Effects of Various Factors on Reproductive Efficiency1, 2

Effeds of Various Fadors on Reprodudive Efficiency1'2 J. MATSOUKAS ~ and T. P. FAIRCHILD Animal Sciences Department University of New Hampshire Durham 03824 Abstract

high production and breeding efficiency while others (2, 5, 13, 17) reported either little or no relationship. This study was to investigate the relationship between production and reproductive efficiency and to study the influence of various factors on general measures of breeding efficiency.

Records of 370 Holsteins and 223 Jerseys from four university herds were used to study the effects of various factors on the number of services per conception, days from first breeding to conception, and calving interval. Relatiouships between each of these measures of breeding efficiency and milk production were also estimated. There were differences among herds in breeding efficiency which for the Holstein data ranged from 1.66 to 2.54 services per conception, from 18.5 to 43.5 days from first breeding to conception, and from a 388 to a 419 day calving interval. Similar for the Jersey data were 1.71 to 2.24 services, 18.5 to 39.3 days, and 382 to 405 days. There were differences among years for all measures of breeding efficiency for the Jersey data only. Lactation number had an effect on days from first breeding to conception and on calving interval for the Holstein data. The herd-by-year interaction was significant for all measures of breeding efficiency for the Jersey data. Seasonal effects on breeding efficiency were not evident. There was some indication of a small antagonistic relationship between production and breeding efiqciency.

Data and Methods

Introduction

High production and reproductive efficiency are economically important traits in dairy catfie. The relationship between these traits was studied by several investigators, but their findings are contradictory. Some workers (4, 7, 8, 11) found a negative relationship between Received March 21, 1974. Published with the approval of the Director of the New Hampshire Agricultural Experiment Station as Scientific Contribution No. 723. 2 Partially supported by Grant-in-Aid from the Eastern Artificial Insemination Cooperative, Ithaca, NY. Department of Animal Husbandry, University of Thessalonikl, Thessaloniki, Greece.

The data consisted of breeding and production records of 370 Holstein (1015 lactations) and 223 Jersey cows (630 lactations) of the dairy herds of the Universities of Connecticut, Massachusetts, Maine, and New Hampshire. These data included all Holstein and Jersey cows in these herds which were born from January 1, 1953, (Jerseys) and January 1, 1955, (Holstein) to January 1, 1969, and which had one complete lactation followed by a new calving. A conception was defined as an event terrninating with the birth, or abortion, of a calf. Embryonic deaths and short term abortions were not considered conceptions because such events were not recorded accurately. As a rule, cows were inseminated on the first heat 60 to 70 days postpartum. Reproductive examinations were by veterinarians 30 to 60 days after parturition with follow-up examinat-ions as required. These examinations included pregnancy confirmations and diagnosis of any detectable infection of the reproductive tract or abnormal ovarian activity. When cystic follicles or persistent corpus lutea were diagnosed, they were either ruptured or treated with appropriate hormones, A different veterinarian was associated with each of the different herds. Also for all herds but one the same veterinarian made all reproductive examinations for that herd from 1953 through 1969. Three veterinarians were involved in making reproductive exams in the other herd. The following measured breeding efficiency, number of services per conception, days from first breeding to conception, and calving interval. Date of conception was estimated by subtraeting 280 days from the subsequent calving date. Production records were adjusted to a 2x,

540

541

REPRODUCTIVE EFFICIENCY

TABLE 1. General means and standard errors of three measures of breeding efficiency and milk produetion.

Holsteins

Jerseys

2.12 ± .06

1.90 ± .07

33.6 ± 1.8 401 ± 2 7858 ± 79

26.8 ± 2.4 392 --- 3 5793 ± 70

Variable No services per conception Days from first breeding to conception Calving interval (days) Milk production (kg)

305-day, mature equivalent (ME), 4% fat corrected milk (FCM) basis adjusted for days open by factors determined by MeDaniel et al. (10), Gaines (6), and Smith and Legates (13). Incomplete records of less than 305 days were discarded. A least squares analysis of variance was used to estimate regression coefficients of measures of breeding efficiency on milk production and to investigate effects of herd, year of calving, season of calving, lactation number, and herdby-year interaction on these measures of reproductive efficiency. The following model was used for this analysis: Yijkln = u + h i + y j + sk + ll + (hy)ij + bl (XljkZ. -- x') 2 + bz (xijkl~ -- X2) ~- e i j k l n ,

where u represents the general mean, hi is the effect of the ith herd, Yl is the effect of the jth year of calving, sk is the effect of the kth month of calving, 1z is the effect of the lth lactation, (hy)ij is the effect of the interaction of the ith herd by the jth year of calving, b 1

is the linear regression coefficient of the respective measure of breeding efficiency on milk production, b2 is the corresponding quadratic regression coefficient, and eijkln represents random error. Correlations between the various measures of breeding efficiency and milk production were estimated within herd because the analysis of variance had indicated a significant herd effect on measures of breeding efficiency. These correlations were on a cow basis rather than on a lactation basis. Prior to statistical analysis distributions of the various measures of breeding efficiency and of milk production were studied. Milk production was normally distributed for both breeds. Number of services per conception and days from first breeding to conception were not normally distributed nor was calving interval fox" the Jersey breed. Those variables which were not normally distributed were subjected to square root and logarithmic transformations to obtain nol~nally distributed variables. Transformations failed to improve the distributions. Therefore, the original unadjusted data were

TABLE 2. Herd means for production and three measures of breeding efficiency. Herd A

Herd B

Hord C

Herd D

316 168

237 179

297 174

165 109

8663 6752

7297 5605

7921 5883

7880 5203

2.28 2:07

1.66 1.71

2.54 1.71

1.98 2.24

40.9 35.4

18.8 18.5

43.5

21.4

37.1 39.3

419 405

388 382

406 386

402 403

NO reCOlXJ.s

Holsteins Jerseys Production (kg) Holsteins Jerseys Services per conception Holsteins Jerseys Days from first breeding to conception Holsteins Jerseys Calving interval (days) Holsteins Jerseys

JOURNAL OF DAIRY SCIENCE VOL. 58, NO. 4

542

MATSOUKAS AND FAIRCHILD

TABLE 3. Effect of lactation number on breeding efficiency for Holsteins. La~ation no No of records Services per conception Days from first breedir~g to conception Calving interval (days)

1-5

6

7

8

9

lO

953 2.03 to 2.29

35 2.71

16 2.43

7 2.86

3 3.33

1 3.95

30 to 38 398 to 412

52 425

62 442

62 448

103 467

113 478

used with the realization that not all variables were normally distributed. Results and Discussion

General measures of breeding efficiency. Jerseys (Table 1) required fewer services per conception and had shorter calving intervals (P < .05) than did Holsteins. As expected, the difference in milk production between the two breeds was significant. Analysis of variance; effect of various [actors on reproductive efficiency. There were differences (P < .01) among herds for all three measures of breeding efficiency for both breeds. This was largely due to one herd with superior reproductive efficiency in comparison to the other three (Table 2). There was no way to pinpoint reasons for this difference. General herd management, veterinarians responsible for reproductive checks, breeding practices, service sires, and culling policies all varied from one herd to another. Spears et al. (15) studied the effect of different sources of variance on fertility (nonreturns) of cows in 23 herds in each of 22 artificial breeding locals and estimated that 7.5% of the total variance was due to differences between herds within locals and 4.6% was between locals. Olds et al. (12) found that 13.2% of the total variance was due to differences between herds within locals and 1.5% between locals. There were differences among years of calving (P < .05) for all three measures of breeding efficiency in the Jersey breed. However, year of calving had no significant effect on these measures of breeding efficiency for Holstein data. Inspection of means for each year revealed no time trend. Spears et al. (15) estimated that the effect of year on fertility accounted for 1.4% of total variance while Olds et al. (12) found this component of variance was 2.0% of the total. Month of calving which was an indicator oi seasonal effect did not show any significant (P < .05) effect on measures of breeding efficiency in either breed and did not show arty ]OURNAL OF ~)AIRY SCIENCE VOL. 58, NO. 4

consistent trend. This agrees with Armstrong (1) and Morrow (11) but not others (3, 4, 9). Lactation number had a significant (P < .05) effect on days from first breeding to conception and calving interval in the Holstein breed. However, for Holsteins, lactation number had no significant effect on services per conception, and for Jerseys lactation number had no significant effect on any of the measures of breeding efficiency. Inspection of the means for the three measures of breeding effieiency for each lactation did not show any consistent effect in the Jersey breed nor in the Holstein breed from the first to the fifth lactation. However, beyond the fifth lactation breeding efficiency showed a definite decline for the Holstein breed (Table 3). There were few lactations beyond the fifth lactation for the Jersey data so there was no evidence of a possible corresponding decline in breeding efficiency for this breed. Results of Tanabe and Salisbury (16) and Carman (4) were similar to these, but Morrow (11) reported that parity was not related to the number of days open or services per conception. The herd-by-year of calving interaction was not significant (P < .05) for Holsteins but for Jerseys was significant for all three measures of breeding efficiency. This indicates that, for the Jersey data, herd differences were not consistent in magnitude but varied from year to year. Spears et al. (15) estimated that 4.9% of the total variance was due to herd-by-year interaction within locals and 2.0% due to the TABLE 4. Linear regression coefficients (b --+ SE) of breeding efficiency on milk production in 1,000 kg units. Measure of breeding efficiency

Holsteins

Jerseys

Services per conception --.03-+ .04 .04--- .06 Days from first breeding to conception .26_+1.45 1.12_+2.03 Calving interval (days) 2.24_+1.68 3.28_+2.22

REPRODUCTIVE

543

EFFICIENCY

interaction between )'ears and locals. Olds et al. (12) estimated these components of variance accounted for 7.7% and 3%, respectively, of the total variance.

TABLE 5. Pooled correlatitrns within herds between breeding efficiency and prodlmtio.n. Measure of breeding efficiency Holsteins

Jerseys

Analysis of variance; regression of measures of breeding efficiency on milk production. As

Services per conception Days from first breeding to coneeption Calving interval (days)

.083

.149 a

.108 ~ .125~

.117 .129.

in Table 4, all of the linear regression coefficients of breeding efficiency on milk production were positive except for regression of services per conception on milk production for the Holsteins. However, none of these regression coefficients was statistically significant. With respect to the quadratic regression all of them were practically equal to zero except the quadratic regression for service per conception on milk production in the Holstein data. Taking into consideration that the corresponding linear regression is small and not sig~fificant, this small quadratic regression seemed meaningless. Touchben T e t al. (17) reported the regression of services per conception on fat production (kg) was .0028 (P < .05). However, the partial regression of services per conception on butterfat production for a constant servioe interval was negative and smaller in absolute value. Everett et al. (5) also reported a linear regression of services per conception on a 120day production (kg) was .0025 in the Guernsey breed and .0017 in the Holstein breed. With regard to the linear regression of days from first breeding to conception and calving interval on milking production, Everett et al. reported small and negative ones for both measures of breeding efficiency. These workers indicated that as 120-day production increased, there was a slight decrease of days fi'om first breeding to conception and calving interval.

Correlations within herds between measures of breeding efficiency and production. To obtain a more complete picture of the possible relationship between breeding efficiency and production, correlations within herds were computed between measures of breeding efficiency and milk production on a cow, rather than a lactation, basis. These correlations were within herd because the analysis of covariance had indicated that there was a herd effect on breeding efficiency. After these correlations were esti,mated for each herd, they were tested for homogeneity and then combined according to the method of Snedecor and Coehran (14). The combined or pooled correlations are shown in Table 5. In general, these coaTelations were higher than those reported bv others (4, 9, 12). The regression and correlation coefficients

These correlations were significantly different from zero at P < .05. indicate that there was a small antagonistic relationship between milk production and breeding efficiency. These results were probably biased by the fact that lower producing cows were culled sooner and, therefore, had fewer services than higher producers. Also, because of the abnormal distribution of some of the variables, the results which apply to these vmSables should be considered tentative. Acknowledgments

The authors wish to express their appreciation to William S. Gaunya, University of Connecticut; Stanley N. Gaunt, University of Massachusetts; and to H. A. Leonard, University of Maine for providing data from their respective university herds, The authors would also like to thank Wfllard E. Urban, Jr., Assistant Director, N. H. Experimental Station, at the University of New Hampshire for his assistance with the statistical analysis of the data. References

(1) Armstrong, D. V. 1964. Breeding efficiency in a so.uthem Calffornh~ dairy herd. Unpublished M.S. Thesis, Miehiga~ State University, East Lansing. (2) Boyd, L. J., D. M. Seath, and D. Olds. 1954. Relationship betweerr level of milk production and breeding efficiency in dairy cattle. J. Anita. Sci. 13:89. (3) Branton, C., W. S. Griffith, H. W. Norton, and J. G. Hall. 1956. The influence of heredity and environment on the fertility of dairy cattle. J. Dairy Sei. 39:933. (Abstr.) (4) Camaan, G. M. 1955. Interrelatiov~s of milk production and breeding efficiel~cy in dairy cows. J. Ar~im. S:ei. 14:753. (5) Everett, R. W., D. V. Armstrong, and L. J. Boy& 1966. Genetic relationship between production and breeding efficiency. J. Dairy Sci. 49,:879. (6) Gaines, W. L. 1928. The energy basis of measuring yield in dairy cattle. Illinois Agr. Exp. Sta., Bull. 308. (7) Jones, I. R., R. W. Dottgherty, and T. R. Haag. 1941. Reproduetive performance in ]OURNAL OF DAIRY SCIENCE VOL. 58, N o .

i

544

(8)

(9)

(10)

(11)

MATSOUKAS AND FAIRCHILD

daily cattle. Oregon Agr. Expt. Sta., Bull. 395. Lewis, R. C., and R. E. Holweood. 1950. The influence of age, level of production, and management on the calving interval. Michigan Agr. Exp. Sta., Quart. 'Bull. 32:546. Mercier, E., and G. W. Salisbury. 1947. Seasonal variations in hours of daylight associated with fertility level of cattle under natural breeding conditions. J. Dairy Sci. 30:747. McDaniel, B. T., R. H. Miller, E. L. Corley, and R. D. Plowman. 1967. DHIA age adiuslanent factors for standardizing lactations to a mature basis. Dairy Herd Improvement Letter. U.S. Dep. Agr. ARS-44188. Morrow, D. A. 1969. Postparttun ovarian activity and involution of the uterus and cervix in dairy cattle. Vet. Scope. Vol. XIV, No. 1. The Upjohn Co., Kalamazoo, MI.

IOLqINAL OF DAIRY SCIENCE VOL. 58, NO. 4

12) Olds, D., L. D. Colvin, T. Cooper, and O. W. Deaton. 1966. Sources of variance affecting dairy herd fertility and delayed returns to service. J. Dairy Sci. 49:1004. 13) Smith, J. W., and J. E. Legates. 1962. Relation of days open and days dry to, lactation milk and fat yields. J. Dairy Sci. 45:1192. 14) Snedecor, G. W., and W. G. Coehran. Statistical methods. Iowa State Press. 15) Spears, J. R., D. Olds, and T. Cooper. 1965. Evaluation of sources of varfanee in dairy herd fertility. J. Dairy Sei. 48:90. 16) Tanabe, T., and G. W. Salisbury. 1946. The influence of age on breeding efficiency of dairy cattle in artificiM insemination. J. Dairy Scf. 29:337. 17) Touchberry, R. W., K. Rottensten, and H. Audersen. 1959. Associations between service interval, interval from first service to conception, number of services per conception, and level of butterfat prod~tetion. J. Dairy Sci. 42':1157.