GENETICS
Genetic parameters of egg quality traits on different pedigree layers
with special focus on dynamic stiffness
A. E. Blanco,1 W. Icken, D. Ould-Ali, D. Cavero, and M. Schmutz
Lohmann Tierzucht GmbH, Am Seedeich 9-11, 27472 Cuxhaven, Germany
ABSTRACT Egg quality traits are of utmost importance in layer breeding programs due to their effect
on profitability in the egg production industry and on
the production of quality chicks. Therefore, the aim of
this study was to analyze and estimate genetic parameters of different quality traits: egg weight, breaking
strength, dynamic stiffness (Kdyn), egg shape index,
eggshell thickness, and albumen height. Eggs were obtained from 4 pure lines of birds. Two different tests
were performed: a white breeding program, with eggs
from a male and female line of a white egg layer program that were analyzed at 67 to 70 wk of age, and a
brown breeding program, with eggs from a male and
female line of a brown egg layer program that were
analyzed at 32 to 36 wk of age. In general, heritabilities were moderate to high for all traits (h2 = 0.23
to 0.71). A high genetic correlation was estimated in
both tests between breaking strength and Kdyn (rg =
+0.40 to +0.61). Shell thickness was also positively correlated with breaking strength (rg = +0.50 to +0.63)
and Kdyn (rg = +0.28 to +0.69). These moderate relationships demonstrate that the strength of an egg not
only relies on the shell thickness but also on the quality
and uniformity of eggshell construction. Dynamic stiffness might be preferred for breeding purposes due to
its lower negative genetic correlation with egg weight
and its higher heritability (h2 = 0.35 to 0.70) compared
with breaking strength (h2 = 0.23 to 0.35). Breaking
strength and Kdyn were positively correlated with shape
index, which confirms that round eggs will show higher
shell stability. Therefore, it is necessary to monitor egg
shape to maintain an optimal form.
Key words: layer, breeding, selection, egg quality, genetic parameter
2014 Poultry Science 93:2457–2463
http://dx.doi.org/10.3382/ps.2014-04132
INTRODUCTION
Egg quality is one of the most important requirements of today’s market to guarantee the integrity of
the egg and to reduce the numbers of eggs lost on the
way to the consumer. According to Harms et al. (1996),
approximately 6 to 8% of the total egg production is
not usable or marketable due to the poor quality of
shells. Hunton (1995) observed major financial losses
during routine handling and transport from producer
to retail outlets. Therefore, eggshell stability traits play
a major role because only eggs with an intact shell
are considered salable. Thus, if egg quality, and specifically, eggshell stability, is guaranteed, the layer industry could increase the number of salable eggs produced
by each hen housed. Consequently, techniques for determining eggshell stability such as the measurement
of dynamic stiffness (Kdyn) have been developed and
compared with more traditional measurements of eggshell strength by De Ketelaere et al. (2002), Dunn et
al. (2005), and Icken et al. (2006). According to the
©2014 Poultry Science Association Inc.
Received April 22, 2014.
Accepted June 25, 2014.
1 Corresponding author: [email protected]
last authors, Kdyn, from a breeding point of view, is
preferred to breaking strength (BS) for the following
3 reasons:
1) Its genetic correlation with egg weight (EW; rg
= −0.14) is less negative than between EW and
BS (rg = −0.57).
2) Its heritability (h2 = 0.40) is higher than BS (h2
= 0.10).
3) Dynamic stiffness is a nondestructive measuring
process.
Other traits (e.g., the egg shape index; SI) are becoming increasingly important to maintain a desirable
shape for commercial table eggs (Icken et al., 2006)
as well as to ensure good hatchability. According to
Scholtyssek (1994), an optimal SI is 74, and therefore,
eggs with a higher index (too round) might be confounded when setting in the hatchery, resulting in a
decreased hatchability.
However, egg quality does not only involve external
but also internal characteristics that must be considered within these traits. According to De Ketelaere et
al. (2004), albumen height (AH) is considered to be
the most important internal quality trait, which is of
great relevance in countries such as Japan where the
2457
2458
Blanco et al.
Table 1. Number of laying hens and eggs tested per line1
Item
Hens
Eggs tested
Farm
Number of rows
1Line:
White layers
Brown layers
A
D
A
D
1,177
3,008
1
1
1,192
2,916
1
2
1,494
4,255
2
1
1,488
4,039
2
2
A = male line; D = female line.
Improving shell stability and internal egg quality by
genetic selection is a matter of great importance on
both the production and consumption levels. Therefore,
the aim of the present study was to analyze egg quality
traits as well as their genetic parameters in 2 pure lines
of the breeding program of Lohmann Selected Leghorn
and 2 pure lines of the breeding program of Lohmann
Brown.
MATERIALS AND METHODS
population also consumes raw eggs. Wolc et al. (2012)
reported a heritability of albumen height of h2 = 0.55
that allows the improvement of this trait by means of
selection.
Genetic selection helps to continuously improve the
laying performance, efficiency, livability, and adaptability of the birds to different environments as well as egg
quality (Preisinger and Flock, 2000). For this purpose,
more than 30 different traits are included in the selection index of the laying hen breeding programs. All
traits are closely monitored and their relations to each
other are considered, making it possible for a balanced
genetic progress and improvements in different traits
even when they are negatively correlated with each
other. Estimations of genetic parameters for different
egg quality traits have been reported in literature (Seeland et al., 1995; Dunn et al., 2005; Icken et al., 2006;
Flock et al., 2007). According to Dunn et al. (2005)
and Flock et al. (2007), heritabilities are in a range of
h2 = 0.52 to 0.64 for EW and vary between h2 = 0.33
to 0.53 for Kdyn in brown and white egg layers. Egg
weight is a major criterion in determining the market
price system, and according to Flock et al. (2007), EW
is easily adaptable to the requirements of the market
thanks to its high heritability. Icken et al. (2006) estimated a heritability for Kdyn and SI in pedigreed pure
line hens of Rhode Island Red of h2 = 0.40 and h2 =
0.38, respectively, which were at a higher level than for
shell thickness (ST; h2 = 0.19) and BS (h2 = 0.10). The
heritabilities of these traits are moderate to high and
could therefore be easily improved by selection.
Genetic differences in eggshell formation characteristics are evident between breeds, strains, and families
within the species (Anderson et al., 2004). The significant influence of different strains of laying hens on production level, egg quality traits, and egg size have been
extensively reviewed (Curtis et al., 1985; Silversides
and Scott, 2001; De Ketelaere et al., 2002; Silversides
and Budgell, 2004), as well as the effect of hen age on
eggshell properties (Scholtyssek, 1994; De Ketelaere et
al., 2002; Rodriguez-Navarro et al., 2002). Eggs of older
hens tend to have lower BS (De Ketelaere et al., 2002),
thinner shells but greater AH (Rodríguez-Navarro et
al., 2002), and a bigger size (Scholtyssek, 1994). Anderson et al. (2004) indicated that since the 1950s, genetic
selection is giving rise to larger and rounder eggs with
greater BS, although no differences in the ST have been
observed so far.
Experimental Design
A sample of 14,218 eggs from 2 breeding programs of
Lohmann Tierzucht GmbH was tested for egg quality,
one for white eggs of Lohmann Selected Leghorn and
one for brown eggs of Lohmann Brown. Two lines from
each breeding program were tested: a male line (line A)
and a female line (line D). Egg collection for egg quality measurements took place in 1 d per week during 3
consecutive weeks. The following traits were recorded:
EW, BS, Kdyn, SI, ST, and AH.
All laying hens were housed according to their respective breeding programs on 2 similar breeding farms under identical management conditions (white layer lines
in farm 1 and brown layer lines in farm 2). Each house
was equipped with enriched single bird cages in 4 different rows, each on a 3-tier level (first tier = bottom,
second tier = middle, and third tier = top). Male and
female lines were, however, housed in different rows.
The tested white layers descend from 119 pure line
sires and 798 pure line dams, and the tested brown
layers descend from a higher number of sires (207) and
dams (1,150). Therefore, the average number of hens
per sire was 15 and 20, for brown and white egg lines,
respectively, and 3 offspring per dam over all lines. As
shown in Table 1, a total of 5,924 eggs from 2,369 white
pure line hens (1,177 from line A and 1,192 from line D)
were tested. The age of the white layers tested ranged
between 67 to 70 wk. The white egg layers came from 3
different hatches and were uniformly distributed within
one row on all 3 tiers. A total of 8,294 eggs from 2,982
brown pure line hens (1,494 from line A and 1,488 from
line D) were tested. The brown layers were 32 to 36 wk
of age during testing. The brown egg layers came from
2 different hatches and were housed within one row in
3 different tiers. However, in this case, the majority of
each hatch was housed in one tier.
Egg Quality Traits
Egg weight was measured with a scale calculated in
grams with an accuracy of ±0.01 g. The Kdyn of the
eggs represents the uniformity and strength of the eggshell and provides some hints about the probability of
cracking of the eggshell during transportation (Bain et
al., 2006), which was determined with a device called
the Crack Detector. According to De Ketelaere et al.
(2002), modeling the egg as a mass-spring system, the
dynamic stiffness is given as
GENETIC PARAMETERS OF EGG QUALITY TRAITS
Kdyn = m × RF2 × cte,
with m being the mass of the egg in kilograms, RF the
first resonant frequency of the vibration in Hertz, and
cte a constant = 4 × π2 according to Coucke (1998),
but set to 0.01 in this study for a better visualization
of the data. The lower the Kdyn value, the lower its dynamic stability. The SI was determined with a caliper
and calculated with the formula SI = width × 100/
length. The BS of the eggs at the blunt end of the egg
was measured in Newtons and was determined using
a BS device of Technical Services and Supplies Ltd.
(TSS, York, UK). To determine the ST (mm) in the
equatorial region, a micrometer screw from Mitutoyo
America (Aurora, IL) was used. The eggs were broken
onto a flat glass surface and the height of the albumen
was determined at an approximate distance of 1 cm
from the edge of the yolk using a device of Futura–Werner Fürste (Lohne, Oldenburg, Germany).
Statistical Analysis
Because the layers from the white and the brown
program are completely different strains and had different ages, no comparisons were made between white and
brown egg strains. The analysis was made separately
for the 2 tests (i.e., white and brown layers).
To investigate whether the line of the hens, hatch
week, testing week, or tier level had an influence on the
different egg quality criteria (EW, BS, Kdyn, SI, ST,
and AH), an ANOVA was performed using the MIXED
procedure from the SAS statistical program (SAS Institute Inc., 2004) and applying the following statistical
model:
Yijklmn = µ + Li + Tj + Hk + Wl + am + eijklmn,
where Yijklmn = eggshell quality characteristics (EW,
BS, Kdyn, SI, ST, AH), μ = overall mean, Li = fixed
effect of line, Tj = fixed effect of tier level, Hk = fixed
effect of hatch, Wl = fixed effect of the week of measurement, am = random effect of the animal, and eijklmn
= residual effect.
The normal distribution was assumed for all traits
based on the results obtained with the UNIVARIATE
procedure from SAS. To calculate the phenotypic correlation between these traits, the procedure CORR was
used.
The effect of the tier level did not show any significant differences on the egg quality traits studied in the
variance analysis of the white egg lines. Therefore, this
effect was not included in further analysis. The brown
egg layers of the 2 different hatches were housed in different tiers, and therefore, the effect of the tier level
was not included in any statistical analysis because it
was confounded with hatch.
The variance and covariance components were estimated by using the software VCE 4 (Groeneveld, 1998),
using the restricted maximum likelihood method. For
the genetic analysis, the effects mentioned above and
2459
the full pedigree information of all layers from 4 generations were used. The genetic parameters were estimated
based on the mean of the 3 measurements per hen.
RESULTS AND DISCUSSION
When the egg quality test started, the white layer
hens were 35 wk older than the brown layer hens. Due
to this difference in age and its effect on the eggshell
properties, it was not possible to make any comparison
between white and brown strains. Thus, the analysis
was focused on the comparison between lines (male
and female) within each breeding program (white and
brown strains). It should be noted that at the time in
which the egg quality traits were measured, the average
egg production was 88% in the male line and 86% in
the female line from white layer hens, and 96 and 94%
in male and female line, respectively, from brown layer
hens.
Phenotypic Comparisons
Table 2 shows the average values and standard deviations for all egg quality traits of the white and brown
egg strains. Regardless white or brown egg layers, eggs
of the male line were between 2 and 5 g heavier than
those of the female line. In accordance with Narushin
and Romanov (2002), this is not surprising because female lines are selected for better hatchability. Hatching
eggs achieve the optimal hatchability results when the
EW ranges between 50 to 60 g. Beyond this range,
hatchability decreases with increasing EW within the
line. The negative influence of EW on hatchability was
confirmed by Cavero and Schmutz (2009), who found
a negative correlation between EW and hatchability in
Leghorn layers varying between rg = −0.43 to −0.52,
and suggested to confine the selection for better hatchability to female lines and to select the male lines for
higher EW in the breeding programs for layers. Thus,
it is possible to obtain a good hatchability at the parent stock level and to reach a good EW level in the
commercial hybrid layer. Further differences between
male and female lines were observed in this study for
BS (Table 2). However, the difference of the average BS
between the male and female line within one breed was
higher in the white layers (7 N) than in the brown layers (3 N). Similar to the difference in BS, the average
Kdyn values in the brown breeding program were higher
for the male line compared with the female line. On the
contrary, the average Kdyn value in the white breeding
program was higher for eggs tested from the female
line than those from the male line. The average values
ranged between 145 to 158 in the white egg strains and
from 138 to 159 in the brown egg strains.
As shown in Table 2, there were no differences in ST
between brown male and female lines (ST = 0.35 mm)
from brown egg strains, whereas in white egg strains,
the eggshell of the male line was 0.05 mm thicker than
the average eggshell of the female line. Although the
2460
Blanco et al.
Table 2. Means, SD, as well as minimum (Min) and maximum (Max) values for egg quality traits in 2 breeding programs: white egg
lines (67–70 wk of age) and brown egg lines (32–36 wk of age)
Line A1
Line
Trait2
White egg line
EW (g)
BS (N)
Kdyn
ST (mm)
SI
AH (mm)
EW (g)
BS (N)
Kdyn
ST (mm)
SI
AH (mm)
Brown egg line
1Line:
Line D1
n
Mean
SD
Min
Max
n
Mean
SD
Min
Max
3,001
3,006
2,932
3,008
3,005
3,001
4,223
4,250
4,070
4,255
4,254
4,245
62.4
40,0
145.0
0.36
74.0
5.3
65.3
52.0
159.0
0.35
78.0
6.0
4.8
9.7
18.5
0.04
2.6
1.1
4.8
9.3
18.1
0.03
2.5
1.1
49.0
11.0
91.0
0.21
62.0
2.0
52.0
11.3
93.0
0.21
65.0
2.1
79.4
72.0
212.0
0.85
83.0
10.0
80.0
79.2
229.0
0.63
87.0
10.0
2,916
2,906
2,815
2,915
2,916
2,898
4,038
4,038
3,910
4,039
4,002
4,011
60.3
33.1
158.0
0.31
77.1
6.6
60.0
49.0
138.0
0.35
79.0
6.0
4.0
9.1
17.3
0.04
2.4
1.0
4.1
10.0
18.6
0.03
2.6
1.3
45.3
10.0
90.0
0.18
68.0
2.1
43.3
10.1
90.0
0.22
49.0
2.0
79.0
65.0
226.0
0.67
87.0
10.0
76.0
79.3
205.0
0.56
97.0
10.0
A = male line; D = female line.
EW = egg weight; BS = breaking strength; Kdyn = dynamic stiffness; ST = shell thickness; SI = shape index; AH = albumen height.
2Trait:
measurement of ST is quite labor intensive, data collection on this trait is worthwhile in accordance to Bennett (1992), because the hatchability of thin shell eggs
can be reduced by 3 to 9% as compared with normal
eggshell. The SI was lowest in the male line (SI = 74)
from white layers, which means that these eggs are less
round than the eggs of the female line (SI = 77) and
even more elongated than the average of all the brown
eggs tested (SI = 78 to 79). Egg shape index is a criterion that has to be considered in regard to commercial
table egg production to maintain a desirable shape for
consumers and also for hatching eggs to prevent wrong
placement on the setter trays (Icken et al., 2006). The
influence of SI on hatchability has been discussed in
literature. According to Cavero and Schmutz (2009),
SI (defined as width/length) has a negative correlation with hatchability and rounded eggs will have lower
hatchability, whereas Sahin et al. (2009) did not find
any significant effects of the SI on hatching. Bauer et
al. (1990) observed that the hatchability of eggs incubated with their large ends up was 16 to 27% higher
than eggs incubated with their small ends up. These
authors reported that the frequencies of wrong positioned eggs ranged from 2.3 to 3.4% under commercial
conditions. The percentage of wrong positioned eggs
from the same flock set carefully in the laboratory was
much lower and ranged from 0.22 to 0.37%. Therefore,
it can be expected that under practical conditions in a
hatchery the frequency of wrong positioned eggs will
further increase with rounder eggs, where it is difficult
to distinguish the large and small ends, which negatively affect their hatchability.
The AH values are also presented in Table 2. The
average AH obtained was 6 mm for the brown eggs
of both lines and is therefore in accordance with the
results obtained by Silversides and Scott (2001) in ISA
Brown hens at 31 to 45 wk of age. A lower average
AH (5.3 mm) was measured for the eggs of the male
line from white egg layers, whereas the highest AH was
found in the female line from white egg layers (AH =
6.6 mm).
Variance Analysis
As shown in Table 3, the line (male and female) within each breeding program showed a significant effect
on all measured egg quality traits. Breeds and lines of
the same strain differ in reproductive traits and Curtis
et al. (1985) found that different strains of laying hens
show different eggshell quality, egg size, and level of
production.
The results obtained in this study showed that the
3 different tiers had no significant effects on any egg
quality traits for the white layer hens, which is in accordance with Yildiz et al. (2006) who observed that
the tier level had no effects on EW, ST, or SI. However,
shell strength decreased significantly from the lower
to the upper tier. These authors concluded that the
effect of the tier depends on the design of the house
and cages, which can influence the temperature, light
distribution, and so on. In the present study, the data
were collected in the breeding farm, where conditions
are highly standardized, a uniform climate is provided,
and the birds dispose of a large air space, which might
explain the low impact of the tier level on the different
traits.
The hen’s age has a big influence on egg quality. With
increasing age, EW increases and BS decreases (Rodriguez-Navarro et al., 2002). Due to the different weeks
of hatch and the consequent variation of the hen’s age
of up to 3 wk, the EW was significantly influenced by
the hen’s age in the white and brown egg strains (Table
3), which is also in accordance to Scholtyssek (1994),
who investigated the effects of the hen’s age on the
eggshell quality characteristics. The week of hatch did
not affect the value of Kdyn significantly in white or
brown egg strains. However, the differences in age within the tested lines were very small, and therefore it is
not possible to confirm the conclusion of De Ketelaere
et al. (2002), who observed that Kdyn increases with
age (from 36 to 76 wk) in 6 different strains, except
for Leghorn hens, which produced eggs of a constant
Kdyn. Albumen height was higher in eggs from younger
2461
GENETIC PARAMETERS OF EGG QUALITY TRAITS
Table 3. Repeatability and level of significance of fixed effects for different egg quality traits
Trait1
Line
Effect
EW
BS
Kdyn
ST
White egg line
Repeatability
Line
Tier
Hatch
Week
Repeatability
Line
Hatch
Week
0.75
***
NS
***
***
0.74
***
***
***
0.33
***
NS
NS
***
0.32
***
***
***
0.71
***
NS
NS
***
0.68
***
NS
***
0.36
***
NS
**
***
0.51
**
NS
***
Brown egg line
SI
0.65
***
NS
NS
NS
0.42
***
***
***
AH
0.23
***
NS
***
***
0.36
**
***
***
1Traits: EW = egg weight; BS = breaking strength; K
dyn = dynamic stiffness; ST = shell thickness; SI = shape
index; AH = albumen height.
**P < 0.001.
***P < 0.0001.
layers in accordance to Silversides and Budgell (2004).
Additionally to the effects of the hen’s age, Silversides
and Budgell (2004) and Samli et al. (2005) observed
that by extending the storage period, EW, and AH
would decrease.
The testing week had a significant effect on all the
egg quality traits measured except on the ST from
white layer lines, as indicated in Table 3. In accordance
with the results of De Ketelaere et al. (2002), the eggs
tested from brown layer lines showed a significant increase in EW, whereas ST and BS decreased.
Table 3 also shows the repeatability of the different
traits (on the basis of 3 eggs per hen), representing
the upper limit of the heritability. In both breeding
programs, repeatability in EW (w2 = 0.74 to 0.75) and
Kdyn (w2 = 0.68 to 0.71) were the highest followed by
the SI and ST. The lowest repeatability was estimated
for BS (w2 = 0.32 to 0.33). The heritability of the average BS can thus be increased by efficiently evaluating
more eggs per hen.
Heritabilities and Genetic
and Phenotypic Correlations
Table 4 shows the heritabilities, which were estimated based on the mean of 3 eggs. The heritabilities for
all egg quality traits are very similar for all lines on the
white and brown breeding programs. The SE of the estimated heritabilities were in the range of 0.03 to 0.06.
In regard to the genetic correlations, the picture is less
uniform, and the SE were in the range of 0.04 to 0.12.
The highest heritabilities were estimated for EW (h2
= 0.42 to 0.71). Flock et al. (2007) argued that EW
has a high heritability, and although the EW curve
across the lifetime of an individual cannot be adjusted,
the EW can be easily adaptable to the requirements of
the market through selection of the bird. Furthermore,
high heritabilities were estimated for Kdyn (h2 = 0.35
to 0.70), whereas the heritabilities for BS and ST were
lower with h2 = 0.23 to 0.35 and h2 = 0.27 to 0.44, respectively. These results are in accordance with Dunn
et al. (2005), who estimated the first heritabilities of
Kdyn, which were on a higher level (h2 = 0.33 to 0.53)
than for BS (h2 = 0.15 to 0.18). According to Dunn et
al. (2005), eggshell is a biological material and is therefore influenced by both the environmental and genetic
components.
As shown in Table 4, heritability estimates in this
study for AH were high (h2 = 0.28 to 0.69), especially in the brown egg lines. These estimates are in accordance with the results of Wolc et al. (2012), who
showed a heritability for AH of h2 = 0.55 in a flock of
brown layers. Flock et al. (2007) reported that consistency of albumen has a heritability h2 = 0.20 to 0.30,
which is high enough to provide an improvement in
selection. However, these authors argued that to obtain
the best internal egg quality at the consumer’s level, it
is crucial to guarantee optimal storage conditions and
minimum storage times. Furthermore, selection for better hatchability has a negative correlation with AH and
a positive correlation with SI (SI = length/width), according to Cavero and Schmutz (2009).
Heritability levels for SI in the white layer lines were
moderate (h2 = 0.35 to 0.47), whereas this trait showed
higher heritabilities in the brown layer lines (h2 = 0.56
to 0.58).
As expected, the 3 traits related with shell stability (BS, Kdyn, and ST) were positively correlated with
each other, especially in terms of BS and ST, as shown
in Table 4. The genetic correlation between ST and
BS (rg = +0.50 to +0.78) is consistent with the values
reported by Seeland et al. (1995), who estimated a genetic correlation of rg = +0.37 to +0.40 between the 2
traits. Positive but not that high was the genetic relationship between ST and Kdyn (rg = +0.28 to +0.69),
which is higher than the estimated genetic correlations
of rg = +0.20 by Icken et al. (2006). However, genetic
correlations are similar to the phenotypic relationship
(rp = +0.26 to +0.64) estimated in this study and by
the investigations of De Ketelaere et al. (2002; rp =
+0.56).
In this study, for white and brown egg layers, a positive correlation was found between SI and shell stability
traits (Table 4), which corresponds with the idea that
2462
+0.25
+0.07
−0.38
−0.17
−0.12
−0.03
−0.11
+0.03
+0.24
−0.03
0.69
0.64
+0.01
−0.01
−0.05
+0.17
+0.14
+0.25
−0.04
+0.20
0.56
0.58
+0.23
+0.11
−0.15
+0.01
+0.63
+0.50
+0.42
+0.28
0.44
0.37
−0.03
+0.01
−0.13
−0.07
2Standard
1Standard
AH
SI
ST
Kdyn
BS
errors of the estimated heritabilities were in the range of 0.03 to 0.06.
errors of the estimated genetic correlations were in the range of 0.04 to 0.12.
3Trait: EW = egg weight; BS = breaking strength; K
dyn = dynamic stiffness; ST = shell thickness; SI = shape index; AH = albumen height.
4Line: A = male; D = female.
−0.15
+0.01
+0.40
+0.55
0.70
0.65
+0.35
+0.26
+0.20
+0.13
−0.03
−0.03
−0.19
−0.36
0.35
0.34
+0.33
+0.30
+0.46
+0.41
+0.01
+0.06
−0.19
−0.10
0.65
0.71
−0.19
−0.19
+0.01
+0.06
−0.02
+0.12
+0.04
+0.02
+0.2
+0.15
−0.14
+0.26
+0.31
−0.23
−0.05
+0.19
+0.00
+0.08
+0.00
+0.40
0.32
0.28
+0.09
−0.03
+0.29
+0.27
+0.58
+0.61
+0.20
+0.13
0.35
0.47
+0.12
+0.16
+0.19
+0.10
+0.78
+0.65
+0.69
+0.62
0.27
0.29
+0.05
+0.00
+0.05
+0.14
+0.26
−0.14
+0.55
+0.61
0.43
0.35
+0.53
+0.64
+0.46
+0.42
+0.06
+0.09
−0.19
−0.32
0.23
0.33
+0.47
+0.47
+0.50
+0.50
+0.16
+0.07
+0.04
+0.02
A
D
A
D
A
D
A
D
A
D
A
D
EW
0.49
0.42
−0.08
−0.05
+0.21
+0.12
+0.18
+0.26
+0.04
−0.04
+0.13
+0.20
SI
ST
Kdyn
Line4
Trait3
EW
BS
Kdyn
ST
SI
AH
EW
BS
Brown egg line
White egg line
Table 4. Heritabilities1 (diagonal) and genetic correlations2 (above the diagonal) and phenotypic correlations (below the diagonal) of the different egg quality traits
AH
Blanco et al.
round eggs show higher shell stability. The positive phenotypic and genetic correlations between SI and Kdyn
that were estimated in this study (rp = +0.13 to +0.46
and rg = +0.14 to +0.61) are in accordance with Dunn
et al. (2005), who estimated a negative phenotypic correlation (rp = −0.13) between these traits due to the
different definitions of egg shape (SI = length/width).
Seeland et al. (1995) also found a negligible and negative phenotypic correlation between SI (SI = width/
length) and BS. However, the positive correlation found
in the current study between SI and shell stability is
undesired; thus, SI should be monitored to guarantee
optimum hatchability because more rounded eggs show
a lower hatchability (Cavero and Schmutz, 2009). Egg
shape should therefore be monitored to counteract the
selection for better shell quality to maintain a perfect
egg shape either to produce commercial table eggs or to
ensure good hatchability.
One main selection criterion in layer breeding programs is to increase shell stability and at the same time
to increase egg mass, which means egg numbers multiplied by EW. With the exception of ST and Kdyn in
the male lines from white layers and the female lines
from brown layers, the estimated genetic correlations
between the criteria shell stability and EW were negative and therefore undesired from a breeder’s point
of view. However, due to modern breeding values estimations, including all covariances, it is possible to
generate genetic progress in both parameters despite
negative correlations. However, the higher the negative correlation, the lower the genetic progress that can
be realized in both traits. Therefore, due to the fact
that the negative genetic correlations between BS and
EW (rg = −0.19 to −0.36) were higher than for EW
and Kdyn (rg = −0.15 to +0.26), it would be advantageous to use Kdyn as a selection trait measurement to
achieve an optimal combination of EW and adequate
shell strength. However, the Kdyn value is not suitable
to compare one genetic line with another one and also
not for strain comparisons as it is possible for the traits
BS or ST. Inconsistent genetic correlations between
EW and Kdyn may indicate a nonlinear relationship
between both traits. However, in this study no clear
relationship could be found between EW and the Kdyn
value by examining the plots.
Furthermore, Kdyn cannot be compared across different ages. Contrary to what it would be expected, Kdyn
increases with the hen’s age, which is in contrast with
the age-related changes for BS and for the eggshell stability in general (De Ketelaere et al., 2002). Further investigations should be carried out to clarify this point.
As shown in Table 4, the genetic correlation between
BS and Kdyn (rg = +0.40 to +0.61) is positive, but not
close to 1, which means that the traits are recording
different characteristics of the eggshell. According to
Bain (2005), the eggshell BS captures the maximum
load that can be withstood by an egg and provides
information about the strength required to crack the
eggshell. On the other hand, Kdyn is based on acoustic
GENETIC PARAMETERS OF EGG QUALITY TRAITS
resonance test and offers information about the uniformity and eggshell strength, as well as the probability
of egg cracking (Bain et al., 2006). As stated by De
Ketelaere et al. (2002), the strength of an egg not only
depends on its shape and ST but also on the quality of
its construction. Thus, from a breeder’s point of view
it is worthwhile to include both traits into the selection
index. Combining both criteria in the selection process
will further increase breeding progress on eggshell stability.
Additionally, even though the ST and BS heritabilities are similar, the coefficient of variation is lower for
ST than for BS or Kdyn. Besides, measuring ST is very
labor intensive as compared with other shell stability
criteria. It can therefore be concluded that including
ST into the selection index will not guarantee very
much additional genetic progress in shell stability. It
also needs to be borne in mind that integrating another
trait into the index reduces the selection pressure on
other selection criteria.
The correlations estimated between the different egg
quality traits in this study are not always desired from
a breeding point of view. Therefore, special care should
be taken to monitor and to take all traits and their
genetic correlations into account to achieve a balanced
genetic progress. It can be concluded that the results
obtained in this study confirm the relatively high heritabilities for all egg quality traits in the pure lines
analyzed, which guarantee a good genetic response by
including them in the breeding program. Continuous
genetic progress can be guaranteed even in future generations, which gives the commercial egg producer the
possibility to increase the production cycle length and
to generate more revenue per hen housed. Although
these lines have been under intensive selection for more
than 50 yr now, there are still plenty of genetic variations.
REFERENCES
Anderson, K. E., J. B. Tharrington, P. A. Curtis, and F. T. Jones.
2004. Shell characteristics of eggs from historic strains of Single
Comb White Leghorn chickens and the relationship of egg shape
to shell strength. Int. J. Poult. Sci. 3:17–19.
Bain, M. M. 2005. Recent advances in the assessment of eggshell
quality and their future application. World’s Poult. Sci. J.
61:268–277.
Bain, M. M., I. C. Dunn, P. W. Wilson, N. Joseph, B. De Ketelaere,
J. De Baerdemaeker, and D. Waddington. 2006. Probability of an
egg cracking during packing can be predicted using a simple nondestructive acoustic test. Br. Poult. Sci. 47:462–469.
Bauer, F., S. G. Tullett, and H. R. Wilson. 1990. Effects of setting
eggs small end up on hatchability and posthatching performance
of broilers. Br. Poult. Sci. 31:715–724.
Bennett, C. D. 1992. The influence of shell thickness on hatchability in commercial broiler breeder flocks. J. Appl. Poult. Res.
1:61–65.
Cavero, D., and M. Schmutz. 2009. Relationship between egg quality
traits and hatchability in pure-line white layer strains. In World
Poultry Science Association Proceedings of the European Poultry
Symposium on quality of poultry meat, and quality of eggs and
egg production, Turku, Finland 21–25 June 2009 (Vol. 7).
2463
Coucke, P. 1998. Assessment of some physical egg quality parameters
based on vibration analysis. PhD Thesis. KU Leuven, Belgium.
Curtis, P. A., F. A. Gardner, and D. B. Mellor. 1985. A comparison
of selected quality and compositional characteristics of brown
and white shell eggs. I. Shell quality. Poult. Sci. 64:297–301.
De Ketelaere, B., F. Bamelis, B. Kemps, E. Decuypere, and J. De
Baerdemaeker. 2004. Non-destructive measurements of the egg
quality. World’s Poult. Sci. J. 60:289–302.
De Ketelaere, B., T. Govaerts, P. Coucke, E. Dewil, J. Visscher, E.
Decuypere, and J. De Baerdemaeker. 2002. Measuring the eggshell strength of 6 different genetic strains of laying hens: Techniques and comparisons. Br. Poult. Sci. 43:238–244.
Dunn, I. C., M. Bain, A. Edmond, P. W. Wilson, N. Joseph, S.
Solomon, B. De Ketelaere, J. De Baerdemaeker, M. Schmutz, R.
Preisinger, and D. Waddington. 2005. Heritability and genetic
correlation of measurements derived from acoustic resonance frequency analysis; a novel method of determining eggshell quality
in domestic hens. Br. Poult. Sci. 46:280–286.
Flock, D. K., M. Schmutz, and R. Preisinger. 2007. Optimization
of egg quality from the breeders’ point of view. Zuchtungskunde
79:309–319.
Groeneveld, E. 1998. VCE4 User’s Guide and Reference Manual Version 1.1. Institute of Animal Husbandry and Animal Behaviour,
Mariensee, FAL, Neustadt, Germany.
Harms, R. H., C. R. Douglas, and D. R. Sloan. 1996. Midnight feeding of commercial laying hens can improve eggshell quality. J.
Appl. Poult. Res. 5:1–5.
Hunton, P. 1995. Understanding the architecture of the egg shell.
World’s Poult. Sci. J. 51:141–148.
Icken, W., M. Schmutz, and R. Preisinger. 2006. Dynamic stiffness
measurements with the “crack detector”: A new method to improve egg shell strength. Lohmann Information 41:13.
Narushin, V. G., and M. N. Romanov. 2002. Egg physical characteristics and hatchability. World’s Poult. Sci. J. 58:297–303.
Preisinger, R., and D. K. Flock. 2000. Genetic changes in layer
breeding: Historical trends and future prospects. BSAS Occasional Publication 27:20–28.
Rodriguez-Navarro, A., O. Kalin, Y. Nys, and J. M. Garcia-Ruiz.
2002. Influence of the microstructure on the shell strength of eggs
laid by hens of different ages. Br. Poult. Sci. 43:395–403.
Sahin, E. H., E. Sengor, M. Yardimci, and I. S. Cetingul. 2009.
Relationship between pre-incubation egg parameters from old
breeder hens, egg hatchability and chick weight. J. Anim. Vet.
Adv. 8:115–119.
Samli, H. E., A. Agma, and N. Senkoylu. 2005. Effects of storage
time and temperature on egg quality in old laying hens. J. Appl.
Poult. Res. 14:548–553.
SAS Institute Inc. 2004. SAS/STAT User’s Guide (Release 8). Version 9.3. SAS Inst. Inc., Cary, NC.
Scholtyssek, S. 1994. Charakteristische Merkmale des Eies und ihre
Prüfungsverfahren. Pages 362–399 in Ei und Eiprodukte. W.
Ternes, L. Acker, and S. Scholtyssek, ed. Paul Parey, Berlin and
Hamburg, Germany.
Seeland, G., R. Hübner, and B. Röder. 1995. Beziehungen zwischen
der Legeleistung und Eiqualitätsmerkmalen von Legehennen.
Arch. Tierzucht 38:489–501.
Silversides, F. G., and K. Budgell. 2004. The relationships among
measures of egg albumen height, pH, and whipping volume.
Poult. Sci. 83:1619–1623.
Silversides, F. G., and T. A. Scott. 2001. Effect of storage and layer age on quality of eggs from two lines of hens. Poult. Sci.
80:1240–1245.
Wolc, A., J. Arango, P. Settar, N. P. O’Sullivan, V. E. Olori, I. M.
S. White, W. G. Hill, and J. C. M. Dekkers. 2012. Genetic parameters of egg defects and egg quality in layer chickens. Poult.
Sci. 91:1292–1298.
Yildiz, A., E. Lacin, A. Hayirli, and M. Macit. 2006. Effects of cage
location and tier level with respect to light intensity in semiconfined housing on egg production and quality during the late laying period. J. Appl. Poult. Res. 15:355–361.