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Genetic Correlations Between Lifetime Production and Linearized Type in Canadian Holsteins
Genetic Correlations Between Lifetime Production and Linearized Type in Canadian Holsteins D. J. KLASSEN, H. G. MONARDES, L. JAIRATH, R. 1. CUE, and J. F. HAYES Department of Animal Science Macdonald College of McGill University 21 ,I 11 Lakeshore Road Ste. Anne de Bellevue, W,Canada H9X 1CO ABSTRACT
trait is a function of production per lactation, length of productive life (longevity), age at first calving, calving interval, feed and milk prices (2), as well as health and husbandry aspects, such as mastitis, reproductive failure, disposition, and udder problems (1, 4, 21). Dairy farmers are reluctant to accept first lactation production as an adequate indicator of lifetime profitability. Lifetime production traits combine production and longevity information. The influence of higher lifetime production on lifetime profitability can be assumed to come from increased income from sale of milk as well as decreased costs because when cows live longer, fewer replacements are necessary. Milk sales increase because cows are better producers and because more cows in the herd are producing at a mature cow level. However, lifetime production traits can only be measured on cows at the end of their productive lives. Relationships of various measures of type with first lactation production (7, 8, 10, l l ) , lifetime production (8, 11, 12), or longevity (3, 5 , 6, 11, 17, 18, 20) have been reported. The objective of this study was to examine genetic and phenotypic correlations between lifetime cumulative milk, fat, and protein; lifetime income from milk sales over feed costs; lifetime days in milk; and total number of lactations with the 28 linearized type traits recorded on the Holstein Classification Report.
Genetic and phenotypic correlations were estimated between 6 lifetime production and 28 linearized type traits using REML. The data set contained 34,322 cows, each with a record for all 34 traits. The analyses accounted for the fixed effects of herd, year-month, classifier, age at first calving, and stage of lactation. Heritabilities were low for lifetime traits and moderate for most type traits except stature, size, capacity, thurl width, and pin setting, which had high heritabilities. Most phenotypic correlations between lifetime production and type were in the range of .15 to .20 except for capacity, rump, and feet and legs, which were around .07. Genetic correlations were strong between lifetime production and angularity (.44 to .55) and dairy character ( 5 3 to S6). Genetic correlations were low to moderate between lifetime production and stature (.14 to .25), size (.07 to .18), texture (.19 to .26), style (.11 to .27), head (.15 to .23), pin setting (.lo to .16), rear udder (.19 to .25), and rear attachment (.lo to .22). The only notable negative genetic correlations were lifetime production with rear heel (-.16 to -.27), thurl width (-.18 to -.24), and fore udder (-.05 to -.11). (Key words: genetic correlations, lifetime production, type, Holstein)
MATERIALS AND METHODS Data
INTRODUCTION
Lifetime profitability can be regarded as the ultimate breeding objective in dairy cattle. This
Received September 16, 1991 Accepted April 2. 1992. 1992 J Dairy Sci 75:2272-2282
A total of 176,778 type classifications, performed between June 1981 and June 1986, were obtained from the Holstein Association of Canada. Preliminary analysis of type data showed that about 81% were classified during first parity. Classifications at later parities were not used. Approximately 8% of the records were reclassifications. For those cows, the first
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classification of record was used. Records with no calving date (4%) and records for cows older than 40 mo or younger than 22 mo (5%) were removed in the initial editing, leaving 114,3 14 type records. Approximately 960,000 lactation records, initiated between 1980 and 1989, were obtained from Quebec Dairy Herd Analysis Service. Lifetime measures for 222,3 15 cows were constructed, ensuring that all cows had a first lactation starting between 18 and 40 mo of age. Only cows with consecutive lactations in the data were included. All cows were required to have either a reason for disposal recorded for their last lactation or a code indicating that they were still in production. All cows were required to have feed intake recorded. There were 53,941 records with both lifetime and type information, one for each cow, identified using cow registration number and birth date to match the files. Only 131 cows calved for the first time before January 1982, and those records were deleted to ensure adequate numbers of cows in each year-month subcell. A study of the effects of truncation on estimates of genetic parameters for lifetime traits, using a data set in which all cows had completed their productive lives (Jairath, 1992, unpublished study), indicated that, for cows still producing in the herd, data sets should be chosen so as to allow the youngest cows the opportunity to have at least 4 yr in production. Following this recommendation, cows first calving after December 1985 (15,895 records) were removed from the data set. Therefore, the data set consisted of cows that had completed their lifetimes in the herd and of cows in the herd that had at least 4 yr of production. Cows from sires with fewer than 5 records (2467 cows from 1180 sires) and herds with fewer than 5 records (978 cows from 395 herds) were excluded to reduce the effects of biases from preferential treatment of a particular sire's daughters in a particular herd or group of herds. To ensure adequate numbers of records in each fixed effect, cows younger than 24 mo (164 records) or older than 40 mo (387 records) at first calving were excluded. Also, records from classifiers with fewer than 250 records in tokl were excluded (589 records). There were 34,322 records that met these prerequisites.
Traits
Apart from the lists of defects, the type classification report from the Holstein Association of Canada reports 28 traits, all of which were used in this study (see Table 1). These can be broken down to general characteristics (4 traits), description of parts (14 traits), score card traits (8 traits), and final classification (2
TABLE 1. Phenotypic means and standard deviations for lifetime production and linear type traits. Trait
X
SD
Lifetime Milk production 18,360 12,521 Fat yield 654 448 Protein yield 583 397 Milk value over feed cost 4640 3361 Number of lactations 3.17 1.39 Days in milk 981 474 Final classification 3.4 .6 Final class (1 to 6) Final score (1 to 100) 78.4 2.6 Score card (1 to 18) General appearance 8.8 1.6 Dairy character 10.9 1.5 Capacity 10.9 1.7 Rump 2.0 9.4 Feet and legs 9.4 1.9 Mammary system 9.4 1.6 Fore udder 9.4 1.6 Rear udder 9.6 1.8 General characteristics (1 to 9) Stature 5.7 1.5 Size 5.6 1.3 Style 4.5 1.2 Angularity 5.6 1.1 Description of parts (1 to 9) Front end 1.1 5.6 Head Midsection 5.6 Chest 1.1 6.2 Loin 1.3 Rump 6.0 Thurl width 1.3 1.1 Pin setting' 5.1 Feet and legs Rear heel 4.9 1.2 Bone 5.9 1.3 Rear set' 1.2 5.1 Mammary system Texture 5.7 1.1 1.1 Fore attachment 5.0 Rear attachment 5.0 1.2 Median suspensory ligament 6.0 1.1 Fore teat placement 5.5 1.4 Rear teat ulacement 1.4 6.9 lIntermediate values are desirable. Journal of Dairy Science Vol. 75, No. 8, 1992
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traits). Score card traits included a code (1 to 6) and a rank within that code (1 to 3) with higher numbers being more desirable. These two numbers were combined to give a single measure, which ranged from 1 to 18 (e.g., 3(code - 1) + rank), to make the score card traits more linear. Six lifetime traits were examined in this study: cumulative milk, fat, and protein production over the lifetime of the animal, cumulative days in milk, cumulative milk value over feed cost, and total number of lactations. The amount and average cost of feed for each lactation were available to allow calculation of lifetime feed cost. Cumulative days in milk and total number of lactations relate mainly to survival, whereas the other 4 traits combine survival and production information. All lifetime totals utilized actual lactation information and did not precorrect data to a 305-d lactation. Statistical Analysis
For computational ease, type traits were split into two groups: 1) score card and final classification traits in group 1 and 2) general characteristics and description of parts in group 2. Each group was analyzed separately for lifetime traits using a multivariate model. Group 1 analysis included 14 traits: 4 lifetime traits and 10 linear type traits. Group 2 analysis included 24 traits: 4 lifetime traits, 2 survival traits, and 18 linear type traits. Before analysis, all traits were transformed to have a mean of 0 and a standard deviation of 1. Initial analyses indicated herd, round, classifier, age at' first calving (in months), and stage of lactation (12 monthly classes, the last class being for 12 mo or more) were important fixed effects for most of the 28 type traits. Year-month of first calving and age at first calving were important for the lifetime traits. Herd-year-month combination was not considered because of small subcell size. Herd plus year-month accounted for more variation than herd-year-season in the preliminary least squares analyses. A multivariate model was chosen to produce equal design matrices for both fixed and random effects as follows: Yijho
= Hi + YMj + Clk + eijko
+ A1 + L, + S n
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where Yi,um,, is observation ijklmno for each trait in the model, Hi is the fixed effect of herd i (141 1 levels), YMj is the fixed effect of yearmonth j (48 levels), Clk is the fixed effect of classifier k (7 levels), A1 is the fixed effect of age 1 at first calving (17 levels), L, is the fixed effect of stage of lactation m (13 levels), S, is the random effect of sire n (1043 levels), and q , h 0 is the random residual associated with cow ijklmno. Sires and residuals were assumed to be independently distributed with zero means and variances G * A and R * I, respectively, where G is the matrix of sire (co)variances, A is the relationship matrix between sires, R is the residual (co)variance matrix, I is the identity matrix, and the asterisk refers to the direct product of two matrices. A computing package (REMLPK) from K. Meyer (University of New England, Armidale, New South Wales, Australia) was used to analyze the data. The algorithm was designed specifically for analysis of traits with equal design matrices. The traits are first transformed to canonical scale to reduce the problem to a series of univariate analyses as proposed by Meyer (9). The expectation-maximization algorithm is used in conjunction with a transformation to tridiagonalize the mixed model equations to estimate the (co)variance components (19). The algorithm forces the covariance matrix to be semi-positive definite, which is an important advantage when a large number of traits are in the analysis. Approximate large sample standard errors are calculated by the algorithm using numerical differentiation around the converged values. RESULTS AND DISCUSSION Means, Standard Deviations, and Fixed Effects
The means and standard deviations of the lifetime production, survival, and type traits are given in Table 1. The linear type traits tended to be close to a normal distribution, but the lifetime traits tended to be skewed, as can be seen in Figure 1 for lifetime milk production. Figure 2 shows the distribution of lifetime milk production after a log transformation. A preliminary analysis using a subset of lifetime production and type traits found that
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LIFETIME PRODUCTION AND TYPE CORRELATIONS
--"
1500
5
z
$
1000
a 51
i 500
-1.5
0
4.4
Figure 1. Distribution of lifetime cumulative milk yield standardized to have zero mean and unit variance.
overparameterized in the fixed effects because we assumed that there was less chance of inadvertently biasing the estimates than precorrection of the data. The lifetime traits were particularly vulnerable to biases arising from precorrection because of possible truncation at the end of the data, at which time long-lived cows had only partial records in the data because they had not finished their lives. The data set was truncated at December 1985 to minimize the number of cows in the data set with incomplete herd lives. However, the least squares estimates for year-month of first calving (Figure 3) show a decline in lifetime milk production over time. These effects were only slightly different when sire was included in the model, indicating that the decline was probably not genetic in origin. This decline could be partially due to dairy farmers culling more older cows, but it is unlikely that the average number of lactations would drop by .25 lactations over 4 yr for this reason alone. However, the most likely explanation is that the truncation effect has not been completely eliminated from the data. However, the biases in the variance component estimates from truncation should be minimal (Jairath, 1992, unpublished study).
heritabilities and genetic and phenotypic correlations of the log transformed traits were unchanged from the untransformed traits. Based on these results, no log transformations of lifetime production traits were utilized in this study. The fixed effects of classifier and stage of lactation accounted for approximately 1.5 and 4% of the variation after correction for the mean in most of the type traits. These effects accounted for less than 1% of the variation in the lifetime traits and were generally not significant. Age at first lactation accounted for .5 Canonical Traits and .7% of the variation in lifetime production In the group 1 analysis, the heritabilities of and type traits, respectively. Year-month accounted for 2 to 3% of the variation in the the canonical variates ranged from near zero to lifetime traits and around 1% in the type traits. -52. In the group 2 analysis, the heritabilities Round was not fitted because it was con- of the canonical variates ranged from near zero founded with year-month. The model was to .70. Obtaining heritabilities close to zero
30001
I
83 -.6
0
I .9
Figure 2. Distribution of the log of lifetime cumulative milk yield plus a constant.
I
I I
84
85
I 86
Year - month
Figure 3. The effect of year-month of first calving on lifetime milk yield. Least squaes estimates are deviated from first subclass.
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means that the eigenvalues of the (co)variance matrix are close to zero and indicates that some of the parameter estimates are close to the edge of the parameter space. This is not surprising in analyses with large numbers of traits. However, these parameter constraints probably did not have a large influence on parameter estimates, because several preliminary analyses using different subsets of traits resulted in parameter estimates similar to those described in this paper. In both group 1 and group 2 analyses, the canonical variate with the largest heritability was largely defined by lifetime milk minus lifetime fat.
and fore udder (-.30). Large phenotypic and genetic correlations existed between final class, score, and general appearance; genetic correlations were close to unity. Mammary system is highly correlated to both rear and fore udder (phenotypic correlation >.80 and genetic correlation >.88), with lower correlations between fore and rear udder (phenotypic correlation S O and genetic correlation .60).All score card traits have phenotypic correlations greater than .3 with final score, final class, and general appearance; phenotypic correlations for mammary traits were from .58 to .78.Genetic
Heritabilities of Type and Lifetime Traits
TABLE 2. Heritability estimates and standard errors from group 1 and group 2 analyses for lifetime production and linear type traits.
Heritability estimates are presented in Table 2. Lifetime production traits of milk, fat, and Traits protein yields, and lifetime milk value over feed cost had a heritability of approximately Lifetime Milk production .lo; number of lactations and lifetime days in Fat yield milk had heritabilities of .05 and .07; linear Protein yield type traits had heritabilities ranging from .10 Milk value over feed cost to .48. Most type traits had moderate heritabili- Number of lactations ties between .10 and .25. Traits with heritabili- Days in milk classification ties greater than .40 were stature, size, and pin Final Final class setting; .30 to .39 were capacity and thurl Final score width; .10 or less were rear heel, head, and Score card udder texture. Lifetime production traits tended General appearance to have a heritability between that of survival Dairy character Capacity traits and first lactation production. Correlations Between Lifetime Tralta
Genetic and phenotypic correlations between lifetime traits (Table 3) were all extremely high (.91 to .99), indicating that many of the same factors are involved in controlling these traits. The lowest correlations were between number of lactations and the lifetime production traits with phenotypic correlations of .91 to .93 and genetic correlations of .92 to .95. Correlations Between Type Traits
Genetic and phenotypic correlations between linear type traits in group l are presented in Table 4. All phenotypic correlations and most of the genetic correlations were positive. The only negative genetic correlation larger than -.2 was between dairy character Journal of Dairy Science Vol. 75, No. 8, 1992
RWP Feet and legs Mammary system Fore udder Rear udder General characteristics Stature Size Style Angularity
Description of parts Head Chest Loin Thurl width Pin setting Rear heel Bone Rear set Texture Fore attachment Rear attachment Median suspensory ligament Fore teat placement Rear teat ulacement
h2
SE
.10 .10
.01 .01 .01
.09
.10 .05 .07
.01
.12 .16
.02 .02
.17 .29 .33 .28 .I3 .15 .16 .14
.02 .03 .03 .03 .02 .02 .02
.48 .43 .17 .25
.04
.10 .23
.o 1
.19
.31 .41 .07 .21 .20 .10 .18 .19 .13 .21 .21
.01 .01
.02
.04
.02 .03
.02 .02 .03 .04
.01 .02 .02 .01
.02 .02 .02 .02 .02
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LIFETIME! PRODUCTION AND TYPE CORRELATIONS TABLE 3. Genetic' (below diagonal) and phenotypic2 (above diagonal) correlations between lifetime traits. Trait
1
1. Milk production
2. 3. 4. 5. 6.
Fat yield Protein yield Milk value over feed cost Number of lactations Days in milk
.91 .98 .97 .95 .97
2
3
4
5
6
.98
.99 .99
.99 .99 .99
.93 .93 .93 .9 1
.97 .97 .98 .96 .95
.95 .98 .92 .94
.98 .95 .97
.94 .97
.98
'Standard error less than .02. 2Standard error less than .01.
correlations are generally higher, in the range of .6 to .8. Exceptions are dairy character and feet and legs, which have genetic correlations of around .15 and .25, respectively, with final score, final class, and general appearance. Genetic and phenotypic correlations between linear type traits in group 2 are presented in Table 5. The highest phenotypic correlations were between stature, size, and chest (.51 to .88) and between mammary traits (.27 to .66). Style had moderate phenotypic correlations (.22 to .44),and traits were referred to as general characteristics and descriptions of parts. Most other phenotypic correlations were small except for texture with angularity (.43). Genetic correlations among udder traits ranged from -.03 to .96 but were mainly moderately favorable. Genetic correlations were also moderate and favorable between stature, size, style, and most other traits. The highest genetic correlations were between size and stature (.97) and between fore and rear teat placement ( 3 5 ) .
Pin settings and rear set were the only traits with mainly negative phenotypic correlations (-.12 to .30); most other phenotypic correlations were positive. Moderate negative genetic correlations existed between pin setting and thurl width (-.32) and heel (-.21) as well as between rear set and chest (-.24), heel (-.45), fore attachment (--27) and rear attachment (-.26). In both pin setting and rear set, an intermediate value is considered to be desirable by Holstein Canada type scorers, making it difficult to assess the impact of the correlations on a breeding program. Moderate negative genetic correlations also existed between bone and size (-.21), chest (-.46), and thurl width (-.38), and between angularity and heel (-.25) and fore attachment (-.34). Correlations Between Lifetime and Type Traits
Genetic and phenotypic correlations between lifetime production and group l type
TABLE 4. Genetic' (below diagonal) and phenotypic2 (above diagonal) correlations between linear type traits in group 1 analysis. 1 1. Final class 2. Final score 3. General appearance 4. Dairy character 5. Capacity 6. Rump 7. Feet and legs 8. Mammary system 9. Fore udder 10. Rear udder
3
2
.89 1.00 .99 .12
.61 .62 .28 .83 .70 .78
1.00 .14 .63 .63 .27 .82 .70 .77
.88 .94 .18 .63 .65 26 .79 .66 .77
5
4 .30 .34 .34 .24 .ll -.03 -.09
-.30 .14
.31 .37 .38 .19 .41 -.14 .27 .23 25
6
7
8
9
10
.39 .45 .46 .13 .30
.34 .39 .38 .15
.71 .78 .74 .22 .15 .20 .17
.58 .65 .60 .ll .12 .14 .12 .80
.63 .70 .66 25 .14
.05
.14 .01 .29 .20 .33
.14 .14 .12
.90 .88
20
.18 33
so
.60
'Standard error between .O and .lo. 2Standaxd error less than .01. Journal of Dairy Science Vol. 75, No. 8, 1992
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KLASSEN ET AL.
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LIFETIME PRODUCTION AND TYPE CORRELATIONS
TABLE 6. Phenotypic' and genetic2 correlations betwen lifetime production and linear type traits from group 1 analysis. Phenotypic correlations Milk Fat production yield
Protein yield
Genetic correlations Milk value over feed cost
~
Final class Final score General appearance Dairy character Capacity Rump Feet and legs Mammary system Fore udder Rear udder
.18 .19 .19 .22 .07 .06
.08 .16 .ll .17
Fat Milk production yield ~
.I8 .20 .19 .21 .07 .06
.OS .17 .12 .17
.18 .20 .20 .2 1 .07 .06 .08 .17 .12 .17
.17 .19 .I8 .21 .05 .06
.10 .ll
.53 .05
.54 .05 -.02 -.06 .07 -.05
.01 -.02
.16 .ll .16
-.09 .21
.04
Milk value over feed cost
~
.I1 .12 .15
.07
Protein yield
.13
.23
.14 .I5 .18 .56 .07 0 .02 .07
-.07
.25
.04
.06
.os .54
0 -.04 -.06 .01 -.11 .19
'Standard errors equal to .01. 2Standard errors between .09 and .lo, except dairy character with standard error of .07
traits are presented in Table 6. Most phenotypic correlations were between .15 and .20 except for capacity, rump, and feet and legs, which were around .07. The highest genetic correlations were lifetime production with rear udder at between .I9 and .25 and lifetime production with dairy character at between .53 and .56. Genetic correlations between lifetime production and capacity, rump, feet and legs, and mammary system were close to 0 (-.06to .07). Genetic correlations between lifetime production and final class, final score, and general appearance were small and favorable (.04to .18), and genetic correlations between lifetime production and fore udder were small and unfavorable (-.05 to -.I 1). Genetic and phenotypic correlations between lifetime traits and group 2 type traits are presented in Table 7. All phenotypic correlations were positive; most were less than .lo. Only style and angularity had phenotypic correlations larger than .15. Genetic correlations were negative, -.20, between lifetime production traits and both rear heel and thurl width. Angularity had the highest genetic correlation with lifetime production traits (ca. S 5 ) . The genetic correlations between angularity and the survival traits were around .45. Genetic correlations were low to moderate between lifetime traits and stature (.14 to .25), size (.07to .I@, style (.11 to .27), head (.I5 to .23), pin setting (.lo to .16), texture (.I9 to .26), and rear attachment (.IO to .22). Stature, size, style, and rear attachment tend to be more strongly corre-
lated genetically with survival traits (Le., lifetime days in milk and number of lactations) than to lifetime production of milk, fat, or protein and least correlated genetically with milk value over feed costs. Strong positive genetic correlations have been reported between first lactation production and angularity (or dairyness) (7, IO), between first lactation production and dairy character (ll), and between dairy character and angularity (15). The high genetic correlations between lifetime production traits and both dairy character and angularity in the present study are not surprising, considering the partwhole relationship between lifetime production and first lactation production. Lifetime milk value over feed costs appears to have lower correlations to traits related to size than to other lifetime traits. Stature or size in dairy cattle may be more closely related to lifetime milk production than to lifetime profit. This could be due to increased maintenance requirements of the larger cows. Rear udder attachment had moderate genetic correlations with lifetime production traits, and fore udder attachment had low negative correlations. In other studies (16), strong fore attachments are associated with improved udder health, perhaps because stronger fore attachments are associated with higher udders. This suggests that lactation milk production is a more important component than udder health in determining the genetic correlations between lifetime production and other type traits. Journal of Dairy Science Vol. 75, No. 8, 1992
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LIFETIME PRODUCTION AND TYPE CORRELATIONS
This may be a partial reflection of the high voluntary culling for low milk production versus involuntary culling for health reasons. Rear heel and thurl width were the only other notable negative genetic correlations between type and lifetime production (-. 16 to -.27). Studies (13, 14) that separate reason for disposal into voluntary (e.g., culled for low production) and involuntary (e.g., culled because of reproductive failure or mastitis) suggest that the high correlations between survival traits and yield traits, which are estimated from field data, are a reflection of the high amount of voluntary culling based on milk production. Accordingly, correlations between survival and type traits such as dairy character and angularity, which are strongly correlated to milk production, are also affected by voluntary culling practices. Because lifetime production traits have a survival component, voluntary culling practices based on production may be partially responsible for the high correlations with dairy character and angularity. CONCLUSIONS
This study summarizes the genetic and phenotypic correlations between and among type and lifetime production traits under existing industry culling practices. Under these practices, genetic correlations between survival and lifetime production traits are high. Genetic correlations among type traits are similar to values from other studies on type traits in Canadian Holsteins. Many of the type traits that are recorded appear to be unrelated to lifetime production. A strong positive relationship has been established between dairy character, angularity, and lifetime production. Weaker negative correlations are indicated with fore attachment, heel, and thurl width. ACKNOWLEDGMENTS
We thank K. Meyer for the use of her computer programs, Quebec Dairy Herd Analysis Service, and the University of Guelph for providing data. We acknowledge financial assistance from Le Ministhe de 1’Enseignement Sup&rieuret de la Science and Conseil des Recherches en Peche et en Agroalimentaire du QuCbec (M.E.S.S. Project Number 4.1 l), Le Conseil des Recherches en Peche
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et en Agro-alimentaire du Qukbec, and the Canadian Association of Animal Breeders. We would also like to thank S . Joyal, S. des Marchais, and R. K. Moore for their work in preparing the Quebec Dairy Herd Analysis Service data file. REFERENCES
1 Allaire, F. R., H. R. Stenverf, and T. M. Ludwick. 1977. Variations in removal reasons and culling rates with age for dairy females. J. Dairy Sci. 60:254. 2 Burnside, E. B., A. E. McClintock, and K. Hammond. 1984. Type, production and longevity in dairy cattle. Anim. Breed. Abstr. 52:711. 3 DeLorenzo, M. A., and R. W. Everett. 1982. Relationships between milk and fat production, type, and stayability in Holstein sire evaluation. J. Dairy Sci. 65: 1277. 4Dentine, M. R., B. T. McDaniel, and H. D. Norman. 1987. Comparison of culling rates, reasons for disposal, and yields for registered and grade Holstein cattle. J. Dairy Sci. 70:2616. 5 Evans, D. L., C. Branton, and B. R. Farthing. 1964. Heritability estimates and interrelationships among production per day of production life, longevity, breeding efficiency, and type in a herd of Holstein cows. J. Dairy Sci. 47:699. 6Everett. R. W., J. F. Keown, and E. E. Clapp. 1976. Relationships among type, production and stayability in Holstein Cattle. J. Dairy Sci. 59:1505. 7 Foster, W. W., A. E. Freeman,and P. J. Berger. 1988. Linear type trait analysis with genetic parameter estimation. J. Dairy Sci. 71:223. 8 Honnette, J. E., W. E. Vinson, J. M. White, and R. H. Kliewer. 1980. Contributions of descriptively coded type traits to longevity of Holstein cows. J. Dairy Sci. 63307. 9Meyer, K. 1985. Maximum likelihood estimation of variance components for a multivariate mixed model with equal design matrices. Biometrics 41:153. lOMeyer, K., S. Brotherstone, W. G. Hill, and M. R. Edwards. 1987. Inheritance of linear type traits in dairy cattle and correlations with milk production. Anim. Prod. 44:l. 11 Norman, H.D., B. G. Cassell, R. E. Pearson, and G. R. Wiggans. 1981. Relation of first lactation production and conformation to lifetime performance and profitability in Jerseys. J. Dairy Sci. M104. 12Norman. H. D., and L. D. Van Vleck. 1972. Type appraisal: 111. Relationships of first lactation production and type traits with lifetime performance. J. Dairy Sci. 55:1726. 13 Rogers, G. W., B. T. McDaniel, M. R. Dentine. and L. P. Johnson. 1988. Relationships among survival rates, predicted differences for yield, and linear type traits. J. Dairy Sci. 71:214. 14Rogers. G. W., J.A.M. Van Arendonk, and B. T. McDaniel. 1988. Influence of involuntary culling on optimum culling rates and annualized net revenue. J. Dairy Sci. 71:3463. 15 Schaeffer, L. R. 1983. Estimates of variance components for Holstein-type traits. Can. J. Anim. Sci. 63: 763. Journal of Dairy Science Vol. 75, No. 8, 1992
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16 Seykora, A. J., and B. T. McDaniel. 1985. Udder and teat morphology related to mastitis resistance: a review. J. Dairy Sci. 68:2087. 17 Specht, L. W., H. W. Carter, and L. D. Van Vleck. 1967. First classification score and length of herd life. J. Dairy Sci. 501690. 18 Sullivan, B. P., B. J. Van D ~ ~ n n a aand l , E. B. Burnside. 1988. An analysis of the linearized type characteristics as predictors of stayability in Canadian Holsteins. J. Dairy Sci. 71(Suppl. 1):267.(Abstr.) 19Taylor, J. F.. B. Bean, C. E. Marshall, and J. 1.
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Sullivan. 1985. Genetic and environmental components of semen production traits of artificial insemination Holstein bulls. J. Dairy Sci. 68:2703. 20Van Doormaal, B. J., E. B. Burnside, and L. R. Schaeffer. 1986. An analysis of the relationships among stayability, production, and type in Canadian milk-recording programs. J. Dairy Sci. 69510. 21 Westell, R. A., E. B. Bumside, and L. R. Schaeffer. 1982. Evaluation of Canadian Holstein-Friesian sires on disposal m o n s of their daughters. J. Dairy Sci. 65:2366.
trait is a function of production per lactation, length of productive life (longevity), age at first calving, calving interval, feed and milk prices (2), as well as health and husbandry aspects, such as mastitis, reproductive failure, disposition, and udder problems (1, 4, 21). Dairy farmers are reluctant to accept first lactation production as an adequate indicator of lifetime profitability. Lifetime production traits combine production and longevity information. The influence of higher lifetime production on lifetime profitability can be assumed to come from increased income from sale of milk as well as decreased costs because when cows live longer, fewer replacements are necessary. Milk sales increase because cows are better producers and because more cows in the herd are producing at a mature cow level. However, lifetime production traits can only be measured on cows at the end of their productive lives. Relationships of various measures of type with first lactation production (7, 8, 10, l l ) , lifetime production (8, 11, 12), or longevity (3, 5 , 6, 11, 17, 18, 20) have been reported. The objective of this study was to examine genetic and phenotypic correlations between lifetime cumulative milk, fat, and protein; lifetime income from milk sales over feed costs; lifetime days in milk; and total number of lactations with the 28 linearized type traits recorded on the Holstein Classification Report.
Genetic and phenotypic correlations were estimated between 6 lifetime production and 28 linearized type traits using REML. The data set contained 34,322 cows, each with a record for all 34 traits. The analyses accounted for the fixed effects of herd, year-month, classifier, age at first calving, and stage of lactation. Heritabilities were low for lifetime traits and moderate for most type traits except stature, size, capacity, thurl width, and pin setting, which had high heritabilities. Most phenotypic correlations between lifetime production and type were in the range of .15 to .20 except for capacity, rump, and feet and legs, which were around .07. Genetic correlations were strong between lifetime production and angularity (.44 to .55) and dairy character ( 5 3 to S6). Genetic correlations were low to moderate between lifetime production and stature (.14 to .25), size (.07 to .18), texture (.19 to .26), style (.11 to .27), head (.15 to .23), pin setting (.lo to .16), rear udder (.19 to .25), and rear attachment (.lo to .22). The only notable negative genetic correlations were lifetime production with rear heel (-.16 to -.27), thurl width (-.18 to -.24), and fore udder (-.05 to -.11). (Key words: genetic correlations, lifetime production, type, Holstein)
MATERIALS AND METHODS Data
INTRODUCTION
Lifetime profitability can be regarded as the ultimate breeding objective in dairy cattle. This
Received September 16, 1991 Accepted April 2. 1992. 1992 J Dairy Sci 75:2272-2282
A total of 176,778 type classifications, performed between June 1981 and June 1986, were obtained from the Holstein Association of Canada. Preliminary analysis of type data showed that about 81% were classified during first parity. Classifications at later parities were not used. Approximately 8% of the records were reclassifications. For those cows, the first
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classification of record was used. Records with no calving date (4%) and records for cows older than 40 mo or younger than 22 mo (5%) were removed in the initial editing, leaving 114,3 14 type records. Approximately 960,000 lactation records, initiated between 1980 and 1989, were obtained from Quebec Dairy Herd Analysis Service. Lifetime measures for 222,3 15 cows were constructed, ensuring that all cows had a first lactation starting between 18 and 40 mo of age. Only cows with consecutive lactations in the data were included. All cows were required to have either a reason for disposal recorded for their last lactation or a code indicating that they were still in production. All cows were required to have feed intake recorded. There were 53,941 records with both lifetime and type information, one for each cow, identified using cow registration number and birth date to match the files. Only 131 cows calved for the first time before January 1982, and those records were deleted to ensure adequate numbers of cows in each year-month subcell. A study of the effects of truncation on estimates of genetic parameters for lifetime traits, using a data set in which all cows had completed their productive lives (Jairath, 1992, unpublished study), indicated that, for cows still producing in the herd, data sets should be chosen so as to allow the youngest cows the opportunity to have at least 4 yr in production. Following this recommendation, cows first calving after December 1985 (15,895 records) were removed from the data set. Therefore, the data set consisted of cows that had completed their lifetimes in the herd and of cows in the herd that had at least 4 yr of production. Cows from sires with fewer than 5 records (2467 cows from 1180 sires) and herds with fewer than 5 records (978 cows from 395 herds) were excluded to reduce the effects of biases from preferential treatment of a particular sire's daughters in a particular herd or group of herds. To ensure adequate numbers of records in each fixed effect, cows younger than 24 mo (164 records) or older than 40 mo (387 records) at first calving were excluded. Also, records from classifiers with fewer than 250 records in tokl were excluded (589 records). There were 34,322 records that met these prerequisites.
Traits
Apart from the lists of defects, the type classification report from the Holstein Association of Canada reports 28 traits, all of which were used in this study (see Table 1). These can be broken down to general characteristics (4 traits), description of parts (14 traits), score card traits (8 traits), and final classification (2
TABLE 1. Phenotypic means and standard deviations for lifetime production and linear type traits. Trait
X
SD
Lifetime Milk production 18,360 12,521 Fat yield 654 448 Protein yield 583 397 Milk value over feed cost 4640 3361 Number of lactations 3.17 1.39 Days in milk 981 474 Final classification 3.4 .6 Final class (1 to 6) Final score (1 to 100) 78.4 2.6 Score card (1 to 18) General appearance 8.8 1.6 Dairy character 10.9 1.5 Capacity 10.9 1.7 Rump 2.0 9.4 Feet and legs 9.4 1.9 Mammary system 9.4 1.6 Fore udder 9.4 1.6 Rear udder 9.6 1.8 General characteristics (1 to 9) Stature 5.7 1.5 Size 5.6 1.3 Style 4.5 1.2 Angularity 5.6 1.1 Description of parts (1 to 9) Front end 1.1 5.6 Head Midsection 5.6 Chest 1.1 6.2 Loin 1.3 Rump 6.0 Thurl width 1.3 1.1 Pin setting' 5.1 Feet and legs Rear heel 4.9 1.2 Bone 5.9 1.3 Rear set' 1.2 5.1 Mammary system Texture 5.7 1.1 1.1 Fore attachment 5.0 Rear attachment 5.0 1.2 Median suspensory ligament 6.0 1.1 Fore teat placement 5.5 1.4 Rear teat ulacement 1.4 6.9 lIntermediate values are desirable. Journal of Dairy Science Vol. 75, No. 8, 1992
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KLASSEN ET AL.
traits). Score card traits included a code (1 to 6) and a rank within that code (1 to 3) with higher numbers being more desirable. These two numbers were combined to give a single measure, which ranged from 1 to 18 (e.g., 3(code - 1) + rank), to make the score card traits more linear. Six lifetime traits were examined in this study: cumulative milk, fat, and protein production over the lifetime of the animal, cumulative days in milk, cumulative milk value over feed cost, and total number of lactations. The amount and average cost of feed for each lactation were available to allow calculation of lifetime feed cost. Cumulative days in milk and total number of lactations relate mainly to survival, whereas the other 4 traits combine survival and production information. All lifetime totals utilized actual lactation information and did not precorrect data to a 305-d lactation. Statistical Analysis
For computational ease, type traits were split into two groups: 1) score card and final classification traits in group 1 and 2) general characteristics and description of parts in group 2. Each group was analyzed separately for lifetime traits using a multivariate model. Group 1 analysis included 14 traits: 4 lifetime traits and 10 linear type traits. Group 2 analysis included 24 traits: 4 lifetime traits, 2 survival traits, and 18 linear type traits. Before analysis, all traits were transformed to have a mean of 0 and a standard deviation of 1. Initial analyses indicated herd, round, classifier, age at' first calving (in months), and stage of lactation (12 monthly classes, the last class being for 12 mo or more) were important fixed effects for most of the 28 type traits. Year-month of first calving and age at first calving were important for the lifetime traits. Herd-year-month combination was not considered because of small subcell size. Herd plus year-month accounted for more variation than herd-year-season in the preliminary least squares analyses. A multivariate model was chosen to produce equal design matrices for both fixed and random effects as follows: Yijho
= Hi + YMj + Clk + eijko
+ A1 + L, + S n
Journal of Dairy Science Vol. 75, No. 8. 1992
where Yi,um,, is observation ijklmno for each trait in the model, Hi is the fixed effect of herd i (141 1 levels), YMj is the fixed effect of yearmonth j (48 levels), Clk is the fixed effect of classifier k (7 levels), A1 is the fixed effect of age 1 at first calving (17 levels), L, is the fixed effect of stage of lactation m (13 levels), S, is the random effect of sire n (1043 levels), and q , h 0 is the random residual associated with cow ijklmno. Sires and residuals were assumed to be independently distributed with zero means and variances G * A and R * I, respectively, where G is the matrix of sire (co)variances, A is the relationship matrix between sires, R is the residual (co)variance matrix, I is the identity matrix, and the asterisk refers to the direct product of two matrices. A computing package (REMLPK) from K. Meyer (University of New England, Armidale, New South Wales, Australia) was used to analyze the data. The algorithm was designed specifically for analysis of traits with equal design matrices. The traits are first transformed to canonical scale to reduce the problem to a series of univariate analyses as proposed by Meyer (9). The expectation-maximization algorithm is used in conjunction with a transformation to tridiagonalize the mixed model equations to estimate the (co)variance components (19). The algorithm forces the covariance matrix to be semi-positive definite, which is an important advantage when a large number of traits are in the analysis. Approximate large sample standard errors are calculated by the algorithm using numerical differentiation around the converged values. RESULTS AND DISCUSSION Means, Standard Deviations, and Fixed Effects
The means and standard deviations of the lifetime production, survival, and type traits are given in Table 1. The linear type traits tended to be close to a normal distribution, but the lifetime traits tended to be skewed, as can be seen in Figure 1 for lifetime milk production. Figure 2 shows the distribution of lifetime milk production after a log transformation. A preliminary analysis using a subset of lifetime production and type traits found that
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LIFETIME PRODUCTION AND TYPE CORRELATIONS
--"
1500
5
z
$
1000
a 51
i 500
-1.5
0
4.4
Figure 1. Distribution of lifetime cumulative milk yield standardized to have zero mean and unit variance.
overparameterized in the fixed effects because we assumed that there was less chance of inadvertently biasing the estimates than precorrection of the data. The lifetime traits were particularly vulnerable to biases arising from precorrection because of possible truncation at the end of the data, at which time long-lived cows had only partial records in the data because they had not finished their lives. The data set was truncated at December 1985 to minimize the number of cows in the data set with incomplete herd lives. However, the least squares estimates for year-month of first calving (Figure 3) show a decline in lifetime milk production over time. These effects were only slightly different when sire was included in the model, indicating that the decline was probably not genetic in origin. This decline could be partially due to dairy farmers culling more older cows, but it is unlikely that the average number of lactations would drop by .25 lactations over 4 yr for this reason alone. However, the most likely explanation is that the truncation effect has not been completely eliminated from the data. However, the biases in the variance component estimates from truncation should be minimal (Jairath, 1992, unpublished study).
heritabilities and genetic and phenotypic correlations of the log transformed traits were unchanged from the untransformed traits. Based on these results, no log transformations of lifetime production traits were utilized in this study. The fixed effects of classifier and stage of lactation accounted for approximately 1.5 and 4% of the variation after correction for the mean in most of the type traits. These effects accounted for less than 1% of the variation in the lifetime traits and were generally not significant. Age at first lactation accounted for .5 Canonical Traits and .7% of the variation in lifetime production In the group 1 analysis, the heritabilities of and type traits, respectively. Year-month accounted for 2 to 3% of the variation in the the canonical variates ranged from near zero to lifetime traits and around 1% in the type traits. -52. In the group 2 analysis, the heritabilities Round was not fitted because it was con- of the canonical variates ranged from near zero founded with year-month. The model was to .70. Obtaining heritabilities close to zero
30001
I
83 -.6
0
I .9
Figure 2. Distribution of the log of lifetime cumulative milk yield plus a constant.
I
I I
84
85
I 86
Year - month
Figure 3. The effect of year-month of first calving on lifetime milk yield. Least squaes estimates are deviated from first subclass.
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KLASSEN ET AL.
means that the eigenvalues of the (co)variance matrix are close to zero and indicates that some of the parameter estimates are close to the edge of the parameter space. This is not surprising in analyses with large numbers of traits. However, these parameter constraints probably did not have a large influence on parameter estimates, because several preliminary analyses using different subsets of traits resulted in parameter estimates similar to those described in this paper. In both group 1 and group 2 analyses, the canonical variate with the largest heritability was largely defined by lifetime milk minus lifetime fat.
and fore udder (-.30). Large phenotypic and genetic correlations existed between final class, score, and general appearance; genetic correlations were close to unity. Mammary system is highly correlated to both rear and fore udder (phenotypic correlation >.80 and genetic correlation >.88), with lower correlations between fore and rear udder (phenotypic correlation S O and genetic correlation .60).All score card traits have phenotypic correlations greater than .3 with final score, final class, and general appearance; phenotypic correlations for mammary traits were from .58 to .78.Genetic
Heritabilities of Type and Lifetime Traits
TABLE 2. Heritability estimates and standard errors from group 1 and group 2 analyses for lifetime production and linear type traits.
Heritability estimates are presented in Table 2. Lifetime production traits of milk, fat, and Traits protein yields, and lifetime milk value over feed cost had a heritability of approximately Lifetime Milk production .lo; number of lactations and lifetime days in Fat yield milk had heritabilities of .05 and .07; linear Protein yield type traits had heritabilities ranging from .10 Milk value over feed cost to .48. Most type traits had moderate heritabili- Number of lactations ties between .10 and .25. Traits with heritabili- Days in milk classification ties greater than .40 were stature, size, and pin Final Final class setting; .30 to .39 were capacity and thurl Final score width; .10 or less were rear heel, head, and Score card udder texture. Lifetime production traits tended General appearance to have a heritability between that of survival Dairy character Capacity traits and first lactation production. Correlations Between Lifetime Tralta
Genetic and phenotypic correlations between lifetime traits (Table 3) were all extremely high (.91 to .99), indicating that many of the same factors are involved in controlling these traits. The lowest correlations were between number of lactations and the lifetime production traits with phenotypic correlations of .91 to .93 and genetic correlations of .92 to .95. Correlations Between Type Traits
Genetic and phenotypic correlations between linear type traits in group l are presented in Table 4. All phenotypic correlations and most of the genetic correlations were positive. The only negative genetic correlation larger than -.2 was between dairy character Journal of Dairy Science Vol. 75, No. 8, 1992
RWP Feet and legs Mammary system Fore udder Rear udder General characteristics Stature Size Style Angularity
Description of parts Head Chest Loin Thurl width Pin setting Rear heel Bone Rear set Texture Fore attachment Rear attachment Median suspensory ligament Fore teat placement Rear teat ulacement
h2
SE
.10 .10
.01 .01 .01
.09
.10 .05 .07
.01
.12 .16
.02 .02
.17 .29 .33 .28 .I3 .15 .16 .14
.02 .03 .03 .03 .02 .02 .02
.48 .43 .17 .25
.04
.10 .23
.o 1
.19
.31 .41 .07 .21 .20 .10 .18 .19 .13 .21 .21
.01 .01
.02
.04
.02 .03
.02 .02 .03 .04
.01 .02 .02 .01
.02 .02 .02 .02 .02
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LIFETIME! PRODUCTION AND TYPE CORRELATIONS TABLE 3. Genetic' (below diagonal) and phenotypic2 (above diagonal) correlations between lifetime traits. Trait
1
1. Milk production
2. 3. 4. 5. 6.
Fat yield Protein yield Milk value over feed cost Number of lactations Days in milk
.91 .98 .97 .95 .97
2
3
4
5
6
.98
.99 .99
.99 .99 .99
.93 .93 .93 .9 1
.97 .97 .98 .96 .95
.95 .98 .92 .94
.98 .95 .97
.94 .97
.98
'Standard error less than .02. 2Standard error less than .01.
correlations are generally higher, in the range of .6 to .8. Exceptions are dairy character and feet and legs, which have genetic correlations of around .15 and .25, respectively, with final score, final class, and general appearance. Genetic and phenotypic correlations between linear type traits in group 2 are presented in Table 5. The highest phenotypic correlations were between stature, size, and chest (.51 to .88) and between mammary traits (.27 to .66). Style had moderate phenotypic correlations (.22 to .44),and traits were referred to as general characteristics and descriptions of parts. Most other phenotypic correlations were small except for texture with angularity (.43). Genetic correlations among udder traits ranged from -.03 to .96 but were mainly moderately favorable. Genetic correlations were also moderate and favorable between stature, size, style, and most other traits. The highest genetic correlations were between size and stature (.97) and between fore and rear teat placement ( 3 5 ) .
Pin settings and rear set were the only traits with mainly negative phenotypic correlations (-.12 to .30); most other phenotypic correlations were positive. Moderate negative genetic correlations existed between pin setting and thurl width (-.32) and heel (-.21) as well as between rear set and chest (-.24), heel (-.45), fore attachment (--27) and rear attachment (-.26). In both pin setting and rear set, an intermediate value is considered to be desirable by Holstein Canada type scorers, making it difficult to assess the impact of the correlations on a breeding program. Moderate negative genetic correlations also existed between bone and size (-.21), chest (-.46), and thurl width (-.38), and between angularity and heel (-.25) and fore attachment (-.34). Correlations Between Lifetime and Type Traits
Genetic and phenotypic correlations between lifetime production and group l type
TABLE 4. Genetic' (below diagonal) and phenotypic2 (above diagonal) correlations between linear type traits in group 1 analysis. 1 1. Final class 2. Final score 3. General appearance 4. Dairy character 5. Capacity 6. Rump 7. Feet and legs 8. Mammary system 9. Fore udder 10. Rear udder
3
2
.89 1.00 .99 .12
.61 .62 .28 .83 .70 .78
1.00 .14 .63 .63 .27 .82 .70 .77
.88 .94 .18 .63 .65 26 .79 .66 .77
5
4 .30 .34 .34 .24 .ll -.03 -.09
-.30 .14
.31 .37 .38 .19 .41 -.14 .27 .23 25
6
7
8
9
10
.39 .45 .46 .13 .30
.34 .39 .38 .15
.71 .78 .74 .22 .15 .20 .17
.58 .65 .60 .ll .12 .14 .12 .80
.63 .70 .66 25 .14
.05
.14 .01 .29 .20 .33
.14 .14 .12
.90 .88
20
.18 33
so
.60
'Standard error between .O and .lo. 2Standaxd error less than .01. Journal of Dairy Science Vol. 75, No. 8, 1992
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KLASSEN ET AL.
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LIFETIME PRODUCTION AND TYPE CORRELATIONS
TABLE 6. Phenotypic' and genetic2 correlations betwen lifetime production and linear type traits from group 1 analysis. Phenotypic correlations Milk Fat production yield
Protein yield
Genetic correlations Milk value over feed cost
~
Final class Final score General appearance Dairy character Capacity Rump Feet and legs Mammary system Fore udder Rear udder
.18 .19 .19 .22 .07 .06
.08 .16 .ll .17
Fat Milk production yield ~
.I8 .20 .19 .21 .07 .06
.OS .17 .12 .17
.18 .20 .20 .2 1 .07 .06 .08 .17 .12 .17
.17 .19 .I8 .21 .05 .06
.10 .ll
.53 .05
.54 .05 -.02 -.06 .07 -.05
.01 -.02
.16 .ll .16
-.09 .21
.04
Milk value over feed cost
~
.I1 .12 .15
.07
Protein yield
.13
.23
.14 .I5 .18 .56 .07 0 .02 .07
-.07
.25
.04
.06
.os .54
0 -.04 -.06 .01 -.11 .19
'Standard errors equal to .01. 2Standard errors between .09 and .lo, except dairy character with standard error of .07
traits are presented in Table 6. Most phenotypic correlations were between .15 and .20 except for capacity, rump, and feet and legs, which were around .07. The highest genetic correlations were lifetime production with rear udder at between .I9 and .25 and lifetime production with dairy character at between .53 and .56. Genetic correlations between lifetime production and capacity, rump, feet and legs, and mammary system were close to 0 (-.06to .07). Genetic correlations between lifetime production and final class, final score, and general appearance were small and favorable (.04to .18), and genetic correlations between lifetime production and fore udder were small and unfavorable (-.05 to -.I 1). Genetic and phenotypic correlations between lifetime traits and group 2 type traits are presented in Table 7. All phenotypic correlations were positive; most were less than .lo. Only style and angularity had phenotypic correlations larger than .15. Genetic correlations were negative, -.20, between lifetime production traits and both rear heel and thurl width. Angularity had the highest genetic correlation with lifetime production traits (ca. S 5 ) . The genetic correlations between angularity and the survival traits were around .45. Genetic correlations were low to moderate between lifetime traits and stature (.14 to .25), size (.07to .I@, style (.11 to .27), head (.I5 to .23), pin setting (.lo to .16), texture (.I9 to .26), and rear attachment (.IO to .22). Stature, size, style, and rear attachment tend to be more strongly corre-
lated genetically with survival traits (Le., lifetime days in milk and number of lactations) than to lifetime production of milk, fat, or protein and least correlated genetically with milk value over feed costs. Strong positive genetic correlations have been reported between first lactation production and angularity (or dairyness) (7, IO), between first lactation production and dairy character (ll), and between dairy character and angularity (15). The high genetic correlations between lifetime production traits and both dairy character and angularity in the present study are not surprising, considering the partwhole relationship between lifetime production and first lactation production. Lifetime milk value over feed costs appears to have lower correlations to traits related to size than to other lifetime traits. Stature or size in dairy cattle may be more closely related to lifetime milk production than to lifetime profit. This could be due to increased maintenance requirements of the larger cows. Rear udder attachment had moderate genetic correlations with lifetime production traits, and fore udder attachment had low negative correlations. In other studies (16), strong fore attachments are associated with improved udder health, perhaps because stronger fore attachments are associated with higher udders. This suggests that lactation milk production is a more important component than udder health in determining the genetic correlations between lifetime production and other type traits. Journal of Dairy Science Vol. 75, No. 8, 1992
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KLASSEN ET AL.
LIFETIME PRODUCTION AND TYPE CORRELATIONS
This may be a partial reflection of the high voluntary culling for low milk production versus involuntary culling for health reasons. Rear heel and thurl width were the only other notable negative genetic correlations between type and lifetime production (-. 16 to -.27). Studies (13, 14) that separate reason for disposal into voluntary (e.g., culled for low production) and involuntary (e.g., culled because of reproductive failure or mastitis) suggest that the high correlations between survival traits and yield traits, which are estimated from field data, are a reflection of the high amount of voluntary culling based on milk production. Accordingly, correlations between survival and type traits such as dairy character and angularity, which are strongly correlated to milk production, are also affected by voluntary culling practices. Because lifetime production traits have a survival component, voluntary culling practices based on production may be partially responsible for the high correlations with dairy character and angularity. CONCLUSIONS
This study summarizes the genetic and phenotypic correlations between and among type and lifetime production traits under existing industry culling practices. Under these practices, genetic correlations between survival and lifetime production traits are high. Genetic correlations among type traits are similar to values from other studies on type traits in Canadian Holsteins. Many of the type traits that are recorded appear to be unrelated to lifetime production. A strong positive relationship has been established between dairy character, angularity, and lifetime production. Weaker negative correlations are indicated with fore attachment, heel, and thurl width. ACKNOWLEDGMENTS
We thank K. Meyer for the use of her computer programs, Quebec Dairy Herd Analysis Service, and the University of Guelph for providing data. We acknowledge financial assistance from Le Ministhe de 1’Enseignement Sup&rieuret de la Science and Conseil des Recherches en Peche et en Agroalimentaire du QuCbec (M.E.S.S. Project Number 4.1 l), Le Conseil des Recherches en Peche
2281
et en Agro-alimentaire du Qukbec, and the Canadian Association of Animal Breeders. We would also like to thank S . Joyal, S. des Marchais, and R. K. Moore for their work in preparing the Quebec Dairy Herd Analysis Service data file. REFERENCES
1 Allaire, F. R., H. R. Stenverf, and T. M. Ludwick. 1977. Variations in removal reasons and culling rates with age for dairy females. J. Dairy Sci. 60:254. 2 Burnside, E. B., A. E. McClintock, and K. Hammond. 1984. Type, production and longevity in dairy cattle. Anim. Breed. Abstr. 52:711. 3 DeLorenzo, M. A., and R. W. Everett. 1982. Relationships between milk and fat production, type, and stayability in Holstein sire evaluation. J. Dairy Sci. 65: 1277. 4Dentine, M. R., B. T. McDaniel, and H. D. Norman. 1987. Comparison of culling rates, reasons for disposal, and yields for registered and grade Holstein cattle. J. Dairy Sci. 70:2616. 5 Evans, D. L., C. Branton, and B. R. Farthing. 1964. Heritability estimates and interrelationships among production per day of production life, longevity, breeding efficiency, and type in a herd of Holstein cows. J. Dairy Sci. 47:699. 6Everett. R. W., J. F. Keown, and E. E. Clapp. 1976. Relationships among type, production and stayability in Holstein Cattle. J. Dairy Sci. 59:1505. 7 Foster, W. W., A. E. Freeman,and P. J. Berger. 1988. Linear type trait analysis with genetic parameter estimation. J. Dairy Sci. 71:223. 8 Honnette, J. E., W. E. Vinson, J. M. White, and R. H. Kliewer. 1980. Contributions of descriptively coded type traits to longevity of Holstein cows. J. Dairy Sci. 63307. 9Meyer, K. 1985. Maximum likelihood estimation of variance components for a multivariate mixed model with equal design matrices. Biometrics 41:153. lOMeyer, K., S. Brotherstone, W. G. Hill, and M. R. Edwards. 1987. Inheritance of linear type traits in dairy cattle and correlations with milk production. Anim. Prod. 44:l. 11 Norman, H.D., B. G. Cassell, R. E. Pearson, and G. R. Wiggans. 1981. Relation of first lactation production and conformation to lifetime performance and profitability in Jerseys. J. Dairy Sci. M104. 12Norman. H. D., and L. D. Van Vleck. 1972. Type appraisal: 111. Relationships of first lactation production and type traits with lifetime performance. J. Dairy Sci. 55:1726. 13 Rogers, G. W., B. T. McDaniel, M. R. Dentine. and L. P. Johnson. 1988. Relationships among survival rates, predicted differences for yield, and linear type traits. J. Dairy Sci. 71:214. 14Rogers. G. W., J.A.M. Van Arendonk, and B. T. McDaniel. 1988. Influence of involuntary culling on optimum culling rates and annualized net revenue. J. Dairy Sci. 71:3463. 15 Schaeffer, L. R. 1983. Estimates of variance components for Holstein-type traits. Can. J. Anim. Sci. 63: 763. Journal of Dairy Science Vol. 75, No. 8, 1992
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16 Seykora, A. J., and B. T. McDaniel. 1985. Udder and teat morphology related to mastitis resistance: a review. J. Dairy Sci. 68:2087. 17 Specht, L. W., H. W. Carter, and L. D. Van Vleck. 1967. First classification score and length of herd life. J. Dairy Sci. 501690. 18 Sullivan, B. P., B. J. Van D ~ ~ n n a aand l , E. B. Burnside. 1988. An analysis of the linearized type characteristics as predictors of stayability in Canadian Holsteins. J. Dairy Sci. 71(Suppl. 1):267.(Abstr.) 19Taylor, J. F.. B. Bean, C. E. Marshall, and J. 1.
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Sullivan. 1985. Genetic and environmental components of semen production traits of artificial insemination Holstein bulls. J. Dairy Sci. 68:2703. 20Van Doormaal, B. J., E. B. Burnside, and L. R. Schaeffer. 1986. An analysis of the relationships among stayability, production, and type in Canadian milk-recording programs. J. Dairy Sci. 69510. 21 Westell, R. A., E. B. Bumside, and L. R. Schaeffer. 1982. Evaluation of Canadian Holstein-Friesian sires on disposal m o n s of their daughters. J. Dairy Sci. 65:2366.