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Relationship of parity and body condition score to pregnancy rates in Florida beef cattle
Therisogenology
39: 1143-I
152,1993
RELATIONSHIP OF PARITY AND BODY CONDITION SCORE TO PREGNANCY RATES IN FLORIDA BEEF CATTLE D.O. Rae,’ W.E. Kunkle,’
P.J. Chenoweth,’
R.S. Sand2 and T. Tran’
‘Department of Large Animal Clinical Sciences College of Veterinary Medicine University of Florida PO Box 100136 Gainesville, FL 32610-0136 2Department of Animal Science Institute of Food and Agricultural Sciences University of Florida Gainesville, Florida Received
for publication: Accepted:
June 16, 1992 Febmary 4, 1993
ABSTRACT Pregnancy rates, determined by per rectum palpation, were analyzed with respect to cow parity (range 1 to >8 calvings) and body condition score (BCS, l=thin to 9=fat) at pregnancy examination for 3734 beef cattle females on 3 commercial beef operations (8 herds) in 3 Florida counties in 1989 and 1990. The mean:s and standard deviations for the herds were the following: pregnancy rate, 81.3 :c 39% (range 62.1 to 91.5%); BCS, 4.7 -+ 0.6 (range 4.3 to 4.9); and parity, 3.9 2 2.3 (range 2.8 to 4.8). Significant associations were found between pregnancy rate, parity, BCS and herd (P < 0.001); and between the variable interactions, parity with BCS, herd with BCS, and herd with parity (P < 0.001). Cows with a BCS ~54had a pregnancy rate of 59%; those with a BCS 25 had a pregnancy rate of 90’%. Cows having a parity of <4 had a PR of 80%, while cows having a parity 14 had a PR of 85%. The interaction of parity with BCS was significant, resulting in pregnancy rates as follows; parity <4 and BCS I 4 was 51%; parity c 4 and BCS ;> 5 was 88%; parity 14 and BCS < 4 was 66%; and parity 25 and BCS 2 5 was 93%. Body condition, parity, and the interaction of body condition and parity play important roles in the reproductive performance of commercial beef cows in Florida. Key words:
beef cattle, body condition,
Acknowledgments This study is Florida Agricultural
parity, pregnancy
Experiment
Copyright Q 1993 Butterworth-Heinemann
rate, reproduction
Station Journal Series #R-02465.
1144
Theriogenoiog
y
INTRODUCTION Optimal calf production is dependent on high reproductive efficiency in beef cattle (l-4). Since weaned calf estimates are only approximately 70% nationally (5 7), the need for increasing this number is evident. While non reproductive components such as disease and injury may contribute to a reduced number of calves, the primary cause is the failure of cows to become pregnant (3). Factors which have been identified that can influence failure to become pregnant include those nutrition and parity (8). Inadequate nutrient intake, namely energy and/or protein, lowers the pregnancy rate and reduces the first service conception rate by prolonging the interval from calving to the first postpartum estrus (9). Protein and energy deficiencies appear to affect both hypothalamic and pituitary functions, altering hormonal release and producing a less fertile ovarian environment than is found in cattle that are maintained at adequate nutritional levels (9-13). The nutritional state of the cow can be appraised by scoring the body condition (14-17). The body condition score (BCS) is a subjective measure of nutrient reserves (9); it is a simple, functional indicator closely associated with the body composition of mature slaughtered cows (18). As with nutritional studies, female body condition has been related to certain reproductive parameters such as the postpartum return to estrus, services per conception, pregnancy rate, and calving interval (1,2,5,16,19,20). It has been shown that cows that maintained optimal body condition after parturition, regardless of the calculated nutrient requirements, had enhanced pituitary function and reproductive performance compared with cows that lost body condition (10). In addition, the subsequent conception rate was reduced when cows calved in good body condition and then lost weight prior to the breeding season (20). Characterization of groups of animals prone to suboptimal reproductive performance within the herd would allow for the implementation of corrective management strategies. Previous research has evaluated the relationship of BCS at calving and at breeding to the pregnancy rate (9,17,21), but research examining the relationship of BCS at pregnancy examination to the pregnancy rate is limited (22). Thus, the objective of this study was to examine the relationship between parity (number of calvings), BCS at pregnancy examination and the pregnancy rate in commercial beef herds in Florida.
MATERIALS
AND METHODS
Data were collected over a 2 year period from 8 commercial beef herds in Florida. Data at a south-central Florida ranch were collected on 4 herds in 1989 (Herds 1,2,3, and 4) and on 3 herds in 1990 (Herds 2,5, and 6). Herd 2 was
Therisogenology
1145
included in both years; data for each year for Herd 2 were pooled to estimate variables. Data for Herds 7 and 8 were collected in 1990 on ranches located in north-central Florida. Although breed composition in all the herds was diverse, all 4114 cows in the study were indigenous crossbred cattle with from one-eighth to one-half Brahman breeding. Bteeding management regimens varied at the various ranches with regard to the length of the breeding season, time of year, and bull-to-cow ratio. Herds 1 through 6 had a 150-day breeding season (January 1 to May 31) and a 1:20 bull-to-cow ratio. Herd 7 had a 120-day breeding season (April 15 to August 15) and a 1:60 bull-to-cow ratio. Herd 8 had a 120-day breeding season (April 1 to August 1) and a 1:25 bull-to-cow ratio. Heifers from Herds 1 through 6 were bred to first calve at 36 months of age; heifers in Herds 7 and 8 were bred to calve first at 24 months of age.. There was no control for year, herd management (nutrition, health, bull management), and environmental factors (climatic conditions). Examination for pregnancy diagnosis was performed at 60 to 100 days, following bull removal, by 1 of 3 experienced technicians. At examination, the following information was collected for each cow: year born, body condition score and pregnancy status. Year brands provided year of birth for calculation of age and subsequently parity. A 1 to 9 body condition score (14-17), was determined visually by practiced evaluators. Of the original 4114 animal records, 380 were excluded from the study because of incomplete data (n=165), unscheduled pregnancies (n=3), and limited parity 0 representation (n=212; only in 2 of the 8 herds), leaving 3734 records for analysis. Because of herd differences relative to age at first exposure to a bull, an estimate of parity was employed to facilitate comparison among herds. Parity of individual animals was calculated by subtracting age of the cow at the first exposure to a bull (for the herd) from age of the cow at the time of pregnancy examination; thus, a 3-year-old cow, which was first exposed to a bull at age 1, was classified as Parity 2; a 3-year-old cow which was first exposed to a bull at age 2 was classified as Parity 1. Several variable categories (ie. BCS<3, BCS>6, Parity=O) did not have sufficient numbers of observations for evaluation. For this reason BCS and parity Body condition scores of 53, 4, and >5 were variable categories were grouped. Parities of 1, 2, 3, 4 to 7 (mature cows), and 28 (old cows) were utilized. employed; heifers were not evaluated due to an inadequate sample size. Data were analyzed by Analysis of Variance using the General Linear Model function (SAS; 23). Mean separation of data was established by least squares means analysis. The statistical model included parity, BCS, herd, parity by BCS interaction, herd by BCS interaction, and herd by parity interaction. The herd was evaluated as an important but nonspecific variable.
Theriogenology
1146
RESULTS Descriptive statistics by herd (Table 1) show herd size (range 216 to 665, averaging 415 animals per herd). Mean pregnancy rate and standard deviation for the study herds was 81.3 + 39% (range 62.1 to 91.5%); the mean BCS was 4.7 + 0.6 (averages range from 4.3 to 4.9); and the mean parity was 3.9 f 2.3 calves (averages range from 2.8 to 4.8). Herds with below average BCS (Herds 3 and 7) and one below average parity (Herd 4) had lower herd pregnancy rates (75.2, 62.1, and 66.2%, respectively) than the other herds.
Table 1. Summary Herd 1 2e 3 4 5 6 7 8
a b c d e
of the study herds
na 364 1022 452 216 341 412 262 665
BCSb 4.6 2 0.6 4.9 2 0.4 4.4 + 0.8 4.7 ” 0.6 4.9 + 0.4 4.8 + 0.5 4.3 -+ 0.7 4.6 + 0.6
Paritvc 3.7 k 2.5 3.7 + 2.3 4.8 + 2.5 2.8 k 2.2 4.3 z!z 1.8 4.7 -c 1.8 4.0 * 2.0 3.3 -c 2.2
PRd 79.7 + 40 85.9 + 35 75.2 2 43 66.2 k 47 88.0 ” 33 91.5 + 28 62.1 + 49 88.3 + 32
3734 Total Herd average 415
4.7 ” 0.6
3.9 r 2.3
81.3 + 39
Number of observations per herd. Body condition score at pregnancy examination + standard deviation Mean parity of the herd + SD. Pregnancy rate (%) determined by per rectum examination f SD. Herd 2 represents observations over 2 years; n,,=511, n,,=512.
(SD).
Statistical evaluation using Analysis of Variance was used to prove all independent variables and their interactions to be significant (P < 0.001; Table 2). The model described 26% of the variability in the pregnancy rate (PR) and was represented as follows:
PR = BCS + parity + herd + BCS*parity
+ BCS*herd
+ parity*herd
+ error.
Theriogenology
1147
Table 2. Analysis of variance msendent PRa
Variable
Source B(35 Parity+ He:rdd BCS x Parity= BCS x Herde Parity x Herde Error a b c d e
for pregnancy R-Square 0.259
df 2 4 7 8 14 26 3729
rate (PR) by independent
variables
C.V. 40.05
Root MSE 0.330
PR 0.824
F Value 192.53 9.32 6.67 4.09 7.30 3.58
P>F
Type III Sum of Sauares 41.98 4.06 5.09 3.57 11.14 10.16 539.98
0.0001 0.0001 0.0001 O.oool 0.0001 0.0001
Pregnancy rate. Body condition score at pregnancy examination; 53, 4, 25. Parity category; 1, 2, 3, 4-7, 28. Herdslto8. Interaction of variables; BCS, parity, and herd.
Groups of cows having body condition scores OE ~3, 4 and ~5 had pregnancy rates of 31, 60 and 89% respectively (P
Table 3. Least squares mean pregnancy
Herd 1 2e 3 4 5 6 7 8
53 20.4 f 35.7 +: 24.8 f 9.3 2 23.3 f 65.8 f 1.5 + 66.5 +
To1al n (%)d a b
c d
e
ratea by body condition
Bodv condition scoreb 4 6.2 47.5 + 4.5 8.8 74.3 f 3.3 4.4 58.3 f 3.8 9.8 34.1 k 5.6 14.0 68.6 f 5.5 12.2 75.9 f 4.4 6.9 44.5 f 3.5 7.6 79.6 f 2.7
30.9 f 3.4x 222(5.9%)
60.4 + 1.7v 722(19.3%)
25 93.5 f 87.3 2 92.2 f 78.4 f 90.4 f 92.5 2 86.0 f 92.5 +
score within herd
2.1 1.2 2.1 2.7 2.1 2.0 3.1 1.8
89.1 f l.O* 2790(74.7%)
Pregnancy rate (%) + standard error. Body condition score at pregnancy examination. Parity categorization as an estimate of number of offspring. Number of observations in category and percentage of all observations. Herd 2 represents observations over 2 years; na9=511, n =512. Values in rows with different superscripts differ (P c 0.88).
Total 79.7 f 85.9 + 75.2 + 66.2 + 88.0 + 91.5 + 61.9 ” 88.4 +
2.1 1.1 2.0 3.2 1.8 1.4 3.0 1.2
82.4 + 0.6 3734
1148
Theriogenology
Pregnancy rates by Parity 1, 2, 3, 4 to 7 and 28 were 84, 71, 85, 87 and 74%, respectively (Table 4). Parities 2 and ~8 had similar pregnancy rates. Cows in parities 1, 3 and 4-7 had similar pregnancy rates; these were greater (P c 0.05) than cows in parities 2 and ~8. The PR in younger cows (~4 parities) was 80% and was lower (P < 0.05) than that of older cows (24 parities, 85%).
Table 4. Least squares mean pregnancy
Parity’ 1 2 3 4-7 t8
a b
C d
X.Y
53 19.6 -t 21.8 f 22.5 f 47.5 f 37.1 +
8.8 5.1 9.0 4.2 6.5
rate’ by body condition
Body condition scoreb rs 4 53.2 f 3.5 90.3 + 50.0 f 3.1 84.2 f 59.7 + 3.8 89.9 + 71.6 ?I 2.0 92.2 + 67.3 ~tr4.9 89.0 f
1.4 1.6 1.7 1.1 3.4
score within parity
All 84.1 rf: 1.3x 70.8 2 1.v 85.0 f 1.5x 86.7 f 0.9’ 74.1 f 3.2r
n (%)d 806 (22%) 660 (18%) 534 (14%) 1537 (41%) 193 ( 5%)
Pregnancy rate 2 standard error. Body condition score at pregnancy examination. Parity categorization as an estimate of number of offspring. Number of observations in category and percentage of all observations. Values in a column with different superscripts differ (P c 0.05).
Body condition score by parity (Table 4) difference in pregnancy rate was most distinct between Parity 2 and Parties 4 to 7. The parity 2 pregnancy rate was 71% (at BCS 13 the pregnancy rate was 28%, at BCS 4 it was 50%, and at BCS 5 it was 84%). Parities 4 to 7 had an overall pregnancy rate of 87%, (at BCS 13 pregnancy rate was 48%, at BCS 4 it was 72%, and at BCS 5 it was 92%). Cows in Parity <4 and with a BCS 14 had a pregnancy rate of 51%; similar parity cows in BCS 25 had a pregnancy rate of 88% (P < 0.05). Cows in Parity 24 and with a BCS 54 had a pregnancy rate of 66%; those with a BCS ~5 had a pregnancy rate of 93% (P < 0.05).
DISCUSSION The BCS by pregnancy rate demonstrated a consistent and significant pattern across the 8 herds; the pregnancy rate improved with increasing cow body condition score. Body condition scores in this study were assigned at pregnancy examination (some months following calving and the onset of breeding). Other studies have evaluated pregnancy rate relative to BCS at calving and/or at breeding (9,15,17,21,24); results of these studies show a similar positive correlation between pregnancy rates and increasing BCS classification. The body condition of cows is known to change during the course of the year. Florida cattle are usually at their
Ther,iogenology
1149
maximum body condition in the mid to late summer, declining in the fall and winter, and being lowest in late winter and early spring (5). Homogenous type cattle, having common nutritional resources, may maintain a consistent pattern of BCS relative to the herd over time. This relationship of pregnancy rate and BCS measured at calving, breeding and pregnancy examination warrants further study. The body condition score of cattle at pregnancy examination is a useful tool in descr:ibing the pregnancy rate outcome, and more importantly in assessing nutritional management during gestation, in preparation for the subsequent breeding season. In our study, cows with a BCS of 5 or greater at pregnancy examination had an 85% or higher pregnancy rate. Herd 3 had a pregnancy of 75%, but cows with a BCS of ~5 in that same herd had a 92% pregnancy rate; thus, it is likely that cows with the lower body condition scores would respond favorably to improved nutritional management. In groups with a BCS t5 and a pregnancy rate below 90% other factors such as, disease, bull infertility, or genetic factors may contribute to limiting the pregnancy rate. In herd 4, the pregnancy rate was 66%, and cows with a BCS of 5 had a rate of 79%. In this instance, however factors other than nutrition probably lowered the pregnancy rate. Cows in parities 4 to 7 had the highest pregnancy rate. These mature cows are presumed to be the most productive of the herd, since annual selection and culling practices result in a population of healthy, fertile cows having no nutrient demands for growth. The 3 herds with the lowest pregnancy rates (Herds 7, 4 and 3) also had low pregnancy rates for Parities 4 to 7. In Herd 7, low pregnancy rates were seen in all the parity groups, especially for Parties 4 to 7. The diminished reproductive performance in these normally highly productive groups of cattle whomd suggest a need for a herd clinical investigation. Pregnancy rate increases with increasing BCS category in all parity groups, but the effect of a low BCS on the pregnancy rate appears most distinct in young cows. Cows in Parities (1 to 4) and a BCS <4 had a pregnancy rate of 51%, while cows with a similar BCS in Parities ~4 had pregnancy rates of 66% (P < 0.05). Cows in Parity 2 appeared to be the most susceptible to the adverse effects of BCS. First calf heifers (Parity 1) were more likely to conceive again than cows in Parity 2. Tb: decrease in the pregnancy rate of cows in parity 2 was differed (P c 0.05) from that of Parities 1 and 3. Heifers which calve at 24 months of age have a high demand placed on their body reserves for postpartum involution, for continued growth and for lactation. Parturition frequently occurs during the late winter when forage growth is at a minimum and its nutrient content is low. This nutrient demand at a time when forage is deficient in quantity and quality may result in young cows having a prolonged postpartum interval to es&us, delayed conception and, thus, delayed calving. Failure to conceive, however, may not occur until the subsequent breeding season (Parity 2) when the cow gives birth late in the season and a return to estrus
Theriogenology
1150
is further delayed. The interaction of BCS, cow parity, and time interval conception within the breeding season also needs to be investigated.
to
The effect of herd on BCS and pregnancy rate indicates the importance of herd differences in reproductive performance. Although within-herd pregnancy rates consistently increased with increasing BCS category in our study, the range of pregnancy rates within BCS categories were highly variable between herds. This variation in pregnancy rate over BCS categories probably encompasses factors attributable to the herd, including herd change in body condition during the year, cow genotype, bull fertility, local environment, and possible management practices. Characterization of the pregnancy rate by means of parity, body condition score and herd may identify factors which limit production in beef herds. These data also suggest that BCS and parity may serve as useful criteria for allocating cattle into nutritional groups to improve pregnancy rates. Maintenance of body condition especially in young cattle, is critical for the optimization of herd pregnancy rates.
REFERENCES 1. Wiltbank, J.N., Warwick, E.J., Vernon, E.H. and Priode, B.M. Factors affecting net calf crop in beef cattle. J. Anim. Sci. 20:409-414 (1961). 2. Wiltbank, J.N., Rowden, W.W., Ingalls, J.E. and Zimmerman, D.R. Influence of postpartum energy level on reproductive performance of Hereford cows restricted in energy intake prior to calving. J. Anim. Sci. 23:1049-1053 (1964). 3. Bellows, R.A., Short, R.E. and Staigmiller R.B. Research areas in beef cattle reproduction. In: Hawk, H. (ed), Proc. Beltsville Symposium on Animal Reproduction, No 3, Allanheld, Osmun, Montclair, NJ 1978, pp. 3-18. 4. Dziuk, P.J. and Bellows, R.A. Management of reproduction sheep and pigs. J. Anim. Sci. 52 (Suppl 2):355-379 (1983).
of beef cattle,
5. Kunkle, W.E. and Sand, R.S. Effect of Body Condition on Rebreeding. Proc. 39th Ann. Beef Cattle Short Course, Department of Animal Science, University of Florida, Gainesville, Florida, 1990, pp. 154-165. 6. USDA Livestock and Meat Situation. Economic Printing Office, Washington DC, 1988.
Research
7. Williams, G.L. Suckling as a regulator of postpartum review. J. Anim. Sci. 68: 831-852 (1990).
Service, Government
rebreeding
in cattle: a
1151
Tberbgenoiogy
8. Short, R.E., Bellows, R.A., Staigmiller, R.B., Berardinelli, J.G. and Custer, E.E. Physiological mechanisms controlling anestrus and infertility in postpartum beef cattle. J. Anim. Sci. @:799-816 (1990). 9. Randel, R.D. Nutrition 68: 853-862 (1990).
and postpartum
rebreeding
in cattle. J. Anim.
Sci.
10. Rutter, L.M., Randel, R.D. Postpartum nutrient intake and body condition: effect on pituitary function and onset of estrus in beef cattle. J. Anim. Sci. s:265-274 (1984). 11. Nolan, C.J., Bull, R.C., Sasser, R.G., Ruder, CA., Panlasigui, P.M., Schoeneman, H.M. and Reeves, J.J. Postpartum reproduction in protein restricted beef cows: effect on the hypothalamic-pituitary-ovarian axis. J. Anim. Sci. @:3208-3217 (l!,SS). 12. Killen, J.H., Forrest, D.W., Byers, F.M., Schelling, G.T. and Long, C.R. Gonadotropin-releasing hormone-induced luteinizing hormone release in heifers: effect on nutrition during gestation. J. Anim. Sci. 67: 496-500 (1989). 13. Rasby, R.J., Wettemann, R.P., Geisert, R.D., Wagner, J.J. and Lusby, K.S. Influence of pituitary, ovarian, and thyroid function of nonlactating beef cows. J. Anim. Sci. @:2073-2080 (1991). 14. Whitman, R.W., Remmenga, E.E. and Wiltbank, J.N. Weight change, condition and beef cow reproduction. J. Anim. Sci. a:387 abstr. (1975). 15. Herd, D.B. and Sprott, L.R. Body condition, nutrition, cows. Texas Agric. Ext. Serv. B-1526 (1986).
and reproduction
body
of beef
16. Spitzer, J.C. Influences of nutrition on reproduction in beef cattle. In: Morrow, D.A. (ed), Current Therapy in Theriogenology, W. B. Saunders Co., Philadelphia, 1986, pp. 320-341. 17. Richards, M.W., Spitzer, J.C. and Warner, M.B. Effect of varying levels of postpartum nutrition and body condition at calving on subsequent reproductive performance in beef cattle. J. Anim. Sci. @:300-306 (1986). 18. Wagner, J.J., Lusby, K.S., Oltjen, J.W., Rakestraw, J., Wettemann, R.P. and Walters, L.E. Carcass composition in mature Hereford cows: estimation and effect on daily metabolizable energy during winter. J. Anim. Sci. &:603-612 (I 988). 19. D’unn, T.G. and Kaltenbach, C.C. Nutrition and the postpartum ewe, sow and cow. J. Anim. Sci. 51 (Suppl 2):29-39 (1980).
interval of the
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y
20. Rakestraw,
J., Lusby, K.S., Wettemann, R.P. and Wagner, J.J. Postpartum weight and body condition loss and performance of fall-calving cows. Theriogenology @461-473 (1986).
21. Selk, G.E., Wettemann, R.P., Lusby, K.S., Oltjen, J.W., Mobley, S.L., Rasby, R.J. and Garmendia, J.C. Relationship among weight change, body condition and reproductive performance of range beef cows. J. Anim. Sci. 66: 3153-3159 (1988). 22. Mortimer, R.G., Boyd, G.W. and Morris, D.L. Evaluating the impact of body condition on production parameters in beef cows. Vet. Med. &5:1030-1036 (1991). 23. SAS. User’s Guide: Statistics. SAS Institute
Inc., Cary, NC, 1985.
24. Ku&e, W.E., Sand, R.S. and Rae, D.O. Effect of Cow Age and Condition on Nutrient Requirements and Management. Proc 40th Annual Beef Cattle Short Course, Department of Animal Science, University of Florida, 1991, pp.124-132.
39: 1143-I
152,1993
RELATIONSHIP OF PARITY AND BODY CONDITION SCORE TO PREGNANCY RATES IN FLORIDA BEEF CATTLE D.O. Rae,’ W.E. Kunkle,’
P.J. Chenoweth,’
R.S. Sand2 and T. Tran’
‘Department of Large Animal Clinical Sciences College of Veterinary Medicine University of Florida PO Box 100136 Gainesville, FL 32610-0136 2Department of Animal Science Institute of Food and Agricultural Sciences University of Florida Gainesville, Florida Received
for publication: Accepted:
June 16, 1992 Febmary 4, 1993
ABSTRACT Pregnancy rates, determined by per rectum palpation, were analyzed with respect to cow parity (range 1 to >8 calvings) and body condition score (BCS, l=thin to 9=fat) at pregnancy examination for 3734 beef cattle females on 3 commercial beef operations (8 herds) in 3 Florida counties in 1989 and 1990. The mean:s and standard deviations for the herds were the following: pregnancy rate, 81.3 :c 39% (range 62.1 to 91.5%); BCS, 4.7 -+ 0.6 (range 4.3 to 4.9); and parity, 3.9 2 2.3 (range 2.8 to 4.8). Significant associations were found between pregnancy rate, parity, BCS and herd (P < 0.001); and between the variable interactions, parity with BCS, herd with BCS, and herd with parity (P < 0.001). Cows with a BCS ~54had a pregnancy rate of 59%; those with a BCS 25 had a pregnancy rate of 90’%. Cows having a parity of <4 had a PR of 80%, while cows having a parity 14 had a PR of 85%. The interaction of parity with BCS was significant, resulting in pregnancy rates as follows; parity <4 and BCS I 4 was 51%; parity c 4 and BCS ;> 5 was 88%; parity 14 and BCS < 4 was 66%; and parity 25 and BCS 2 5 was 93%. Body condition, parity, and the interaction of body condition and parity play important roles in the reproductive performance of commercial beef cows in Florida. Key words:
beef cattle, body condition,
Acknowledgments This study is Florida Agricultural
parity, pregnancy
Experiment
Copyright Q 1993 Butterworth-Heinemann
rate, reproduction
Station Journal Series #R-02465.
1144
Theriogenoiog
y
INTRODUCTION Optimal calf production is dependent on high reproductive efficiency in beef cattle (l-4). Since weaned calf estimates are only approximately 70% nationally (5 7), the need for increasing this number is evident. While non reproductive components such as disease and injury may contribute to a reduced number of calves, the primary cause is the failure of cows to become pregnant (3). Factors which have been identified that can influence failure to become pregnant include those nutrition and parity (8). Inadequate nutrient intake, namely energy and/or protein, lowers the pregnancy rate and reduces the first service conception rate by prolonging the interval from calving to the first postpartum estrus (9). Protein and energy deficiencies appear to affect both hypothalamic and pituitary functions, altering hormonal release and producing a less fertile ovarian environment than is found in cattle that are maintained at adequate nutritional levels (9-13). The nutritional state of the cow can be appraised by scoring the body condition (14-17). The body condition score (BCS) is a subjective measure of nutrient reserves (9); it is a simple, functional indicator closely associated with the body composition of mature slaughtered cows (18). As with nutritional studies, female body condition has been related to certain reproductive parameters such as the postpartum return to estrus, services per conception, pregnancy rate, and calving interval (1,2,5,16,19,20). It has been shown that cows that maintained optimal body condition after parturition, regardless of the calculated nutrient requirements, had enhanced pituitary function and reproductive performance compared with cows that lost body condition (10). In addition, the subsequent conception rate was reduced when cows calved in good body condition and then lost weight prior to the breeding season (20). Characterization of groups of animals prone to suboptimal reproductive performance within the herd would allow for the implementation of corrective management strategies. Previous research has evaluated the relationship of BCS at calving and at breeding to the pregnancy rate (9,17,21), but research examining the relationship of BCS at pregnancy examination to the pregnancy rate is limited (22). Thus, the objective of this study was to examine the relationship between parity (number of calvings), BCS at pregnancy examination and the pregnancy rate in commercial beef herds in Florida.
MATERIALS
AND METHODS
Data were collected over a 2 year period from 8 commercial beef herds in Florida. Data at a south-central Florida ranch were collected on 4 herds in 1989 (Herds 1,2,3, and 4) and on 3 herds in 1990 (Herds 2,5, and 6). Herd 2 was
Therisogenology
1145
included in both years; data for each year for Herd 2 were pooled to estimate variables. Data for Herds 7 and 8 were collected in 1990 on ranches located in north-central Florida. Although breed composition in all the herds was diverse, all 4114 cows in the study were indigenous crossbred cattle with from one-eighth to one-half Brahman breeding. Bteeding management regimens varied at the various ranches with regard to the length of the breeding season, time of year, and bull-to-cow ratio. Herds 1 through 6 had a 150-day breeding season (January 1 to May 31) and a 1:20 bull-to-cow ratio. Herd 7 had a 120-day breeding season (April 15 to August 15) and a 1:60 bull-to-cow ratio. Herd 8 had a 120-day breeding season (April 1 to August 1) and a 1:25 bull-to-cow ratio. Heifers from Herds 1 through 6 were bred to first calve at 36 months of age; heifers in Herds 7 and 8 were bred to calve first at 24 months of age.. There was no control for year, herd management (nutrition, health, bull management), and environmental factors (climatic conditions). Examination for pregnancy diagnosis was performed at 60 to 100 days, following bull removal, by 1 of 3 experienced technicians. At examination, the following information was collected for each cow: year born, body condition score and pregnancy status. Year brands provided year of birth for calculation of age and subsequently parity. A 1 to 9 body condition score (14-17), was determined visually by practiced evaluators. Of the original 4114 animal records, 380 were excluded from the study because of incomplete data (n=165), unscheduled pregnancies (n=3), and limited parity 0 representation (n=212; only in 2 of the 8 herds), leaving 3734 records for analysis. Because of herd differences relative to age at first exposure to a bull, an estimate of parity was employed to facilitate comparison among herds. Parity of individual animals was calculated by subtracting age of the cow at the first exposure to a bull (for the herd) from age of the cow at the time of pregnancy examination; thus, a 3-year-old cow, which was first exposed to a bull at age 1, was classified as Parity 2; a 3-year-old cow which was first exposed to a bull at age 2 was classified as Parity 1. Several variable categories (ie. BCS<3, BCS>6, Parity=O) did not have sufficient numbers of observations for evaluation. For this reason BCS and parity Body condition scores of 53, 4, and >5 were variable categories were grouped. Parities of 1, 2, 3, 4 to 7 (mature cows), and 28 (old cows) were utilized. employed; heifers were not evaluated due to an inadequate sample size. Data were analyzed by Analysis of Variance using the General Linear Model function (SAS; 23). Mean separation of data was established by least squares means analysis. The statistical model included parity, BCS, herd, parity by BCS interaction, herd by BCS interaction, and herd by parity interaction. The herd was evaluated as an important but nonspecific variable.
Theriogenology
1146
RESULTS Descriptive statistics by herd (Table 1) show herd size (range 216 to 665, averaging 415 animals per herd). Mean pregnancy rate and standard deviation for the study herds was 81.3 + 39% (range 62.1 to 91.5%); the mean BCS was 4.7 + 0.6 (averages range from 4.3 to 4.9); and the mean parity was 3.9 f 2.3 calves (averages range from 2.8 to 4.8). Herds with below average BCS (Herds 3 and 7) and one below average parity (Herd 4) had lower herd pregnancy rates (75.2, 62.1, and 66.2%, respectively) than the other herds.
Table 1. Summary Herd 1 2e 3 4 5 6 7 8
a b c d e
of the study herds
na 364 1022 452 216 341 412 262 665
BCSb 4.6 2 0.6 4.9 2 0.4 4.4 + 0.8 4.7 ” 0.6 4.9 + 0.4 4.8 + 0.5 4.3 -+ 0.7 4.6 + 0.6
Paritvc 3.7 k 2.5 3.7 + 2.3 4.8 + 2.5 2.8 k 2.2 4.3 z!z 1.8 4.7 -c 1.8 4.0 * 2.0 3.3 -c 2.2
PRd 79.7 + 40 85.9 + 35 75.2 2 43 66.2 k 47 88.0 ” 33 91.5 + 28 62.1 + 49 88.3 + 32
3734 Total Herd average 415
4.7 ” 0.6
3.9 r 2.3
81.3 + 39
Number of observations per herd. Body condition score at pregnancy examination + standard deviation Mean parity of the herd + SD. Pregnancy rate (%) determined by per rectum examination f SD. Herd 2 represents observations over 2 years; n,,=511, n,,=512.
(SD).
Statistical evaluation using Analysis of Variance was used to prove all independent variables and their interactions to be significant (P < 0.001; Table 2). The model described 26% of the variability in the pregnancy rate (PR) and was represented as follows:
PR = BCS + parity + herd + BCS*parity
+ BCS*herd
+ parity*herd
+ error.
Theriogenology
1147
Table 2. Analysis of variance msendent PRa
Variable
Source B(35 Parity+ He:rdd BCS x Parity= BCS x Herde Parity x Herde Error a b c d e
for pregnancy R-Square 0.259
df 2 4 7 8 14 26 3729
rate (PR) by independent
variables
C.V. 40.05
Root MSE 0.330
PR 0.824
F Value 192.53 9.32 6.67 4.09 7.30 3.58
P>F
Type III Sum of Sauares 41.98 4.06 5.09 3.57 11.14 10.16 539.98
0.0001 0.0001 0.0001 O.oool 0.0001 0.0001
Pregnancy rate. Body condition score at pregnancy examination; 53, 4, 25. Parity category; 1, 2, 3, 4-7, 28. Herdslto8. Interaction of variables; BCS, parity, and herd.
Groups of cows having body condition scores OE ~3, 4 and ~5 had pregnancy rates of 31, 60 and 89% respectively (P
Table 3. Least squares mean pregnancy
Herd 1 2e 3 4 5 6 7 8
53 20.4 f 35.7 +: 24.8 f 9.3 2 23.3 f 65.8 f 1.5 + 66.5 +
To1al n (%)d a b
c d
e
ratea by body condition
Bodv condition scoreb 4 6.2 47.5 + 4.5 8.8 74.3 f 3.3 4.4 58.3 f 3.8 9.8 34.1 k 5.6 14.0 68.6 f 5.5 12.2 75.9 f 4.4 6.9 44.5 f 3.5 7.6 79.6 f 2.7
30.9 f 3.4x 222(5.9%)
60.4 + 1.7v 722(19.3%)
25 93.5 f 87.3 2 92.2 f 78.4 f 90.4 f 92.5 2 86.0 f 92.5 +
score within herd
2.1 1.2 2.1 2.7 2.1 2.0 3.1 1.8
89.1 f l.O* 2790(74.7%)
Pregnancy rate (%) + standard error. Body condition score at pregnancy examination. Parity categorization as an estimate of number of offspring. Number of observations in category and percentage of all observations. Herd 2 represents observations over 2 years; na9=511, n =512. Values in rows with different superscripts differ (P c 0.88).
Total 79.7 f 85.9 + 75.2 + 66.2 + 88.0 + 91.5 + 61.9 ” 88.4 +
2.1 1.1 2.0 3.2 1.8 1.4 3.0 1.2
82.4 + 0.6 3734
1148
Theriogenology
Pregnancy rates by Parity 1, 2, 3, 4 to 7 and 28 were 84, 71, 85, 87 and 74%, respectively (Table 4). Parities 2 and ~8 had similar pregnancy rates. Cows in parities 1, 3 and 4-7 had similar pregnancy rates; these were greater (P c 0.05) than cows in parities 2 and ~8. The PR in younger cows (~4 parities) was 80% and was lower (P < 0.05) than that of older cows (24 parities, 85%).
Table 4. Least squares mean pregnancy
Parity’ 1 2 3 4-7 t8
a b
C d
X.Y
53 19.6 -t 21.8 f 22.5 f 47.5 f 37.1 +
8.8 5.1 9.0 4.2 6.5
rate’ by body condition
Body condition scoreb rs 4 53.2 f 3.5 90.3 + 50.0 f 3.1 84.2 f 59.7 + 3.8 89.9 + 71.6 ?I 2.0 92.2 + 67.3 ~tr4.9 89.0 f
1.4 1.6 1.7 1.1 3.4
score within parity
All 84.1 rf: 1.3x 70.8 2 1.v 85.0 f 1.5x 86.7 f 0.9’ 74.1 f 3.2r
n (%)d 806 (22%) 660 (18%) 534 (14%) 1537 (41%) 193 ( 5%)
Pregnancy rate 2 standard error. Body condition score at pregnancy examination. Parity categorization as an estimate of number of offspring. Number of observations in category and percentage of all observations. Values in a column with different superscripts differ (P c 0.05).
Body condition score by parity (Table 4) difference in pregnancy rate was most distinct between Parity 2 and Parties 4 to 7. The parity 2 pregnancy rate was 71% (at BCS 13 the pregnancy rate was 28%, at BCS 4 it was 50%, and at BCS 5 it was 84%). Parities 4 to 7 had an overall pregnancy rate of 87%, (at BCS 13 pregnancy rate was 48%, at BCS 4 it was 72%, and at BCS 5 it was 92%). Cows in Parity <4 and with a BCS 14 had a pregnancy rate of 51%; similar parity cows in BCS 25 had a pregnancy rate of 88% (P < 0.05). Cows in Parity 24 and with a BCS 54 had a pregnancy rate of 66%; those with a BCS ~5 had a pregnancy rate of 93% (P < 0.05).
DISCUSSION The BCS by pregnancy rate demonstrated a consistent and significant pattern across the 8 herds; the pregnancy rate improved with increasing cow body condition score. Body condition scores in this study were assigned at pregnancy examination (some months following calving and the onset of breeding). Other studies have evaluated pregnancy rate relative to BCS at calving and/or at breeding (9,15,17,21,24); results of these studies show a similar positive correlation between pregnancy rates and increasing BCS classification. The body condition of cows is known to change during the course of the year. Florida cattle are usually at their
Ther,iogenology
1149
maximum body condition in the mid to late summer, declining in the fall and winter, and being lowest in late winter and early spring (5). Homogenous type cattle, having common nutritional resources, may maintain a consistent pattern of BCS relative to the herd over time. This relationship of pregnancy rate and BCS measured at calving, breeding and pregnancy examination warrants further study. The body condition score of cattle at pregnancy examination is a useful tool in descr:ibing the pregnancy rate outcome, and more importantly in assessing nutritional management during gestation, in preparation for the subsequent breeding season. In our study, cows with a BCS of 5 or greater at pregnancy examination had an 85% or higher pregnancy rate. Herd 3 had a pregnancy of 75%, but cows with a BCS of ~5 in that same herd had a 92% pregnancy rate; thus, it is likely that cows with the lower body condition scores would respond favorably to improved nutritional management. In groups with a BCS t5 and a pregnancy rate below 90% other factors such as, disease, bull infertility, or genetic factors may contribute to limiting the pregnancy rate. In herd 4, the pregnancy rate was 66%, and cows with a BCS of 5 had a rate of 79%. In this instance, however factors other than nutrition probably lowered the pregnancy rate. Cows in parities 4 to 7 had the highest pregnancy rate. These mature cows are presumed to be the most productive of the herd, since annual selection and culling practices result in a population of healthy, fertile cows having no nutrient demands for growth. The 3 herds with the lowest pregnancy rates (Herds 7, 4 and 3) also had low pregnancy rates for Parities 4 to 7. In Herd 7, low pregnancy rates were seen in all the parity groups, especially for Parties 4 to 7. The diminished reproductive performance in these normally highly productive groups of cattle whomd suggest a need for a herd clinical investigation. Pregnancy rate increases with increasing BCS category in all parity groups, but the effect of a low BCS on the pregnancy rate appears most distinct in young cows. Cows in Parities (1 to 4) and a BCS <4 had a pregnancy rate of 51%, while cows with a similar BCS in Parities ~4 had pregnancy rates of 66% (P < 0.05). Cows in Parity 2 appeared to be the most susceptible to the adverse effects of BCS. First calf heifers (Parity 1) were more likely to conceive again than cows in Parity 2. Tb: decrease in the pregnancy rate of cows in parity 2 was differed (P c 0.05) from that of Parities 1 and 3. Heifers which calve at 24 months of age have a high demand placed on their body reserves for postpartum involution, for continued growth and for lactation. Parturition frequently occurs during the late winter when forage growth is at a minimum and its nutrient content is low. This nutrient demand at a time when forage is deficient in quantity and quality may result in young cows having a prolonged postpartum interval to es&us, delayed conception and, thus, delayed calving. Failure to conceive, however, may not occur until the subsequent breeding season (Parity 2) when the cow gives birth late in the season and a return to estrus
Theriogenology
1150
is further delayed. The interaction of BCS, cow parity, and time interval conception within the breeding season also needs to be investigated.
to
The effect of herd on BCS and pregnancy rate indicates the importance of herd differences in reproductive performance. Although within-herd pregnancy rates consistently increased with increasing BCS category in our study, the range of pregnancy rates within BCS categories were highly variable between herds. This variation in pregnancy rate over BCS categories probably encompasses factors attributable to the herd, including herd change in body condition during the year, cow genotype, bull fertility, local environment, and possible management practices. Characterization of the pregnancy rate by means of parity, body condition score and herd may identify factors which limit production in beef herds. These data also suggest that BCS and parity may serve as useful criteria for allocating cattle into nutritional groups to improve pregnancy rates. Maintenance of body condition especially in young cattle, is critical for the optimization of herd pregnancy rates.
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