ,111 atreraged ovcr the first 26 wecks of lactation; CLW
,~nd[: CS arr li\,e weight a~ndc ondition score at calx,ing.
CCS, which was most strongly obser~edIn the later
Signs agree between the phenotypic and genetic lactations.
correlations for the Langhill traits (Table 3), with the
excevtioi-t of some of the correlations close to zero. A When measured during the first 26 weeks of lactation
negative correlation was fou~idb etween average LW ('Table 5) the same body measures appear to be useful
and ii-tilk production, ai-td a small positive genetic for the prediction of I>W and for the prediction of
correlntion between C1 W and production. Average CLW. ANG was strongly negatively correlated with
LW and CTdW were highly correlated, 0.85 and 0.80 LW in heifers as well and CW was highly positively
in the full and heifer data set respectively. Average correlated with CS in heifers and cows. CW and BD
CS wds negati\,ely correlated writh yield (from -0.29 were moderately correlated with DMI, whereas some
to -0.36), but highly positively correlated with of the udder traits (i.e. udder depth (UD) in both data
\\.eight (0.66 and 0.67 in heifer data and heifer and sets, plus udder support (US) and teat placement
cow data respecti~~elyD).M T and average [,W were side (TI'S) in heifers only) also appeared to be
moclerately but positively correlated (0.31 and 0.27). correlated with intake. The highly iiegative genetic
correlation of -0.69 betweeii rear legs and DMI in
Heritabilities for the type traits were all close t o the heifers is somewlhnt surprising, especially because it
l-teritabilities in the iiCltional p ~ p u l ~ ~ t i o nw as much smaller (-0.14) when later lactatioiis were
(Brotherstone, 1994) ('['able 3) . Genetic correlations added to the data set.
between CLW and the body measures of STA, CW,
KLI and rump width were high, ranging from 0.56 to
0.78. AN(; was not correlated ml-ith LW at first Discussion
calving but \vlien later calvings were added this Tl-te e5tlmatt.d \dr~ancec omponents between y~eld
correlation was -0.31. Some of the udder traits were and intake obtained In Table 2 and 3 agree w ~ t hth e
moderatelv correlated with LW at first calving. I>ess reported parameters in other studies (Persaud c7t 111,
;ui-tgular animals with a wider chest had a higher 1991, \ a n Aleiidonk r t 111 1991, Svendseii ct 171, 1994,
Genetic correlatio~~ins dairy cattle 389
Table 1 i ; i z i i i . t i i ~ 'c i r r~~l i i t rc ili~rsc ~ l i i ~ c/~i icl i~zii cilc ,i:.$it i i i i i i ce~i i i i i t io i>i c-ore7i l t i r ~ / ~ > i i(iC, yl 11; i i i i i i (-(-.S1 i i i i ~ i i ~ i c i ifi~t dL i i i i ; ; / i i / l i i i i i i l i i i i2ir i-f !ijli'
i i i ~ ~ i i ~ i i i i ~fii oi ii i~i ~l ~i o~tfl ii . iiii,yliiil i i i i i i tire i ~ i i l r o i i ii~l ili l i i % c 7 /
(Jenetic corre1,ition
1 lei ter. Hcitct-5 , c .o \ \ 5
I'otal score I \C
Stature. STA
Chest tvidtli C W
Body Jcpth nn
Angularit) ANC
Rump angle RA
liump 11.i J th IiW
Rt,ar legs side R1 5
Foot angle t A
Forc udcler ,ittCichment I-U/\
Udder support US
Udder depth U L)
Teat placement rear TPR
Tedt plC1cements ide I 1'5
Teat It.ngth TI
liange for s.e.
Jensen i,t nl., 1995). Herithilities wcre somewhat these studies. Similarly the genetic correlation
lower in the full data set, compared with the heifer between the different measures of live weight and
data set, the most likely explanation is the large yield varies between -0.30 and 0.20 in this study. In
negative sampling correlation observed between the the heifer data primarily, the genetic correlation
heritability and the permanent environmental effect. between yield and live weight at cal\,ing and
This suggests that heritabilities in the full data set between yield and live weight during lactation were
might be on the low side, whereas the permanent negative and positive respectively. Hence this
environmental effects might be on the high side. correlation seems to change over the lactation period
as was also suggested by van Elzakker and van
Reports of the genetic correlation between yield and Arendonk (1993). One possible reason for this is that
live weight have been less consistent across most of stored body fat is an important contributor to live
Table 5 Geiictic. c-orrtdntioiis b i~t i [~c,cd~r1i l1 - i i i i i t tc~ii itilh-t~i LlMl?, l i i s , i i ~ i ~ i c y(lLi tW )i ziiil c.oridltiori score, (CS?i iii~lbiirc'~1[1i t Lri i i ,y/i i l / i l i ir i i i ,y
f i r s t 26 i ~ l e ~ i k1?s~ 1i1ct1iti11i1i1i i ~/i i i i? [ i r ~ , I / ~i Iici ~ ~ i i s i i r c ~ ~ r1~1t1c11~1L ~f l~i i t~sy /~i i~i/1/1c 1~~t1~ii i~, i~~ i l t i o i i i[~l [ll t i i sclt
Heifers Heifers + cows
DMI LW CS DMI LW CS
TSC O.08 -0.14 0.19 -0.05 0.05 -0.06
STA 0.18 0.64 11-32 0-13 0.52 l1 1.3
CW 0.25 0.86 0.57 0.28 0-79 0.7.3
BD 0.20 0.8 1 (1.22 11-04 0.69 0-24
ANC -0.2 1 -0 56 -0.51 0.07 -0.13 -0.77
RA -0.12 0.07 0-18 -0 14 -0.15 0-(16
RW 0.1 1 0.71 0.14 0.24 0.70 0.29
R1.S -0.h9 -0.18 0 . 5 4 -0- 1 1 0.04 -017
F/ \ 0.2 1 0-19 0.42 0.06 II.08 0.10
PU A -0.10 -0.32 -0.12 -0.25 -0.06 11- l 1
US 0.46 0.24 -0.02 0.116 0.12 0.09
UD -0.46 -0-26 0.16 -0.55 O.O8 0.1s
TPR 0.06 -0.04 -0. I I -0. IS -0.07 -0.07
TI'S -0.30 11- 1.3 -0.14 0.06 0.05 -0.31
TL, 0.25 0.33 0.01 0.19 0.27 0.1 6
li,lngc tor s.e. 0-11 -0-19 0.06-0-19 0.11 -0.24 0.06-0.11 0.03-0.12 0.03-0.13
390 Veerka~nya nd Brotherstone
consequence ci t genetic st~lection, might not
ilc~ct>ss,l)r i be I ~ n r mfu l tor licLltll i or 12 cxlt,>rtt ot the,
dairy con. (tlicrc. is littlc c\,idence ; ~ b o ~tlhte ;;c' i lc ' f ic.
relationship bcttceen colidition scarc dnd I1eclllh 01-
Li\ C. \ \ cxi:;lit
fertilit!,), some concern might be justified bec'lusc of
'lli]ll\ttYd tor
tlie 'hioIogic,ll h~~fferinfgu nction' of bodq t i s i ~ ~ e .
1-i\ c> \ \ ~ > ~ g l lCt~ I I L I ~ ~ I I \IcI oI t-c
Tlicrcfnrt~ the high gc,netic correl,ition bet~vccnt lie
\liil, -ll.IlL1 0.2'1 yield traits ,111~1 conclition scorrl found ill this s t~ldy
I-<] t \-i~xlLi 0.0.3 0..32 (r,lnging from -0.29 to 0 .46) is an irnpc>rt,ultf inding,
l'l-cltC~ll1\ ieId 0-112 11.25 c~sp~ci~ilbleyc ause simply increasing thc r'itio of
[ ) v \ -111‘1 ttc,r lll l<, 0.27 LL.37
cmncrntratt, to forage given docs not seem an adequate
Condition score 0.b7 0.00
solution; results from Veerk'lrnp 1.t ill. (1995b) suggest
C'lie%t\ \.idth 0 70 0-4I
thdt conclition scorc decreclses for a selection line on
. \ t i g ~ ~ l ~ ~ r i t > 04.3 (1. 12
either ,l high or Ion, input system. This neptive
U ~ i ~ idtc~xpr t h 0 -OS 41-27
correlation is not surprising howc\lcr, given that
I c,it plxvtnent iidia 0.05 0.35
correlated increase in intake from selectio11f or yiclcl is
expectcd to cover less than 50(X, of the requireincnts
needed for the extra milk procluction (van Arendonk
c ' t ill., 199 l ; Veerkamp, 1991).
iceight during solne parts of thc lact,~tion, lnd high The reduction in conditio~si core '3s a consc~qucnceo f
p r o d ~ ~ c ic~olwg s might be expected to mobili~cm~o re genetic selection is likely to be accelerated since
body f , ~ t . This hypothesis is confirmed by the large ,~ngularity( or dairyness) is generally perceived by
genetic correl'3tion between live weigl~t and breeders as C? trait for which a high score is
condition score (0.67) reported in this study and favourable. Gi\rm the strong genetic correlation
given that the patterns cif tissue mobilization and between condition score and angul,~rity,e ven inorc
inilk yield differ across Idctation, co\~ariances selection pressure might be put on body tissue
betwecm yield and live weight inight also depc~ndo n mobilization. Also, in some countries selection for
tlie st'lge of lactation. The, rt,marknble effect of clecrcasing live weight (simultaneously with
adjusting li\,e weight for condition score is shown in ii!creasing yield) appears to be of economic interest.
Table h. The genetic correlation bet~reenm ilk yield L11 that situatioix condition score is expected to
and live weight (-0.09), for example, changes to 0.29 cleclrease even further because of tlie strong positive
after adjustment, and hence, selection for yield brill genetic correlation betwecn live weight and
result in heavier cows when comparecl at the same conditioi~s core. Hence selection for higher yield,
conclitioi~s corr.. This seems in line with the genetic more ang~11~1cro ws and a ~owerli ve weight all seem
correlation bctcveen measures of size (which will bc to increase body tissue mobilizatioi~c luring lactation.
one of the I'irgest components of adjusted 1iL.c
weight) and yield reported by Brotlierstone (lYC)-l): Alternatively, by using a restricted selection index
correlcltions between stdturc and milk, fat dnd (Brascamp, 1984) genetic selection can be used to
protein yield were 0.22, 0.l h and 0.25 rcspecti\,ely. ~ n ~ ~ i n tcaoinnd ition score at its current level, whilst
Also, the correlation between dry-1nattc.r intake and milk yield is increastd s im~~l t anco~T~hselv e.x pected
li\ e weight is larger after adjusting lice w,cight for reduction in genetic gain for profitability '1s a
condition score and solnc of tlir correlations with the consccluence of such an indcx can be illustrated by
type traits c11~1ngc c~nsicler~~b(ley. g. dng~~lari ty using the genetic parameters reported in this study
changes from -0.43 to 0.12). Thus, al t l io~~gthh e and the economic values of the profit index (PIN)
correlation bet~veent he two measures of live weight used in the Uniteci Kingdom (Veerkamp rt irl.,
is consistcntl>. high in this study dnd in line with 1995'1). A s s ~ ~ ~ n ioin~eg stai~d~lrcid eviation of
\,alues reported by \,ail Blzakker dnd \.ail Arendonk selection, selection on PIN alone increases milk yiclcl
(1993) and S\.endseii 1.f 171. (1994), correlc?tions by 324 kg per lactation and the margin over food
het\&,ecn Ii1.e weight and other traits (e.g. yield or costs by E64.60, but a\.erage condition score will
type) might depei~dm ore on tlie stage of lactation drop by 7.0 units (units 0 to 500). When condition
that 1iL.e wreight is rneas~iredA. nother exxnple is the score w7as included in a restricted index, then the
correlation between ,~ngul~~rai tnyd weight at first response in mxgin using the same selection
c;ll\,ing ~ r h i cils~ o nlv 0.07, ~ I i e r et~hils ~co rrel'ition intensity uras rcduced to Ehl.40, and the increase in
incrcdsed to -0.43 wlien a\.emge weight during milk yield can be expected to be 271 kg only.
lactation ~v,lsc onsiderecl c~ind1'1 1 lactatic~iisw hcrc Therefore c~ltliought he drop in conclitio~~sc ore
analysecl simultaneously. appears moderate as a consequence of selection for
Genetic correlations in dairy cattle 391
yield o n l ~m, 'l~ntainingc olictition scorc at its c~lrrcnt The optimal direction ot selection tor eclcli of the typcs
le\.el can bc. donc '1t tlic expense ot ~1 5"0 d r ~ in~ ) trdits is not ?as\ to establish until the eco~lomic
genetic progrc'ss. ~1t.s tor l i \ , c ~\ \.eight ancl food intake ,Ire known.
Strong genetic correlations between some of thc t).pe
The genetic ,~ssoci~itions~ ~ i t lilo ~icl~tioiis core traits m a k r it e\.en more difficult to ;~nticip,lteL Z hat
rcportcd in this s t u ~ l ym ake it e\,en less ob\.ious ]low o p t i n ~i~nd~elx \reiglits tor thc body trdits niight bc.
to us? the‘ genetic \~'iri,ltion of the complex of yield,
dry-m'1ttcr int'lke ,111d li\.e weight in the breeding C;enerallq, ~ l l i l s t i t is still ~ ~ n c l e ahro \v much
objccti\e. Ch,erall, food costs can be reduced by emph,lsis in the brceding goal should be placecl on
reducing maintc~n,?ncc cost (i.e. Is\z,csring li\,cl dry-niattcr intake, live wreiglit, condition score ,lncl
weight), incrcascd food intake capacity so that morc tlic rclatcd type traits it is clear that (i) there is
fol.,lge c,in hc used to s~ iyp lytl ic cmcrgy for tlie sanit- c~ns ider~ lbglet~ iieticv ariation in these tr<lits,a nd t11,lt
a m o ~ i notf yield (i.e. incrttclsing 1iL.e \\,eight), '1 change the whole com~7lexo f trenetic correlations s l~ouldb e
in pc~~-titiiinionfg f oocl (i.e. lo\.vering condition score) considered together wit11 the econornic \.alues to
or e\,en improving net efficiency (e.g. Klcike and determine the breeding goal, m d subsequently tlic
Cuslodio, 1983; C h e n and Kor\,er, 1989; Veerk'lmp optimum size of the dairy cow '3 rd (ii) li\,c weight
r ~ ~ i Edn imans, 1995; Veerkamp, 1996). Which m d food intake can be predicted from tlie type traits
(cornbin'~tion)o f these options is most feasible is not with little loss in accur'lcy. Because linear type traits
o b v i o ~ ~bsu, t it is c l e x th'lt economic and genctic are meC1surcd in most (inter-) national bretding
,~rgumcnts liould be considered sirr~ultaneouslyF. or programmc,s, thcy appcar to bi, a cheap altcrnati\.t\ to
cxaniplc, it is interesting to note that the economic r ~ i e ~ ~ s u rliin\,gc wciglit and foocl intake.
\.alue ot food intake m d 1 is.e weight could be eclually
important in sonle c i r c ~ ~ m s t ~ ~ nbcuets ,i n opposite
Acknowledgements
directions (Veerkamp, 1996). Ci\ren that these two
We tllrlnk Dr G. 51nin1a nd I'rofessol- W. C;. I l i l l for valuable
tr,iits are genetically correlated as well, including
disc~lssions 'ind Arnoud van de Lugt and Eildert
either one of the two traits needs careful
Grocnex~eldf or help with portiiig VCE to our oper<~tiiig
consideration. This is because what might be
systrni. The tram at 1.nnghill is acknowledged for tlieir
yercei\,ed to be p i n e d by including one of these
valuable contribution to the collection of tlic data, and we
traits, might in f,lct be lost because the other trait is thank tlie Holstein rriesian Society, Milk Development
changed ,IS a consequence of the correlated response Council, MAFF and SOAFD for supporting this work.
in the other direction.
References
Measurement of an individual cow's nerformance for
Arendonk, J . A. M. van, Nieuwhof, G. I., Vos, H. and
live weight and food intake is not common practice
Korver, S. 1991. Genetic ,~spects of feed intake and
for mc~stb reeding programmes, and therefore there efficiency in lactating dairy lieitcrs. Liilc.stc~iiiI 'riiiliictioii
is great interest in other traits which may help to S[-ic,iiicl2 9: 260-275.
predict these potential goal traits. Sieber r't 01. (1988)
Blake, R. W. and Custodio, A. A. 1984. Feed cftiCirncy: a
found negative correlations between estimated composite trait of dairy cattle. loiirili71 i!f Dniril Scic>iii,c6' 7:
efficiency and seven body measurcmcnts and 2075-2083.
Gravert (1985) reported that chest circumference is
Brascamp, E. W. 1984. Selection indexes with constraints.
an accurate predictor of food intake. Genetic Airii~ii~Rln ~tiiii:: A1~itr~ic.5l.2i : 645-651.
correlations between live weitrht dnd the bodv traits
Brotherstone, S . 1994. Cenetic and phenotypic correlations
were consistently high in this study, even after hrtween linear type traits and production traits in Holstein-
a d j u s t ~ l ~ efnotr condition score, and chest width and Friesian dair! c'1ttle. Aiirrriiil I'roiliri-tioii 59: 183-18 8.
body depth were moder,ltel!~ correlated with dry-
Dempfle, L. 1986. liicrc~iisiiii~lic . i$?cicvicy of tliij iIiiir!/ i i i i i l
matter intake. When stature, chest width, body
ziitll riz,yiiril to bo~1.11ri zca. IZcsaircIi birllctiir ilo. 4. Li~estock
depth, c lng~~lar iatyn d rump width are combined in Iinl.7ro\enicnt Co., N ~ LZVra lancl Dairy Board, I laniilton,
one index, tlic accuracies of selection on this inclcx Ne~vZ ealand.
for dry-[natter intake, live weiglit ( c ~ d j ~ ~ sftoer dC S) Elzakker, P. J . M. van and Arendonk, J . A. M. van. 1993.
and condition score arc 0.65, 0.84 and 0.88, Feed intake, body weight and 111ilk prod~ction:g enetic
respecti\~ely.W hen milk, fat dnd protein yield were ,~n,lly\is of dittcrcnt meas~~reiiientisn lactdting d,liry
included in the index tlie accuracy with dry-matter heifers. Lii~c~stoPikr odiictioii Scicvrcc, 37: 177-5L .
intake increased to 0.90. Hence, selection for live Gravert, H. 0. 1'185. Cicnetic f<~ctorsc ontrolling feed
weight and perhaps for food intake can be done efficiency in dairy cows. lir~c~torPki o~i~ictioiSi cicziic-I, 13:
relatively cheaply, because linear type traits are 87-9'1
measured in most (inter-) national breeding Groen, A. F. 1989. Econonlic vnlues in c'lttle breeding. 11.
programmes, and appear to harre high genetic Influcncc. of production cir'u~nstanccs in situ,ltions with
correlations with these traits of economic interest. output limit,itions. l irr'stocli Proiiirctioil Sciriirr 22: 17-00.
392 Veerkamp and Brotherstone
Groen, A. F. and Korver, S. 19SY. 'Tie economic x-,~lueo t Veerkamp, R. F. 1904. Genet~ci nipro\c,mt.nt ot econotntc
feed intake capdcit!, ot Jairq co~vs.L ii~i',t~i-kP roiiiic.tro17 performance i l l dairy cdttl~.. 1'11 P,/ lii,sii, 1ii i i i~izi~o/it ~/
Sii~,iic.c2,2 : 269-28 1 Liiliillili;~/i.
Groen, A. F., Arendonk, J. A. M. van, Steverink, M. H. A. Veerkamp, R. F. ILIOh. Live tvciglit and f e t d rntnkc in ~1,111-h
and Berentsen, P. B. M. 1994. The economic \,alue of body c,lttlt, brtwlit~pg, o ~ lP. r occ~c~iiiii,iy~i tl ii, iiiti~iiiiit~i~iii~iii r.iiiiio;~
weight in dairy cattlc: influences of t,lrnl intensit? ,incl i l l1 ~ l l ~ ~ ~ ~lit. il l~t5 l il lr ~Li~lttlii ,, ~~i~llrl~llllRiYc7,I ;~l1lirl1. 11tcr~~llI
en\ ironmental legislatioil. Fort!/-fittli iiii~iiiiiii r i c ~ c ~ t i ioif ~ tliiz hulletin no. 12, pp. 173178.
E i i r i ~ / ~Ac,~.i~~t~-ini t ii~ioi f Aiiiiiiiii Proiiiic~lioiiL, ii'iiihiir~~li.
Veerkamp, R. F. and Emmans, G. C. IC)L)5S. oi~rcc'i ot
Groeneveld, E. 19'16. IitML VCE i7 ~iiiiiliinir.iiiti~ii~ii lti rrioiiei genetic xariation in energetic efficicnc! ol d,iirv CLIIVA, a
i.i~~trictc~riri ~ i i ~ i i i i i i ~ ilii ki~liliooii (1'11) iliii-iiiiic-13 ioi7ijioii~iit rcvicm,. L I ~ Y ~ S / O Cl/ <'r oiiii~-tic~SiiC I~'I4I4C: ~87' -'17.
i~stiiiriitioiiy iiclcii~~V.c ~rsir~3ii. 2 iiii~r'i~ iir~iiF.e. deral I<esearch
Veerkamp, R. F., Hill, W. G., Brotherstone, S., Stott, A. M'.
Centre of Agricult~~rMe,a riensee, Germany.
and Simm, G. I'1C)5c1.S clt9ction for longexrity and yielJ in
Jensen, J., Hohenboken, W. D., Madsen, P. and Andersen, Jairy c ~ t t l eu sing transmitting '~hilitics~ O I -y ield a n d type.
B. B. 1995. Sire X nutrition ~nteractions and genetic Aiiiirinl Scic~iic-c6,1 : 189-197.
parameters for energy intake, production, and efficiency of
Veerkamp, R. F., Simm G. and Oldham. J. D. IC194.E ffects
nutrient utilisation in young bulls, heifers and lactating
o f interaction between gcnotype and feeding system o n
cows. Actii A,qrii.iiltirriz[~S i.iliidii?ii.i~ic4ii5 : 8 1-9 1.
milk production, feed intakt., efficient) and hod! tissirt.
Lowman, B. G., Scott, N. and Somerville, S. 1976. Coi7ditioi7 mobilisation in dairq- coiws. Lii1c.stoc.X Proiiiiitioii S~,ii,irc-3i>9 :
sc.orin,y of c~~ttlcR.. PII~S(~z'dLit~i~ ir.B ulletin ot the East Scot1,lnd 229-23 1.
College of Agriculture, no. 6.
Veerkamp, R. F., Simm, G. and Oldham, J. D. 19Y5h.
Milk Marketing Board. 1990. Report i!f tlic Fiirrpr Scrr1icc.s C;enotype by en\ironmrnt intercletion: expericncc from
Drilrsroir 1988/89, no. 39. MMB, Thames Ditton, Surrey, UK . Langhill. In Brc~dii?:: iiird fi.c~diiit~l?i z lir,yli ,~ivrc~/irii.c ,rit iiciiiy
c.oiO (d.T . I,. J. Law~rcnce,F . J . Gordon and A. Carson), pp.
Persaud, P., Simm, G. and Hill, W. G. 1991. Genetic and
59-66. British Society of Animal Science occasional
phenotypic parameters for yield, food intake and efficiency
publication no. l').
of dairy cows fed od libiturrr. 1. Estimates for 'total' lactation
measures and their relationship with live-weight traits. Visscher, P. M., Bowman, P. and Goddard, M. E. 1993.
Atrirt7nl Productiorl 52: 435-444. Brceding objectives for pasture based dairy production
systems~1o iiriiiil of Diiir,t/ SC~~'I7I6C:( (' suppl. l ) 255.
Sieber, M., Freeman, A. E. and Kelley, D. H. 1988.
IZelationships between body measurements, body weight,
and productivity m Holstein dairy cows. /oilr.rinl c$ Dairy
Science 71: 3437-3445.
Svendsen, M., Skipenes, P. and Mao, I. L. 1994 Genet~c
correlation In the feed conversion complex of primlparous
cows at a recommended and a rcduccd plane of n u t ~ ~ t l o n
lo~ritiaoi fAri11riol Scii>rlcc7. 2: 1441-1449
Effect of altering the non-structural: structural carbohydrate ratio in a
pasture diet on milk production and ruminal metabolites in cows in
early and late lactation
V. K. Cdrruthers, P G. Neil and D E Dalleyt
Diiiryir~gR c.ic~izr~1C1' c~rpowtlor~P,I rz~ntB[i~zg 3123, Fli7ir11lfo1N1r,( r1 Zcizlilil~f
Abstract
Thr e f i~ct oil L ~ I ~ L ~ I s1 1~ 1 1Ir i 1~~ 1tI1n c~~tInb~ol~tr, sri, r ~crobrnlp rotrlrl 51/r1thrsrs and 11l11k~ Y I ) ~ I I L (~fI iOr ~~ i z n ~ p ~ i l a f l i ~ g
thr non s t t ~ ~ ~ t iI N~ Sr C[ ~) I5 t ~ 1 1 ~ f ~( S~Ci )n cnl r boll~drizt tY~Q ~ I O11 1 17 p r t ~ d ~ n ~ i ~ ~pans~trz~frlrd yl ef ions r~~vesflgirte11d1
cocvs rn eizrly (/urn/ 1 ) 1712d lute ( f ~ l n2l ) lilt tilfrorl T i / ~ ~ l l t y Lf O ~~ U~I I ~I~ f 11n11 n11d 15 COWS ln f i lal 2 rurrcJ ofired
/7niflrvcJo n ly (P) , 0 85 P p1115 O 15 NSC/;~rotclrl ~rrlxtrlre( PR),a nd P jd1~5n il addrtl~rrnl0 1 ( i ~ l n1l ) 0 1 U 15 ( t ~ ~2n) l
N S C ( P E ) rn u Lntirl-5quarc izr r a ~ r g ~ m e nAfl l rirrti were rsonifrogenous and P arid P R ~ v c r cii oenergtJtlc PE but
riot P R 111~1riz5c~dn rcrobr~pzlu otelr~s ynt!rt,s~sa nd decr~asedr nnrnlal nmmonrn ancl iirrlk urea lcvcls, colnpnred ~111th
P E f f i c l m ~ yof rrlicroE~lnli ynthr5ri (g N per kg drgcst~blro rpnrc rnrrttev ~ i ~ t a k tm?n) s not altered by tveatnrrnt
Trcntr1rcrzt5 llnd r n ~ ~ r oefif ccfs or1 re~rilinalp H and no cfiect on 71olatllcfatty ncrd concentrntlorzs PE a n ~Pi R d ~ dno t
affc-t irnlk yleld or profein yield and decrtvseclfat ylcld corripared w l th P i n trla1 1 Mrlk ylcld 7uas ~rzcreasedo n PE
ancl P R iorizpavrd w i th P urld was gremter or1 PE Mlarl PR, 111 trml 2. Ylrlds o f f a t and j n o t ~ l nw ere hlglzer on PE
than on P and yleld of protrrn was hzxher on P R t l ~ a n01 1 P. Tlze res~rltss uggest that rrzcreasing the rat10 of
N S C . profern b y rnLrrasln<yt ofnl cnrhohydrafe lrzfakc was mort7 tIffecflve 1n lnlprovlng nltroigcn u t ~ l r z a t ~ o17i1 ~tl ze
rlrrnerl t!1i711z uas rncreailng the N S C . S C rat10 w l t h o ~ l~ntc renszng carbohydrate ~ n t a k e
Key7uords cnrbohydratrs, darry cows, nlrlk pmductroiz, pnsfure.
Introduction excessive excretion of nitrogen (N) in the urine
Temperate pastures based on ryegrass (Lolilrnl (Ulyatt cf al., 1988; van Vuuren et al., 1986 and 1991).
pprcnrlc L.) and white clover (Trifalillullr .cpcrls L.) are AS a consequence of the high rate and extent of
characterized by crude protein (CI') concentrations of Pa"ure CP degradation, the amino acid supply to
200 to 300 g/& of pasture dry matter (DM) and non- the "all intestine in pasture-fed cows may limit
structural carbohydrate (NSC) concentrations of 50 animal performance. Syllthesis of microbial protein
to 250 g/kg DM. The concentration of neutral- from ruminally degraded Cp is energy dependent
detergent fibre (NDF) ranges from 450 to 500 g/kg and rumen fermentable energy can be first limiting.
DM, Tllese Cp and NDF concentrations are high; and Increasing the ruminal availability of energy, and/or
the NSC low, compared with diets synchronizing the rates of fermentation of protein
for high dairy cows and carbohydrate, are considered by some to be
(National Research Council, 1989). The CP in pasture importallt for optimal microbial protein syllthesis
is characterized by the high rate and extent of (Chase, 1993; Mansfield ('1 a/., 1994; Sinclair et ill.,
rLllninal degradability, which can result ill high 1993; van Vuuren et al., 1990). The relatively IOW
concentrations of ammonia in the rumell and NSC levels in some pastures could limit microbial
efficiency and milk solids production in pasture-fed
dairy cows.
t I'rescnt address: A g r i c u l t ~ ~ rVe i ctoria, Dairy Research
Institute, Ellinh'ink, RMB2460, W,lrragul, Victoria 3820, Two trials are described which aimed to determine
Australia. whether increasing the proportion of NSC and
393
794 Carruthers, Neil and Dalley
dttcrc,asing thcs proportion of struct~~rca;lr boliycir,itc~ N per 11'1 was applied to the t \ ; \~a) r e z regrall-n for
(S<:) o f 1' pwd(~inin;untly pasture diet ,iffectc,d h,~r\,cstin pc.rioc1 3. I',istt~rr ~ v a sIi ar\.ested using a
1lti1iz;ltion 0t dietary N ,~nd microbial protein reel mower nlid picl\-up \vagon t1vic.c d,iiI> a t 07.00
sy~ithesisi n exly '11id latc lactation. A summary of and 15.00 11 ancl offered to the cow7s at 09.00 to
sollie ot the results wds given bv Carrl~tliers1 .t i l l . 14.00 11 (proportionately 0.35 ot dail! r'ltion) '~ncl
( l 09h). 16.00 to 22.0011 (0.55 of dail! r,ltiol~).T lxe fresh
\v~ighto f pasti~rc to offer 'it e,ich teecling rIras
estimatecl from thc microwa\,c DM c'onctntration of
Material and methods samples o f harvested pasture.
Triizl l :~ ' i z r /I~i7/c -ti1tic111
Coil15 i i i l ~ ft rc~ntir~c~ii'tIs'.~ r e~ i t ) , - fcoo~~~vrs ( 19 Friesi,in [Five Jerseys m d 10 Friesi,~ns wcre penned in 2 X
and five jersey) aged 3 to h ).cars and weighing 10 m pens for individual feecling throug1~)utt he
434 kg live ~veiglit( LW, r~liige3 38 to 525 kg) and 02 trial. The remaining nine rumcn fist~~lateFdr icsians
days in milk (DIM, 1 1 to 49 ddys), czrc,rc dllocated to were penned for days 1 to 4 of each period aiid in
three treatment groups balnnced for DIM, LW and rnct~ibolisms talls tor days 5 to 14. Cows in pens were
milk yield during the week prior to tlie experiinent. released oil to a barc paddock bctwecn 13.00 to 15.00
Twe1L.e of the Friesians were fistulated in the dorsal and 22.00 to 07.00 11. Water was a ~ ~ ~ i l aabt laell tinies
rumen. dncl NaCl blocks were available to cows in the bare
paddock or every 2 to 3 days to cows in metabolism
Metabolirablc cncrgy (ME) intake for each cow was stalls.
estiinatcd (Holmes and Wilson, 1987), based on
LWu7?a iid production in the week prior to period I , The protein and NSC mixtures were inixed with
and ~ ~ s etdo set the total M E intake of diet water c~lldd renched in four equal parts at 09.00,
components for each cow on each treatment. 'Ihe 11.00, 16.00 and 18.0011. Cows were drenched ,1t
treatments were: P - pa s t ~ ~orncl y; PR - 0435 P plus 09.00 and at 16.00 11 with 10 g magnesium as MgCl?
a NSC/protein mixture to provide the reinaining mixed with a pluronic-based bloat preventative.
0.15 of the cow's ME intake; PE - P plus NSC to
provide '3 total ME intake of 1.10 of that on P alone. Siii~ip1117ig~ 1 7 I~ If I L ~ L I ~ L L I ( ~A~ ~sIa~m~ pP l~e~ o~ f herbage was
All treatments were designed to be isonitrogenous taken twice daily for DM determination by w e n
and treatments P aiid ['R to be isocaloric. Individual drying at 100°C for 48 h Oil days 8 to 14 further
ME ~ntakesIn ~7eriod1 were set at 0.9 of calculated subsam~les were collected and bulked tor
requiremeiits, to ensure nil refusals of the pasture determination of organic matter (OM), gross energy
component of tlie diet but were increased 0.02 and (GE), NDF, water-soluble carbohydrate (WSC), total
0.03 in periods 2 and 3, respectively, as the cows' N, soluble protein N, calciurn, sodium, magnesium,
intakes improved. The replacement protein consisted phosphorus and potassium. A further subsample
of a 20 : 50 : 30 mixture of urea, lactic casein (New was bulked fresh over the 7 davs for ~3lants necies
Zealand Dairy Research Institute, Palmerstoii North) determination. Orts were weighed and sampled for
and formaldehyde-treated casein (Brookes, 1984). oven DM deterininatioii after each feeding.
'I'lie NSC niixturc consisted of 50 : 50 maize cornflour
and dextrose monohydrate (NZ Starch Products Ltd, At 4- to h-day inter~~alhse,r bage from paddocks to be
Auckland). The ratio of protein to NSC in treatment cut iii the next 3 to 3 days was sampled by clipping
PR was adjusted every 4 to h days based on the total to mower cutting height, dried at 100°C for 24 h and
N concentrdtion of samples of herbage. ground for total N determination. This was used to
calculate the aniount of N to adnlinister to cows on
Treatments wcre offered during three 14-day periods treatment PR.
in September and October 1994. Measurements were
made over days 8 to 14 of each period. Cows were During days 8 to 14 milk weights were recorded
milked at 07.00 and 15.001i each day. Oestrous at each milking. For penned cows n weighted
behaviour of the cows was controlled using CIDRT" aliquot of milk collected on each of days 10, 12
devices (IiiterAg, H,tmilton, New Zeal'md). and 14 was analysed for fat, protein and lactose.
Cows in inetabolism st'11ls were Inilk sampled
Past~irt 'n ~ l ~ i f i i > i i iT~hl ge. pasture was divided into t o ~ ~ r d aily for fat, protein 'ind lactose determination.
~Jrease, 'icli are'i providing 7 to 10 days of food. Two Forernilk samples were collected from all cows at
of the areas were harvested twice (for periods 1 and 07.00, 11.00, 15.00 aiid 19.00h oil days 10, 12
3) aiid tlie remaining dreas once (period 2). Each area and 13 for urea determination. Samples were
received 90 kg N per ha as urea in an equal split centrifuged at 1500 X g for 15 min and the fat
,~pplication2 8 1'11d 21 days before thc first harvest free portion was stored at 4°C and bulked across
day on t h ~atr ea. A second split applicatioii of 90 kg days within sample times within cow.