Preventive Veterinary Medicine, 18 (1994) 115-127 115 Elsevier Science Publishers B.V., Amsterdam

Reproductive performance of Ontario beef breeding herds

John J. McDermott a,*, O. Brian Allen b, S. Wayne Martin a, Ken E. Leslie a, Alan H. Meek a, Wayne G. Etherington ~

~Department of Population Medicine, University of Guelph, Guelph, Ont. NIG 2W1, Canada bDepartment of Animal and Poultry Science, University of Guelph, Guelph, Ont. NIG 2W1, Canada

(Accepted 23 April 1993 )

Abstract

Herd reproductive performance was assessed in 180 Ontario cow-calf herds on 170 randomly se- lected farms. Reproductive performance was measured by pregnancy rate and mean calving interval. The mean pregnancy rate was 92.8%, and 75% of herds had pregnancy rates greater than 90%. The mean calving interval was 365 +_ 1.4 days.

Herd pregnancy rate was highest in late-summer and fall-winter breeding herds and was decreased by bull diseases. Pregnancy rates were also associated with a number of pasture and nutrition vari- ables; but, their effects were not easily interpreted.

Decreased mean calving interval was associated with: a decreased interval between first calving dates in 1986 and 1987 (used to control for delayed bull introduction), other than fall-winter breed- ing, natural service, pasture weed control, closed barn winter housing and manager ownership; in- creased calving interval was associated with bull chronic disease.

There are two main conclusions. The first is that, regardless of management goals, approximately 20% of producers realistically could improve their herd pregnancy rate. The second is that, in Ontario, a short breeding season will be easiest to maintain by having spring and early summer breeding sea- sons, by natural service, by the timely introduction of herd sire(s), and by monitoring bull health carefully.

Introduction

Research and herd health activities in beef breeding herds have been fo- cused primarily on reproductive performance. Such an emphasis is justifia- ble, since the returns on the substantial investment of maintaining a breeding herd are only realized by the sale of calves. On a relative scale, Trenkle and Willham (1977) estimate that selection for reproductive merit is five times more important than selecting for growth performance.

Reproductive performance is generally measured by pregnancy rate. Most estimates of herd pregnancy rates have been calculated using data collected

*Corresponding author.

© 1994 Elsevier Science Publishers B.V. All rights reserved 0167-5877/94/$07.00 SSDIO 1 6 7 - 5 8 7 7 (93) 00280-I

l 16 J.J. McDermott et al./Preventive Veterinary Medicine 18 (1994) 115-127

on research stations or large ranches (Bellows et al., 1979; Wiltbank, 1983 ). A few studies have estimated pregnancy rates using data from a sample of 'representative' herds selected through veterinary practices (Janzen, 1976, 1978; Hanly and Mossman 1977 ).

There is great interest in determining what factors or interventions influ- ence herd pregnancy rates. To date, the majority of studies have been experi- ments conducted on research stations. However, if the factors under investi- gation act differently under varied farm conditions then the results cannot be extrapolated beyond the research station.

The first objective of this study was to describe the pregnancy rate and mean calving interval of cow-calf herds in southern Ontario. The second objective was to examine associations between these measures and a number of herd- level variables.

Materials and methods

Study population and data collection

The study population was 180 separate breeding herds on 170 randomly selected cow-calf farms in southern Ontario. These farms, which had at least 25 females calve in either 1984 or 1985, were chosen from a sampling frame of 1444 herds on the Ontario Ministry of Agriculture and Food's Beef Herd Improvement Program (BHIP) (Ontario Ministry of Agriculture and Food, 1986).

Herd information was obtained by personal interview of managers by one of three investigators. Production records (such as calving dates, pregnancy check results and weaning weights ) were collected from farm records and/or from the BHIP data center. Details of the sampling procedure, farm inter- views, questionnaires and other data collection procedures are described else- where (McDermott et al., 1991, 1994).

Outcome measures

Pregnancy rate is the common reproductive measure used; however, by it- self, it may not provide a suitable summary of reproductive performance in herds with extended breeding seasons. Hence, calving interval was chosen as an additional reproductive performance measure.

Cows and heifers were pregnancy checked in 29.4% of herds. In the remain- ing herds, the pregnancy status was classified as: ( 1 ) pregnant, if they calved, aborted or were sold as breeding stock; (2) open, if they were culled by the farmers as open, retained open through the next calving season or culled for no specific cause more than 11 months after the last calving; (3) unknown, if

.LZ McDermott et aL / Preventive Veterinary Medicine 18 (1994) 115-127 1 17

they died prior to calving, were culled for a specific cause other than preg- nancy or were culled for no specific cause within 11 months of the last calving.

Calving intervals were determined for all females that calved in both 1986 and 1987. The herd calving interval was the mean of individual calving inter- vals in the herd.

Variables associated with reproductive performance

Variables potentially associated with herd reproductive performance were in five main categories: ( 1 ) manager/herd, (2) environment/housing, (3) nutrition/pasture, (4) reproductive management and ( 5 ) bull factors (Table 1 ). The number and proportion of herds within each independent variable class are listed elsewhere (McDermott et al., 1991, 1994). Variables within each of the five categories were examined for associations with pregnancy rate and herd calving interval. Variables that were significant from each category model (P< 0.05 ) were examined subsequently in an overall model.

Three variables considered a priori to be associated with reproductive per- formance (main breeding season, type of breeding and length of breeding sea- son; see Table 1 ) were forced into all models. In all pregnancy rate models, pregnancy check status was forced to control for potential biases introduced by the two different methods of pregnancy classification. For calving interval models, planned variations in herd calving interval (e.g. shifting the main calving season) were controlled by adjusting for the interval from the starting date of the 1986 calving season to the starting date of the 1987 calving season.

Stat&tical modelling

A model for pregnancy rate was developed using the statistical packages EGRET (Statistics and Epidemiology Research Corporation, 909NE 43rd, Suite 310, Seattle, WA 98105) and GLIM (Numerical Algorithms Group, Mayfield House, 256 Banbury Road, Oxford UK, OX2 7DH). The expected proportion of females pregnant for each herd was modelled as a binomial outcome with herd level covariates as predictors via logistic regression.

After initial inclusion of forced variables, additional variables were se- lected based on score statistics (Pregibon, 1982 ) available in EGRET. Vari- ables were entered until no additional terms were significant (P< 0.05 ). All terms in this model were checked for retention by both score and likelihood- ratio tests (McCullagh and Nelder, 1989). Influential observations were identified using delta-beta values (Pregibon, 1981) generated by EGRET. The presence of outliers was examined by plotting Pearson residuals (Mc- Cullagh and Nelder, 1989 ) vs. fitted values in GLIM. Given that within-herd clustering and other problems might lead to poor model fit, a quasi-likelihood model (Wedderburn, 1974 ), in which the final logistic regression model was

118 .tJ. McDermott et al. /Preventive Veterinary Medicine 18 (1994) 115-127

Table 1 Potential factors examined for associations with herd pregnancy rate in Ontario cow-calf herds, 1986-1987

Manager/farm characteristics Manager:

owner (yes/no) age (years) experience (years) education (primary/secondary/community college/university) off-farm employment (full-time/part-time/none)

Proportion of total farming time devoted to cow-calf herd Full-time hired help (yes/no) Regular family help (yes/no) Level of veterinary service (none/consultative herd health/advice and treatments/emergencies only) Level of record keeping: calving records (yes/no)/disease records (yes/no)/records used for management

(yes/no) Purebred versus commercial herds

Environment/housing Main breeding season1 (fall_winter (Oct.-Mar.)/spring (Apr.-May)/early summer (June)/late summer

(July-Sept.) Housing in breeding season (closed barn/yard + barn/pasture + barn/pasture) Housing in winter (closed barn/yard + barn/pasture + barn/pasture ) Region of Ontario (southern/western/central/eastern)

Nutrition~pasture Forages in breeding season (main forage (hay or pasture) only/main forage plus supplemental forage) Forages in over-wintering period (hay only/hay and silage ) Grain feeding prior to breeding ('flushing') (yes/no) Percentage of improved pasture Length of pasture season (days) Percentage of time pasture is supplemented Pasture rotation ( < 1 week/1-3 weeks)/continuous) Pasture improvement: fertilizer (yes/no)/weed control (yes/no) Stocking density (acres per breeding female ) Average pasture size (acres) Average age of pastures (years) Percentage of legume pasture acreage

Reproductive management Type of breeding ~ (majority AI/some AI/all natural service) Length of breeding/calving season ~ (days for 90% to calve) Replacement heifers bred (no heifers bred/yes with cows/yes bred separately)

Bull factors Multiple vs. single sire breeding groups Bulls used in other herds (none/some/all) Veterinary assessment of breeding soundness (none/some/all) Bull's experience (all inexperienced/all experienced/combination ) Housed separately from cows in non-breeding season (yes/no) Supplemental grain feeding:

prebreeding 2 season (none/some/all) breeding season (none/some/all) non-breeding season (none/some/all )

Bull disease during breeding season (none/acute/chronic) Cow: bull ratio

~Variables considered important a priori and included in all models. 2The period 2 months prior to breeding.

J.J. McDermott et al. / Preventive Veterinary Medicine 18 (1994) 115-127 1 19

extended with an overdispersion parameter, was also fit in GLIM (Mc- Cullagh and Nelder, 1989 ).

Herd calving interval was modelled using the stepwise multiple regression package BMDP 2R (BMDP Statistical Software, Los Angeles, CA) . The standard diagnostic measures available in this program were used for the ex- amination of influential observations, outliers and normality.

Results

Pregnancy rate

Overall, herd pregnancy rates were very high (Fig. 1 ). Approximately 75% of herds had pregnancy rates greater the 90%.

Herds that bred in the spring and early summer had lower pregnancy rates than herds that bred in the late summer and fall/winter periods (Table 2). Herds in which the majority of females were bred by artificial insemination (AI) had higher pregnancy rates than other herds.

Of the variables selected for entry into the model, the greatest number came

30

25

O3 20

c'-

0

15

E

10

0 <70 70 73 76 79 82 85 88 91 94 97 100

herd pregnancy rate (%)

Fig. 1. Distribution of herd pregnancy rate for 180 Ontario cow-calf herds, 1986.

120 Z& McDermott et aL / Preventive Veterinary Medicine 18 (1994) 115-127

Table 2 Herd pregnancy rate logistic regression model for 180 Ontar io beef cow-calf herds, 1986-1987

Variable b Deviance ~ P-value ~ (in order o f entry) logistic

Logistic Quasi-l ikelihood s

Intercept 2 3.48

Pregnancy checked 2 - 0.03 0.09 0.77 0.84

Breeding season 2 16.29 < 0.01 0.04 Spring - 0.43 Early s u m m e r - 0.21 Late s u m m e r (vs. fa l l -winter) 0.06

Length of breeding season 2 (days) - 0 . 0 0 0.11 0.74 0.82

Type o f breeding 2 5.67 0.06 0.24 Majority AI 0.47 Some AI (vs. all na tura l ) - 0 , 0 1

Pasture weed control 0.50 25.08 < 0.01 < 0.01

Proport ion o f days pasture - 0 . 0 1 14.07 <0.01 <0.01 supplemented

Supplemental forage in winter - 0 . 4 1 19.10 <0.01 <0.01

Winter housing 22.71 < 0.01 0.01 Barn + yard - 0.27 Barn + pasture - 0.80 Pasture (vs. closed barn) - 0 . 2 9

Bull disease 10.55 < 0.01 0.07 Acute - 0.38 Chronic (vs. no disease) - 0 . 3 2

Pasture fertilized - 0 . 2 6 7.68 <0.01 0.05

Supplemental forage in breeding season - 0 . 2 7 5.99 0.01 0.08

Separate bull housing in non- breeding season 0.20 4.47 0.04 0.13

Region o f Ontario 8.58 0.04 0.23 West 0.07 Central 0.30 East (vs. sou th) - 0 . 1 0

1Deviance is dis tr ibuted as approximately chi-square with d.f. equal to the number of parameters added. P-values to remove te rms f rom the final model. 2Variables forced prior to the entry o f other variables. SP-values f rom a more conservat ive quasi-l ikelihood model.

from the pasture/nutrition category. Pregnancy rates were higher in herds grazing pastures on which some method of weed control was used, and in herds that received less supplementation with other feeds during the pasture grazing period. Pregnancy rates were lower in herds grazing fertilized pas- tures, in herds fed both hay and silage (vs. hay alone) in the winter, and in

J.J. McDermott et al. / Preventive Veterinary Medicine 18 (1994.) 115-127 121

herds in which the main forage in the breeding season was supplemented with an additional forage.

From the environmental /housing category, winter housing and region of Ontario were selected. Herds housed in closed barns over winter had higher herd pregnancy rates than all other winter housing categories. Herds in the central region of Ontario had higher pregnancy rates than the other regions.

Herds in which a bull was either acutely or chronically ill during the breed- ing season had lower herd pregnancy rates.

As anticipated, based on the distribution of herd pregnancy rates in Fig. 1 (in which there was a greater proportion of herds with pregnancy rates close to 100% than would be expected for a binomial distribution with mean value 92.8% and average herd size of 46 ), the final logistic regression model fit the data poorly. The observed final-model Pearson chi-square statistic of 316.9 was well above the expected value of 158 (McCullagh and Nelder, 1989). Thus, the logistic model was compared with a more conservative quasi-like- lihood model (Table 2). In this quasi-likelihood model, breeding type, bull housing and region of Ontario were markedly less significant (P> 0.10 ).

25

20

(2) c- 15

0 (~

(D 10

322 332 342 352 362 372 382 392 402 412 422

herd calving interval (days)

Fig. 2. Distribution of mean herd calving interval for 180 Ontario cow-calf herds, calving season 1986 to calving season 1987.

122 J.J. McDermott et al. / Preventive Veterinary Medicine 18 (1994) 115-127

Table 3 S u m m a r y of herd calving interval regression model, selected by combining significant variables f rom category analyses, for 180 Ontario cow-calf herds, 1986-1987

Variable b SE (b ) P-value Multiple ( in order o f en t ry) (days ) ( f inal) r 2

Intercept ~ 264.43

Interval between 1st I calving dates 0.30 1986-1987

0.05 <0.01 0.18

Breeding season Spring - 9.25 3.38 Early summer - 7.18 3.27 Late summer (vs. fa l l -win ter ) - 6.58 3.31

Length of breeding season ~ (days ) 0.02

Type of breeding Majority AI 2.78 Some AI (vs. n o A I ) 6.33

0.02

3.63 2.42

0.06 0.23

0.21 0.25

0.03 0.26

Bull chronic disease 10.36 2.65 < 0.01 0.33

Manager is owner - 9.18 2.93 < 0.01 0.33

Pasture weed control - 4.63 1.71 < 0.01 0.39

Winter housing Barn + yard 6.69 2.80 Barn + pasture 1.54 3.63 Pasture (vs. closed ba rn ) 7.50 3.42

0.04 0.42

~These variables were forced into the model prior to the entry of other variables.

Herd calving interval

Figure 2 shows the distribution of mean herd calving interval. This distri- bution is roughly normal, with a mean of 365 days, a standard error of 1.4 days, and skewed slightly towards longer calving intervals. While the mean herd calving interval was constant across all herd sizes, the variance was in- versely proportional to herd size. Thus, for all calving interval models, the mean herd calving interval was weighted by herd size to reduce estimated standard errors.

The initial stage of the modelling process was to screen for variables asso- ciated with mean herd calving interval, from each of the variable categories listed in Table 1. During this process, one outlier, with a herd calving interval of 420 days, was detected but no data errors were found so it was retained. The two largest herds had small residuals but were extremely influential due

J.J. McDermott et al. / Preventive Veterinary Medicine 18 (1994) 115-127 123

to the herd-size weighting. Since these two herds were considerably larger than the other herds (both 50% larger than the next largest herd), they were ex- cluded from further analyses.

An overall herd calving interval model is listed in Table 3. The most im- portant forced variable was the interval from the start of calving in 1986 to the start of calving in 1987; each 1 day increase in this interval increased the herd calving interval by 0.3 days.

Chronic bull disease increased the herd calving interval by approximately 10 days. Herds that were owned by the manager had herd calving intervals 9 days shorter than other herds. Herds that grazed pastures with some type of weed control had herd calving intervals approximately 5 days shorter than other herds. Herds housed in a closed barn during the winter had the shortest herd calving intervals of all winter housing categories.

Herd calving interval and herd pregnancy rate were not correlated either crudely ( R = - 0 . 1 1 , P=0 .16) or after adjustment for variables forced into the calving interval model (P= 0.90).

Discussion

The high mean herd pregnancy rate of 92.8% was not surprising, given the breeding conditions in most southern Ontario herds. The shape of the distri- bution of herd pregnancy rates was similar to that found by Janzen ( 1978 ) in western Canada.

A major objective was to investigate associations between the two chosen outcomes of reproductive performance and covariate information collected from farm records and survey questionnaires. The advantage of such a broad based study is that data on a large number of potential factors from randomly sampled herds are available, providing a comprehensive picture of events in the true population of interest. A key disadvantage is that in many cases proxy information such as pasture acreage, pasture fertilization and pasture rota- tion practices must be relied on rather than more specific information such as pasture quantity and quality. A second disadvantage is that important as- sociations of interest may be distorted by the effects of unknown and, there- fore, uncontrolled variables. Thus, the role of this study in hypothesis testing is limited to modifying the strength of belief in current hypotheses about re- productive performance in Ontario cow-calf herds, as well as to generate n~w questions for further more rigorous controlled studies.

The observed lack of fit of the herd pregnancy rate model was most likely due to a combination of lack of fit of the pregnancy rate data to the assumed binomial distribution and missing or misspecified covariates. Thus, the more conservative P-values generated by the quasi-likelihood model (Table 2 ) are preferred.

Herd pregnancy check status had no influence on the predicted proportion

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pregnant in any model. No systematic pattern in a plot of residuals vs. preg- nancy check status was evident. The two largest outliers corresponded to herds that were not pregnancy checked. Both of these herds had low rather than high pregnancy rates.

Females bred in the late summer, fall and winter had the highest pregnancy rates. This finding is in accord with an Ontario research station study by King and MacLeod (1984). This seasonal effect has been attributed to photoper- iod and prepartum nutrit ion (Peters and Riley, 1982).

The expected effects of the two other variables forced into pregnancy rate models were not observed. Within a given herd, pregnancy rate would be ex- pected to increase (or peak) if the breeding season is lengthened. However, as found by Janzen ( 1978 ), no association was found between the length of breeding season determined by the producer and the herd's pregnancy rate. Breeding season length varied between herds and was long in many herds. Approximately 8% of herds had breeding seasons of less than 6 weeks; 20% had seasons of 6 to less than 9 weeks,; 23% had seasons of 9 to less than 12 weeks; 9% had seasons of 12 to less than 15 weeks; and 40% had seasons of greater than 15 weeks. Perhaps producers who restricted breeding season were superior managers, thus confounding the expected association.

The other unexpected result concerned the type of breeding. Herds in which the majority of females were bred by artificial insemination had higher preg- nancy rates than naturally bred herds although it is reasonable to assume that under comparable conditions natural service with fertile bulls should result in higher pregnancy rates. It is suspected that unincluded factors associated with shorter breeding seasons and /o r the use of artificial insemination may be confounding the observed associations between these two variables and pregnancy rate.

The effects of pasture weed control and pasture fertilization were in oppo- site directions. The other pasture/nutr i t ion variables selected indicate that herds that supplemented the main forage with an additional forage had lower pregnancy rates than those that did not supplement. When the analysis was limited to herds with a spring and early summer breeding season, the same results were obtained. These relationships may indicate overconditioning, at- tempts to correct underlying nutritional problems (such as poor pasture), or associations with an unincluded confounder. Our previous caveat about proxy information is probably important in this instance. As well, there was a poten- tial problem of time sequence, since feeding changes may be a response to previous reproductive problems.

Current recommendat ions to veterinarians and producers are that prepar- tum and postpar tum energy deficiencies can have an important impact on pregnancy rate (Corah, 1988). This advice is based on a number of experi- ment station feeding trials (Wiltbank et al., 1962, 1964; Dunn et al., 1969). However, the results of such feeding trials have not always been consistent,

J.J. McDermott et al. / Preventive Vet eri nary Medicine 18 (1994) 115-127 125

leading Koch and Algeo (1983 ), in their review of beef cow nutrition trials to caution that "... the interactions of nutrition and reproduction are not clearly understood".

Owing to the small number of low pregnancy rate herds, a case-control study, investigating factors associated with low herd pregnancy rate would be a log- ical follow-up to this study. Little improvement in pregnancy rates is possible for 75-80% of producers. For the other 20-25%, the diagnosis and solution of particular breeding problems could be of great practical importance.

With few exceptions, cow-calf producers aim for herd calving intervals of 12 months. In herds with extended breeding seasons, calving interval might be a more sensitive indicator of breeding problems than pregnancy rate.

Interval between first calving dates in 1986 and 1987 (for females calving in that herd in both years) was the variable most strongly associated with herd calving interval. This variable was used to control for variations in calv- ing interval due to delayed bull exposure. For the 64 herds recording date of bull exposure, the interval between first calving dates and the interval from first calving date to bull exposure were strongly associated (R=0.79, P < 0.001 ). A possible danger of controlling for interval between first calving dates is that instead of simply controlling for delayed bull exposure it is pos- sible to overcontrol and fail to detect delays in the start of the 1987 calving season that were due to reproductive problems. However, this potential prob- lem does not appear to be important. A scatter plot of interval between first calving dates and interval from first calving date to bull exposure indicates that only 3 of 64 herds (4.7%) had noticeably longer (approximately 15 days) intervals between first calving dates than were expected from the bull expo- sure dates. In addition, when first calving date interval was excluded from the analysis, the same variables were selected, but the proportion of herd calving interval variability explained by the model was reduced (R 2 __ 0.29 vs. 0.42 ).

Variables in the final herd calving interval model explained a moderate proportion of the overall variation (R 2= 0.42 ). Residual and normal proba- bility plots indicated that the model fit the data reasonably well. While a large proportion of the overall variation remains unexplained, more confidence can be placed in both selected and excluded associations of the calving interval than in the pregnancy rate model.

The association between main breeding season and mean herd calving in- terval was different from the main breeding season-pregnancy rate relation- ship described previously. The shortest calving intervals were for spring-bred herds, longer for summer-bred herds and longest for herds bred in the fall/ winter. It is possible that there may be an interaction between main breeding season and length of breeding season, with producers who breed cows in the spring and wean calves in the fall striving for more uniform calf crops than producers weaning calves in other seasons. The association between "type of breeding" and calving interval was as expected.

126 z z McDermott et al. / Preventive Veterinary Medicine 18 (1994) 115-127

The most important of the non-forced variables was bull disease. Herds in which a principal herd sire suffered from a chronic disease during the breed- ing season had a 10.4 day longer herd calving interval than other herds.

The three other calving interval associations selected require further refine- ment for interpretation. "Manager is the herd owner" presumably encompas- ses some specific management practices which decrease calving interval. Likewise, 'overwintering in a closed barn' may represent a combination of influential management practices and environmental conditions. However, the most important area for variable refinement is in the pasture/nutrition category. It is presumed that variables in this category strongly influence both calving interval and pregnancy rate, but as previously outlined, the nature of these relationships remains elusive. In these analyses, herds with some form of a pasture weed control had significantly higher.pregnancy rates and signif- icantly shorter calving intervals. Whether this is a specific effect of weed con- trol or (more likely, we think) that weed control happens to be the best mea- sure of pasture quality in this data set, requires further investigation.

Measurement of herd reproductive performance should be conditioned on the goals of the herd manager. In a previous paper (McDermott et al., 1992), an association between increased culling rate and shorter breeding season was noted. However, as that paper highlighted, culling policy (for reproductive performance or other reasons) was not consistent across herds. Variations of cow maintenance costs may be one contributing factor. Average annual cow- maintenance variable costs for Ontario ( 1991 ) were C$ 574 but the means of the lowest and highest quartiles (ranked by profit per cow) ranged from C$ 636 to C$ 562 (De Jong and Lindsay, 1992).

Given that individual manager goals must be accounted for, two study re- suits bear emphasis. The first is that regardless of management goals, approx- imately 20% of producers realistically could improve their herd pregnancy rate. The other point is that for producers attempting to maintain a specific breeding season of less than 7 weeks certain tradeoffs exist. Such a program will be easiest to maintain by breeding in the spring and early summer, by natural service, by timely introduction of the herd sire (s) and by monitoring bull health carefully.

Acknowledgments

Financial support for this study was provided by the Ontario Ministry of Agriculture and Food. J.J. McDermott was supported by a fellowship from the Medical Research Council of Canada. The authors gratefully acknowledge the assistance of the cooperating cow-calf producers. M. Gignac provided data handling support. A. de Marchi, S. Hogenkamp, N. Loudon and R. Sansom assisted with data collection and handling. Drs. D. Alves and N. Anderson were coinvestigators in the larger study from which these data were drawn. R.

ZZ McDermott et al. /Preventive Veterinary Medicine 18 (1994) 115-127 127

McCartney, M. Singer and others at the Ontario Ministry of Agriculture and Food's Red Meat Centre provided computerized calving data.

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