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Egg Quality Genetic Variation and Covariation1
MINERAL UPTAKE BY BONE National Research Council, 1954. Nutrient requirements for domestic animals. No. 1, Nutrient requirements for poultry. Palmer, R. F., R. C. Thompson and H. A. Romberg, 19S8. Factors affecting the relative deposition of strontium and calcium in the rat Science, 128: 1505-1506. Ray, R. D., D. E. Stedman and N. K. Wolff, 1956.
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Bone metabolism. III. The effect of various diets on the mobilization of strontium from the rat skeleton. J. Bone Joint Surg. 38-A: 637-654. Wasserman, R. H., and C. L. Comar, 1960. Effect of dietary calcium and phosphorus levels on body burdens of ingested radiostrontium. Proc. Soc. Exp. Biol. Med. 103: 125-129.
Egg Quality Genetic Variation and Covariation1 STEVEN C. KING, 2 J. DAVID MITCHELL, 3 WENDELL H. KYLE 4 AND W. J. STADELMAN3 Poultry Research Branch, Animal Husbandry Research Division, ARS, Regional Poultry Breeding Laboratory, Purdue University, Lafayette, Indiana (Received for publication September 19, 1960)
T
HE time lag between the day an egg is laid and the day the housewife breaks open that egg for consumption is a period of continual loss in albumen quality as it is presently denned. While attempts are being made to shorten the span of time in marketing channels and thus reduce the total loss in albumen quality, it appears that few housewives will obtain eggs averaging less than 7 days old. Egg grading stations have begun to demand eggs of a certain minimum albumen quality and some poultrymen have found themselves without a suitable market when their eggs failed to reach this standard. 'This investigation was conducted as a portion of the cooperative research of the NC-47 Regional Poultry Breeding Project, entitled, "Evaluation of Breeding Systems for Chickens." **It was presented, in part, at the 48th Annual Meeting of the poultry Science Association. 2 Present address: Poultry Research Branch, AHRD, Beltsville, Md. 3 Poultry Science Department, Purdue University, 'Lafayette, Ind. 4 ARS Pioneering Research Laboratory, Population Genetics Institute, Life Science Building, Purdue University, Lafayette, Ind. ** This work was supported in part by a grant from Merck and Company, Rahway, N.J. Agricultural Experiment Station, Purdue University, Journal paper No. 1661.
The purpose of the research reported in this paper was to determine the degree to which albumen quality loss is heritable and to study its relationship with other economic traits in the Regional Cornell Control population. For purposes of our investigation albumen quality loss was measured in Haugh units over a two week storage period, a time interval approximating the current time lag from the hen's laying to consumer use of an egg. While it has been known for some time that albumen quality deteriorates with time, only recently have investigators inquired into the possibility of inherited differences in rate of loss in quality. McClary and Bearse (1956) concluded that heredity had no measurable effect on decline in albumen quality, since they found a genetic correlation between Haugh units of fresh and stored eggs of .94 and .99 in two groups of pullets. However, May, Schmidt and Stadelman (1957) reported a significant interaction between albumen quality loss in storage and strains. The fact that their analysis included a false variable (days), which could have been nested within replications or perhaps better all eight days could have been treated as replications, makes their conclusion subject to doubt. This would
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S. C. KING, J. D. MITCHELL, W.. H. KYLE AND W. J. STADELMAN
imply the existence of hereditary differences pullet flocks of the Regional Cornell Conin rate of albumen quality decline itself or trol population hatched in 1957 and 1958. an important degree of relationship between This randombred control population was initial or stored albumen quality and the established as a replication of the Cornell rate of decline in quality. Kyle and Mitch- Randombred Control population in 1956, ell (1958) showed that the heritability of when pedigreed hatching eggs were obtained albumen quality loss during a two week from all Cornell Randombred breeders in storage period was 0.25 and 0.57 when esti- production. The Cornell Randombreds have mated from sires' and dams' variance com- a broad genetic base as the result of pooling ponents, respectively, in the Regional Cor- a number of prominent commercial strains nell Control population. of White Leghorns, the last cross being Studying the factors influencing albumen made in 1955. Thus, our data were secured quality loss on a phenotypic basis, Mueller from pullets of the second and third gen(1959) concluded that the initial Haugh erations of random breeding in this popuunit score was responsible for 66.4% and lation. Further details on the development egg weight only 0.2% of the variation in and maintenance procedures utilized for quality loss. These two traits plus three this population may be found elsewhere others dealing with internal physical proper- (King, Carson and Doolittle, 1959). ties of the egg accounted for 71.9% of the The pullets from which these data were total variation in loss of Haugh units dur- collected were the progeny of at least 50 ing storage. single male matings each year. In order to These preliminary investigations, then, make it possible to estimate sire by dam seem to indicate that hereditary differences interaction effects a sire shifting procedure in rate of albumen quality decline do exist. was utilized, in which the same 50 males Certainly enough evidence has been accu- and 250 females were mated in two shifts, but a different randomization each shift mulated to warrant further inquiry. Considerable knowledge is available con- was used to assign each male his 5 female cerning the level of heritability of albumen mates. Thus, each male was mated to a quality in fresh eggs. The information rela- total of 10 pullets and each female was tive to genetic relationships with other eco- mated to 2 cockerels during the breeding nomic traits is more fragmentary. Goodman season. Eggs for setting were saved for a and Godfrey (1955), Johnson and Merritt two week period and pedigreed to both (1955), King and Hall (1955) and Yao dam and sire. A minimum of two weeks (1958), all reported negative genetic cor- elapsed from rerandomization of matings relations between albumen quality and egg for the second shift and the beginning of production. Although Johnson and Merritt egg saving again. In 1957 there was a period also reported a small positive correlation in of seven weeks between first and second a population of Barred Plymouth Rocks, it shift hatches, while in 1958 this period beis quite evident that high albumen quality tween hatches was four weeks. Enough pulis generally associated with lower egg pro- lets were banded so that approximately two duction, but the relationship is not very progeny per dam could be housed in each shift. Since not all dams reproduced, the high. actual number of pullets housed per dam MATERIALS AND METHODS was somewhat higher as will be seen later. The results reported in this paper were Our investigation of albumen quality loss obtained by analysis of data collected on involved sampling eggs for egg quality
967
EGG QUALITY VARIATION
measurements during a two week period beginning at the time the pullets reached 32 weeks of age. October, November or December were the months when this occurred. Eggs were saved on each of six days in two successive weeks. Sunday, Tuesday and Thursday eggs were broken on the following day, having been stored overnight at 5S°F. and a relative humidity of approximately 7 5 % . The alternate Monday, Wednesday and Friday eggs were stored for a two week period in the same egg room before being broken out for egg quality measurement. Egg weights and albumen heights were recorded after which Haugh units were calculated. At the same time a subjective scoring of yolk mottling was carried out, where the scores ranged from 0 for no yolk mottling to 9 for very severe mottling. As a part of other studies data were available at the end of the year on several economic traits so that correlation analyses could be made. Having broken out 12 days' eggs, the average Haugh units on 6 days' fresh eggs and 6 days' stored eggs were computed for each pullet. A total of approximately 20,000 eggs were broken; however, some pullets were later excluded from this study because they had only fresh eggs broken or only stored eggs broken. Table 1 gives further details about the population sizes for both breeder parents and their progeny. Two measures of albumen quality loss were considered in this study. The first was the actual Haugh units lost, determined from Haugh units fresh minus Haugh units stored for each pullet. The second measure was percent Haugh units stored of Haugh units fresh. Presumably the latter measure would tend to exclude a possible relationship between initial Haugh units and the number of Haugh units lost. Yolk mottling was scored on both fresh and stored eggs. In addition the change in yolk mottling was studied, both in terms of ac-
TABLE 1.—Typical analysis of variance Source
.Ari
.ACQ
Shifts Sires Dams Sire X Dam Interaction Full Sibs
1 50 184
1 54 181
62 489
80 528
Total
787
845
Sum of squares A - C . T. S - C . T. D - C . T. S D - S - D + C . T. T - A - S D + C . T. T
tual score units and percentage change. The statistical analyses utilized in this paper were based on the assumption of the linear model: Xhijk
=
ix-\-dh-{-Si-\-dj-\-{sd)ij-\-ehijk
where n is common to all observations, ah to all pullets in the hih shift (also hatch in this case, since there is only one hatch per shift), 5,- to all observations from the •ith sire, dj to all records made by progeny of the jih dam, (sd)ij to all records made by full sib progeny of the jih dam and iih sire. Peculiar to each observation is the random error euik- I t is assumed t h a t except for ix, all elements of the model are uncorrelated variables with zero means and variances
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S. C. KING, J. D. MITCHELL, W. H. KYLE AND W. J. STADELMAN TABLE 2.—Summary of derivation of genetic variances from variance components
Components
Fractions of genetic variance contained (2 loci)* f> ft-ft ft-^ w
a "
Sire ov Dam ov2 Sire X Dam aJ Within Full Sibs a? Environment
o
o"io } i
9
9
cr 2 o a YS YS \ f |
cor \
i \
f 1
1
9
o
an
iroi Sex-linked effects Maternal effects
i f i 1
TS ft f 1
(Sex-linked effects Maternal effects)
* trio2 = additive,
ing the sums of squares to their expectations under the assumption of Model II. Solving the resulting set of equations yields estimates of the unknown variances, or covariances in the case of covariance analyses. A more detailed discussion of the method of analysis used may be found in King (1961). Presented in Table 1 is a typical analysis of variance showing the degrees of freedom associated with each source of variance. A prominent peculiarity will be noted in the degrees of freedom associated with the sire by dam interaction. In 1957 and 1958 there were 73 and 48 dams, respectively, that had only one instead of two subclasses filled. This reduces the number of degrees of freedom in the sire X dam interaction by the same amount, thus the relatively low number of degrees of freedom for this source of variation. Clearly, any additional steps that could be taken to insure a higher proportion of dams with records on progeny from both their sire mates are highly desirable in increasing the efficiency of estimating variance components in this type of experiment. Presented in Table 2 is a summary of the portions of genetic parameters contained in each of the variance components estimated from an analysis of the type
just described. Jerome, Henderson and King (1956) discuss in detail the derivation of these genetic parameters where their design and analysis was quite similar to ours. I t is important to note that &s2 and a / are both estimates of the same genetic variances except that cs2 includes sex-linked effects and a£ includes maternal effects. Recall that in the nested classification (King and Henderson, 1954) ai contains, in addition to the genetic variances shown here, the dominance and other non-additive variances shown in Table 2 for o„i. The difference between the sire component and the dam component of variance,
Heritability estimates are presented in Table 3 by traits and year. In calculating estimates of genetic parameters the denominator, frp2 did not contain aa2, the variance due to shifts or hatches. Whether
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EGG QUALITY VARIATION
albumen quality loss Was measured in terms of Haugh units lost during storage, of percent stored of fresh Haugh units, the heritability appears to be approximately the same. However, the measurement of albumen quality loss in terms of pefcent stored of fresh seems to result in somewhat higher estimates of genetic variation, especially variation due to dominance. While there was a greater pof tion of genetic variation due to dominance in 1958 than in 1957, the total genetic variation was about the same for both years as may be seen by the similarity of the estimates of variance due to the environment. Of considerable interest is the fairly large source of variation due to dominance and other non-additive effects which average out to be higher than the heritability due to additive effects. The mean Haugh units lost in storage was nearly identical between years. The heritability of albumen quality itself was very high, being .61 for both Haugh units fresh and stored. In spite of
the lower mean value of Haugh units stored, the phenotypic variance, ap2, was higher than for Haugh units fresh and with the heritabilities being the same, there was a higher genetic variance for use in selection. The Haugh unit value of both fresh and stored eggs was slightly higher in 1958 than in 1957. It is interesting to note that the slightly negative estimates of dominance for Haugh units fresh or stored in the 1957 data were accompanied by higher than expected estimates of heritability based on the dam component, when compared with the estimates derived from the sire component. This is not an entirely unexpected result in view of the nature of the analysis and our experience with other estimation problems of a similar nature. Note that the analysis of the 1958 data apparently overestimates the dominance fraction and underestimates the dams' additive fraction of genetic variance for Haugh units of both fresh and stored eggs, just the opposite of the 1957 data.
TABLE 3.—Estimates of heritability, environment, variance and means* Trait H. U. Loss Stored/fresh H. U. Fresh H. U. Stored Mottling Change** Mottling, Fresh Mottling, Stored
1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av.
, , , 4£s2 4£ d 2 i k » =ziT' ^ = T T " , h,d Op Op !
hi
h?
0.32 0.31 0.09 0.14 0.22 0.23 0.37 0.34 0.19 0.12 0.28 0.23 0.67 0.83 0.70 0.25 0.680.55 0.69 0.85 0.62 0.30 0.66 , 0.57 -0.01 0.15 -0.01 0.04 -0.01 0.10 -0.17 -0.64 -0.14 0.04 -0.16 -0.36 -0.07 0.25 0.08 -0.20 0.00 0.04 =
4S- S r f 2
—r,
V
W=
0.20 0.43 0.31 0.31 0.57 0.44 -0.13 0.40 0.13 -0.02 0.49 0.240.22 0.40 0.30 1.36 0.73 1.10 0.40 0.69 0.53
0.48 0.46 0.47 0.35 0.28 0.31 0.38 0.12 0.26 0.25 0.05 0.15 0.71 0.59 0.65 0.05 0.31 0.02 0.51 0.37 0.45
av arp2
Sgore units ffom 0 to 9 with 0 = n o mottling and 9 = severe mottjing,
16.20 14.34 15.27 24.01 22.42 23.21 34.69 33.75 34.17 43.54 45.22 44.38 0.58 0.49 0.54 0.22 0.16 0.19 0.46 0.39 0.42
16.09 16.19 16.14 80.51 80.59 80.55 82.76 83.55 83.16 66.66 67.36 67.01 1.53 0.91 1.22 0.59 0.73 0.66 2.12 1.64 1.88
H. U. H. U. H. U.
% % % H. U. H. H. H. H. H.
U. U. U. U. U.
s. s. s. s. s. s. s. s. s.
u. u. u. u. u. u. u. u. u.
970
S. C.
K I N G , J.
D.
MITCHELL,
T A B L E 4.—-Correlations between albumen loss and other traits measured* H . U. Loss and
"',
% Stored of Fresh H. U. Fresh H. U. Stored 32 Wk. Egg Wt. Age 1st Egg % Prod. Early % Prod. Year 32 Wk. Body Wt. June, USDA Score
— .89 .13 .45 .77 - .18 .00 .51 .40 .03
'd
'sd
r
W.'. H.
quality
'i
'p
-.88 -.17 -.52 .82 .01 .52 .20 .97 -.31
-1.03 .21 .80 .82 -1.22 .21 .03 -.90 .51
-.97 .60 -.35 .64 .16 .04 .02 .30 -.02
-.95 .11 -.49 .22 -.08 .17 .12 .22 .05
.61 .87 -.72 .15 -.64 -.38 -.85 -.10
1.49 1.36 1.51 .69 -.25 .06 .53 -.03
-1.31 - .57 -3.01 - .08 .03 .02 -.26 -.36
.06 .64 -.30 .14 -.20 -.14 -.21 -.23
% Stored Fresh and H. U. Fresh H. U. Stored 32 Wk. Egg Wt. Age 1st Egg % Prod. Early % Prod. Year 32 Wk. Body Wt. June, USDA Score
.54 .78 .55 .37 .16 .59 .35 - .55
* r s =genetic correlation estimated from and variance components. Similarly, Yd from from the sireXdam covariance and variance is an estimate of the environmental co-relation mate of the phenotypic correlation.
sire covariance the dam and rsj components. re and rPis an esti-
In running a check on our procedures, reported in more detail in King (1961), a machine error caused a single observation to be included twice in one of the sire by dam subclass totals. This, of course, caused the SD subclass sum of squares to be much too large and upon solution of the simultaneous equations, the estimate of a£, was approximately six times larger than expected while the estimate of CT.,/, was negative and about the same magnitude. However, the estimate of as2 was hardly changed at all when the corrected analysis was completed. This serves to illustrate the degree of dependence between estimates and points u p the possible effect which chance alone m a y have on estimates of other parameters when one sum of squares (right hand member of a simultaneous equation) happens to be larger or smaller than usual. For this reason it is particularly important to look for a counteracting deviate in other genetic parameter estimates, when one of the estimates appears to be unrealistic. The discussion in the foregoing paragraph is perhaps best illustrated in the estimates of genetic parameters presented
K Y L E AND W.
J.
STADELMAN
in Table 3 for yolk mottling. In particular, note the estimates for mottling fresh, where hi and hi are both negative and hs/ is highly positive. In all probability there is little, if any, additive genetic variance for yolk mottling of fresh eggs in this population. By the same token, there is little evidence for additive genetic variation in yolk mottling of stored eggs or change in mottling during storage. Possibly there is some dominance variation, but in view of the frequent negative estimates of additive genetic variance, we would have little confidence in such a conclusion. The mean yolk mottling score and phenotypic variances were so small that any genetic variance that may exist would be of little consequence. Thus, no genetic correlations were estimated for yolk mottling. An analysis of covariance components was completed for albumen quality loss and other economic traits. The results are presented in Table 4 in the form of estimates of genetic, environmental and phenotypic correlations averaged over years. Possibly the results by years would be of interest, but this involves such a voluminous amount of material t h a t it was decided to present only the average results with text comments being utilized to emphasize any consistency or inconsistency of yearly estimates. Clearly, there is a high genetic correlation between Haugh units lost in storage and percent stored of fresh Haugh units. The results between years were amazingly consistent, giving one confidence in the reliability of these estimates. I t is interesting to note that while percent stored of fresh Haugh units was utilized in order to guard against the possibility of Haugh unit loss being dependent on initial Haugh unit value, actually there is a small positive phenotypic correlation between Haugh units fresh and both Haugh unit
EGG QUALITY VARIATION
loss and percent stored of fresh Haugh units. However, this means t h a t eggs with higher Haugh units tend to have greater loss, but when expressed in terms of percent stored of fresh they have less loss. In view of the low magnitude of these correlations, it is doubted whether there is any real advantage in considering percent stored of fresh Haugh units over the actual loss in Haugh units. Of more interest is the consistent result t h a t the genetic correlations between albumen quality loss in storage and initial albumen quality would indicate t h a t genes causing high initial albumen quality also tend to maintain albumen quality better during storage. Therefore, breeding for high initial albumen quality would not be antagonistic to maintaining minimum storage loss in this population. Some comment must be interjected at this point concerning the nature of the correlations between the measures of albumen quality utilized in this investigation. All of them exhibit part-whole relationships, directly or indirectly, so t h a t the spurious or automatic nature of these correlations must be recognized in evaluating the various correlations between albumen quality traits. The fact t h a t the genetic correlation between albumen quality loss and the Haugh unit value of fresh eggs was negative, and thus opposite in sign to t h a t expected on the basis of its part-whole relationship, lends support to the significance of this result. The relatively high genetic and phenotypic correlations between the various methods of measuring albumen quality loss in storage is not unexpected, then. Rather surprising is the high correlation between egg weight and Haugh units loss or percent stored of fresh Haugh units. I t is particularly surprising because the correlations from sire or dam covariance components indicate t h a t larger eggs
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have greater losses of albumen quality in storage (due to additive genetic effects), while the sire by dam component (due to dominance effects) seems to indicate t h a t just the opposite holds, where larger eggs tend to have lesser losses in storage. This result is consistent between years and method of determining the trait, albumen quality loss in storage. Because of rather inconsistent results between years, methods of measuring albumen quality loss and which covariance component was used in estimation, it is doubtful whether the small genetic correlations between age at first egg and albumen quality loss mean anything. The genetic correlation between albumen quality loss and egg production (whether part year or whole year) appears to present an antagonism to the breeder, since higher egg production is associated with genes for higher albumen quality loss. Body weight presents about the same picture as egg weight, the genetic correlations being of about the same magnitude and also showing a consistent opposite sign for the correlations due to additive genetic effects as compared to t h a t due to dominance effects. Large body size is associated with greater albumen quality loss in storage for additive genes, but just the opposite relationship is shown for dominance effects. Correlations between albumen quality (both fresh and stored) and other economic traits also were computed and will be found in Table 5. I t is interesting t h a t our genetic correlations between Haugh units fresh and stored, ts and u, were .94 and .92, respectively and agree very closely with one of the estimates (.94) of McClary and Bearse (1956). Recall t h a t in spite of the high genetic correlation between Haugh units fresh and stored, we found heritable differences in albumen quality loss. The correlation {tsa) was .79,
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S. C. K I N G , J. D. M I T C H E L L ,
W.. H. K Y L E AND W. J. STADELMAN
TABLE S.—Correlations between albumen quality and other economic traits H. U. Fresh and
^ r,
H. U. Stored .94 32 Wk. Egg W t . .30 Age 1st Egg .40 % Prod. Early -.33 % Prod. Year -.30 32 Wk. Body W t . .03 June, USDA Score - 1 . 1 4
A
'd
'sd
.92 .32 .33 -.34 -.45 .31 -.67
.79 -1.48 -1.59 -.38 .69 -1.95 -.28
.52 1.18 .41 .21 .00 .52 -.16
.81 .12 .23 -.13 -.06 .03 -.51
.03 .28 -.49 -.49 -.13 -.51
-.41 -.21 -.39 1.27 1.29 .96
.70 .37 .70 1.32 -1.65 -.96
-.02 .25 -.10 .22 -.21 -.55
'el
r
p
H. U. Stored and 32 Wk. Egg Wt. Age 1st Egg % Prod. Early % Prod. Year 32 Wk. Body W t . June, USDA Score
.01 .42 -.29 -.51 -.13 -1.07
somewhat lower than those due to additive effects, but still high. The rather inconsistent correlations between Haugh units fresh and egg weight lead us to believe t h a t only a small positive genetic correlation exists, if any. This is further confirmed by the lack of consistency and practically zero correlation found between egg weight and Haugh units stored. The inconsistent results for fs and fd probably mean that the figures for fsd are rather meaningless. There appears to be a positive correlation due to additive effects, but a negative correlation due to dominance effects between albumen quality and age at first egg. Clearly, there is cause for concern over the consistent negative genetic correlations between egg production and albumen quality. Our results indicate that the correlation due to additive effects lies somewhere between — .29 and —.49 for early production and between —.30 and —.51 for full year egg production and albumen quality fresh or stored. There is some indication that the correlation due to dominance effects may shift from positive to negative when going from early to full year production; however, this result is not well determined, since full year egg records were not completed for the 1958 data in time for this analysis. There was a fairly high correla-
tion, both genetic and phenotypic, between Haugh units and J u n e USDA albumen scores, some 7 months later; however, only 1957 data were available and the number of pullets with data at both times was markedly reduced. Since Kyle and Mitchell (1958) had already reported some of the 1957 data analyzed in the form of the nested classification, we thought it would be informative to compare t h a t method with the one used in this paper. The comparison is presented in Table 6. I n every case hs2 was higher when the sire variance component was determined over both shifts rather than within shifts. The dam variance component was reduced to the point where hi was slightly less than hs% for both albumen quality loss measurements. The reduction apparently turns up in hsi as expected. Little difference existed in the sire and dam components (nested) for Haugh units fresh and the factorial classification apparently leads to poorer estimates of heritability. For Haugh units stored, the factorial classification resulted in some reduction in the dam component. Perhaps little dominance exists for Haugh units fresh and stored and accounts for the results obtained here. I t is also possible t h a t maternal effects on Haugh units fresh and stored inflated the estimates of hi for t h a t year. I t seems to be a common practice to assume t h a t every new trait t h a t proves to have heritable differences should be added to the repertoire of characters TABLE 6.—Comparison of analyses based on nested and factorial classifications, 1957 data Analysis
£>
W
Nested Factorial Nested Factorial Nested Factorial Nested Factorial
.25 .32 .25 .37 .64 .67 .56 .69
.58 .31 .76 .34 .68 .83 .96 .85
£*i2 .20
— — - . 0— 2 .31
-.13
If .59 .48 .50 .34 .34 .38 .24 .25
EGG QUALITY VARIATION
which each breeder must include in his selection program. Albumen quality loss might be such a character, but we believe some thought should be given to the subject before coming to a conclusion which further complicates an already complex situation for the breeder. As far as albumen quality is concerned the ultimate objective is to provide an egg of high quality at the point of consumption. So long as the quality is high at this stage, it matters little what rate of loss existed during the interval from laying to consumer utilization. Recall t h a t our results indicated t h a t the heritability due to additive genetic variance was .225 for Haugh unit loss and .255 for percent stored of fresh. With the phenotypic variance being 15.3 and 23.2, respectively, the genetic standard deviations would be 1.85 and 2.43. Compare this with Haugh units fresh and stored which had heritabilities of .61 and phenotypic variances of 34.2 and 44.4, respectively. Now the genetic standard deviations are 4.57 and 5.20. Clearly, the opportunity for progress is greatest when selection is practiced on Haugh units stored, which is also the trait of ultimate concern. Further, our results showed a strong negative genetic correlation between Haugh unit loss and Haugh units stored, so t h a t selection for one produces a favorable correlated response in the other. Selection for Haugh units fresh is only slightly less efficient than selection based on stored albumen quality, partly due to the fact t h a t the favorable correlated response on albumen quality loss would probably be somewhat less according to our data. I n addition to the considerations already discussed, one has to remember t h a t dominance deviations play a proportionately much greater role in the genetic variation of albumen quality loss than is
973
the case for either Haugh units fresh or stored. The relatively high estimates of dominance for albumen quality loss (.31 and .44 for Haugh unit loss and percent stored of fresh, respectively), and even the .24 for dominance variation in Haugh units stored, indicates the desirability of being on the lookout for considerable nicking effect when dealing with strain and breed crosses. How to explain the large genetic correlations between albumen quality loss and egg weight or body weight presents a problem. The phenotypic correlations are only one-half to one-third as large as the genetic correlations. I t isn't too difficult to see why the correlations with egg weight and body weight are so similar, because it is a well known fact t h a t there is a close relationship between egg weight and body weight. However, why should large eggs lose albumen quality faster t h a n small eggs? Moreover, why should the genes causing large egg size be associated with greater albumen quality loss, to an extent even greater t h a n indicated b y the phenotypic correlations? One might hypothesize t h a t the greater egg volume o u t p u t taxes the ability of the hen to include sufficient of the factors which tend to maintain albumen quality. Or it m a y be that the larger eggs tend to have more porous shells. However, it may be due to the fact t h a t egg weight is a linear trait, while it is logarithmic in H a u g h units. Assuming t h a t our results are indicative of the true situation, then we have evidence t h a t the genes causing dominance deviations act differently t h a n those causing purely additive genetic variation. Note the opposite signs of t, or fa compared with the r,a correlation for albumen quality loss and egg weight or body weight. Unless these results are atypical of other genetic situations t h a t m a y exist or due entirely to sampling
974
S. C. KING, J. D. MITCHELL, W.'. Ff. KYLE AND W. J. STADELMAN
error, perhaps we should not be too surprised at the difficulties encountered in attempting to change populations through continued selection. Our discussion would not be complete without some comment relative to the applicability of these results to other populations. We emphasize that the Regional Cornell Controls may differ in many respects, to long time closed populations of chickens. For many years it was out of fashion to introduce unrelated stock into a closed flock for fear of disastrous results. With more and more evidence of genetic plateaus, it has become fashionable again to introduce new genetic variation into flocks under selection. For flocks which recently have had their genetic bases broadened, our results may be indicative of what to expect. The relatively, very high heritability of albumen quality in our flock may be an indication of the merit in broadening the genetic base occasionally. While our results are of some value in the early generations of selection in a newly established population such as this one, the real significance is yet to come. Several subsamples from this population have been put under various systems of selection. Heritability studies after some generations of selection should be especially valuable in determining the consequences of selection on the genetic parameters estimated. One can verify whether correlated responses developed as one would predict from these data. SUMMARY The degree to which albumen quality loss in storage is heritable and its relationships with other economic traits was studied. The method of analysis of variance and covariance components was utilized on two years data collected from 106 males, 367 dams and 1,632 progeny. By using a double shift of males in which each cockerel was mated again to a group of females as-
signed under a different randomization than his first group of mates, it was possible to estimate the sire by dam interaction. From this type of analysis estimates of the heritability of additive and non-additive effects could be computed separately. The heritability of albumen quality loss was .225 (additive) and .31 (non-additive) when expressed in terms of Haugh unit loss, and was .225 (additive) and .44 (non-additive) when expressed in terms of percent stored of fresh Haugh units. The heritability of both Haugh units fresh and stored was .61 for additive effects. The heritability due to non-additive effects was .13 and .24, respectively. Yolk mottling, whether expressed as mottling fresh or stored or the difference between fresh and stored exhibited little, if any, additive genetic variation and the relatively high estimates of non-additive variance are believed to be artifacts which result from counteracting the many negative estimates of additive variance A genetic correlation of —.88 between Haugh unit loss and percent stored of fresh indicates little difference in these two methods of measuring albumen quality loss. Haugh units stored is highly correlated with percent stored of fresh Haugh units, which in spite of the spurious nature of this correlation, taken together with its much higher heritability and genetic standard deviation, appears to be the most logical trait to use in selection for better albumen quality at the point of consumption. There was a high correlation due to additive effects between egg size and albumen quality loss, but a high correlation of opposite sign due to non-additive effects. Genetic correlations between body weight and albumen quality loss were similar in size and sign to those between egg size and albumen quality loss. The average genetic correlation between Haugh units fresh and stored was .93, but nevertheless, there still remained consider-
975
EGG QUALITY VARIATION
able genetic variation in albumen quality loss. Our genetic correlations indicated that early sexual maturity is associated with lower egg quality. Similarly, consistent negative correlations between egg production and egg quality were found. REFERENCES Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3 : 1-21. Goodman, B. L., and G. F. Godfrey, 1955. Genetic, phenotypic and environmental correlations between some egg quality traits and egg production and hatchability. Poultry Sci. 34: 1197. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Jerome, F. N., C. R. Henderson and S. C. King, 1956. Heritabilities, gene interactions, and correlations associated with certain traits in the domestic fowl. Poultry Sci. 35: 995-1013. Johnson, A. S., and E. S. Merritt, 1955. Heritability of albumen height and specific gravity of eggs from White Leghorns and Barred Rocks and the correlations of these traits with egg production. Poultry Sci. 34: 578-587.
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 G. 0. Hall, 1955. Egg quality studies at the New York Random Sample Test. Poultry Sci. 34: 799-809. King, S. C , and C. R. Henderson, 1954. Variance components analysis in heritability studies. Poultry Sci. 33 : 147-154. Kyle, W. H., and J. D. Mitchell, 1958. Heritability of the change in egg quality during storage. Poultry Sci. 37: 1219. May, K. N., F. J. Schmidt and W. J. Stadelman, 1957. Strain variation in albumen quality decline of hen's eggs. Poultry Sci. 36: 1376-1379. McClary, C. F., and G. E. Bearse, 1956. The genetic correlation of albumen quality in fresh and stored eggs. Poultry Sci. 35: 1157. Mueller, W. J., 1959. Factors affecting the quality loss in egg albumen during storage. Poultry Sci. 38: 843-846. Yao, K. T. S., 1958. Egg interior quality of purebred, inbred, incross and incrossbred chickens. Poultry Sci. 37: 1254-1255.
Inheritance of Economic Traits in the Regional Cornell Control Population 1 STEVEN C. K I N G 2
Poultry Research Branch, Animal Husbandry Research Division, ARS, Regional Breeding Laboratory, Purdue University, Lafayette, Indiana
Poultry
(Received for publication September 19, 1960)
K
NOWLEDGE of genetic parameters is useful in designing efficient breeding systems. Estimation of genetic parameters raises the problem of suitable material as a source of data. Until recently, genetic pa1 This investigation was conducted as a portion of the cooperative research of the NC-47 Regional Poultry Breeding Project, entitled, "Evaluation of Breeding Systems for Chickens." 2 Present address: Poultry Research Branch, Animal Husbandry Research Division, Beltsville, Maryland.
rameters in poultry populations have been estimated from data collected from inbred lines or selected populations. Estimates obtained from inbred lines have required correction factors in order to compensate for changes in genetic variance due to inbreeding. In addition, few of these inbred lines were developed without considerable natural and/or artificial selection. Estimates obtained from non-inbred populations under artificial selection have ignored, for the most part, the bias which may result from
965
Bone metabolism. III. The effect of various diets on the mobilization of strontium from the rat skeleton. J. Bone Joint Surg. 38-A: 637-654. Wasserman, R. H., and C. L. Comar, 1960. Effect of dietary calcium and phosphorus levels on body burdens of ingested radiostrontium. Proc. Soc. Exp. Biol. Med. 103: 125-129.
Egg Quality Genetic Variation and Covariation1 STEVEN C. KING, 2 J. DAVID MITCHELL, 3 WENDELL H. KYLE 4 AND W. J. STADELMAN3 Poultry Research Branch, Animal Husbandry Research Division, ARS, Regional Poultry Breeding Laboratory, Purdue University, Lafayette, Indiana (Received for publication September 19, 1960)
T
HE time lag between the day an egg is laid and the day the housewife breaks open that egg for consumption is a period of continual loss in albumen quality as it is presently denned. While attempts are being made to shorten the span of time in marketing channels and thus reduce the total loss in albumen quality, it appears that few housewives will obtain eggs averaging less than 7 days old. Egg grading stations have begun to demand eggs of a certain minimum albumen quality and some poultrymen have found themselves without a suitable market when their eggs failed to reach this standard. 'This investigation was conducted as a portion of the cooperative research of the NC-47 Regional Poultry Breeding Project, entitled, "Evaluation of Breeding Systems for Chickens." **It was presented, in part, at the 48th Annual Meeting of the poultry Science Association. 2 Present address: Poultry Research Branch, AHRD, Beltsville, Md. 3 Poultry Science Department, Purdue University, 'Lafayette, Ind. 4 ARS Pioneering Research Laboratory, Population Genetics Institute, Life Science Building, Purdue University, Lafayette, Ind. ** This work was supported in part by a grant from Merck and Company, Rahway, N.J. Agricultural Experiment Station, Purdue University, Journal paper No. 1661.
The purpose of the research reported in this paper was to determine the degree to which albumen quality loss is heritable and to study its relationship with other economic traits in the Regional Cornell Control population. For purposes of our investigation albumen quality loss was measured in Haugh units over a two week storage period, a time interval approximating the current time lag from the hen's laying to consumer use of an egg. While it has been known for some time that albumen quality deteriorates with time, only recently have investigators inquired into the possibility of inherited differences in rate of loss in quality. McClary and Bearse (1956) concluded that heredity had no measurable effect on decline in albumen quality, since they found a genetic correlation between Haugh units of fresh and stored eggs of .94 and .99 in two groups of pullets. However, May, Schmidt and Stadelman (1957) reported a significant interaction between albumen quality loss in storage and strains. The fact that their analysis included a false variable (days), which could have been nested within replications or perhaps better all eight days could have been treated as replications, makes their conclusion subject to doubt. This would
966
S. C. KING, J. D. MITCHELL, W.. H. KYLE AND W. J. STADELMAN
imply the existence of hereditary differences pullet flocks of the Regional Cornell Conin rate of albumen quality decline itself or trol population hatched in 1957 and 1958. an important degree of relationship between This randombred control population was initial or stored albumen quality and the established as a replication of the Cornell rate of decline in quality. Kyle and Mitch- Randombred Control population in 1956, ell (1958) showed that the heritability of when pedigreed hatching eggs were obtained albumen quality loss during a two week from all Cornell Randombred breeders in storage period was 0.25 and 0.57 when esti- production. The Cornell Randombreds have mated from sires' and dams' variance com- a broad genetic base as the result of pooling ponents, respectively, in the Regional Cor- a number of prominent commercial strains nell Control population. of White Leghorns, the last cross being Studying the factors influencing albumen made in 1955. Thus, our data were secured quality loss on a phenotypic basis, Mueller from pullets of the second and third gen(1959) concluded that the initial Haugh erations of random breeding in this popuunit score was responsible for 66.4% and lation. Further details on the development egg weight only 0.2% of the variation in and maintenance procedures utilized for quality loss. These two traits plus three this population may be found elsewhere others dealing with internal physical proper- (King, Carson and Doolittle, 1959). ties of the egg accounted for 71.9% of the The pullets from which these data were total variation in loss of Haugh units dur- collected were the progeny of at least 50 ing storage. single male matings each year. In order to These preliminary investigations, then, make it possible to estimate sire by dam seem to indicate that hereditary differences interaction effects a sire shifting procedure in rate of albumen quality decline do exist. was utilized, in which the same 50 males Certainly enough evidence has been accu- and 250 females were mated in two shifts, but a different randomization each shift mulated to warrant further inquiry. Considerable knowledge is available con- was used to assign each male his 5 female cerning the level of heritability of albumen mates. Thus, each male was mated to a quality in fresh eggs. The information rela- total of 10 pullets and each female was tive to genetic relationships with other eco- mated to 2 cockerels during the breeding nomic traits is more fragmentary. Goodman season. Eggs for setting were saved for a and Godfrey (1955), Johnson and Merritt two week period and pedigreed to both (1955), King and Hall (1955) and Yao dam and sire. A minimum of two weeks (1958), all reported negative genetic cor- elapsed from rerandomization of matings relations between albumen quality and egg for the second shift and the beginning of production. Although Johnson and Merritt egg saving again. In 1957 there was a period also reported a small positive correlation in of seven weeks between first and second a population of Barred Plymouth Rocks, it shift hatches, while in 1958 this period beis quite evident that high albumen quality tween hatches was four weeks. Enough pulis generally associated with lower egg pro- lets were banded so that approximately two duction, but the relationship is not very progeny per dam could be housed in each shift. Since not all dams reproduced, the high. actual number of pullets housed per dam MATERIALS AND METHODS was somewhat higher as will be seen later. The results reported in this paper were Our investigation of albumen quality loss obtained by analysis of data collected on involved sampling eggs for egg quality
967
EGG QUALITY VARIATION
measurements during a two week period beginning at the time the pullets reached 32 weeks of age. October, November or December were the months when this occurred. Eggs were saved on each of six days in two successive weeks. Sunday, Tuesday and Thursday eggs were broken on the following day, having been stored overnight at 5S°F. and a relative humidity of approximately 7 5 % . The alternate Monday, Wednesday and Friday eggs were stored for a two week period in the same egg room before being broken out for egg quality measurement. Egg weights and albumen heights were recorded after which Haugh units were calculated. At the same time a subjective scoring of yolk mottling was carried out, where the scores ranged from 0 for no yolk mottling to 9 for very severe mottling. As a part of other studies data were available at the end of the year on several economic traits so that correlation analyses could be made. Having broken out 12 days' eggs, the average Haugh units on 6 days' fresh eggs and 6 days' stored eggs were computed for each pullet. A total of approximately 20,000 eggs were broken; however, some pullets were later excluded from this study because they had only fresh eggs broken or only stored eggs broken. Table 1 gives further details about the population sizes for both breeder parents and their progeny. Two measures of albumen quality loss were considered in this study. The first was the actual Haugh units lost, determined from Haugh units fresh minus Haugh units stored for each pullet. The second measure was percent Haugh units stored of Haugh units fresh. Presumably the latter measure would tend to exclude a possible relationship between initial Haugh units and the number of Haugh units lost. Yolk mottling was scored on both fresh and stored eggs. In addition the change in yolk mottling was studied, both in terms of ac-
TABLE 1.—Typical analysis of variance Source
.Ari
.ACQ
Shifts Sires Dams Sire X Dam Interaction Full Sibs
1 50 184
1 54 181
62 489
80 528
Total
787
845
Sum of squares A - C . T. S - C . T. D - C . T. S D - S - D + C . T. T - A - S D + C . T. T
tual score units and percentage change. The statistical analyses utilized in this paper were based on the assumption of the linear model: Xhijk
=
ix-\-dh-{-Si-\-dj-\-{sd)ij-\-ehijk
where n is common to all observations, ah to all pullets in the hih shift (also hatch in this case, since there is only one hatch per shift), 5,- to all observations from the •ith sire, dj to all records made by progeny of the jih dam, (sd)ij to all records made by full sib progeny of the jih dam and iih sire. Peculiar to each observation is the random error euik- I t is assumed t h a t except for ix, all elements of the model are uncorrelated variables with zero means and variances
968
S. C. KING, J. D. MITCHELL, W. H. KYLE AND W. J. STADELMAN TABLE 2.—Summary of derivation of genetic variances from variance components
Components
Fractions of genetic variance contained (2 loci)* f> ft-ft ft-^ w
a "
Sire ov Dam ov2 Sire X Dam aJ Within Full Sibs a? Environment
o
o"io } i
9
9
cr 2 o a YS YS \ f |
cor \
i \
f 1
1
9
o
an
iroi Sex-linked effects Maternal effects
i f i 1
TS ft f 1
(Sex-linked effects Maternal effects)
* trio2 = additive,
ing the sums of squares to their expectations under the assumption of Model II. Solving the resulting set of equations yields estimates of the unknown variances, or covariances in the case of covariance analyses. A more detailed discussion of the method of analysis used may be found in King (1961). Presented in Table 1 is a typical analysis of variance showing the degrees of freedom associated with each source of variance. A prominent peculiarity will be noted in the degrees of freedom associated with the sire by dam interaction. In 1957 and 1958 there were 73 and 48 dams, respectively, that had only one instead of two subclasses filled. This reduces the number of degrees of freedom in the sire X dam interaction by the same amount, thus the relatively low number of degrees of freedom for this source of variation. Clearly, any additional steps that could be taken to insure a higher proportion of dams with records on progeny from both their sire mates are highly desirable in increasing the efficiency of estimating variance components in this type of experiment. Presented in Table 2 is a summary of the portions of genetic parameters contained in each of the variance components estimated from an analysis of the type
just described. Jerome, Henderson and King (1956) discuss in detail the derivation of these genetic parameters where their design and analysis was quite similar to ours. I t is important to note that &s2 and a / are both estimates of the same genetic variances except that cs2 includes sex-linked effects and a£ includes maternal effects. Recall that in the nested classification (King and Henderson, 1954) ai contains, in addition to the genetic variances shown here, the dominance and other non-additive variances shown in Table 2 for o„i. The difference between the sire component and the dam component of variance,
Heritability estimates are presented in Table 3 by traits and year. In calculating estimates of genetic parameters the denominator, frp2 did not contain aa2, the variance due to shifts or hatches. Whether
969
EGG QUALITY VARIATION
albumen quality loss Was measured in terms of Haugh units lost during storage, of percent stored of fresh Haugh units, the heritability appears to be approximately the same. However, the measurement of albumen quality loss in terms of pefcent stored of fresh seems to result in somewhat higher estimates of genetic variation, especially variation due to dominance. While there was a greater pof tion of genetic variation due to dominance in 1958 than in 1957, the total genetic variation was about the same for both years as may be seen by the similarity of the estimates of variance due to the environment. Of considerable interest is the fairly large source of variation due to dominance and other non-additive effects which average out to be higher than the heritability due to additive effects. The mean Haugh units lost in storage was nearly identical between years. The heritability of albumen quality itself was very high, being .61 for both Haugh units fresh and stored. In spite of
the lower mean value of Haugh units stored, the phenotypic variance, ap2, was higher than for Haugh units fresh and with the heritabilities being the same, there was a higher genetic variance for use in selection. The Haugh unit value of both fresh and stored eggs was slightly higher in 1958 than in 1957. It is interesting to note that the slightly negative estimates of dominance for Haugh units fresh or stored in the 1957 data were accompanied by higher than expected estimates of heritability based on the dam component, when compared with the estimates derived from the sire component. This is not an entirely unexpected result in view of the nature of the analysis and our experience with other estimation problems of a similar nature. Note that the analysis of the 1958 data apparently overestimates the dominance fraction and underestimates the dams' additive fraction of genetic variance for Haugh units of both fresh and stored eggs, just the opposite of the 1957 data.
TABLE 3.—Estimates of heritability, environment, variance and means* Trait H. U. Loss Stored/fresh H. U. Fresh H. U. Stored Mottling Change** Mottling, Fresh Mottling, Stored
1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av. 1957 1958 Av.
, , , 4£s2 4£ d 2 i k » =ziT' ^ = T T " , h,d Op Op !
hi
h?
0.32 0.31 0.09 0.14 0.22 0.23 0.37 0.34 0.19 0.12 0.28 0.23 0.67 0.83 0.70 0.25 0.680.55 0.69 0.85 0.62 0.30 0.66 , 0.57 -0.01 0.15 -0.01 0.04 -0.01 0.10 -0.17 -0.64 -0.14 0.04 -0.16 -0.36 -0.07 0.25 0.08 -0.20 0.00 0.04 =
4S- S r f 2
—r,
V
W=
0.20 0.43 0.31 0.31 0.57 0.44 -0.13 0.40 0.13 -0.02 0.49 0.240.22 0.40 0.30 1.36 0.73 1.10 0.40 0.69 0.53
0.48 0.46 0.47 0.35 0.28 0.31 0.38 0.12 0.26 0.25 0.05 0.15 0.71 0.59 0.65 0.05 0.31 0.02 0.51 0.37 0.45
av arp2
Sgore units ffom 0 to 9 with 0 = n o mottling and 9 = severe mottjing,
16.20 14.34 15.27 24.01 22.42 23.21 34.69 33.75 34.17 43.54 45.22 44.38 0.58 0.49 0.54 0.22 0.16 0.19 0.46 0.39 0.42
16.09 16.19 16.14 80.51 80.59 80.55 82.76 83.55 83.16 66.66 67.36 67.01 1.53 0.91 1.22 0.59 0.73 0.66 2.12 1.64 1.88
H. U. H. U. H. U.
% % % H. U. H. H. H. H. H.
U. U. U. U. U.
s. s. s. s. s. s. s. s. s.
u. u. u. u. u. u. u. u. u.
970
S. C.
K I N G , J.
D.
MITCHELL,
T A B L E 4.—-Correlations between albumen loss and other traits measured* H . U. Loss and
"',
% Stored of Fresh H. U. Fresh H. U. Stored 32 Wk. Egg Wt. Age 1st Egg % Prod. Early % Prod. Year 32 Wk. Body Wt. June, USDA Score
— .89 .13 .45 .77 - .18 .00 .51 .40 .03
'd
'sd
r
W.'. H.
quality
'i
'p
-.88 -.17 -.52 .82 .01 .52 .20 .97 -.31
-1.03 .21 .80 .82 -1.22 .21 .03 -.90 .51
-.97 .60 -.35 .64 .16 .04 .02 .30 -.02
-.95 .11 -.49 .22 -.08 .17 .12 .22 .05
.61 .87 -.72 .15 -.64 -.38 -.85 -.10
1.49 1.36 1.51 .69 -.25 .06 .53 -.03
-1.31 - .57 -3.01 - .08 .03 .02 -.26 -.36
.06 .64 -.30 .14 -.20 -.14 -.21 -.23
% Stored Fresh and H. U. Fresh H. U. Stored 32 Wk. Egg Wt. Age 1st Egg % Prod. Early % Prod. Year 32 Wk. Body Wt. June, USDA Score
.54 .78 .55 .37 .16 .59 .35 - .55
* r s =genetic correlation estimated from and variance components. Similarly, Yd from from the sireXdam covariance and variance is an estimate of the environmental co-relation mate of the phenotypic correlation.
sire covariance the dam and rsj components. re and rPis an esti-
In running a check on our procedures, reported in more detail in King (1961), a machine error caused a single observation to be included twice in one of the sire by dam subclass totals. This, of course, caused the SD subclass sum of squares to be much too large and upon solution of the simultaneous equations, the estimate of a£, was approximately six times larger than expected while the estimate of CT.,/, was negative and about the same magnitude. However, the estimate of as2 was hardly changed at all when the corrected analysis was completed. This serves to illustrate the degree of dependence between estimates and points u p the possible effect which chance alone m a y have on estimates of other parameters when one sum of squares (right hand member of a simultaneous equation) happens to be larger or smaller than usual. For this reason it is particularly important to look for a counteracting deviate in other genetic parameter estimates, when one of the estimates appears to be unrealistic. The discussion in the foregoing paragraph is perhaps best illustrated in the estimates of genetic parameters presented
K Y L E AND W.
J.
STADELMAN
in Table 3 for yolk mottling. In particular, note the estimates for mottling fresh, where hi and hi are both negative and hs/ is highly positive. In all probability there is little, if any, additive genetic variance for yolk mottling of fresh eggs in this population. By the same token, there is little evidence for additive genetic variation in yolk mottling of stored eggs or change in mottling during storage. Possibly there is some dominance variation, but in view of the frequent negative estimates of additive genetic variance, we would have little confidence in such a conclusion. The mean yolk mottling score and phenotypic variances were so small that any genetic variance that may exist would be of little consequence. Thus, no genetic correlations were estimated for yolk mottling. An analysis of covariance components was completed for albumen quality loss and other economic traits. The results are presented in Table 4 in the form of estimates of genetic, environmental and phenotypic correlations averaged over years. Possibly the results by years would be of interest, but this involves such a voluminous amount of material t h a t it was decided to present only the average results with text comments being utilized to emphasize any consistency or inconsistency of yearly estimates. Clearly, there is a high genetic correlation between Haugh units lost in storage and percent stored of fresh Haugh units. The results between years were amazingly consistent, giving one confidence in the reliability of these estimates. I t is interesting to note that while percent stored of fresh Haugh units was utilized in order to guard against the possibility of Haugh unit loss being dependent on initial Haugh unit value, actually there is a small positive phenotypic correlation between Haugh units fresh and both Haugh unit
EGG QUALITY VARIATION
loss and percent stored of fresh Haugh units. However, this means t h a t eggs with higher Haugh units tend to have greater loss, but when expressed in terms of percent stored of fresh they have less loss. In view of the low magnitude of these correlations, it is doubted whether there is any real advantage in considering percent stored of fresh Haugh units over the actual loss in Haugh units. Of more interest is the consistent result t h a t the genetic correlations between albumen quality loss in storage and initial albumen quality would indicate t h a t genes causing high initial albumen quality also tend to maintain albumen quality better during storage. Therefore, breeding for high initial albumen quality would not be antagonistic to maintaining minimum storage loss in this population. Some comment must be interjected at this point concerning the nature of the correlations between the measures of albumen quality utilized in this investigation. All of them exhibit part-whole relationships, directly or indirectly, so t h a t the spurious or automatic nature of these correlations must be recognized in evaluating the various correlations between albumen quality traits. The fact t h a t the genetic correlation between albumen quality loss and the Haugh unit value of fresh eggs was negative, and thus opposite in sign to t h a t expected on the basis of its part-whole relationship, lends support to the significance of this result. The relatively high genetic and phenotypic correlations between the various methods of measuring albumen quality loss in storage is not unexpected, then. Rather surprising is the high correlation between egg weight and Haugh units loss or percent stored of fresh Haugh units. I t is particularly surprising because the correlations from sire or dam covariance components indicate t h a t larger eggs
971
have greater losses of albumen quality in storage (due to additive genetic effects), while the sire by dam component (due to dominance effects) seems to indicate t h a t just the opposite holds, where larger eggs tend to have lesser losses in storage. This result is consistent between years and method of determining the trait, albumen quality loss in storage. Because of rather inconsistent results between years, methods of measuring albumen quality loss and which covariance component was used in estimation, it is doubtful whether the small genetic correlations between age at first egg and albumen quality loss mean anything. The genetic correlation between albumen quality loss and egg production (whether part year or whole year) appears to present an antagonism to the breeder, since higher egg production is associated with genes for higher albumen quality loss. Body weight presents about the same picture as egg weight, the genetic correlations being of about the same magnitude and also showing a consistent opposite sign for the correlations due to additive genetic effects as compared to t h a t due to dominance effects. Large body size is associated with greater albumen quality loss in storage for additive genes, but just the opposite relationship is shown for dominance effects. Correlations between albumen quality (both fresh and stored) and other economic traits also were computed and will be found in Table 5. I t is interesting t h a t our genetic correlations between Haugh units fresh and stored, ts and u, were .94 and .92, respectively and agree very closely with one of the estimates (.94) of McClary and Bearse (1956). Recall t h a t in spite of the high genetic correlation between Haugh units fresh and stored, we found heritable differences in albumen quality loss. The correlation {tsa) was .79,
972
S. C. K I N G , J. D. M I T C H E L L ,
W.. H. K Y L E AND W. J. STADELMAN
TABLE S.—Correlations between albumen quality and other economic traits H. U. Fresh and
^ r,
H. U. Stored .94 32 Wk. Egg W t . .30 Age 1st Egg .40 % Prod. Early -.33 % Prod. Year -.30 32 Wk. Body W t . .03 June, USDA Score - 1 . 1 4
A
'd
'sd
.92 .32 .33 -.34 -.45 .31 -.67
.79 -1.48 -1.59 -.38 .69 -1.95 -.28
.52 1.18 .41 .21 .00 .52 -.16
.81 .12 .23 -.13 -.06 .03 -.51
.03 .28 -.49 -.49 -.13 -.51
-.41 -.21 -.39 1.27 1.29 .96
.70 .37 .70 1.32 -1.65 -.96
-.02 .25 -.10 .22 -.21 -.55
'el
r
p
H. U. Stored and 32 Wk. Egg Wt. Age 1st Egg % Prod. Early % Prod. Year 32 Wk. Body W t . June, USDA Score
.01 .42 -.29 -.51 -.13 -1.07
somewhat lower than those due to additive effects, but still high. The rather inconsistent correlations between Haugh units fresh and egg weight lead us to believe t h a t only a small positive genetic correlation exists, if any. This is further confirmed by the lack of consistency and practically zero correlation found between egg weight and Haugh units stored. The inconsistent results for fs and fd probably mean that the figures for fsd are rather meaningless. There appears to be a positive correlation due to additive effects, but a negative correlation due to dominance effects between albumen quality and age at first egg. Clearly, there is cause for concern over the consistent negative genetic correlations between egg production and albumen quality. Our results indicate that the correlation due to additive effects lies somewhere between — .29 and —.49 for early production and between —.30 and —.51 for full year egg production and albumen quality fresh or stored. There is some indication that the correlation due to dominance effects may shift from positive to negative when going from early to full year production; however, this result is not well determined, since full year egg records were not completed for the 1958 data in time for this analysis. There was a fairly high correla-
tion, both genetic and phenotypic, between Haugh units and J u n e USDA albumen scores, some 7 months later; however, only 1957 data were available and the number of pullets with data at both times was markedly reduced. Since Kyle and Mitchell (1958) had already reported some of the 1957 data analyzed in the form of the nested classification, we thought it would be informative to compare t h a t method with the one used in this paper. The comparison is presented in Table 6. I n every case hs2 was higher when the sire variance component was determined over both shifts rather than within shifts. The dam variance component was reduced to the point where hi was slightly less than hs% for both albumen quality loss measurements. The reduction apparently turns up in hsi as expected. Little difference existed in the sire and dam components (nested) for Haugh units fresh and the factorial classification apparently leads to poorer estimates of heritability. For Haugh units stored, the factorial classification resulted in some reduction in the dam component. Perhaps little dominance exists for Haugh units fresh and stored and accounts for the results obtained here. I t is also possible t h a t maternal effects on Haugh units fresh and stored inflated the estimates of hi for t h a t year. I t seems to be a common practice to assume t h a t every new trait t h a t proves to have heritable differences should be added to the repertoire of characters TABLE 6.—Comparison of analyses based on nested and factorial classifications, 1957 data Analysis
£>
W
Nested Factorial Nested Factorial Nested Factorial Nested Factorial
.25 .32 .25 .37 .64 .67 .56 .69
.58 .31 .76 .34 .68 .83 .96 .85
£*i2 .20
— — - . 0— 2 .31
-.13
If .59 .48 .50 .34 .34 .38 .24 .25
EGG QUALITY VARIATION
which each breeder must include in his selection program. Albumen quality loss might be such a character, but we believe some thought should be given to the subject before coming to a conclusion which further complicates an already complex situation for the breeder. As far as albumen quality is concerned the ultimate objective is to provide an egg of high quality at the point of consumption. So long as the quality is high at this stage, it matters little what rate of loss existed during the interval from laying to consumer utilization. Recall t h a t our results indicated t h a t the heritability due to additive genetic variance was .225 for Haugh unit loss and .255 for percent stored of fresh. With the phenotypic variance being 15.3 and 23.2, respectively, the genetic standard deviations would be 1.85 and 2.43. Compare this with Haugh units fresh and stored which had heritabilities of .61 and phenotypic variances of 34.2 and 44.4, respectively. Now the genetic standard deviations are 4.57 and 5.20. Clearly, the opportunity for progress is greatest when selection is practiced on Haugh units stored, which is also the trait of ultimate concern. Further, our results showed a strong negative genetic correlation between Haugh unit loss and Haugh units stored, so t h a t selection for one produces a favorable correlated response in the other. Selection for Haugh units fresh is only slightly less efficient than selection based on stored albumen quality, partly due to the fact t h a t the favorable correlated response on albumen quality loss would probably be somewhat less according to our data. I n addition to the considerations already discussed, one has to remember t h a t dominance deviations play a proportionately much greater role in the genetic variation of albumen quality loss than is
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the case for either Haugh units fresh or stored. The relatively high estimates of dominance for albumen quality loss (.31 and .44 for Haugh unit loss and percent stored of fresh, respectively), and even the .24 for dominance variation in Haugh units stored, indicates the desirability of being on the lookout for considerable nicking effect when dealing with strain and breed crosses. How to explain the large genetic correlations between albumen quality loss and egg weight or body weight presents a problem. The phenotypic correlations are only one-half to one-third as large as the genetic correlations. I t isn't too difficult to see why the correlations with egg weight and body weight are so similar, because it is a well known fact t h a t there is a close relationship between egg weight and body weight. However, why should large eggs lose albumen quality faster t h a n small eggs? Moreover, why should the genes causing large egg size be associated with greater albumen quality loss, to an extent even greater t h a n indicated b y the phenotypic correlations? One might hypothesize t h a t the greater egg volume o u t p u t taxes the ability of the hen to include sufficient of the factors which tend to maintain albumen quality. Or it m a y be that the larger eggs tend to have more porous shells. However, it may be due to the fact t h a t egg weight is a linear trait, while it is logarithmic in H a u g h units. Assuming t h a t our results are indicative of the true situation, then we have evidence t h a t the genes causing dominance deviations act differently t h a n those causing purely additive genetic variation. Note the opposite signs of t, or fa compared with the r,a correlation for albumen quality loss and egg weight or body weight. Unless these results are atypical of other genetic situations t h a t m a y exist or due entirely to sampling
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S. C. KING, J. D. MITCHELL, W.'. Ff. KYLE AND W. J. STADELMAN
error, perhaps we should not be too surprised at the difficulties encountered in attempting to change populations through continued selection. Our discussion would not be complete without some comment relative to the applicability of these results to other populations. We emphasize that the Regional Cornell Controls may differ in many respects, to long time closed populations of chickens. For many years it was out of fashion to introduce unrelated stock into a closed flock for fear of disastrous results. With more and more evidence of genetic plateaus, it has become fashionable again to introduce new genetic variation into flocks under selection. For flocks which recently have had their genetic bases broadened, our results may be indicative of what to expect. The relatively, very high heritability of albumen quality in our flock may be an indication of the merit in broadening the genetic base occasionally. While our results are of some value in the early generations of selection in a newly established population such as this one, the real significance is yet to come. Several subsamples from this population have been put under various systems of selection. Heritability studies after some generations of selection should be especially valuable in determining the consequences of selection on the genetic parameters estimated. One can verify whether correlated responses developed as one would predict from these data. SUMMARY The degree to which albumen quality loss in storage is heritable and its relationships with other economic traits was studied. The method of analysis of variance and covariance components was utilized on two years data collected from 106 males, 367 dams and 1,632 progeny. By using a double shift of males in which each cockerel was mated again to a group of females as-
signed under a different randomization than his first group of mates, it was possible to estimate the sire by dam interaction. From this type of analysis estimates of the heritability of additive and non-additive effects could be computed separately. The heritability of albumen quality loss was .225 (additive) and .31 (non-additive) when expressed in terms of Haugh unit loss, and was .225 (additive) and .44 (non-additive) when expressed in terms of percent stored of fresh Haugh units. The heritability of both Haugh units fresh and stored was .61 for additive effects. The heritability due to non-additive effects was .13 and .24, respectively. Yolk mottling, whether expressed as mottling fresh or stored or the difference between fresh and stored exhibited little, if any, additive genetic variation and the relatively high estimates of non-additive variance are believed to be artifacts which result from counteracting the many negative estimates of additive variance A genetic correlation of —.88 between Haugh unit loss and percent stored of fresh indicates little difference in these two methods of measuring albumen quality loss. Haugh units stored is highly correlated with percent stored of fresh Haugh units, which in spite of the spurious nature of this correlation, taken together with its much higher heritability and genetic standard deviation, appears to be the most logical trait to use in selection for better albumen quality at the point of consumption. There was a high correlation due to additive effects between egg size and albumen quality loss, but a high correlation of opposite sign due to non-additive effects. Genetic correlations between body weight and albumen quality loss were similar in size and sign to those between egg size and albumen quality loss. The average genetic correlation between Haugh units fresh and stored was .93, but nevertheless, there still remained consider-
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EGG QUALITY VARIATION
able genetic variation in albumen quality loss. Our genetic correlations indicated that early sexual maturity is associated with lower egg quality. Similarly, consistent negative correlations between egg production and egg quality were found. REFERENCES Eisenhart, C , 1947. The assumptions underlying the analysis of variance. Biometrics, 3 : 1-21. Goodman, B. L., and G. F. Godfrey, 1955. Genetic, phenotypic and environmental correlations between some egg quality traits and egg production and hatchability. Poultry Sci. 34: 1197. Henderson, C. R., 1953. Estimation of variance and covariance components. Biometrics, 9: 226-252. Jerome, F. N., C. R. Henderson and S. C. King, 1956. Heritabilities, gene interactions, and correlations associated with certain traits in the domestic fowl. Poultry Sci. 35: 995-1013. Johnson, A. S., and E. S. Merritt, 1955. Heritability of albumen height and specific gravity of eggs from White Leghorns and Barred Rocks and the correlations of these traits with egg production. Poultry Sci. 34: 578-587.
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 G. 0. Hall, 1955. Egg quality studies at the New York Random Sample Test. Poultry Sci. 34: 799-809. King, S. C , and C. R. Henderson, 1954. Variance components analysis in heritability studies. Poultry Sci. 33 : 147-154. Kyle, W. H., and J. D. Mitchell, 1958. Heritability of the change in egg quality during storage. Poultry Sci. 37: 1219. May, K. N., F. J. Schmidt and W. J. Stadelman, 1957. Strain variation in albumen quality decline of hen's eggs. Poultry Sci. 36: 1376-1379. McClary, C. F., and G. E. Bearse, 1956. The genetic correlation of albumen quality in fresh and stored eggs. Poultry Sci. 35: 1157. Mueller, W. J., 1959. Factors affecting the quality loss in egg albumen during storage. Poultry Sci. 38: 843-846. Yao, K. T. S., 1958. Egg interior quality of purebred, inbred, incross and incrossbred chickens. Poultry Sci. 37: 1254-1255.
Inheritance of Economic Traits in the Regional Cornell Control Population 1 STEVEN C. K I N G 2
Poultry Research Branch, Animal Husbandry Research Division, ARS, Regional Breeding Laboratory, Purdue University, Lafayette, Indiana
Poultry
(Received for publication September 19, 1960)
K
NOWLEDGE of genetic parameters is useful in designing efficient breeding systems. Estimation of genetic parameters raises the problem of suitable material as a source of data. Until recently, genetic pa1 This investigation was conducted as a portion of the cooperative research of the NC-47 Regional Poultry Breeding Project, entitled, "Evaluation of Breeding Systems for Chickens." 2 Present address: Poultry Research Branch, Animal Husbandry Research Division, Beltsville, Maryland.
rameters in poultry populations have been estimated from data collected from inbred lines or selected populations. Estimates obtained from inbred lines have required correction factors in order to compensate for changes in genetic variance due to inbreeding. In addition, few of these inbred lines were developed without considerable natural and/or artificial selection. Estimates obtained from non-inbred populations under artificial selection have ignored, for the most part, the bias which may result from