Genetic Parameters of Monthly Egg Production in the Cornell Controls1

Genetic Parameters of Monthly Egg Production in the Cornell Controls1 L. D. VANVLECK 2 AND D. P. DOOLITTLE 3 Cornell University, Ithaca, N. Y. (Received for publication October 3, 1963) INTRODUCTION

T

HE value of using part of the annual egg production for the early selection of superior sire and dam lines in fowl has been widely accepted. An early report of Lerner and Cruden (1948) showed that because of the high genetic correlation between part year production and total annual production selection for the latter based on the former would not diminish genetic progress as compared to selection based on complete records. In fact, the decreased generation interval due to the use of part records could actually increase genetic progress. The object of the present analysis was to substantiate, if possible, and to amplify these results from observations taken in a random bred flock. The suitability of random bred data for the establishment of genetic parameters has been discussed elsewhere (King, Carson and Doolittle, 1959). MATERIALS

The monthly trapnest records of the Cornell Random Bred Control flock of White Leghorns were available for the 1 This investigation was conducted by the Department of Poultry Husbandry at Cornell University as a part of the Northeastern (NE-6) Regional Poultry Breeding Project, supported in part by Poultry Research Branch of the United States Department of Agriculture. 2 Department of Animal Husbandry, Cornell University, Ithaca, New York. 3 Graduate School of Public Health, University of Pittsburgh, Pittsburgh 13, Pennsylvania.

1959-60 and 1960-61 seasons. The general rearing conditions and breeding practices have been described by King et al. (1959). Wilcox et al (1963) have described the feeding regime and trap nesting procedure for the 1959-60 season. These features were not changed materially for the 1960-61 season. The birds were trapped 15 days per month in 1959-60 and 16 days per month in 1960-61. Two shifts (hatches) were set in each season about four weeks apart. Females were put in the laying house at about 150 days of age. Only those hens that laid at least one egg were included in the subsequent analysis. The first month of production for first hatch birds was July, and for second hatch birds, August. Monthly production was recorded for eleven months. If a hen died during the period her production was taken to be zero for the remainder of the laying period. Thus, capacity to produce and viability are confounded. The means of monthly egg production are shown in Figure 1. The number of hens, sire groups, and dam groups included in each hatch and the means of yearly production and age at sexual maturity are given in Table 1. The egg production values are adjusted to a 30day month basis. ANALYSIS

The data were analyzed separately for each hatch group according to the model:

560

yak(m) =v-+Si+dij+eijk

561

PARAMETERS OF MONTHLY PRODUCTION TABLE 1.—Yearly means and numbers of observations, sires, and dams 1959-60

Yearly egg production Age at sexual maturity No. Hens No. Sires No. Dams

1960-61

Hatch Hatch 1 2

Hatch Hatch 1 2

197.2

184.8

189.6

191.2

179.1 386 51 186

181.8 470 49 178

177.7 513 49 199

185.1 417 48 176

where ys-,-fc(m) is the observation on the m t h trait on the k t h hen in the ij t h dam group and the i th sire group. It was further assumed that the s», d*y, and e,-/* were random variables, independently and identically distributed, each with zero mean and variances Sm2, Dm2, and Em2 respectively. This is model II of Eisenhart (1947). Components of variance and covariance were estimated by Henderson's

(1953) Method 1. Covariance components between traits m and m' can be denoted a s Om,mf,

-L'm.m'j a n d S-Jm,m'-

Estimates of heritability can be obtained in three ways from the estimated components of variance as described for poultry data by King and Henderson (1954). These methods are: 2_

4-S2 y2

2

= h/ =

where

r 2 = 52+Z)2+£2

4-Z)2

2-

y2

2-(S*+D*)

S2 may contain variance due to sex linkage and D2 may contain variance due to maternal effects and variance due to interaction between the sire and dam genotypes. These estimates were comPR0DUCTI0N

FIG. 1. Average monthly egg production, and pooled estimates of heritability from sire and dam components of variance.

562

L. D. VANVLECK AND D. P. DOOLITTLE

TABLE 2.—Analysis of variance of monthly heritability estimates from sire and dam components of variance Source

D.F.

F-ratio

Sire vs dam Year Hatch/year Month Sire vs. dam X year Sire vs. damXhatch Sire vs. dam X month Year X month

1 1 2 10 1 2 10 10

27.42 .06 .08 2.05 8.68 14.07 2.82 .49

Residual

50 Mean square==.0303

puted for each trait for each hatch period. Estimates of genetic correlations were obtained in analogous fashion by three methods:

gd

~

(Dj-Dm,y*

+Dm

,m'

Pooled estimates for the four hatches were obtained by averaging the estimated components of variance and covariance for all hatches after correcting for the unequal number of days trapped per month in the two years. RESULTS AND DISCUSSION

Pooled estimates of heritability are shown in Figure 1 for monthly egg yield and for cumulative production. The analysis of variance of the heritability estimates from sire and dam components is presented in Table 2. All effects were considered fixed—sex, year, hatch, and month. The heritability estimates are not independent since the denominators of the sire and dam estimates of heritability are the same for any month-hatch combination. The records of the same birds also appear in all 11 monthly estimates for a particular hatch. This lack of

independence was assumed to be unimportant. The significant difference between dam and sire estimates suggests that either maternal or sire by dam interaction effects are important. The dam component estimates exceeded the sire estimates 30 times out of 44 for monthly production and each time for annual egg production. Figure 1 shows, however, that the differences in estimates occur in the first and last parts of the production year. Maternal effects appear important in describing differences in reaching complete sexual maturity and in persistency of production. The cumulative effect of these factors results in a large difference between the sire and dam heritability estimates of annual production—.06 versus .44. This result for annual production was previously emphasized by King (1961) and King, VanVleck and Doolittle (1963) for the same population using a different analysis. Four determinants of egg production adumbrated by Hays (1924) all enter into the monthly production records considered in these studies. These determinants are sexual maturity (classically measured as age at first egg), intensity of production (length of runs of consecutive days on each of which an egg is produced), persistency of production (length of period until production ceases and the bird begins to moult), and occurrence of pauses (periods of consecutive days, usually more than four, during which no eggs are laid). Mortality also effects these production records since a bird is counted as having laid zero eggs after death. Pauses are usually caused by spells of broodiness and are unlikely to be important in this flock, derived from crossing several Single Comb White Leghorn stocks. Differences in sexual maturity influence the measures of egg production in

563

PARAMETERS OF MONTHLY PRODUCTION

TABLE 3.—Estimates of genetic correlations among monthly and 500-day {Sum) egg production, and age at sexual maturity from sire and dam components of variance and covariance* Month 1 Month 1 2 3 4 5 6 7 8 9 10 11 Sum Sexual maturity a

0.76 0.83 1.07 0.94 0.89 0.58 0.68 0.42 0.39 0.79 0.76 -0.94

2 0.25 1.00 0.61 0.52 0.42 0.58 0.79 0.56 0.46 0.59 0.71 -0.98

3 •- 0 . 1 4 0.75

4 0.03 0.26 0.57

1.05 0.59 1.86 0.50 0.89 0.58 0.63 0.70 0.87

0.16 1.73 0.83 1.68 1.60 1.23 1.82 1.31

-1.06

-0.77

5

6

•- 0 . 4 4 •- 0 . 1 1 0.20 1.17

•- 0 . 7 9 •- 0 . 3 4 •- 0 . 1 6 1.06 1.00

1.33 0.97 1.27 1.24 1.07 1.08 1.07 -0.88

7

8

9

10

11

Sum

Sexual maturity

1.34 1.50 1.15 0.89 1.20 1.22

— — — — —

-0.36 0.17 0.26 1.01 0.82 0.84

•- 0 . 9 1 •- 0 . 1 2 •- 0 . 1 8 1.20 1.47 1.90

•- 1 . 0 2 •- 0 . 1 4 0.22 1.07 1.15 1.86

•- 0 . 4 2 0.38 0.01 0.81 0.97 0.90

•- 0 . 2 8 0.34 0.42 1.25 0.95 0.75

-0.86 -0.47 -0.25 0.03 0.44 0.74

1.02 0.94 0.58 0.77 0.86

0.99 0.86 1.06 1.05

1.77 0.94 1.34 0.97

1.42 0.28

0.79 0.64 1.85

0.94 0.87 1.17 0.94

0.16 0.43 0.49 0.07 0.01

-0.55

-0.47

-0.66

-0.40

—

•

1.14 0.85 -0.48

1.09 -0.67

-0.73

Estimates from sire components are above the diagonal and from dam components are below the diagonal.

the first and to a lesser extent later months as will be shown in Table 3. Intensity of production certainly enters into all monthly records, and is probably the primary influence on production after the second month until differences in persistency and viability begin to have a major effect which increase in importance with time. The low heritability estimates from month two through six indicate that heritability of intensity of production is low. After the sixth month, heritability estimates from dam families rise while those from sire families remain low. The rise may be due to increasing variability of persistency and viability during the period while the difference between the two estimates indicates that non-additive gene or maternal effects and not additive gene effects are responsible for the higher estimates. The difference between the sire and dam components could be used to estimate the joint non-additive and maternal component assuming sex linkage to be absent. For annual production this difference is 10%. King et al. (1963), in a more definitive analysis, found no evidence for epistasis and attributed the 10% to maternal effects from data for the same populations used in this study.

Crude estimates of standard errors for the heritability estimates were computed using the equal numbers formulae of Robertson (1959). These are undoubtedly too low but may give some indication of reliability of the heritability estimates. For heritability estimates in the range .00 to .52 the standard error for sire estimates is 0.01 and for dam estimates is 0.005. The estimated genetic correlations between monthly production and annual production are given in Table 3. The comparable estimates also from sire and dam components, for cumulative production are shown in Table 4. Low estimates of heritability are likely to be associated with widely fluctuating estimates of genetic correlations. There are no methods available for estimating the sampling errors of genetic correlations from unbalanced data. Some pattern seems to emerge from the pooled estimates of correlations of monthly production with the yearly total. The highest estimates are for the middle months and the lowest for the first two or three months. Accordingly after the third month of production, essentially the same effects apparently contribute to monthly as to annual egg production. The pooled sire plus dam component estimates of genetic correlations and the

564

L. D. VANVLECK AND D. P. DOOLITTLE

TABLE 4.- -Estimates of genetic correlations among cumulative monthly egg production, and age at sexual

maturity, from sire and dam components of variance and covariance*Cumulative month 1

2

3

4

5

6

7

0.88

0.69 0.93

0.60 0.85 0.96

0.41 0.65 0.80 0.95

0.21 0.45 0.61 0.84 0.97

0.03 0.25 0.48 0.81 0.99 1.02

8

9

10

Sexual maturity

11

Month 1 2 3 4 5 6 7 8 9 10 11

Sexual maturity a

0.97 0.95 0.96 1.00 0.97 0.92 0.87 0.80 0.76 0.76

1.00 1.00 1.01 0.96 0.93 0.88 0.83 0.79 0.78

1.00 1.00 0.98 0.94 0.90 0.85 0.82 0.80

1.00 0.99 0.95 0.93 0.89 0.86 0.86

1.00 0.98 0.97 0.95 0.93 0.92

0.99 0.99 0.97 0.95 0.95

1.00 0.99 0.98 0.97

-0.94

-1.01

-1.03

-1.00

-1.02

-0.94

-0.88

-0.08 0.14 0.35 0.70 0.91 0.98 0.98 1.00 0.98 0.97 -0.83

-0.16 0.06 0.26 0.61 0.85 0.95 0.94 1.00 0.99 0.99 -0.77

-0.24 -0.03 0.17 0.53 0.78 0.92 0.94 1.01 1.00 1.00 -0.74

-0.28 -0.05 0.12 0.46 0.72 0.87 0.92 0.99 0.98 1.00

-0.86 -0.88 -0.83 -0.71 -0.51 -0.32 -0.19 -0.10 -0.05 0.00 0.01

-0.73

Estimates from sire components are above the diagonal and from dam components are below the diagonal.

phenotypic correlations for monthly yield are presented in Table 5. The pooled estimates of genetic correlations of monthly production with 500-day production increase rapidly from a low in the first month up to values near unity in the fourth and fifth months. This suggests that genetic differences in persistency and viability are more important determinants of variation in total annual production than are differences in intensity. This is not surprising since genetic variability with regard to intensity appears to be of a low order in this population. The low correlation of early production with annual production and the higher correlation of the direct measurement of sexual maturity with annual production, suggest that the separate measurement of sexual

maturity may be useful in supplementing selection from part records. The monthly yields close together in time are more highly correlated in general than others as estimated from sire, dam sire plus dam, and residual components. This pattern is much more apparent for the phenotypic correlations. The genetic correlations are also consistently larger than the phenotypic correlations. This result is in agreement with the findings of Lerner and Cruden (1948). The estimates of genetic and phenotypic correlations between cumulative monthly egg production are given in Table 6. The genetic correlations were estimated from pooled sire plus dam components. The estimated genetic correlation between cumulative monthly production and total

TABLE 5.—Estimates of genetic correlations from sire plus dam components of variance and covariance and of phenotypic correlations among monthly and 500-day (Sum) egg production, and age at sexual maturity* Month 1

2

3

4

5

6

7

8

9

10

11

0.61

0.43 0.87

0.54 0.41 0.75

0.38 0.24 0.38 0.77

0.33 0.15 0.91 1.32 1.16

0.34 0.40 0.51 0.99 0.95 1.16

0.41 0.62 0.62 1.25 1.04 1.27 1.00

0.27 0.45 0.36 1.07 1.01 1.09 0.99 1.00

0.23 0.36 0.45 0.86 0.87 0.90 0.73 0.86 0.92

0.35 0.50 0.36 1.21 1.02 1.07 0.84 0.95 1.04 1.06

Sum

Sexual maturity

Month 1 2 3 4 5 6 7 8 9 10 11

0.42 0.14 0.07 0.05 0.04 0.07 0.05 0.07 0.06 0.06 0.28

Sexual maturity -0.75 a

0.55 0.32 0.23 0.19 0.20 0.18 0.18 0.18 0.18 0.48 -0.61

0.60 0.41 0.35 0.30 0.28 0.27 0.27 0.24 0.57 -0.26

0.63 0.51 0.44 0.40 0.37 0.35 0.31 0.65 -0.05

0.74 0.61 0.56 0.50 0.49 0.44 0.75 0.01

0.75 0.64 0.59 0.56 0.51 0.78 0.02

0.76 0.65 0.61 0.54 0.80 -0.01

0.80 0.67 0.59 0.80 0.00

0.79 0.66 0.80 -0.01

0.77 0.79 -0.01

Genetic correlations are above the diagonal and phenotypic correlations are below the diagonal.

0.73 -0.03

0.55 0.62 0.66 1.07 0.93 1.05 0.91 1.02 0.95 0.86 0.98 -0.23

-0.92 -0.82 -0.70 -0.35 -0.30 -0.08 -0.25 -0.42 -0.28 -0.33 -0.38 -0.56

565

PARAMETERS OF M O N T H L Y PRODUCTION

TABLE 6.—Estimates of genetic correlations from sire plu dam components of variance and covariance and phenotypic correlations among cumulative monthly gg production, and age at sexual maturity* Cumulative month 1

Month 1 2 3 4 5 6 7 g 9 10 11

Sexual maturity 1

2

3

4

5

6

7

8

9

10

11

0.95

0.89 0.98

0.88 0.96 0.99

0.85 0.93 0.96 0.98

0.80 0.86 0.91 0.96 1.00

0.74 0.81 0.86 0.92 0.98 0.99

0.68 0.75 0.81 0.88 0.95 0.99 1.00

0.62 0.70 0.75 0.84 0.92 0.96 0.99 1.00

0.58 0.66 0.71 0.80 0.90 0.94 0.97 0.98 1.00

0.55 0.64 0.69 0.78 0.88 0.93 0.96 0.97 0.99 1.00

0.87 0.73 0.63 0.54 0.47 0.42 0.37 0.34 0.30 0.28

0.93 0.84 0.75 0.67 0.60 0.55 0.50 0.47 0.44

0.96 0.89 0.81 0.75 0.69 0.64 0.60 0.57

0.97 0.91 0.85 0.80 0.75 0.71 0.68

-0.75

-0.81

-0.73

-0.62

0.98 0.94 0.90 0.85 0.82 0.78 -0.52

0.98 0.95 0.92 0.89 0.86

0.99 0.96 0.94 0.91

-0.44

-0.38

0.99 0.97 0.95 -0.33

0.99 0.98 -0.29

0.99 -0.26

Sexual maturity -0.92 -0.97 -0.97 -0.92 -0.88 -0.78 -0.72 -0.66 -0.60 -0.58 -0.56

-0.23

Genetic correlations are above the diagonal and phenotypic correlations are below the diagonal.

11 m o n t h production increases rapidly until the fifth month and then more slowly until it is essentially unity a t 9 or 10 months. T h e phenotypic correlations follow the same p a t t e r n but the magnitude of the correlations is smaller, being about the same size as those for the genetic correlations one or two months earlier. For example, the genetic correlation between two cumulative months a n d total production is .64 as compared to the phenotypic correlation between three cumulative months a n d total production of .57. Lerner a n d Cruden (1948) reported a similar pattern. The relative genetic gains to be obtained b y selection on the basis of p a r t records can now be discussed. Table 7 presents the gain per generation to be expected from selection on the basis of single month a n d cumulative records, with or without the use of a supplem e n t a r y measurement of age a t sexual maturity. T h e gain per generation from truncation culling on the index for annual production is TTI
is the

correlation between T, the true genetic value, a n d / , t h e index estimate of T;
properties of the selection index.] T h e genetic gain per unit of time can be obtained from these estimates b y multiplying them b y the ratio of the generation interval when complete records are used to the generation interval when t h a t particular p a r t record is used. The values in Table 7 are expressed as fractions of the gain obtained from the use of complete records, taken as 1.00. Pooled estimates of heritabilities a n d genetic correlations from sire plus d a m TABLE 7.—Efficiencies of selection on single month and cumulative monthly production with or without age at sexual maturity relative to selection on 500-day production for 500-day production

Month

Single month

Single month plus sexual maturity

1 2 3 4 S 6 7 8 9 10 11

.66 .52 .41 .52 .59 .55 .63 1.00 .93 .85 .66

.73 .52 .45 .58 .66 .63 .68 1.04 .97 .89 .71

Cumulative month

.66 .70 .71 .75 .80 .82 .84 .93 .98 1.01 1.00

Cumulative month plus sexual maturity .73 .86 .79 .79 .82 .82 .84 .93 .98 1.01

correlation between selection index and 500-day production Efficiency = \/heritability of 500-day production

566

L. D. VANVLECK AND D. P. DOOLITTLE

components of variance and covariance were used for these calculations. Table 7 shows that a single month's record up to the eighth month does not predict total genetic gains as well as those after the eighth month. A separate measure of sexual maturity increases predictability. If cumulative production records are used, however, a supplemental measure of sexual maturity would add little improvement in progress in annual production, if more than five or six months' records are used. The relative efficiency of selection on part records increases rather rapidly, so that the decrease in generation interval afforded by cutting the production period in half would probably more than make up for the loss in efficiency of selecting on part records. This result is in agreement with Lerner and Dempster (1956) who concluded that experimental results "suggest that pullet breeding is a practical and desirable procedure in programs of* combined family and individual selection for egg production." SUMMARY

The monthly egg production of the Cornell Random Bred Control flock from hatches of two years was used to estimate the genetic relationships between monthly yields and between monthly egg yields and cumulative yield. Two shifts (hatches) were set each year. A total of 1802 records were included in a variance component analysis of a two factor nested classification—dams within sires. The estimates of genetic variance derived from the dam and sire components were quite different. The dam components were, in general, much larger which suggests that maternal effects or sire by dam interaction may be the contributing factors. These possibilities were not tested because analyses by other authors indicated the sire by dam

interaction to be negligible. The estimates suggest that genetic variance makes up a larger part of the total in the beginning and end periods of yearly production. The smaller estimates of heritability occurred in the fourth through sixth months. Estimates of genetic correlations between monthly yield and annual yield followed the opposite pattern. The larger estimates were for the middle months with yearly production. It appears from these results that selection for total annual production based on production from a single month will not be satisfactory unless the month chosen is one in the latter part of the laying year. If, however, cumulative records are used, the decreased generation interval resulting from selection on the part record will probably more than offset the loss in efficiency if records are taken for about half of the full laying year. REFERENCES Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3: 1-21. Hays, F. A., 1924. The application of genetic principles in breeding poultry for egg production. Poultry Sci. 4: 43-50. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Henderson, C. R., 1963. Selection index andexpected genetic advance in Statistical Genetics and Plant Breeding. NAS-NRC 982: 141-163. King, S. C , 1961. Inheritance of economic traits in the regional Cornell control population. Poultry Sci. 40: 975-986. King, S. C , J. R. Carson and D. P. Doolittle, 1959. The Connecticut and Cornell randombred populations of chickens. World's Poultry Sci. J. 15: 139-159. King, S. C , and C. R. Henderson, 1954. Variance component analysis in heritability studies. Poultry Sci. 33: 147-154. King, S. C , L. D. VanVleck and D. P. Doolittle, 1963. Genetic stability of the Cornell randombred control population of White Leghorns. Genetical Research, 4: 290-304. Lerner, I. M., and D. M. Cruden, 1948. The heritability of accumulative monthly and of annual egg production. Poultry Sci. 27: 67-78.

PARAMETERS OF MONTHLY PRODUCTION Lerner, J. M., and E. R. Dempster, 1956. An empirical test of part-record selection for egg production. Poultry Sci. 35: 1349-1355. Robertson, A., 1959. Experimental design in the evaluation of genetic parameters. Biometrics,

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15: 219-226. Wilcox, F. H., F. L. Cherms, Jr., L. D. VanVleck, W. R. Harvey and C. S. Shaffner, 1963. Estimates of genetic parameters of serum cholesterol level. Poultry Sci. 42: 37-42.

Efficiency in Prediction of Egg Weight from Early Measurements1 N. S. COWEN, 2 B. B. BOHREN AND H. E. MCKEAN 3 Purdue University A gricultural Experiment Station, Lafayette, Indiana (Received for publication October 7, 1963)

A

FTER the introduction of the trap• nest, workers have been endeavoring to establish short-term measures of egg production which accurately predict the annual record. Interest in short-period measures was stimulated after it was shown that increase in expected rates of gain in improving egg production was possible by using pullets as breeders (Lerner and Taylor, 1940; Dempster and Lerner, 1947). Short-term or early measures of egg weight have been investigated as well. The average weight of the first ten eggs has been considered (Maw and Maw, 1932) as a method of estimating annual egg weight. Godfrey (1933) studied the increased predictability of annual egg weight by including body weight at first egg and age at first egg in the regression equation in addition to the mean weight of the first ten eggs. Egg weight measured in November was shown to be a more efficient criterion of selection for April egg weight than beginning egg weight (average weight of the first ten eggs) or 1 Journal Paper No. 2221 of the Purdue University Agricultural Experiment Station. 2 Present Address, Babcock Poultry Farm, Ithaca, New York. 3 Department of Statistics.

than April egg weight because of the reduced generation interval (Lerner and Cruden, 1948). Use of a selection index and auxiliary information on sexual maturity and December body weight slightly increased the expected gain over selection based on November egg weight alone. Close agreement of heritability estimates of November egg weight and April egg weight was found by Lerner (1951) Since early egg weight appears to be a function of age, (Bohren, Rapp and Arvidson, 1952) hatch effects would be included in the November measurements. Therefore, it would be expected that a hatch correction would increase the heritability of November egg weight relative to that for November egg weight uncorrected for hatch date effects. Hatch date effects of an extended hatching season (11 to 17 weeks) upon March egg weight were shown to be negligible (Abplanalp, 1956). March egg weights, containing little or no hatch effects, showed no appreciable improvement for the use of a hatch correction. A similar conclusion was reached by King and Henderson (1954) for March egg weight. The purpose of this study was to investigate the efficiency of predicting a late spring egg weight from age at sexual