Fertility Issues in High Producing Cows

Transcription

1 The Babcock Institute University of Wisconsin Dairy Updates Fertility Issues in High Producing Cows Reproduction and Genetics No. 611 Author: Daniel Z. Caraviello 1 Introduction The stress of high milk production, along with increasing herd size and changes in facilities and management, has made fertility one of the main focuses of genetic improvement today. In the US, the reduction in calving rate to first service and the impact of this decrease in fertility on the Holstein breed, mainly in the last 20 years, is of major concern [27]. Figure 1 shows the clear trend for increases in milk yield and reduced conception rates in Jersey and Holstein breeds over time. Milk production per cow has nearly doubled in the past 40 years, and an increase in 40 days open per lactation occurred in the same period (Figure 1). Because there is a positive correlation (roughly +0.35) between milk yield and days open, the task of improving fertility while selecting for high milk production is challenging 1 An important aspect of fertility traits is that they are influenced by both, direct (service sire) and maternal (sire of the cow) effects. In genetic evaluations, the direct effect is regarded as male fertility and the maternal effect as female fertility. Male fertility measures the ability of semen from a service bull to generate pregnancies, while female fertility measures the 1 Daniel Caraviello is a Graduate Research Assistant in the Department of Dairy Science at the University of Wisconsin-Madison. Technical assistance provided by Kent Weigel, Assistant Professor, Dairy Science Department, University of Wisconsin-Madison 4% Fat-Concentrated Milk (kg) Years ability of a cow to cycle normally, show visible estrus, and conceive in a timely manner. Male Fertility Jersey Jersey Holstein Holstein Figure 1: Milk yield and conception rate of 532 Holstein and 29 Jersery herds from 1976 to 1999 [27]. The capacity of sperm to reach the site of fertilization, fertilize the egg, and activate embryonic development are key aspects of male fertility, and a series of laboratory assays have been developed for evaluating these functions. Traits related to male fertility can be divided into compensable and noncompensable categories. Compensable traits (i.e., motility and morphology) do Conception Rate (%) In this Dairy Update 1 Introduction 1 Male Fertility 2 Female Fertility 3 Other Factors Influencing Fertility 6 Summary 7 References The Babcock Institute 2004 Board of Regents of the University of Wisconsin System

2 not affect fertility if the number of spermatozoa used in the insemination is increased [21]. These traits are inexpensive and easy to measure. Because of the high standards for number of spermatozoa per straw, the noncompensable traits, such as: nuclear vacuoles [21], morphological deficiencies that do not suppress movement [6], and defective chromatin structure [2], are the ones that impact fertility on the farm. However, determining male fertility by laboratory assays has limited value, because the particular spermatozoa that fertilizes an egg is highly selected and not representative of the semen sample as a whole. Braundmeier and Miller [4] suggest several proteins that can indicate male fertility, but most have not been studied in detail in cattle. An alternative way to determine male fertility is by non-return rates. In the US, the effect of service sires on 70-day non-return rate after first breeding (i.e., the cow is not re-bred within 70 days) is evaluated by Dairy Records Management Systems in Raleigh, NC. Data are adjusted for the effects of herd-year-month, parity, age of cow, days in milk, energycorrected milk, and genetic level of the cow, and the results are published for service sires with at least 300 inseminations in the last three years. The Estimated Relative Conception Rate (ERCR) rankings can be viewed at and these reflect difference in average conception rate from an average Artificial Service (AI) sire. Evaluations for individual sires span a range of about 15 percent, and this information can be used as a secondary selection tool when choosing among bulls that are elite for production, type, longevity, or Lifetime Net Merit (LNM$). Pecsok et al. [13] concluded that a premium of two dollars per straw can be paid per unit increase in ERCR score. Regarding the accuracy of ERCR information, repeatability estimates are derived from the number of breedings for each sire. For example, there is a 95 percent probability that a sire with ERCR of +1 percent and repeatability 60 to 70 percent has its true ERCR between -2 and +4 percent. Female Fertility The heritability for female fertility is around four percent, and the genetic correlation between productive life and days open is around -0.60, reflecting farmers' tendency to cull cows that don t become pregnant. The quality of data is a major concern in any genetics selection program, especially for fertility traits, where mistakes can occur in judgment of pregnancy and pregnancy losses occur routinely. Most dairy herds provide data regarding calving interval, which is a rough measure of fertility, many also provide insemination data that can generate non-return rates, some provide pregnancy examination data, and relatively few provide data regarding technician, type of breeding, and so on. Progesterone data (indicating the onset of luteal activity) can usually only be obtained from research herds. Recording of variables like visible heats, heat synchronization protocols, veterinary examinations, do not breed designations, dates of exposure to natural service bulls, and occurrence of reproductive disorders (i.e. metrits, ovarian cysts, retained placenta, twins, difficult births, and stillbirths) will be important in generating accurate genetic evaluations for male and female. The highest quality data usually come from on-farm management software, but standardizing these data requires considerable effort. Although traits like days open, calving interval, and non-return rate have low heritability, the coefficient of variation in fertility traits is similar to that of production traits, and genetic improvement in these traits should be possible. Vasconcelos et al. [23] found that Roughly 20 percent of pregnancies are lost between 28 and 98 days of pregnancy and Fricke et al. [8] reported 23 percent losses between days 26 and 72 of pregnancy; in both cases, pregnancy diagnosis occurred via ultrasound. Data from cows that have a subsequent calving can be checked against calving dates, but some cows never calve again. In routine sire evaluations in the US, 280 days (a typical gestation length) is subtracted from the calving date to calculate 2 Dairy Updates 2004

3 days open for each cow. Cows culled for infertility receive a value of 250 days open, and data are analyzed using an animal model. Results are published as daughter pregnancy rate (DPR), where a one percent increase in DPR corresponds to a decrease of four days open, and vice-versa. The US currently uses a 21-day pregnancy rate, which refers to the number of cows that get pregnant during each 21-day period, out of the total number of open cows. The formula to convert from days open to pregnancy rate is: Pregnancy Rate = 21 / (days open voluntary waiting period + 11) This trait is influenced by the post-calving ability of a cow to return to normal reproductive status, her ability to display visible estrus, and her ability to conceive and maintain the pregnancy [30] (Table 1). Young sires (with first-crop daughters only) will usually have reliabilities from 45 to 60 percent, indicating a large influence of pedigree information. Sires DPR values can change more than other traits, because different sources of information (reported breedings, calving intervals, and reproductive culls) arrive at different times during a sire s life. Breeding objectives that were once focused on production and type are becoming broader in scope via inclusion of health and fertility traits. Table 2 shows the weights given to each trait in the new LNM$ index. Recent modifications include direct selection for fertility (daughter pregnancy rate), which receives seven percent of the total emphasis. These changes will provide an expected genetic gain of 0.1 percent in 21-day pregnancy rate per year. Other Factors Influencing Fertility Body Condition Score Body condition score (BCS) is a subjective trait with moderate heritability (0.2 to 0.4) that aims to indicate the amount of reserve tissue (mostly fat) in the body, thereby indicating the Table 1: Daughter pregnancy rates and corresponding days open for some popular Holstein sires Bull s Name Corresponding Days Open DPR Blackstar +0.9% -3.6 days Bellwood +0.2% -0.8 days Celsius -2.6% days Converse +1.2% -4.8 days Duster +2.4% -9.6 days Infinity +3.2% days Jed -1.6% +6.4 days Melwood -2.0% +8.0 days Target +2.0% -8.0 days Source: Table 2: Weights applied to each trait on the old (2000) and new (2003) Lifetime Net Merit Calculation Trait NM$ (2000) NM$ (2003) Milk 5 0 Fat Protein Productive life Somatic cell score -9-9 Udder composite 7 7 Feet/leg composite 4 4 Size composite -4-3 Daughter pregnangy rate 7 Service sire calving difficulty -2 Daughter calving difficulty -2 Source: nutrition and health of a dairy cow [9, 14, 25, 26]. Higher scores for BCS during lactation are related to lower production levels but are favorably related to reproductive performance [5]. Pryce et al. [14] obtained genetic correlations of and between BCS and calving interval before and after adjusting for milk, respectively. Royal et al. [20] found a genetic relationship of between BCS and calving interval. Veerkamp et al. [24] showed that lower BCS was related to increased time to onset of ovarian activity after parturition, and Royal et al. [20] suggested that a delay of six days in the start of luteal activity occurs per one point decrease in BCS (on a 1 to 9 scale). Regarding BCS change, Pryce et al. [14] found that changes in BCS between one and four months postpartum have the greatest impact on Reproduction and Genetics No

4 Table 3: Genetic correlations for milk-adjusted scores [14] BCS Period First Lactation Second Lactation Days to First Service and BCS 1 Services Per Conception and BCS 2 Days to First Service and BCS 3 calving interval. Pryce et al. [14] also found that BCS scores taken one month after parturition had the highest genetic correlation with calving interval in first lactation cows, so this is probably the optimum time to record BCS (Table 3 and 4). Milk Production Westwood et al. [31] evaluated factors that influenced the fertility of 82 multiparous cows in Australia and observed that cows producing more than 38 liters of milk per day were 2.6 times more likely to ovulate late (after 53 days postpartum) than cows producing less than 29 liters per day. They noted that this delay in ovulation will lead to later first estrus and, hence, a longer calving interval. Weigel [28] showed that primiparous cows that produced greater than 36 liters of milk per day and multiparous cows that produced more than 45 liters per day had 1.8 and 1.6 percent lower conception rates, respectively, as compared with other animals of the same age. Pryce et al. [14] obtained estimated genetic correlations of 0.56 to 0.61 between milk, fat, and protein yield and calving interval. Veerkamp and Brotherstone [26] estimated a genetic correlation of between milk yield and BCS, and Royal et al. [19] obtained genetic correlations of and between BCS and fat and protein yields, respectively, indicating that production traits can be an important predictors of fertility. 4 Dairy Updates 2004 Services Per Conception and BCS 4 Calving Postpartum Pregnancy check Dry-off The approximate standard errors average The approximate standard errors range from 0.22 to The approximate standard errors average The approximate standard errors range from 0.21 to 0.29 Table 4: Genetic correlations for BCS [14] BCS Period Genetic Correlation Average BCS month month month month month month month month month month Heat Stress Heat stress is a major concern in some areas, under these conditions cows show decreased feed intake and physical activity, which lead to decreased expression of estrus. Heat stress occurs when the increase in body temperature impacts various body functions. An increase in body temperature at the time of insemination leads to low fertilization and a high incidence of embryonic death, because the viability of the egg, sperm, and embryo are compromised. The incidence, intensity, and duration of standing estrous are also reduced. Heat-stressed cows will have a reduction in the proestrous rise of estradiol, a smaller second-wave dominant follicle, a greater number of follicular waves per estrous cycle, and long luteal phases [32]. Weigel [28] showed that the mean conception rate for summer was 25.9 percent, as compared with a mean of 34.1 percent in winter. Ravagnolo and Misztal [16] evaluate non-return rate at 45, 60, and 90 days after insemination in Florida Holsteins and found a negligible relationship between heat tolerance for milk yield and heat tolerance for fertility. Ravagnolo et al. [17] found that non-return rates were lower at temperature and humidity index (THI) values above 66 to 70 than below these thresholds and noted that each additional point of THI reduced non-return rate by 0.5 to 0.7 percent. Ravagnolo and Misztal [15], evaluating first inseminations of Holstein herds

5 NR45 in Georgia, showed that THI on the day of insemination had the highest effect on NR45, followed by THI two days prior, five days prior, and five days after insemination. Figure 2 shows the reduction in NR45 according to THI for first and later parity cows Nutrition First Lactation 2nd, 3rd and 4th Lactations THI Figure 2: Effect if temperature-humidity index (THI) on non-return at 45 days (NR45) at first and later parities. Westwood et al. [31] observed that animals fed a high proportion of degradable protein (85 percent) were 3.2 times less likely to conceive at first service and three times less likely to be pregnant by 150 days postpartum than animals fed a lower proportion of degradable protein (63 percent); both rations had a 19.3 percent overall crude protein. Cows with plasma cholesterol nadir below 0.9 µmol/l had 2.3 times lower risk of being pregnant by 150 days postpartum than cows above 1.8 µmol/l. In cows with a prolonged calving to first ovulation interval, high mean serum NEFA concentrations (greater than µmol/l) during the first 70 days were associated with a significantly lower risk of achieving pregnancy by 150 days postpartum. Regarding feed intake, animals eating more than 4.03 percent of their body weight in the first 110 days of lactation had almost twice the risk of being pregnant by 150 days postpartum than animals eating less than 3.45 percent of their body weight [31]. Body Weight Veerkamp et al. [24] found a strong negative correlation (-0.54) between the start of luteal activity after calving (using milk progesterone assays) and body weight (BW) at 100 days postpartum. A strong negative genetic correlation (-0.80) was also observed between body weight change in the first 100 days postpartum and start of luteal activity. Two related studies [3, 26] showed that body condition score explained only 12 to 45 percent of the variation in body weight, indicating that change in BCS is a different trait than change in BW. Several studies [3, 10, 24] reported that heavier cows required more services and had longer interval from first service to conception than lighter cows. Westwood et al. [31] observed that cows that lost less than 51 kg of body weight in the first 42 days of lactation were 3.7 times more likely to conceive than cows that lost more than 109 kg in the same period. Type Traits Type traits (particularly body traits), as they are recorded in most countries, infer more about frame size than tissue mobilization, so they usually aren't strongly related to fertility. However, traits like dairy form could be useful for predicting fertility when BCS measures are unavailable. Previous studies reported a genetic correlation of 0.84 between BCS and dairy form. Cows that score higher for dairy form tend to have lower body condition scores. Pryce et al. [14] obtained a genetic correlation of 0.47 between dairy form and calving interval, indicating that selecting sires for high dairy form can lead to poorer reproductive performance. (Table 5) Rogers et al. [18] found a genetic correlation of 0.50 between dairy form and the incidence of reproductive disorders. These results suggest that, once strong selection for milk yield has been applied, selection for low or moderate dairy form values would be beneficial. Reproduction and Genetics No

6 Table 5: Biological extremes of type and management traits and genetic correlation estimates of production, type and management traits with calving interval (CI) Trait 1 9 SE 1 Milk yield 0.61 (0.08) Fat yield 0.56 (0.08) Protein yield 0.57 (0.08) Stature Small Tall 0.33 (0.10) Body depth Shallow Deep 0.26 (0.12) Chest width Narrow Wide 0.28 (0.09) Rump angle High pins Low pins 0.07 (0.12) Angularity Coarse Angular 0.47 (0.10) Rump width Narrow Wide (0.12) Rear leg set Posty Sickled 0.19 (0.11) Foot angle Low Steep (0.12) Fore udder attachment Loose Tight (0.12) Rear udder height Very low Very high 0.07 (0.11) Udder support Broken Strong 0.16 (0.11) Udder depth Shallow Deep (0.01) Teats rear view Wide Close (0.01) Teats side view Close Apart 0.44 (0.10) Teat length Short Long 0.09 (0.11) Milking speed Slow Fast 0.25 (0.15) Temperament Nervous Quiet 0.24 (0.14) Locomotion Poor Excellent (0.14) 1 SE Genetic Correlation with Calving Interval (CI) Parity Second and later lactation cows typically have lower body condition scores than first lactation cows, therefore genetic differences for BCS and fertility may be greater in older animals. First lactation cows have six to seven percent higher non-return rate than cows in sixth or later lactations [12]. Calving Ease Score Miller et al. [12] showed a decrease in nonreturn rate at first service and an increase in days to first service and days open when the calving ease scores (at the onset of the lactation) increased. Weigel and Rekaya [29] also noted that calving ease scores of four and five were associated with lower conception rates. Health Miller et al. [12] showed a small, but significant correlation between non-return rate and somatic cell score (SCS) in Holsteins, but this relationship was not significant in Jerseys. Days open increased by 0.5 days for each unit increase in SCS. The interval from calving to first service (94 versus 71 days) and days open (137 versus 92 days) were greater for cows with mastitis than for those without mastitis, respectively, in a study on Jersey cows [1]. Summary The positive correlation between milk yield and days open has raised interest of researchers on the genetics of fertility, because some of the most important breeds (i.e. Holstein) have shown decreased fertility in the past years. Male fertility and female fertility are two of the ways to select sires for fertility. Female fertility is also included in the Net Merit index (US) calculations. Body condition score, used as a parameter to evaluate nutrition in a farm basis, is one of the main variables influencing fertility, the best moment to measure it is around one month after calving, and it has significant impact on days to first service, and consequently on days open. Heat stress in the day of insemination, and (in a smaller proportion) some days after or before it, has an important impact on fertility, and it makes the decision of inseminating cows under these conditions questionable. High proportions of degradable protein in the diet, and lower feed intake (as a proportion of the body weight) are nutrition factors related to lower fertility. The low correlation between body weight and body condition score shows that these are different traits, heavier cows require more services and have longer interval from first service to conception than lighter cows. 6 Dairy Updates 2004

7 Once strong selection for milk yield has been applied, selection for low or moderate dairy form values would be beneficial. References 1. Baker, A.R., F.N. Schrick, M.J. Lewis, H.H. Dowlen, and S.P. Oliver Influence of clinical mastitis during early lactation on reproductive performance in Jersey cows. J. Dairy Sci. 81: Ballachey, B.E., D.P. Evenson and R.G. Saacke The sperm chromatin structure assay: Relationship with alternate tests of semen quality and heterospermic performance of bulls. J. Androl. 9: Berry D.P., F. Buckley, P. Dillon, R.D. Evans, M. Rath, and R.F. Veerkamp Genetic relationships among body condition score, body weight, milk yield, and fertility in dairy cows J. Dairy Sci. 86: Braundmeier A.G. and D.J. Miller The search is on: Finding accurate molecular markers of male fertility J. Dairy Sci. 84: Dechow C.D., G.W. Rogers and J.S. Clay Heritabilities and correlations among body condition scores, production traits, and reproductive performance J. Dairy Sci. 84: DeJarnette, J.M., R.G. Saacke, J.H. Barne, and C.J. Vogler Accessory sperm: Their importance to fertility and embryo quality, and attempts to alter their numbers in artificially inseminated cattle. J. Anim. Sci. 70: Fohrman, M.H., R.E. McDowell, C.A. Matthews, and R.A. Hilder A crossbreeding experiment with dairy cattle. Tech. Bull, USDA, Washington, DC. 8. Fricke P.M., D.Z. Caraviello, K.A. Weigel, and M.L. Welle Use of Ovsynch for resynchronizing ovulation at various intervals after first postpartum timed artificial insemination in lactating dairy cows J. Dairy Sci. (accepted). 9. Gallo L., P. Carnier, M. Cassandro, R. Dal Zotto, and G. Bittante Genetic aspects of condition score, heart girth and milkyield in Italian Fresian cows. Pages in Metabolic Stress in Dairy Cows. J. D. Oldman, G. Sim, A. F. Groen, B. L. Nielsen, J. E. Pryce, and T.L.J. Lawrence. ed. BSAS Occasional Publ. No. 24. BSAS, Midlothian, Scotland. 10. Hansen, L.B., J.B. Cole, G.D. Marx, and A.J. Seykora Productive life and reasons for disposal of Holstein cows selected for large versus small body size J. Dairy Sci. 82: Kahi, A.K., I.S. Kosgey, V.L. Cardoso, and J.A.M. Van Arendonk Influence of production circumstances and economic evaluation criteria on economic comparison of breeds and breed crosses. J. Dairy Sci Miller R.H., J.S. Clay and H.D. Norman Relationship of somatic cell score with fertility measures J. Dairy Sci. 84: Pecsok S.R., M.L. McGilliard and R.L. Nebel Conception rates. 2. Economic value of unit differences in percentages of sire conception rates J. Dairy Sci. 77: Pryce, J.E., M.P. Coffey and S. Brotherstone The genetic relationship between calving interval, condition score and linear type and management traits in pedigree registered Holstein dairy cows. J. Dairy Sci. 83: Ravagnolo O. and I. Misztal. 2002a. Effect of heat stress on nonreturn rate in Holsteins: Fixed-model analyses J. Dairy Sci. 85: Ravagnolo O. and I. Misztal. 2002b. Effect of heat stress on nonreturn rate in Holstein cows: Genetic analyses J. Dairy Sci. 85: Ravagnolo O., I. Misztal and G. Hoogenboom Genetic component of heat stress in dairy cattle, development of Heat Index Function. J. Dairy Sci. 83: Rogers, G.W., G. Banos and U. Sander-Nielsen Genetic correlations among protein yield, productive life, type traits from the United States and diseases other than mastitis from Denmark and Sweden. J. Dairy Sci. 82: Royal M.D., A.P. Flint and J.A. Woolliams. 2002a. Genetic and phenotypic relationships among endocrine and traditional fertility traits and production traits in Holstein-Friesian dairy cows J. Dairy Sci. 85: Reproduction and Genetics No

8 20. Royal, M.D., J.E. Pryce, J.A. Woolliams, and A.P.F. Flint. 2002b. The genetic relationship between commencement of luteal activity and calving interval, body condition score, production, and linear type traits in Holstein-Friesian dairy cattle. J. Dairy Sci. 85: Saacke, R.G., J.C. Dalton, S. Nadir, R.L. Nebel, and J.H. Bame Relationship of seminal traits and insemination time to fertilization rate and embryo quality. Anim. Reprod. Sci : Saacke. R.G., J. Bame, D.S. Karabinus, J. Mulins, and S.S. Whitman Transport of abnormal sperm in the artificially inseminated cow based upon accessory sperm in the zona pellucida. In 11 th Int. Congress Animal Reproduction and Artificial Insemination. Vol. 3. Dublin, Ireland. P Vasconcelos, J.L.M., R.W. Silcox, J.A. Lacerda, J.R. Pursley and M.C. Wiltbank Pregnancy rate, pregnancy loss, and response to heat stress after AI at 2 different times from ovulation in dairy cows. Biol. Reprod. 56(Supl. 1): Veerkamp R.F., J.K. Oldenbroek, H.J. Van Der Gaast, and J.H.J. Van Der Werf Genetic correlation between days until start of luteal activity and milk yield, energy balance, and live weights. J. Dairy Sci. 83: Veerkamp, R.F Selection for economic efficiency of dairy cattle using information on liveweight and feed intake: A review. J. Dairy Sci. 81: Veerkamp, R.F. and S. Brotherstone Genetic correlations between linear type traits, food intake, liveweight and condition score in Holstein-Friesian dairy cattle. Anim. Sci. 64: Washburn, S.P., W.J. Silvia, C.H. Brown, B.T. McDaniel, and A.J. McAllister Trends in reproductive performance in southeastern Holstein and Jersey DHI herds. J. Dairy Sci. 85: Weigel K.A Improving the reproductive efficiency of dairy cattle through genetic selection. J. Dairy Sci. (submitted). 29. Weigel K.A. and R. Rekaya Genetic parameters for reproductive traits of Holstein cattle in California and Minnesota. J. Dairy Sci. 83: Weigel, K.A. and P. VanRaden New evaluations offer a genetic approach to improving cow fertility ( 31. Westwood C.T., I.J. Lean and J.K. Garvin Factors influencing fertility of Holstein dairy cows: A multivariate description. J. Dairy Sci. 85: Wilson S.J., C.J. Kirby, A.T. Koenigsfeld, D.H. Keisler, and M.C. Lucy Effects of controlled heat stress on ovarian function of dairy cattle. 2. Heifers. J. Dairy Sci. 81: All Babcock Institute publications have a University of Wisconsin Board of Regents copyright. These publications may be copied in whole or in part for local educational use only, provided that the source is identified and materials are not distributed for profit. For further information or to order additional publications, please contact: The Babcock Institute, 240 Agriculture Hall, 1450 Linden Drive, Madison, WI Phone: (608) , Fax: (608) , babcock@cals.wisc.edu, URL: 8 Dairy Updates 2004