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Relationships Between Sire Evaluations at Different Herdmate Levels
Relationships Between Sire Evaluations at Different Herdmate Levels B. T. McDANIEL and E. L. CORLEY
Animal Husbandry Research Division, USDA, Beltsville, Maryland between sire evaluations at different herdmate levels have been high, indicating that progeny groups tend to rank similarly under different herd environments. Robertson et al. (15) divided the progeny of 57 Holstein sires used in A I in England into low, medium, and high levels, depending on the milk yield of their herdmates. Genetic correlations ranged from 0.87 to 0.96 among sire progeny groups at the three levels. VanVleck (18) estimated the genetic ~orre~ations between half-sister sets for all possible pairs of four different management levels for both milk and fat yields. All correlations were high and ranged from 0.93 between tile lowest level and the highest level, to 1.0 for other pairs of levels. Although these studies were conducted with relatively small numbers of daughters per sire, all indicated that A I sires would have similar rankings, regardless of the production level of the herds in which their progeny were located. Indirect evidence that daughters of sires perform similarly in different levels of production has been presented in the form of very small sire-by-herd interactions (3, 5, 9, 11, 14, 19, 20). Such estimates have ranged from zero to about four per cent of the total variance, and suggest that shifts in ranking of sires from herd to herd are of small consequence. Additional indirect evidence has been presented by Lytton and Legates (12), who found high correlations between sets of paternal halfsisters, where one group was located in the Southern United States and the other in the northern states. Contrary evidence has been presented by Bereskin and Lush (4), which indicated that summaries on bulls in high level herds might not be very indicative of their performance lO%. in low level herds. The present study was undertaken to ascertain Since the development of artificial insemina- and demonstrate the relationships between sire tion (AI), concern has been expressed that the evaluations at widely differing herdmate levels progeny of bulls will not rank in the same for bulls used extensively in AI, and to deterorder over a wide range of herd environmental mine the effect of varying herdinate milk yields conditions. This concern has been reinforced on current United States Department of Agriby the practice of evaluating AI bulls by av- culture (USDA) sire evaluation procedures. eraging all of their AI progeny, over all levels of herdmate production. Data I n recent studies (13, 15, 18) correlations The data consisted of the milk yields of firstlactation A I progeny of 40 Holstein bulls and Received for pub]ication November 2, 1966. 735 Abstract
Relationships between independent measures of a bull's breeding value at different levels of herd production were investigated. The data consisted of the 2 times, 305-day, mature equivalent (ME) first lactation records of the artificially inseminated (AI) progeny of 40 Holstein sires. Each bull had 1,000 or more daughters. Progeny were classified into one of four groups, based on milk yield level of herdmates (I ----4,536-5,442 kg; I I ----5,443-6,349 kg; I I I = 6,350-7,256 kg; and IV = 7,2578,164 kg). Daughter averages rose with increases in herdmate level, while the magnitude of the Predicted Difference measure of a sire's breeding value decreased 289 kg (103, 47, --39, and --186 kg, respectively) from low (I) to high ( I ¥ ) herdmate levels. Correlations among sire progeny averages at the different herdmate levels were all very high (0.88 to 0.96) and indicated that bulls ranked in about the same order at all levels. Regressions computed in the same manner indicated the absence of a one-for-one relationship in the magnitude of measures of breeding value at the different herdmate levels. The Predicted Difference measure of a sh'e's breeding value only partially accounted for variation in herdmate milk yields among sires. I t was an effective criterion for ranking bulls evaluated within the same herd levels, but somewhat less effective in establishing absolute breeding merit. The maximum bias in predicted differences of bulls with very high yielding herdmates (6,800 kg of nfilk or nmre) was about 5 to
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the unregressed averages of their herdmates. F i r s t lactations were defined as the first available record of cows which calved at an age of 35 months or less. Other qualifications for record use were that the progeny must have calved between J a n u a r y , 1959, and May, :1_964, with either complete or incomplete lactations of 240 days or more on twice-a-day milking. Incomplete records of both daughters and herdmates were projected to a 305-day basis, and all records adjusted to a mature equivalent basis with standard D a i r y H e r d I m p r o v e m e n t Association ( D H I A ) factors• t t e r d m a t e s were defined as all other Holstein cows calving in the same five-month herd-year-season as the daughter. Incomplete records of all lengths were included in the herdmate averages. 0 n l y progeny that had five or more herdmates were used. Each of the 40 bulls selected had been summarized by U S D A p r i o r to May, 1965, with at least 1,000 A I progeny. All sires had been placed in A I service a f t e r J a n u a r y , 1956.
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The progeny were grouped by herdmate milk production level in intervals of 453.6 kg and starting at 2,724 kg. Since vesT few cows had herdmates averaging less than 4,082 kg or more than 8,164 kg, all analyses and comparisons were made within these levels. Progeny with herdmate levels outside this range were not used. Each of the 40 bulls had progeny at all of the herdmate levels analyzed. Variables studied were daughter averages, daughter-hcrdmate differences, and Predicted Differences ( P D ) for milk yield. Predicted Differences were computed as follows: P D -where
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t~---- breed average (5,924 kg) m =- number of daughters at the i TM herdmate level D~ = d a u g h t e r average at the i ~h herdmate level H M ~ = h e r d m a t e average at the i th herdmate level.
Both standard product-moment and rank correlations were computed between the sire evaluations at the different herdmate levels for Predicted Differences. Regressions were computed by standard variance-covariance procedures. ~D
~g J . D A I R Y SCIEN-0E ~¢'OL. 5 0 , NO. 5
Results and Discussion
The unweighted averages of sire-progeny group means for all variables and levels of
SIRE EVALUATIONS
737
TABLE 2 Averages and standard deviations for first lactation milk yields of the progeny of forty Holstein bulls at four different herdmate levels
Herdmate level" Low Medlmn low Medium high High
No. of progeny
No. of herdmates
Daughter averages
Avg ~
Range ~
Avg
281 708 605 170
53- 667 198-2,440 199-2,490 32- 727
5,296 5,974 6,616 7,174
(~gJ
s
Avg
range
127 129 148 171
19 22 21 19
9-31 13-34 12-40 9-64
Deviation from herdmates Avg
(~g)
193 48 --124 --394
s 126 129 143 166
Predicted Difference Avg
(~g)
103 47 -- 39 --186
s 117 125 137 137
Low = 4,536-5,442 kg; mediunl low = 5,443-6,349 kg; medium high = 6,350-7,256 kg; high = 7,2578,164 kg. b Each of the 40 bulls was represented and weighted equally in each average. ¢ ]~ange in values for individual progeny groups. h e r d m a t e s are shown in T a b l e 1. Overall daught e r averages, which were based on the m e a n s of the 40 p r o g e n y g r o u p s a t each level, increased directly with increases in h e r d m a t e yields. These changes i n d a u g h t e r averages r e i t e r a t e the well-known f a c t t h a t a bull's d a u g h t e r a v e r a g e is largely d e p e n d e n t o n t h e p r o d u c t i o n level o f the h e r d s i n which his p r o g e n y are milked. H e r d m a t e differences decreased consistently as the h e r d m a t e level increased, i l l u s t r a t i n g t h a t the regression of a cow's p r o d u c t i o n on t h a t of h e r h e r d m a t e s is n o t 1.0. Decreases in t h e P D , which assumes t h a t t h e regression of genetic differences o n h e r d p r o d u c t i o n level is 0.10, were n o t as p r o n o u n c e d . These results demons t r a t e t h a t the U S D A P r e d i c t e d Difference is somewhat effective in a c c o u n t i n g f o r v a r i a t i o n in h e r d m a t e levels of milk yield. Because of t h e relatively small n u m b e r of
observations a v a i l a b l e in t h e i n d i v i d u a l 454-kg levels f o r m a n y bulls, wider i n t e r v a l s of 907 k g w i t h r a n g e s of 4,536 to 8,164 kg of milk were computed. U n w e i g h t e d a v e r a g e s o f the 40-sire p r o g e n y g r o u p m e a n s in each of these levels are shown in Table 2. A s i n T a b l e 1, d a u g h t e r averages increased steadily as h e r d m a t e p r o duction r o s e ; a n d conversely, t h e d a u g h t e r h e r d m a t e deviations decreased. A l t h o u g h t h e p r o g e n y of these bulls were, on the average, 193 k g s u p e r i o r to t h e i r lower-yielding h e r d m a t e s (4,536-5,442 k g ) , they were 394 kg inf e r i o r to t h e i r h i g h e s t level stablemates (7,2578,164 k g ) . This c h a n g e clearly illustrates a n d verifies the need f o r a n a d j u s t m e n t f o r level of h e r d m a t e s w h e n bulls a r e c o m p a r e d over a wide r a n g e of e n v i r o n m e n t M conditions. T h e s t a n d a r d deviations i n Table 2 show t h a t the v a r i a t i o n a m o n g the p r o g e n y a v e r a g e s o f the 40 bulls increased as the p r o d u c t i o n level
TABLE 3 Correlations between forty Holstein paternal half-sister groups a t four herdmate levels Herdmate level Herdmate level Low
Medium low
Medium hlgh
Measure of sire's merit Daughter average Daughter-HM difference Predicted Difference Product-moment correlation l~ank correlation Daughter average Daughter-HM difference Predicted Difference Product-moment correlation Rank correlation Daughter average Daughter-HM difference Predicted Difference Product-moment correlation R,ank correlation
Medium low ~
Medium high ~
High
.92 .93
.93 .93
.89 .88
.93 .93
.93 .94 .95 .96
.88 .89 .92 .92
.96 .94
.91 .93 .94 .94 .93 .93
Medium low = 5,443-6,349 kg; medium high = 6,350-7,256 kg. if. DAIRY SCIE~CCE VOId. 50, NO. 5
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of the herdmates of their progeny increased. The average number of records in the sire groups varied between levels and could have affected the standard deviations. However, calculations showed that adjusting the standard deviations for the varying amount of within-sire variation (2_ o ) / ~ did not change the rank or relative amount of increase in the standard deviations as herdmate levels increased. I n other words, these results suggest that a bull's daughters are more likely to deviate markedly from their herdmates when the herchnates are producing at high levels (i.e., variation among progeny groups is greater). Similar findings have been reported previously by numerous investigators (6, 10, 12, 15, ]8). One of the most important questions about sire evaluations in different herd management levels is, Do bulls rank the same way ill all levels? To obtain evidence on this matter, correlations were computed among the sire progeny group means paired in all combinations of the four herdmate levels. Three different measures of the sire's merit--the simple daughter average, the unadjusted daughter-herdmate difference, and the Predicted Difference--were used. Correlations among the progeny group means, shown in Table 3, ranged from 0.88 to 0.96 between herdmate levels. Relationships between adjacent levels were generally highest, and values decreased as the difference in herdmate levels increased. Correlations for all of the measures of breeding merit used were essentially identical. Correlations in Table 3 are similar to those reported by other investigators (6, 13, 15, 18), but based on a much larger sample of daughters for individual bulls, and represent all areas of the United States. The magnitude of the correlations suggests that bulls will rank almost identically from level to level, a conclusion supported by the rank col-relations in Table 3. Also, the obselwed correlations should be lower than the true genetic correlations, since a portion of the within-sire variation is present in the variances among progeny group means. Evaluations on nine individual bulls were selected to illustrate the correlations among sire evaluations at the different herdmate levels. Bulls were ranked from 1 to 40 on their PD at the medium low herdmate level (5,443-6,349 kg), which encompasses the breed average, and their respective ranks at the other levels determined. Summaries on the three most superior bulls (Ranks 1, 2, and 3), the intermediate three (Ranks 19, 20, and 21), and the three most inferior bulls (Ranks 38, 39, and
SIRE
40) are shown individually in Table 4. I n all cases the three superior bulls ranked among the top five bulls at all levels, and the most inferior three were always in the bottom five. I n 10 of the 12 situations, the intermediate bulls ranked very near the middle. I-Iowever, in the two cases where bulls shifted their rankings substantially, absolute changes in PD were very small (26-1.59 kg). Table 4 also shows how the use of the unadjusted daughter average without any knowledge of corresponding herd production levels can be very misleading when evaluating bulls. For example, the top bull's daughter average (A) in the low herdmate group is only 5,643 kg; whereas, the poorest bull's daughter averages in the medium high and high herdmate level groups are 5,791 and 6,235 kg, respectively. From this comparison Bull I would appear the better bull, yet within the four herdmate levels his daughters consistently averaged more than :[,000 kg below that of Bull A's progeny. As might be expected from results of previous investigations (15, 18), correlations between summaries at the two extreme production levels were the lowest (Table 3). The average daughter-herdmate deviations at these two levels are shown for each of the 40 bulls in Figure 1. I t is apparent from this graph that only a few progeny groups deviated from the overall pattern. Some deviations due strictly to chance might be expected, because of the variation between bulls in the number of progeny available at these two levels.
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EVALUATIONS
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HIGH LEVEL HERDS
FIo. 1. ]Relationship between Predicted Differences for milk yield (kilograms × 10-:) in high(7,257-8,164 kg) and low- (4,536-5,442 kg) level herds.
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Fro. 2. Relationships between Predicted Differences for milk yield (kilograms × 10-1) in average(5,443-6,349 kg) and superior- (6,350-7,256 kg) level herds. The high repeatability of sire summaries from breed average herds to those about 1,000 kg higher is illustrated clearly in Figure 2. Deviations h'om the over-all regression line were very small. Regressions of daughter-herdmate deviations at one level on another level of herd production are shown in Table 5. They demonstrate an absence of a one-for-one correspondence in the absolute magnitude of measures of a sire's merit over a wide range of production levels, even though relative rankings are similar (Table 3). Results with Predicted Differences (Table 5) differ substantially from 1.00, and suggest that this measure does not completely account for variation in herdmate levels. However, regressions of PD were generally closer to 1.00 than those for the unadjusted daughterherdmate differences. Regressions for Predicted Difference indicate that the magnitude of this measure of a sire's breeding value can fluctuate 5 to 10% among different herdmate levels. I t h a s been well known that the regression of cows on their herdmates is less than 1.0 (1, 2, 7, 8, 14, 16, 17), and that some differences in the magnitude of a site's unregressed summaries at varying levels of herd production are to be expected. Generally, estimates of the regression have been near 0.9 (2, 7, 14, 17), which states that a bull's daughter-herdmate deviation should drop 100 leg for each 1,000 kg increase in herdmate levels. I n this study the drop was greater, 3-. DAIRY SCI]~TCE ~fOL. 50, NO. 5
McDANIEL
740
AND C O R L E Y
TABLE 5 Regressions between forty Holstein paternM h~f-sister groups at four herdmate levels Regressions Herdmate levels a 1
2
Low
Medium low
Low
Medium high
Low
Nigh
Medium low
Medium high
Medium low
High
Medium high
Nigh
Measure of slre's merit
1 on 2
2 on 1
Daughter-HM difference Predicted Difference Daughter-HM difference Predicted Difference Daughter-HM difference Predicted Difference Daughter-l=[M difference Predicted Difference Da,ughter-HM difference Predicted Difference Daughter-HM difference Predicted Difference
.90±.06 b .87±.06 .81--+.05 .79-+.05 .67-+.06 .75-+.07 .86-+.04 .87-+.04 .71+.05 .83-+.06 .81~.05 .93-+.06
.95+---.06 b 1.00±.06 1.06-+.07 1.09-+.07 1.17-+.10 1.03-+.09 1.06-+.05 1.05±.05 1.18-+.08 1.00-+.07 1.09+.06 .93-+.06
a Low = 4,536-5,442 kg; medium low = 5,443-6,349 kg ; medium high = 6,350-7,256 kg; high = 7,257-8,164 kg. b Standard errors. since t h e d a u g h t e r deviations a d j u s t e d by the 0.9 f a c t o r were 103, 47, --39, a n d - - 1 8 6 kg, respectively. One possible source of the discrepancs~ m i g h t be t h a t t h e r e g r e s s i o n of 0.9 is n o t completely a p p l i c a b l e to the regression of first-lactation cows on t h e i r h e r d m a t e s of all ages. S u p p o r t f o r this h y p o t h e s i s is f o u n d in two i n v e s t i g a t i o n s (1, 8) w h e r e regressions of first-lactation cows on t h e i r h e r d m a t e s of all ages were a p p r e c i a b l y less t h a n 0.9. The results suggest t h a t no serious e r r o r s will occur i f bulls a r e r a n k e d according to t h e i r P r e d i c t e d Difference a n d t h e i r h e r d m a t e averages are w i t h i n 1,000 kg of each other. Also, the P r e d i c t e d Differences of bulls used exelusively in extremely h i g h h e r d levels will be slightly u n d e r e s t i m a t e d . I t should be n o t e d t h a t the d a u g h t e r a v e r a g e s used in this s t u d y were based entirely o n firstlactation cows, while cows of all ages were included in the h e r d m a t e averages. F a i l u r e o f the P r e d i c t e d Differences to completely a c c o u n t f o r the v a r i a t i o n in h e r d m a t e levels is p r o b a b l y associated w i t h this circumstance. I n a c c u r a c i e s in age-correction f a c t o r s m i g h t also c o n t r i b u t e to t h e discrepancy. I n general, conclusions o£ this s t u d y are t h a t : (a) Artificially i n s e m i n a t e d sire p r o g e n y g r o u p s will r a n k in a b o u t the same order, regardless of the h e r d p r o d u c tion level at which they are evaluated. (b) Efforts to r a n k A I bulls on t h e i r d a u g h t e r averages r a t h e r t h a n deviations f r o m h e r d m a t e s m a y lead to serious errors. (e) The U S D A P r e d i c t e d Difference only p a r t i a l l y accounts f o r differences in h e r d m a t e p r o d u c t i o n level, b u t t h e abJ. DAIRY SCIENCE YOL. 50, NO. 5
solute values o£ the e r r o r s are n o t very large, a n d especially where h e r d m a t e a v e r a g e s do n o t v a r y over 1~000 k g f r o m b r e e d average. References
(1) Allaire, F. R., and Gaunt, S. N. 1965. First-Lactation Contemporary Comparisons as Indicators of Enviromnental Influences on Daughter Records Used for Sire Evaluation. J. Dairy Sci., 48: 454. (2) Bereskin, B., and Freeman, A. E. 1965. Genetic aa~d Environmental Factors in Dairy Sire Evaluation. H. Uses and Limitations of Deviation Records and the Role of Dams. J. Dairy Sci., 48: 352. (3) Bereskin, B., Freeman, A. E., and Lush, J. L. 1962. Sources of Variation in D H I A Records Related to Proving A.I. Sires. J. Dairy Sci., 45: 677. (4) Bereskin, B., and Lush, J. L. 1965. Genetic and Environmental Factors in Dairy Sire Evaluation. I I I . Influence of Environmental and Other Extraneous Correlations Among the Daughters. J. Dairy Sei., 48: 356. (5) Burdick, J. M., and McGilliard, L. D. 1963. Interaction Between Sires in Artificial Insemination and Management of Dairy Nerds. J. Dairy Sci., 46: 452. (6) Burnside, E. B., and Rennie, J. C. 1961. The Heritability of Milk Yield at Different Levels of Production and the Effect of Production Differences on Dairy Sire Appraisals. J. Dairy Sei., 44: 1189. (7) Conlin, B. J., and Cole, C. L. 1966. Estimates of Parame£ers from a Nationwide Artificial Insemination Population. J. Dairy Sci., 49: 748. (8) Fairchild, T. P., Tyler, W. J., Barr, G. R., and Corley, E. L. 1966. Estimating Transmitting Abilities of Artificial Insemination Dairy Sires. J. Dairy Sci., 49: 1416.
S~RE EVALVAT~ONS
(9) Kelleher, D. J. L. 1964. The Importance of Bull X Herd-Year-Season Interaction in Milk Production. Unpublished Ph.D. thesis, Iowa State University, Ames. (10) Legates, J. E. 1962. Heritability of F a t Yields in Herds with Different Production Levels. J. Dairy Sei., 45: 990. (11) Legates, J. E., Verlinden, F. J., and Kendriek, J. F. 1956. Sire by Herd Interaction ia Produetioa Traits in Dairy Cattle. J. Dairy Sci., 39: 1055. (12) Lytton, V. H., and Legates, J. E. 1966. Sire by Region Interaction for Production Traits in Dairy Cattle. J. Dairy Sci., 49: 874. (13) Mason, L L., and l~obertson, Alan. 1956. The Progeny Testing of Dairy Bulls at Different Levels of Production. J. Agr. Sci., 47: 367. (14) Pirchner, F., and Lush, J. L. 1959. Genetic and Environmental Factors o2 the Variation Among Herds in B u t t e r f a t Production. J. Dairy Sci., 42: 115.
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(15) Robertson, A., O'Connor, L. K., and Edwards, J. 1960. Progeny Testing Bulls at Different M~nagement Levels. Animal Prod., 2: 141. (16) Robertson, A., and Rendel, J. M. 1954. The Performance of Heifers Got by Artificial Insemination. J. Agr. Sci., 44: 184. (17) VanVleek, L. D. 1963. Regression of Records on Herdmate Averages. J. Dairy Sei., 46 : 846. (18) Vaa~V]eck, L. D. 1963. Genotype and Environment in Sire Evaluation. J. Dairy Sci., 46: 983. (19) VanVleck, L. D., Wadell, L. H., and Henderson, C. R. 1961. Components of Varisalce Associated with Milk and F a t Records of Artificially Sired Holstein Daughters. J. Animal Sci., 20: 812. (20) Wadell, L. H., and McGilliard, L. D. 1959. Influence of Artificial Breeding on Production in Michigaa Dairy Herds. J. Dairy Sci., 42: 1079.
J. DAIRY SCIENCE ~7OL. 50, NO. 5
Animal Husbandry Research Division, USDA, Beltsville, Maryland between sire evaluations at different herdmate levels have been high, indicating that progeny groups tend to rank similarly under different herd environments. Robertson et al. (15) divided the progeny of 57 Holstein sires used in A I in England into low, medium, and high levels, depending on the milk yield of their herdmates. Genetic correlations ranged from 0.87 to 0.96 among sire progeny groups at the three levels. VanVleck (18) estimated the genetic ~orre~ations between half-sister sets for all possible pairs of four different management levels for both milk and fat yields. All correlations were high and ranged from 0.93 between tile lowest level and the highest level, to 1.0 for other pairs of levels. Although these studies were conducted with relatively small numbers of daughters per sire, all indicated that A I sires would have similar rankings, regardless of the production level of the herds in which their progeny were located. Indirect evidence that daughters of sires perform similarly in different levels of production has been presented in the form of very small sire-by-herd interactions (3, 5, 9, 11, 14, 19, 20). Such estimates have ranged from zero to about four per cent of the total variance, and suggest that shifts in ranking of sires from herd to herd are of small consequence. Additional indirect evidence has been presented by Lytton and Legates (12), who found high correlations between sets of paternal halfsisters, where one group was located in the Southern United States and the other in the northern states. Contrary evidence has been presented by Bereskin and Lush (4), which indicated that summaries on bulls in high level herds might not be very indicative of their performance lO%. in low level herds. The present study was undertaken to ascertain Since the development of artificial insemina- and demonstrate the relationships between sire tion (AI), concern has been expressed that the evaluations at widely differing herdmate levels progeny of bulls will not rank in the same for bulls used extensively in AI, and to deterorder over a wide range of herd environmental mine the effect of varying herdinate milk yields conditions. This concern has been reinforced on current United States Department of Agriby the practice of evaluating AI bulls by av- culture (USDA) sire evaluation procedures. eraging all of their AI progeny, over all levels of herdmate production. Data I n recent studies (13, 15, 18) correlations The data consisted of the milk yields of firstlactation A I progeny of 40 Holstein bulls and Received for pub]ication November 2, 1966. 735 Abstract
Relationships between independent measures of a bull's breeding value at different levels of herd production were investigated. The data consisted of the 2 times, 305-day, mature equivalent (ME) first lactation records of the artificially inseminated (AI) progeny of 40 Holstein sires. Each bull had 1,000 or more daughters. Progeny were classified into one of four groups, based on milk yield level of herdmates (I ----4,536-5,442 kg; I I ----5,443-6,349 kg; I I I = 6,350-7,256 kg; and IV = 7,2578,164 kg). Daughter averages rose with increases in herdmate level, while the magnitude of the Predicted Difference measure of a sire's breeding value decreased 289 kg (103, 47, --39, and --186 kg, respectively) from low (I) to high ( I ¥ ) herdmate levels. Correlations among sire progeny averages at the different herdmate levels were all very high (0.88 to 0.96) and indicated that bulls ranked in about the same order at all levels. Regressions computed in the same manner indicated the absence of a one-for-one relationship in the magnitude of measures of breeding value at the different herdmate levels. The Predicted Difference measure of a sh'e's breeding value only partially accounted for variation in herdmate milk yields among sires. I t was an effective criterion for ranking bulls evaluated within the same herd levels, but somewhat less effective in establishing absolute breeding merit. The maximum bias in predicted differences of bulls with very high yielding herdmates (6,800 kg of nfilk or nmre) was about 5 to
736
~cDANIEL
._
AND
CORLEY
the unregressed averages of their herdmates. F i r s t lactations were defined as the first available record of cows which calved at an age of 35 months or less. Other qualifications for record use were that the progeny must have calved between J a n u a r y , 1959, and May, :1_964, with either complete or incomplete lactations of 240 days or more on twice-a-day milking. Incomplete records of both daughters and herdmates were projected to a 305-day basis, and all records adjusted to a mature equivalent basis with standard D a i r y H e r d I m p r o v e m e n t Association ( D H I A ) factors• t t e r d m a t e s were defined as all other Holstein cows calving in the same five-month herd-year-season as the daughter. Incomplete records of all lengths were included in the herdmate averages. 0 n l y progeny that had five or more herdmates were used. Each of the 40 bulls selected had been summarized by U S D A p r i o r to May, 1965, with at least 1,000 A I progeny. All sires had been placed in A I service a f t e r J a n u a r y , 1956.
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Methods and Procedures
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r~ q~
..N
The progeny were grouped by herdmate milk production level in intervals of 453.6 kg and starting at 2,724 kg. Since vesT few cows had herdmates averaging less than 4,082 kg or more than 8,164 kg, all analyses and comparisons were made within these levels. Progeny with herdmate levels outside this range were not used. Each of the 40 bulls had progeny at all of the herdmate levels analyzed. Variables studied were daughter averages, daughter-hcrdmate differences, and Predicted Differences ( P D ) for milk yield. Predicted Differences were computed as follows: P D -where
>
, , , , , , , , ,
O
~t~ + 20
[D, -- .9 ( H M ~
- - tL) - - ;~]
t~---- breed average (5,924 kg) m =- number of daughters at the i TM herdmate level D~ = d a u g h t e r average at the i ~h herdmate level H M ~ = h e r d m a t e average at the i th herdmate level.
Both standard product-moment and rank correlations were computed between the sire evaluations at the different herdmate levels for Predicted Differences. Regressions were computed by standard variance-covariance procedures. ~D
~g J . D A I R Y SCIEN-0E ~¢'OL. 5 0 , NO. 5
Results and Discussion
The unweighted averages of sire-progeny group means for all variables and levels of
SIRE EVALUATIONS
737
TABLE 2 Averages and standard deviations for first lactation milk yields of the progeny of forty Holstein bulls at four different herdmate levels
Herdmate level" Low Medlmn low Medium high High
No. of progeny
No. of herdmates
Daughter averages
Avg ~
Range ~
Avg
281 708 605 170
53- 667 198-2,440 199-2,490 32- 727
5,296 5,974 6,616 7,174
(~gJ
s
Avg
range
127 129 148 171
19 22 21 19
9-31 13-34 12-40 9-64
Deviation from herdmates Avg
(~g)
193 48 --124 --394
s 126 129 143 166
Predicted Difference Avg
(~g)
103 47 -- 39 --186
s 117 125 137 137
Low = 4,536-5,442 kg; mediunl low = 5,443-6,349 kg; medium high = 6,350-7,256 kg; high = 7,2578,164 kg. b Each of the 40 bulls was represented and weighted equally in each average. ¢ ]~ange in values for individual progeny groups. h e r d m a t e s are shown in T a b l e 1. Overall daught e r averages, which were based on the m e a n s of the 40 p r o g e n y g r o u p s a t each level, increased directly with increases in h e r d m a t e yields. These changes i n d a u g h t e r averages r e i t e r a t e the well-known f a c t t h a t a bull's d a u g h t e r a v e r a g e is largely d e p e n d e n t o n t h e p r o d u c t i o n level o f the h e r d s i n which his p r o g e n y are milked. H e r d m a t e differences decreased consistently as the h e r d m a t e level increased, i l l u s t r a t i n g t h a t the regression of a cow's p r o d u c t i o n on t h a t of h e r h e r d m a t e s is n o t 1.0. Decreases in t h e P D , which assumes t h a t t h e regression of genetic differences o n h e r d p r o d u c t i o n level is 0.10, were n o t as p r o n o u n c e d . These results demons t r a t e t h a t the U S D A P r e d i c t e d Difference is somewhat effective in a c c o u n t i n g f o r v a r i a t i o n in h e r d m a t e levels of milk yield. Because of t h e relatively small n u m b e r of
observations a v a i l a b l e in t h e i n d i v i d u a l 454-kg levels f o r m a n y bulls, wider i n t e r v a l s of 907 k g w i t h r a n g e s of 4,536 to 8,164 kg of milk were computed. U n w e i g h t e d a v e r a g e s o f the 40-sire p r o g e n y g r o u p m e a n s in each of these levels are shown in Table 2. A s i n T a b l e 1, d a u g h t e r averages increased steadily as h e r d m a t e p r o duction r o s e ; a n d conversely, t h e d a u g h t e r h e r d m a t e deviations decreased. A l t h o u g h t h e p r o g e n y of these bulls were, on the average, 193 k g s u p e r i o r to t h e i r lower-yielding h e r d m a t e s (4,536-5,442 k g ) , they were 394 kg inf e r i o r to t h e i r h i g h e s t level stablemates (7,2578,164 k g ) . This c h a n g e clearly illustrates a n d verifies the need f o r a n a d j u s t m e n t f o r level of h e r d m a t e s w h e n bulls a r e c o m p a r e d over a wide r a n g e of e n v i r o n m e n t M conditions. T h e s t a n d a r d deviations i n Table 2 show t h a t the v a r i a t i o n a m o n g the p r o g e n y a v e r a g e s o f the 40 bulls increased as the p r o d u c t i o n level
TABLE 3 Correlations between forty Holstein paternal half-sister groups a t four herdmate levels Herdmate level Herdmate level Low
Medium low
Medium hlgh
Measure of sire's merit Daughter average Daughter-HM difference Predicted Difference Product-moment correlation l~ank correlation Daughter average Daughter-HM difference Predicted Difference Product-moment correlation Rank correlation Daughter average Daughter-HM difference Predicted Difference Product-moment correlation R,ank correlation
Medium low ~
Medium high ~
High
.92 .93
.93 .93
.89 .88
.93 .93
.93 .94 .95 .96
.88 .89 .92 .92
.96 .94
.91 .93 .94 .94 .93 .93
Medium low = 5,443-6,349 kg; medium high = 6,350-7,256 kg. if. DAIRY SCIE~CCE VOId. 50, NO. 5
738
McDANIEL
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of the herdmates of their progeny increased. The average number of records in the sire groups varied between levels and could have affected the standard deviations. However, calculations showed that adjusting the standard deviations for the varying amount of within-sire variation (2_ o ) / ~ did not change the rank or relative amount of increase in the standard deviations as herdmate levels increased. I n other words, these results suggest that a bull's daughters are more likely to deviate markedly from their herdmates when the herchnates are producing at high levels (i.e., variation among progeny groups is greater). Similar findings have been reported previously by numerous investigators (6, 10, 12, 15, ]8). One of the most important questions about sire evaluations in different herd management levels is, Do bulls rank the same way ill all levels? To obtain evidence on this matter, correlations were computed among the sire progeny group means paired in all combinations of the four herdmate levels. Three different measures of the sire's merit--the simple daughter average, the unadjusted daughter-herdmate difference, and the Predicted Difference--were used. Correlations among the progeny group means, shown in Table 3, ranged from 0.88 to 0.96 between herdmate levels. Relationships between adjacent levels were generally highest, and values decreased as the difference in herdmate levels increased. Correlations for all of the measures of breeding merit used were essentially identical. Correlations in Table 3 are similar to those reported by other investigators (6, 13, 15, 18), but based on a much larger sample of daughters for individual bulls, and represent all areas of the United States. The magnitude of the correlations suggests that bulls will rank almost identically from level to level, a conclusion supported by the rank col-relations in Table 3. Also, the obselwed correlations should be lower than the true genetic correlations, since a portion of the within-sire variation is present in the variances among progeny group means. Evaluations on nine individual bulls were selected to illustrate the correlations among sire evaluations at the different herdmate levels. Bulls were ranked from 1 to 40 on their PD at the medium low herdmate level (5,443-6,349 kg), which encompasses the breed average, and their respective ranks at the other levels determined. Summaries on the three most superior bulls (Ranks 1, 2, and 3), the intermediate three (Ranks 19, 20, and 21), and the three most inferior bulls (Ranks 38, 39, and
SIRE
40) are shown individually in Table 4. I n all cases the three superior bulls ranked among the top five bulls at all levels, and the most inferior three were always in the bottom five. I n 10 of the 12 situations, the intermediate bulls ranked very near the middle. I-Iowever, in the two cases where bulls shifted their rankings substantially, absolute changes in PD were very small (26-1.59 kg). Table 4 also shows how the use of the unadjusted daughter average without any knowledge of corresponding herd production levels can be very misleading when evaluating bulls. For example, the top bull's daughter average (A) in the low herdmate group is only 5,643 kg; whereas, the poorest bull's daughter averages in the medium high and high herdmate level groups are 5,791 and 6,235 kg, respectively. From this comparison Bull I would appear the better bull, yet within the four herdmate levels his daughters consistently averaged more than :[,000 kg below that of Bull A's progeny. As might be expected from results of previous investigations (15, 18), correlations between summaries at the two extreme production levels were the lowest (Table 3). The average daughter-herdmate deviations at these two levels are shown for each of the 40 bulls in Figure 1. I t is apparent from this graph that only a few progeny groups deviated from the overall pattern. Some deviations due strictly to chance might be expected, because of the variation between bulls in the number of progeny available at these two levels.
(I)
÷ o
+
+
+
4-
-r
÷ ÷++
.-I
.)/4:--" ÷4- 4- 4"
l" o,n I
I 4"
-10,
/5
-~
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739
EVALUATIONS
~0
HIGH LEVEL HERDS
FIo. 1. ]Relationship between Predicted Differences for milk yield (kilograms × 10-:) in high(7,257-8,164 kg) and low- (4,536-5,442 kg) level herds.
4"
**÷ ~,,
+/++++ 4-
_~
+4.++
I~, p. i g 7 AVERAGE HERDS
Fro. 2. Relationships between Predicted Differences for milk yield (kilograms × 10-1) in average(5,443-6,349 kg) and superior- (6,350-7,256 kg) level herds. The high repeatability of sire summaries from breed average herds to those about 1,000 kg higher is illustrated clearly in Figure 2. Deviations h'om the over-all regression line were very small. Regressions of daughter-herdmate deviations at one level on another level of herd production are shown in Table 5. They demonstrate an absence of a one-for-one correspondence in the absolute magnitude of measures of a sire's merit over a wide range of production levels, even though relative rankings are similar (Table 3). Results with Predicted Differences (Table 5) differ substantially from 1.00, and suggest that this measure does not completely account for variation in herdmate levels. However, regressions of PD were generally closer to 1.00 than those for the unadjusted daughterherdmate differences. Regressions for Predicted Difference indicate that the magnitude of this measure of a sire's breeding value can fluctuate 5 to 10% among different herdmate levels. I t h a s been well known that the regression of cows on their herdmates is less than 1.0 (1, 2, 7, 8, 14, 16, 17), and that some differences in the magnitude of a site's unregressed summaries at varying levels of herd production are to be expected. Generally, estimates of the regression have been near 0.9 (2, 7, 14, 17), which states that a bull's daughter-herdmate deviation should drop 100 leg for each 1,000 kg increase in herdmate levels. I n this study the drop was greater, 3-. DAIRY SCI]~TCE ~fOL. 50, NO. 5
McDANIEL
740
AND C O R L E Y
TABLE 5 Regressions between forty Holstein paternM h~f-sister groups at four herdmate levels Regressions Herdmate levels a 1
2
Low
Medium low
Low
Medium high
Low
Nigh
Medium low
Medium high
Medium low
High
Medium high
Nigh
Measure of slre's merit
1 on 2
2 on 1
Daughter-HM difference Predicted Difference Daughter-HM difference Predicted Difference Daughter-HM difference Predicted Difference Daughter-l=[M difference Predicted Difference Da,ughter-HM difference Predicted Difference Daughter-HM difference Predicted Difference
.90±.06 b .87±.06 .81--+.05 .79-+.05 .67-+.06 .75-+.07 .86-+.04 .87-+.04 .71+.05 .83-+.06 .81~.05 .93-+.06
.95+---.06 b 1.00±.06 1.06-+.07 1.09-+.07 1.17-+.10 1.03-+.09 1.06-+.05 1.05±.05 1.18-+.08 1.00-+.07 1.09+.06 .93-+.06
a Low = 4,536-5,442 kg; medium low = 5,443-6,349 kg ; medium high = 6,350-7,256 kg; high = 7,257-8,164 kg. b Standard errors. since t h e d a u g h t e r deviations a d j u s t e d by the 0.9 f a c t o r were 103, 47, --39, a n d - - 1 8 6 kg, respectively. One possible source of the discrepancs~ m i g h t be t h a t t h e r e g r e s s i o n of 0.9 is n o t completely a p p l i c a b l e to the regression of first-lactation cows on t h e i r h e r d m a t e s of all ages. S u p p o r t f o r this h y p o t h e s i s is f o u n d in two i n v e s t i g a t i o n s (1, 8) w h e r e regressions of first-lactation cows on t h e i r h e r d m a t e s of all ages were a p p r e c i a b l y less t h a n 0.9. The results suggest t h a t no serious e r r o r s will occur i f bulls a r e r a n k e d according to t h e i r P r e d i c t e d Difference a n d t h e i r h e r d m a t e averages are w i t h i n 1,000 kg of each other. Also, the P r e d i c t e d Differences of bulls used exelusively in extremely h i g h h e r d levels will be slightly u n d e r e s t i m a t e d . I t should be n o t e d t h a t the d a u g h t e r a v e r a g e s used in this s t u d y were based entirely o n firstlactation cows, while cows of all ages were included in the h e r d m a t e averages. F a i l u r e o f the P r e d i c t e d Differences to completely a c c o u n t f o r the v a r i a t i o n in h e r d m a t e levels is p r o b a b l y associated w i t h this circumstance. I n a c c u r a c i e s in age-correction f a c t o r s m i g h t also c o n t r i b u t e to t h e discrepancy. I n general, conclusions o£ this s t u d y are t h a t : (a) Artificially i n s e m i n a t e d sire p r o g e n y g r o u p s will r a n k in a b o u t the same order, regardless of the h e r d p r o d u c tion level at which they are evaluated. (b) Efforts to r a n k A I bulls on t h e i r d a u g h t e r averages r a t h e r t h a n deviations f r o m h e r d m a t e s m a y lead to serious errors. (e) The U S D A P r e d i c t e d Difference only p a r t i a l l y accounts f o r differences in h e r d m a t e p r o d u c t i o n level, b u t t h e abJ. DAIRY SCIENCE YOL. 50, NO. 5
solute values o£ the e r r o r s are n o t very large, a n d especially where h e r d m a t e a v e r a g e s do n o t v a r y over 1~000 k g f r o m b r e e d average. References
(1) Allaire, F. R., and Gaunt, S. N. 1965. First-Lactation Contemporary Comparisons as Indicators of Enviromnental Influences on Daughter Records Used for Sire Evaluation. J. Dairy Sci., 48: 454. (2) Bereskin, B., and Freeman, A. E. 1965. Genetic aa~d Environmental Factors in Dairy Sire Evaluation. H. Uses and Limitations of Deviation Records and the Role of Dams. J. Dairy Sci., 48: 352. (3) Bereskin, B., Freeman, A. E., and Lush, J. L. 1962. Sources of Variation in D H I A Records Related to Proving A.I. Sires. J. Dairy Sci., 45: 677. (4) Bereskin, B., and Lush, J. L. 1965. Genetic and Environmental Factors in Dairy Sire Evaluation. I I I . Influence of Environmental and Other Extraneous Correlations Among the Daughters. J. Dairy Sei., 48: 356. (5) Burdick, J. M., and McGilliard, L. D. 1963. Interaction Between Sires in Artificial Insemination and Management of Dairy Nerds. J. Dairy Sci., 46: 452. (6) Burnside, E. B., and Rennie, J. C. 1961. The Heritability of Milk Yield at Different Levels of Production and the Effect of Production Differences on Dairy Sire Appraisals. J. Dairy Sei., 44: 1189. (7) Conlin, B. J., and Cole, C. L. 1966. Estimates of Parame£ers from a Nationwide Artificial Insemination Population. J. Dairy Sci., 49: 748. (8) Fairchild, T. P., Tyler, W. J., Barr, G. R., and Corley, E. L. 1966. Estimating Transmitting Abilities of Artificial Insemination Dairy Sires. J. Dairy Sci., 49: 1416.
S~RE EVALVAT~ONS
(9) Kelleher, D. J. L. 1964. The Importance of Bull X Herd-Year-Season Interaction in Milk Production. Unpublished Ph.D. thesis, Iowa State University, Ames. (10) Legates, J. E. 1962. Heritability of F a t Yields in Herds with Different Production Levels. J. Dairy Sei., 45: 990. (11) Legates, J. E., Verlinden, F. J., and Kendriek, J. F. 1956. Sire by Herd Interaction ia Produetioa Traits in Dairy Cattle. J. Dairy Sci., 39: 1055. (12) Lytton, V. H., and Legates, J. E. 1966. Sire by Region Interaction for Production Traits in Dairy Cattle. J. Dairy Sci., 49: 874. (13) Mason, L L., and l~obertson, Alan. 1956. The Progeny Testing of Dairy Bulls at Different Levels of Production. J. Agr. Sci., 47: 367. (14) Pirchner, F., and Lush, J. L. 1959. Genetic and Environmental Factors o2 the Variation Among Herds in B u t t e r f a t Production. J. Dairy Sci., 42: 115.
741
(15) Robertson, A., O'Connor, L. K., and Edwards, J. 1960. Progeny Testing Bulls at Different M~nagement Levels. Animal Prod., 2: 141. (16) Robertson, A., and Rendel, J. M. 1954. The Performance of Heifers Got by Artificial Insemination. J. Agr. Sci., 44: 184. (17) VanVleek, L. D. 1963. Regression of Records on Herdmate Averages. J. Dairy Sei., 46 : 846. (18) Vaa~V]eck, L. D. 1963. Genotype and Environment in Sire Evaluation. J. Dairy Sci., 46: 983. (19) VanVleck, L. D., Wadell, L. H., and Henderson, C. R. 1961. Components of Varisalce Associated with Milk and F a t Records of Artificially Sired Holstein Daughters. J. Animal Sci., 20: 812. (20) Wadell, L. H., and McGilliard, L. D. 1959. Influence of Artificial Breeding on Production in Michigaa Dairy Herds. J. Dairy Sci., 42: 1079.
J. DAIRY SCIENCE ~7OL. 50, NO. 5