Genetic Change in Minnesota Holstein Herds1,2

G e n e t i c C h a n g e in M i n n e s o t a H o l s t e i n H e r d s 1' ~ D. G. JOHNSON s, C. W. YOUNG, R. W. TOUCHBERRY, and G. R. STEUERNAGEL Department of Animal Science University of Minnesota St. Paul 55108 ABSTRACT

First-lactation records of 52,894 Holstein cows in 713 Minnesota herds on Dairy Herd Improvement for 7 yr or more were analyzed to estimate genetic trends in herd averages and to identify breeding practices that enhance herd improvement. Mean predicted difference milk among herds was - 3 kg and mean cow selection differential +118 kg. Annual trends in milk yield as measured by mature equivalent, predicted difference, and selection differential were 117, 20, and 1 kg. Genetic change in herds was estimated by the negative of two times the pooled intrasire regression of daughter contemporary deviation on time. The mean for genetic trend was 60 -+ 30 kg milk. Production averages and production trends for herds were influenced positively by predicted difference and selection differential, predicted difference being the more important of the two. Because of large sampling variances, little of the variation in estimates of genetic change in herds was accounted for. There was a tendency for estimates of genetic change to vary inversely with average predicted difference and directly with the trend in predicted difference. INTRODUCTION

Average production of Minnesota Dairy Herd Improvement (DHI) cows increased 824 kg milk from 1963 to 1970 (6, 7). The trend in production can be partitioned into genetic trend and environmental trend if some of the genotypes are repeated over time (4).

Received May 9, 1975. 1Scientific Journal Series Paper No. 9083, Minnesota Agricultural Experiment Station, St. Paul. ZA contribution to regional project NC-2. 3West Central Experiment Station, University of Minnesota, Morris 56267.

Estimates of genetic change in field populations, since improved sire evaluation techniques have been adopted and accepted, are few. Verde et al. (5) estimated that the Holstein DHI population in Florida increased genetically 33 kg milk per year from 1 9 5 8 to 1964. Estimated genetic trend in six Southeastern states from October 1964 to November 1968 was 53 -+ 13 kg milk (1). Powell and Freeman (3) estimated genetic trend for milk production in 220 Holstein progeny test herds in Minnesota, Iowa, and Nebraska with the preferred among many estimators being 82 +- 29 kg milk per year. The objectives of this study were (a) to quantify selection practices of a sample of Minnesota dairymen, (b) to estimate genetic change for each herd, and (c) to identify the selection practices responsible for variation in rate of genetic change. DATA

All first-lactation records of Minnesota DHI Holsteins were obtained from herds where (a) at least five first-lactation records were available for each of the five calendar years 1966 through 1970, (b) at least 70% of all first-lactation records were identified by sire, and (c) only Holstein breed codes were given. The data included 52,894 first-lactation records from 713 herds where records were initiated between September 1, 1963, and August 31, 1970. Seven years September through August were utilized in calculating trends. A first-lactation record was defined as one from a cow with no previous record that calved at 22 through 34 mo of age. Mature equivalent (ME) records were calculated in the DHI program by seventh degree polynomial equations with separate equations for milk and fat for two seasons, November to June and July to October. First-lactation records of less than 305 days were extended unless lactation was terminated by a dry date prior to 305 days. Records of less than 14 days were not used. The basic DHI record also included production as a deviation from herd and season average, most 293

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JOHNSON ET AL.

recent sire progeny test information, and identification. Dam's first-lactation herdmate deviation milk and fat were obtained by matching dam identification codes with cow identification codes. Age of dam was calculated by difference between dates of birth of dam and daughter. As all data were drawn from a limited period, information for dams from early years was slight. Consequently, information on dam was accepted only from darns aged 22 to 59 mo during years 5 to 7 to avoid bias in estimates of the regression of age of dam on time. For selection differentials, each first-lactation record was coded either "saved" or "culled." Cows that survived to initiate a second lactation were coded saved, and all other cows were assumed culled. The selection differential was the mean first-lactation production of cows coded "saved" minus the mean first-lactation production of all first lactations in the same herd-year grouping. Phenotypic trend was estimated by the linear regression of milk or milk fat production on time, represented by year number. We ~ssumed an individual first lactation, ME 305-day, was composed of effects of population mean, herd, year, sire, and dam and random effects were normally distributed with a mean of zero. Genetic trend was estimated by a modification of a method described by Smith (4), the intrasire regression of contemporary deviation (CD) on time. The CD is the difference between individual performance and the average of all first lactations in the same herd and year. The often used herd-year-season classification was not used in this study to avoid eliminating records where only one first lactation was initiated per season. The sum of all contemporary deviations over the period in which the average was calculated is zero, but a trend in contemporary deviations across time in successive progeny of a sire reflects a trend in the average effect of all sires used in the herd. If the effect of a sire remains constant and mates of a sire are random samples of potential mates, the regression intrasire-herd of contemporary deviations on time is an estimator of minus half the genetic change if sires and dams improve at the same rate. The single herd estimate of genetic change from the pooled weighted sireherd regression of contemporary deviations on time is: Journal of Dairy Science Vol. 59, No. 2

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- - 2 ~ k (bcd.t(hs)/Vbcd.t (hs))/ ~k(1/Vbcd.t(hs)) with variance VAgi = 4 / ~ k (1/Vbcd.t(hs)) where bcd.t(hs) is the regression intrasire-herd of contemporary deviation on time and Ybcd.t(hs) is the variance of the regression coefficient. Subscripts i and k represent herd and sire. R ESULTS AND DISCUSSION

Average production and selection are in Table 1. Milk and fat productions for the 713 herds included in the sample were higher than the average for the state. Average predicted difference was - 3 kg, but many sires may have had a higher predicted difference when they were selected as the most recent p r o o f was used. Average herd selection differential for milk ranged from - 1 1 5 2 kg to 533 kg. Only 23 herds had selection differentials more than one standard deviation below the mean while 70 herds were one standard deviation above the mean. Trends in performance are in Table 2. Annual trend in ME milk production of first lactation as estimated by linear regression is almost equal to the trend in all DHI gross herd averages over the same time. Trend in predicted difference milk indicates improved sire selection practices. Bull studs eliminated inferior bulls during this period and dairymen may have become more astute selectors of bulls. As only the latest predicted difference was available, decreases within sire in predicted difference may have inflated the estimate of trend in sire selection because the predicted difference of

295

older bulls at the time of selection was likely to be higher than the most recent. This should have been offset by genetic trend in herdmates which reduced deviations in later years. The proportion of cows culled in first lactation increased slightly, but the selection differential remained essentially unchanged. Smith (4) pointed out that genetic change estimated from field records may be biased by selection of sires on performance of first progeny, or by a systematic relationship between the length of time a sire was in service and age or production of the sire's mate. Intraherd regression coefficient o f length of sire service on the deviated performance of first progeny group was essentially zero, indicating that by the time a farmer could determine the effectiveness of a bull in his herd, the bull was either no longer available or was not put back in heavy use. Pooled regressions intrasire-herd of dam's deviated production or age on time were extremely variable and correction for them only slightly changed a pooled population estimate of genetic change. Consequently, we did not attempt to adjust herd estimates of genetic trend for selective mating based on age or production deviation. Estimated annual genetic trend for ME milk in the 713 herds ranged from - 3 8 7 9 kg to 3777 kg with an unweighted average of 60 + 30 kg. Wide variation in herd estimates of genetic change was expected because of variation in breeding practices. A standard deviation of average herd selection differential of 140 kg milk and a standard deviation of 53 kg average herd predicted difference milk indicate variation in breeding programs, which would be expected to influence rate and direction of genetic trend. Sampling errors were expected to

TABLE 2. Pooled intraherd linear regression coefficients of yearly trends and standard errors to estimate annual trends in production and selection.

Dependent variable

Regression coefficient

ME milk (kg/yr) ME fat (kg/yr) Predicted difference - Milk (kg/yr) Predicted difference - Fat (kg/yr) Selection differential - Milk (kg/yr) Selection differential - Fat (kg/yr) Percentage culled

117.3 4.2 20.1 .5 1.3 .1 .9

Standard error 2.4 .1 .4 < .1 .8 < .1 .1

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TABLE 3. Multiple regression of herd average ME milk on selection program. c~= 6883

R2 = .0684

F = 12.99 (P<.01)

Independent variable

ba

b 'b

Significance

Predicted difference - Milk Selection differential - Milk Herd size Percent culled

2.6980 .4350 6.0768 -2.6291

.2373 .1003 .0476 -.0331

P<.O1 P<.O1 P>.05 P<.01

apartial regression coefficient. bstandard partial regression coefficient-

be large due to the small intraherd size of the sire progeny group. A total of 4116 sire-herd progeny groups were distributed across 713 Holstein herds. Consequently, an average of 5.8 progeny groups was available per herd, with a range f r o m 1 to 42. S o m e of the regression intrasire-herd are based on as f e w as three daughters, the m i n i m u m n u m b e r to estimate a regression coefficient and its variance. The mean genetic change for milk exceeds m o s t estimates of genetic trend for milk p r o d u c t i o n but is less than that f o u n d by Powell and Freeman (3). Their estimate o f 82 kg was f r o m progeny test herds in the Midwest, including Minnesota. Estimates of annual genetic t r e n d for milk fat in our study averaged 2.0 + .9 kg. T h e influence of the breeding program of the herd on p r o d u c t i v i t y was evaluated by multiple regression of ME milk p r o d u c t i o n , p r o d u c t i o n trend, and estimated genetic trend on selection factors. Effects o f herd averages for p r e d i c t e d difference milk, selection differential milk, size of herd, and percent culled on

average ME milk p r o d u c t i o n are in Table 3. Average predicted difference milk and selection differential positively affected herd average, predicted difference apparently being m o r e t h a n twice as i m p o r t a n t as c o w selection differential as estimated by the ratio of their respective standard partial regression coefficients. A relatively low coefficient of deterruination (R 2 = .0684) is e x p e c t e d as estimates o f genetic differences in herd averages ordinarily range f r o m .1 to .3 (2). As shown in Table 4, averaged p r e d i c t e d difference is t h e m o s t imp o r t a n t variable influencing trends in herd averages. Large herd size appeared to be detrimental to increases in milk production, possibly reflecting m a n a g e m e n t problems resulting f r o m herd expansion. Little variation in estimates of genetic change in milk p r o d u c t i o n was acc o u n t e d for by selection variables in Table 5. However, intraherd trend in p r e d i c t e d difference milk was associated positively with positive genetic trends for milk while average predicted difference milk was a nonsignificant

TABLE 4. Multiple regression of herd trend in ME milk on selection program. a = 125

R 2 = .0260

F = 4.7200 (P<.05)

Independent variable

ba

b'b

Significance

Predicted difference milk Herd size Percent culled Selection differencial

.2660 -3.0663 1.2258 .0670

.1024 -. 1016 .0676 .0067

P<.O1 P<.01 P>.05 P>.O 5

apartial regression coefficient. bstandard partial regression coefficient. Journal of Dairy Science Vol. 59, No. 2

GENETIC CHANGE IN MINNESOTA COWS

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TABLE 5. Multiple regression of herd estimates of genetic trend in ME milk on selection program. a =-8

R2 = .0164

F = 1.93 (P>.05)

Independent variable

ba

b ~b

Significance

Trend in P. D. Milk Trend in selection dif~ P. D. Milk Selection dif. Percent culled Herd size

2.886 -.536 -.897 -.224 1.370 .390

.1029 -.0623 -.0607 -.0396 .0133 .0023

P<.01 P>.05 P>.05 P>.05 P>.05 P>.05

a

.

Partial regression coefficient.

bstandard partial regression coefficient.

negative i n f l u e n c e . This suggests little consist e n t sire s e l e c t i o n so h e r d s of relatively high genetic m e r i t (high p r e d i c t e d difference-sire b a c k g r o u n d ) d i d n o t m a i n t a i n high sire-select i o n s t a n d a r d s , while h e r d s t h a t did increase use of high p r e d i c t e d - d i f f e r e n c e sires as t i m e w e n t o n h a d i m p r o v e d genetic trends. T h e large a m o u n t o f v a r i a t i o n in h e r d e s t i m a t e s o f genetic t r e n d is p r o b a b l y partially r e s p o n s i b l e for t h e l o w c o e f f i c i e n t of d e t e r m i n a t i o n . T h e s e results p r o v i d e s o m e evidence t o s u p p o r t t h e r e c o m m e n d a t i o n t o utilize sires w i t h high p r e d i c t e d d i f f e r e n c e for milk t o achieve high h e r d p r o d u c t i v i t y . A c c e l e r a t e d genetic t r e n d f r o m s e l e c t i o n o f sires w i t h h i g h e r predicted difference than the previous round of sires is suggested, b u t less c o n v i n c i n g l y . ACKNOWLEDGMENTS

The computer programming o f David S c h e m p p was essential t o t h e c o m p l e t i o n o f

this s t u d y . REFERENCES

1 Hargrove, G. L., and J. E. Legates. 1971. Biases in dairy sire evaluation attributable to genetic trend and female selection. J. Dairy Sci. 54:1041. 2 Miller, R. H. 1970. Age, breed, trait, and regional variation in the regression of daughters on herdmates. J. Dairy Sci. 53:1461. 3 Powell, R. L., and A. E. Freeman. 1974. Genetic trend estimators. J. Dairy Sci. 57:1067. 4 Smith, C. 1962. Estimation of genetic change in farm livestock using field records. Anim. Prod. 4:239. 5 Verde, O. G., C. J. Wilcox, F. G. Martin, and C. W. Reaves. 1971. Genetic trends in milk production of Florida Dairy Herd Improvement Association cattle. J. Dairy Sci. 54:783. (Abstr.) 6 Wayne, R. W., C. L. Wilcox, and J. W. Mudge. DHIA program in Minnesota, 1963 Ann. Summary, Univ. Minnesota Agr. Ext. Serv., St. Paul. 7 Wayne, R. W., J. W. Mudge, B. J. Conlin, G. Steuernagel, and D. R. Karr. DHI program in Minnesota, 1970 Ann. Summary, Univ. Minnesota Agr. Ext. Serv., St. Paul.

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