J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

Estimations of Heritability and Breeding Valuefor Postharvest Fruit Softening in Apple
Hiroshi Iwanami1, Shigeki Moriya, Nobuhiro Kotoda, Sae Takahashi, and Kazuyuki Abe
Apple Breeding and Physiology Research Team, National Institute of Fruit Tree Science,
Shimo-kuriyagawa, Morioka 020-0123, Japan
ADDITIONAL INDEX WORDS. Malus ·domestica, general combining ability, specific combining ability, firmness, mealiness
ABSTRACT. Progenies from 38 unbalanced crosses using 20 apple (Malus ·domestica Borkh.) cultivars/selections as
parents were evaluated for changes in flesh firmness after harvest in two seasons to determine the mechanism ofinheritance of fruit softening. The change in firmness was fitted by linear regression, and the softening rate (Nd–1)
expressed as the regression coefficient was used as the phenotypic value of softening after harvest. Fruit were stored
under 20 8C and 85% relative humidity after harvest for up to 40 days. The softening rates in the progeny populations
were distributed continuously around the softening rates of parents, despite a distinct segregation in the degree of
mealiness at 30 days of storage. The narrow-sense heritability of the softening rate was estimated by parent-offspring
regression, and the estimate was high (h2 = 0.93). Because the softening rate can be influenced by mealiness, anundesirable trait in the apple industry, the progenies were divided into individuals with and without mealiness, andthe breeding values of the parents were estimated based on the softening rate of the nonmealy progeny. The softening
rate of the nonmealy progeny was analyzed using a mixed linear model and the restricted maximum likelihood
method, with general combining ability (GCA) as parental effects and specific combining ability (SCA) as parental
interaction effects. The variance of GCA was significant, but the variance of SCA was small and nonsignificant. The
narrow-sense heritability of the softening rate in the nonmealy progeny was estimated by sib analysis, and the estimate
was moderately high (h2 = 0.55). A significant correlation was observed between the phenotypic value and thebreeding value (twice the GCA effects) in nonmealy parents, but the phenotypic value did not significantly correlatewith the breeding value in mealy parents. Therefore, contribution of a mealy parent to the softening rate of nonmealy
progenies cannot be predicted by its phenotypic value.

A major quality problem with apples in the marketplace isfruit softening (Johnston et al., 2002a). The degree or rate ofsoftening after harvest depends on the cultivar (Iwanami et al.,2004). Although ‘Fuji’ and ‘Honeycrisp’ maintain their firmness long after harvest and have good storage capability (Tonget al., 1999; Yoshida et al., 1998), the fruit of ‘Red Delicious’and ‘Golden Delicious’ become mealy (Hampson and Kemp,
2003) and soften rapidly when harvested late. Softening has notbeen sufficiently evaluated among commercial cultivars, and,at times, it is not considered as a trait for selection in apple
breeding, although a cultivar in which the fruit hardly softens isadvantageous to the apple market and industry. Crosses
between commercial cultivars with good eating quality can
produce progenies with varying rates and degrees of softening.
To produce a new cultivar with good storage and shelf life
potential, it is useful to determine genotypic differences in andmechanism of inheritance of fruit softening.
Resemblance among relatives is a basic genetic phenomenon, and the degree of resemblance determines heritability,
which in turn facilitates the choice of a breeding method for use
in genetic improvement (Falconer and Mackay, 1996). The
estimation of the degree of resemblance for fruit softening after
harvest, however, has received little attention in apple breeding
because there is no effective phenotypic value or index for fruit
softening upon which to compare relatives. Fruit softening is
generally expressed as the decrease in firmness after storage.
Apples soften by 25% to 50% of their firmness at harvest, andthe final firmness depends on the cultivars (Johnston et al.,2002a). Furthermore, firmness does not always continue to
Received for publication 2 July 2007. Accepted for publication 5 Oct. 2007.
1
Corresponding author. E-mail: hiwanami@affrc.go.jp.

92

decrease during storage (Iwanami et al., 2004), and the degreeand period of decrease vary widely among cultivars. Johnston
et al. (2001, 2002b) proposed a nonlinear regression model to fit
the change in firmness during storage and to compare cultivars
on degree and rate of softening based on a parameter (e.g., therate of change in firmness) in the model. However, the model
can estimate the parameter only when a rapid reduction in
firmness is observed after harvest and it requires that a large
number of fruit samples be used to estimate the parameter. The
model, therefore, does not lend itself to breeding situations
because apple seedlings do not always bear a sufficient numberof fruit for storage tests or display rapid reduction in fruit
firmness after harvest.
To evaluate differences in the softening of apple genotypes,
Iwanami et al. (2004) proposed a linear regression model to fit
the change in firmness during storage. The regression coefficient measures the softening rate and can be estimated from alimited number of harvested fruit in breeding situations.
Iwanami et al. (2005a) also indicated that, although the estimateof the parameter was influenced by environmental factors suchas year, tree, and sampling date, the magnitudes of the influence
were relatively small, and the estimate was considered to bestable against environmental conditions. The linear regression
coefficient, therefore, can be a useful index for comparing
relatives as the phenotypic value of softening after harvest.
Changes in firmness after storage can also be influenced bymealiness (Iwanami et al., 2005b). A high degree of mealinessoccurred in 7 of 24 cultivars tested and the softening rates ofthe mealy cultivars were all high, with about the same values(Iwanami et al., 2005b). These findings indicate that if a cultivar
in which mealiness occurs produces progeny in which mealiness does not occur, the softening rate of the progeny cannot
J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

be predicted from the softening rate of the parent cultivar
because the softening rate (phenotypic value) of the parent
is affected by mealiness, which is not inherited by the progeny.
To determine the contribution of a mealy parent to the softening
rate of its nonmealy progeny, the estimation of the breedingvalue of the mealy parent is necessary.
Narrow-sense heritability or combining ability has been
estimated to improve breeding strategies and to evaluate thepotential of cultivars for use as parents in fruit breeding
programs for several quantitative traits in blueberry (Vaccinium
L.; Finn and Luby, 1992), grape (Vitis L.; Firoozabady andOlmo, 1987), Japanese quince [Chaenomeles japonica(Thunb.) Lindl. ex Spach] (Rumpunen and Kviklys, 2003),
kiwifruit [Actinidia deliciosa (A. Chev.) C.F. Liang & A.R.
Ferguson] (Daoyu et al., 2002), peach [Prunus persica (L.)
Batsch] (de Souza et al., 1998; Hansche et al., 1972), and sweet
cherry [Prunus avium (L.) L.] (Hansche et al., 1966). However,genetic parameters have not been determined for storage
potential. Other than the estimation of the heritability of several
storage disorders in apple by Volz et al. (2001), genetic
parameters have rarely been determined for fruit storage
potential. The objectives of the current study were to estimate
the heritability and the breeding value for apple fruit softening
to facilitate the selection of new cultivars with good storage
potential in apple breeding programs.
Materials and Methods
PROGENY POPULATION. This study was carried out using
progeny from the apple breeding program at the National
Institute of Fruit Tree Science (NIFTS), Morioka, Japan.
Twenty cultivars/selections (genotypes) were used as parents(Table 1). The genotypes consisted of four cultivars (‘Jonathan’,‘Raritan’, ‘Starking Delicious’, and ‘Golden Delicious’)
from North America and 14 cultivars and two selections(Morioka 54 and Morioka 57) from Japan. The progeny
populations consisted of 40 families, with 10 to 100 individuals
per family. Among the 40 families, 22 and 35 were chosen in2004 and 2005, respectively, for storage tests, whereas 17 were
evaluated in both years (Table 2). However, not every tree
produced fruit in each year; therefore, between 2 and 47
progenies per family and a total of 614 progenies were used
for fruit analysis. There were two reciprocal crosses, but theprogenies of the reciprocal crosses were combined for analysis
because each of the reciprocal crosses had only a few progenies.
Crosses were made solely for producing commercial cultivars
and, therefore, had no specific mating design. As a result, thefrequency of use of a cultivar in crosses differed greatly among
parental genotypes. For example, ‘Fuji’ was used in 11 crosses,
whereas ‘Raritan’, ‘Golden Delicious’, ‘Akagi’, and Morioka
57 were used in only one cross each. Progenies were grafted
onto ‘JM7’ dwarfing rootstocks and were planted in 2000 to
2002 in an orchard. Trees within a family were planted besideeach other at a spacing of 0.5 m within a row with 3 m between
rows. Parental plants were grown in adjacent fields.
FRUIT MATERIALS. Depending on the number of fruit on atree, 25 to 40 fruit samples were randomly harvested from a treeof each parental genotype one to three times weekly during thematurity period, which was determined by sensory evaluations
based on ground color, texture, flavor, and starch staining in
2004 and 2005. The number of fruit on a tree of each progeny
was limited, and 7 to 25 fruit were harvested at one time whenmost of the fruit was judged to be mature by the sensory
evaluations in progeny populations.

Table 1. Fruit softening rate, degree of mealiness at 30 d of storage at ambient conditions, and general combining ability (GCA) for softening rate(estimated from nonmealy progeny only) in 20 parental apple genotypes.
Fruit softening
Degree ofCultivar/selection
Rootstock
Treeagez
rate (Nd–1)
mealiness (%)
GCA ± SE
Nonmealy genotypes
Morioka 57
M.26E
Unknown
2.0y
6y
0.09 ± 0.28
Tsugaru
JM7
81.9
30.12 ± 0.17
JonathanMarubakaido
46
1.7
7–0.06 ± 0.22
Orin
M.9
10
1.7
7
–0.11 ± 0.21
HatsuakiJonathan/Marubakaido
(6)
1.3
2
–0.02 ± 0.22
MegumiUnknown
Unknown
1.2
4
0.14 ± 0.18
Akagi
M.26E
Unknown
1.1
0–0.20 ± 0.25
KotaroJM2
140.8
7–0.25 ± 0.18
Shinsekai
M.26E
Unknown0.8
1–0.26 ± 0.21
Morioka 54
Unknown
Unknown
0.6
0–0.13 ± 0.21
SenshuJM7
11
0.2
0–0.17 ± 0.16
KitaroJM7
140.2
0–0.16 ± 0.21
Fuji
JM7
23
0.0
0
–0.49 ± 0.15
Mealy genotypes
RaritanUnknown
Unknown
3.8
33
0.47 ± 0.28
Akane
Jonathan/Marubakaido
(6)
3.1
30
0.20 ± 0.16
Himekami
M.26E
Unknown
2.6
33–0.10 ± 0.25
Starking Delicious
MM.10632
2.6
53
0.38 ± 0.18
Sansa
M.26E
18
2.3
51
0.67 ± 0.15
Golden Delicious
M.9
10
1.6
36
–0.21 ± 0.28
Toko
Unknown
Unknown
1.5
41
0.11 ± 0.26z

Numeral in parenthesis indicates years since top-grafting on intermediate stock.
Mean value of the measurements obtained from each fruit sample harvested one to three times weekly for 2 years.

yJ. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

93

Table 2. The proportion of progeny with nonmealy fruit in 38 apple families.

Cross
Fuji
Fuji
SenshuKitaroSenshuSenshu
Akagi
Fuji
Fuji
Fuji
Fuji
Fuji
KitaroToko
TsugaruToko
Fuji
SenshuHatsuaki
Fuji
Fuji
SenshuFuji
Sansa
KitaroSenshuKotaroOrin
Jonathan (Sansa)
Tsugaru (Sansa)
Akane
JonathanTsugaru
Golden Delicious
Akane
Sansa
Sansa
Sansa
Total

·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·
·

Morioka 54
KotaroMorioka 54
Shinsekai
Shinsekai
KotaroFuji
Megumi
Hatsuaki
Orin
Tsugaru
Morioka 57
Tsugaru
Morioka 54
SenshuKotaroSansa
Sansa
Megumi
Starking Delicious
Himekami
Himekami
Akane
Shinsekai
Akane
Akane
Akane
Sansa
Sansa (Jonathan)
Sansa (Tsugaru)
Megumi
Starking Delicious
Starking Delicious
Akane
Orin
Starking Delicious
Akane
RaritanProgeny evaluated (no.) in
2004
2005
Both years
15
14
12
8
11
13
11
29
12
16
16
14
4
3
38
6
1
1
3
5
6
7
4
15
4
15
13
10
30
12
12
9
2
8
7
7
5
7
11
6
47
8
9
8
13
4
4
3
27
18
16
16
11
12
15
10
26
37
26
7
7
10
6
26
37
24
9
22
8
21
32
18
252
536
174

Progeny Nonmealy
evaluated progeny(no.)z
(no.)
15
13
14
13
12
6
8
7
13
12 (10)
29
25
12
11
18
16 (12)
4
4
3
3
38
38
6
4 (0)
3
2
5
3
6
5
7
3
15
12 (4)
18
9 (7)
30
26
15
10 (7)
2
2
8
5
9
8 (4)
12
2 (0)
47
26
9
7 (6)
13
5
5
4 (2)
27
8
18
8
21
10 (6)
17
7 (4)37
14 (11)
7
4
11
6 (3)
39
4 (1)
23
5 (2)
35
3 (1)
614
353 (80)

F RUIT SOFTENING EVALUATION .
Firmness measurements on individual fruit were subjected to linear
regression analysis. The linear
regression for a change in firmness
was determined from the harvest
date until firmness decreased by
20% of the harvest value, as
described by Iwanami et al. (2004).
The regression coefficient was
defined as the softening rate (Newtons per day). Phenotypic differences for a change in firmness
during storage were evaluated bycomparing the softening rate.
STATISTICAL ANALYSIS. Analysis
of variance (ANOVA) was performed for the softening rates ofindividual progenies that were sampled in both years to evaluate theeffect of year on family mean. The
softening rates of all progenies werethen analyzed using the following
mixed linear model:
Yijkl = m + Yri + Gjm + Gkf + Sjk+ eijkl[1]

where Yijkl is the softening rate of
the lth progeny from a cross between
the jth male parent and the kth
female parent in ith year; m is theoverall mean; Yri is the fixed effectof ith year; Gj–m and Gk–f are therandom effects of the jth male parent
and the kth female parent, respectively, which are analogous to the
GCA of the jth and kth parents; Sjk is
the random effect of the jth and kth
parent interactions, which is analogous to the SCA; and eijkl is theresidual term indicating the withinfamily deviation resulting from theeffects of the lth progeny of familyzNumbers of nonmealy progenies evaluated in both years are presented in parentheses.
jk. The estimation of the variancecomponents of the random effect in
STORAGE CONDITIONS. One to five fruit from each harvested this model was based on restricted maximum likelihood
sample were used for the measurements of flesh firmness and (REML) in SAS (SAS Institute, Cary, NC) using the MIXED
mealiness at harvest and thereafter, at 5- or 10-d intervals until procedure. REML is well suited for unbalanced designs to
40 d after harvest. Apples were stored in 25-L containers estimate variance components and can give the variance of22) and female GCA (sGCA–f), the variance ofarranged on racks in a chamber controlled at 20 C and 85% male GCA (sGCA–m
2
relative humidity. Fruit with rots were immediately removed SCA (sSCA), and the within-family variance (s2). The breedingvalue, however, is generally expressed as twice the GCA, whichfrom the containers during storage upon visual detection.
MEASUREMENT OF FLESH FIRMNESS AND MEALINESS. Flesh firm- is defined without distinction between males and females inness was measured using a penetrometer (FT327; McCormick diallel mating designs. Therefore, according to the methods
Fruit Technology, Yakima, WA) mounted on a drill press and described by Xiang and Li (2001), dummy variables werefitted with an 11.1-mm probe on the pared surfaces of the sunny constructed for each parent using the IML procedure in SAS to222= sGCA–m= sGCA, and a variance component of theand shady sides of each fruit. Mealiness was measured accord- make sGCA–f
ing to Iwanami et al. (2005b). It was a flesh disc sucrose GCA effect was estimated. Simultaneously, the GCA effects ofinfiltrate and shake method: the degree (percentage) of mea- each parental genotype were obtained by applying the methodliness was determined by the difference between the weights of of best-linear unbiased prediction (BLUP) in the SAS procedure MIXED to this model.
flesh discs before and after shaking in a sucrose solution.
94

J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

The narrow-sense heritability (h2) of the softening rate wasestimated using parent-offspring regression and sib analysis. Because the covariance of half-sibs was COVðHSÞ =1=4V A = s2GCA(where VA = additive genetic variance; Xiang and Li, 2001), thenarrow-sense heritability was estimated using sib analysis as h2 =222/(2sGCA+ sSCA+ s2) (where VP = phenotypic
VA/VP = 4sGCA
variance). The standard error of the heritability estimated by sib
analysis was calculated according to Falconer and Mackay(1996).
Results
Flesh firmness started decreasing immediately after harvestand stopped by 15 d of storage in all parental genotypes, withfew exceptions. The softening rates varied largely among
genotypes, from ‘Fuji’, which did not soften during storage,
to ‘Raritan’, which softened rapidly on a large scale (Table 1).
High degrees of mealiness occurred and developed duringstorage in some genotypes, and little or none was detected inothers. The softening rates tended to be larger in genotypes inwhich mealiness occurred and increased during storage than ingenotypes in which mealiness hardly occurred. There were also
genotypes in which firmness decreased rapidly but the degreeof mealiness was slight. Genotypes could be classified into
two groups based on the degree of mealiness at 30 d of storage:
mealy genotypes, in which mealiness occurred and increased
above 30%, and nonmealy genotypes, in which mealinesshardly occurred and was below 10% at 30 d of storage (Table 1).
The flesh firmness in most progenies decreased rapidly after
harvest, and stopped by 20 d of storage. Mealiness started to be
detected at 5 or 10 d of storage and stopped at 30 d of storage inmany progenies in which mealiness was observed. Segregationof the degree of mealiness at 30 d of storage in the progeny
populations was observed (Fig. 1). The degree of mealinessin most progenies from crosses among nonmealy genotypes(mealiness < 10%) was below 20%, but it was more than 50% insome progenies (Fig. 1A). The degrees of mealiness inprogenies from crosses in nonmealy genotypes (mealiness <10%) and mealy genotypes (mealiness > 30%) tended to be
divided into two groups, one below 15% and the other over 40%(Fig. 1, B and C). The degree of mealiness in most progenies
from crosses among mealy genotypes (mealiness > 30%)
was more than 50% but below 20% in some progenies (Fig.
1, D and E). Therefore, the occurrence and development of
mealiness are considered to involve major genes. When the
degree of mealiness at 30 d of storage was below 20%, theprogeny was defined as nonmealy, and when it was more than
20%, it was defined as mealy. The segregation ratios of theprogeny population varied among families; all 38 progenies
were nonmealy in the ‘Fuji’ · ‘Tsugaru’ cross, whereas three of
35 progenies from the ‘Sansa’ · ‘Raritan’ cross were nonmealy(Table 2).
The softening rates in the progeny populations were distributed continuously around the softening rates of parents (Fig. 2).
The softening rates of most progenies from crosses among
genotypes with softening rates of 0 to 1 were within the samerange (Fig. 2A). All progenies with a softening rate of morethan 3 from these families were mealy. However, not all mealy
progenies had high softening rates, even though mealinessoccurred in these low mealiness crosses, as well as others withhigher mealiness parents. Some progenies showed 0 to 1
softening rates even though mealiness occurred. In crosses
J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

Fig. 1. Frequency distributions of degree of mealiness at 30 d of storage underambient conditions in 31 apple families in 2005. Families were classified into
five groups based on the degree of mealiness of the parents. Each groupconsisted of progenies from (A) 12 crosses (‘Fuji’ · Morioka 54, ‘Fuji’ ·‘Kotaro’, ‘Senshu’ · Morioka 54, ‘Kitaro’ · ‘Shinsekai’, ‘Senshu’ ·‘Shinsekai’, ‘Senshu’ · ‘Kotaro’, ‘Fuji’ · ‘Megumi’, ‘Fuji’ · ‘Orin’, ‘Fuji’· ‘Tsugaru’, ‘Fuji’ · Morioka 57, ‘Kitaro’ · ‘Tsugaru’, and ‘Hatsuaki’ ·‘Megumi’); (B) seven crosses (‘Fuji’ · ‘Himekami’, ‘Senshu’ · ‘Himekami’,‘Fuji’ · ‘Akane’, ‘Kitaro’ · ‘Akane’, ‘Senshu’ · ‘Akane’, ‘Akane’ ·‘Megumi’, and ‘Akane’ · ‘Orin’); (C) nine crosses (‘Fuji’ · ‘Sansa’, ‘Senshu’· ‘Sansa’, ‘Fuji’ · ‘Starking Delicious’ ‘Sansa’ · ‘Shinsekai’, ‘Orin’ ·‘Sansa’, ‘Jonathan’ · ‘Sansa’, ‘Tsugaru’ · ‘Sansa’, ‘Jonathan’ · ‘Starking
Delicious’, and ‘Tsugaru’ · ‘Starking Delicious’); (D) two crosses (‘Sansa’ ·‘Akane’ and ‘Sansa’ · ‘Raritan’); and (E) one cross (‘Sansa’ · ‘Starking
Delicious’). The arrows indicate the degrees of mealiness of the parents.

where the softening rate of one parent on a cross was in a higher
category, the distribution of softening in progenies shifted
toward a higher rate (Fig. 2, B–D). The softening rates innonmealy progenies from crosses between genotypes withsoftening rates of 0 to 1 and 1 to 2 were distributed aroundthe midparent value, but the softening rates in mealy progenies
from the same crosses were higher than the midparent value(Fig. 2B). For crosses of parents with a high softening rate, theproportion of mealy progenies with a high softening rate95

Fig. 2. Frequency distributions of softening rate under ambient conditions in 33 apple families in 2005. Families were classified into nine groups based on thesoftening rate of the parents. Each group consisted of progenies from (A) six crosses (‘Fuji’ · Morioka 54, ‘Fuji’ · ‘Kotaro’, ‘Senshu’ · Morioka 54, ‘Kitaro’ ·‘Shinsekai’, ‘Senshu’ · ‘Shinsekai’, ‘and Senshu’ · ‘Kotaro’); (B) seven crosses (‘Fuji’ · ‘Megumi’, ‘Fuji’ · ‘Orin’, ‘Fuji’ · ‘Tsugaru’, ‘Fuji’ · Morioka 57,‘Kitaro’ · ‘Tsugaru’, ‘Toko’ · Morioka 54, and ‘Toko’ · ‘Kotaro’); (C) six crosses (‘Fuji’ · ‘Sansa’, ‘Senshu’ · ‘Sansa’, ‘Fuji’ · ‘Starking Delicious’, ‘Fuji’ ·‘Himekami’, ‘Senshu’ · ‘Himekami’, and ‘Sansa’ · ‘Shinsekai’); (D) three crosses (‘Fuji’ · ‘Akane’, ‘Kitaro’ · ‘Akane’, and ‘Senshu’ · ‘Akane’); (E) one cross(‘Hatsuaki’ · ‘Megumi’); (F) five crosses (‘Orin’ · ‘Sansa’, ‘Jonathan’ · ‘Sansa’, ‘Tsugaru’ · ‘Sansa’, ‘Jonathan’ · ‘Starking Delicious’, and ‘Tsugaru’ ·‘Starking Delicious’); (G) two crosses (‘Akane’ · ‘Megumi’ and ‘Akane’ · ‘Orin’); (H) one cross (‘Sansa’ · ‘Starking Delicious’); and (I) two crosses (‘Sansa’ ·‘Akane’ and ‘Sansa’ · ‘Raritan’). The arrows indicate the softening rates of the parents.

increased (Fig. 2, E–I). In these families, the softening rates
of nonmealy progenies tended to be lower than the midparent
values, and the softening rates of mealy progenies tended to behigher than the midparent values. However, distinct segregationof the softening rate between nonmealy and mealy progenies was
not observed in all families. Deviation of the softening rate ofeach progeny from the family mean was tested for normality
using the Kolmogorov-Smirnov test, and a normal distribution
was not rejected at P = 0.05 in all families, notwithstanding if
all progenies or only nonmealy progenies were used.
The relationships between the family mean and the midparent value showed almost the same trend among families thatwere sampled in 2004, 2005, and in both years. The regressionof family mean on the midparent mean for softening rate
showed that narrow-sense heritability (h 2 ), which was
96

expressed as the regression coefficient, was high (0.93 ±0.13) when all progenies were used for the estimation (Fig.
3A). When using only nonmealy progenies for the calculationof family mean, the regression coefficient was moderately high,0.56 ± 0.10 (Fig. 3B).
The regression of the family mean of nonmealy progeny on
the midparent cannot reveal the contribution of parents to thesoftening rate of nonmealy progenies because the midparent
was calculated without discriminating between mealy andnonmealy genotypes. Therefore, the breeding values and thenarrow-sense heritability for the softening rate of nonmealy
progeny were estimated by sib analysis using the REML
method. Before the analysis, the homogeneity of residual
variances (within-family variances) was tested by Bartlett’s
test in addition to the above-mentioned test for normality.
J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

Table 3. Variance components based on restricted maximum
likelihood (REML) and narrow sense heritability for softening
rate using nonmealy progeny from 38 families in apple.
Variance components
Estimates
P
Parental effect (GCA)
s2GCA
0.11820.0133
Parental interaction
effect (SCA)
s2SCA
0.05490.0935
Within family
s20.5759<0.0001
Narrow-sense
heritability
h20.545 ± 0.194

A significant correlation was observed between the softening rates (phenotypic values) of the parental genotypes and thebreeding values (twice the GCA effects) estimated by BLUP
methods (P < 0.001; Fig. 4). The phenotypic values of nonmealy genotypes were highly and significantly correlated withthe breeding values (P = 0.003). However, the phenotypicvalues of mealy genotypes did not significantly correlate with
their breeding values (P = 0.310).
Discussion
Because knowledge of the modes of inheritance of agriculturally important traits can improve the breeding efficiency,
there have been many studies on genetics of traits in apple.
Major genes have been found for traits with simple inheritancepatterns that show distinct segregation in the progenies (Brown,1992). However, few studies have been published on thegenetic parameters of quantitative traits, mainly because
experimental data from major breeding programs were notsuited for such estimations (Durel et al., 1998). Genetic
parameter estimates have begun to be generated in apple forfruit traits, following developments in statistical tools andmethods for analyzing unbalanced data, including REML
and BLUP. For example, GCA and SCA estimates for ripening

Fig. 3. Midparent–offspring regressions for softening rate based on (A) all
progenies and (B) nonmealy progenies from 38 apple families.

No significant heterogeneity was detected (P = 0.132) whennonmealy progenies were used for the test, although significant
heterogeneity was detected (P < 0.001) when mealy progenies
were included. Therefore, the analyses using ANOVA and REML
were assumed to be applicable to the nonmealy progeny data.
The effect of family on the softening rate of nonmealy
progenies sampled in both years was highly significant (P <0.001), whereas the effects of year and year · family interaction
were not significant (P = 0.482 and 0.554, respectively). A lackof year · family interaction indicates that the softening rate
fluctuates uniformly in every family and the parental effect canbe estimated reliably using data from different years byadjusting the yearly variation as a fixed effect.
The parental effect (GCA) was significant, but the interaction between parents (SCA) was small and nonsignificant whennonmealy progeny from all families were used (Table 3). The
heritability (h 2 ) estimated by sib analysis was 0.55 ±0.19—almost identical to the heritability estimated by parentoffspring regression (0.56; Table 3 and Fig. 3B).
J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

Fig. 4. The relationships between breeding value (2 · GCA) and phenotypicvalue (softening rate, Nd–1) for softening in nonmealy, mealy, and all
20 parental apple genotypes.

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date (Tancred et al., 1995) and heritability and genetic
correlations for fruit traits (Durel et al., 1998; Oraguzie et al.,2001, 2003).
The continuous distribution of softening rates of progeny
around the midparent in each family is typical of a quantitative
pattern of inheritance. On the other hand, noncontinuous
segregation of the degree of mealiness was observed in theprogeny populations despite being measured quantitatively(Fig. 1). When crossing between parents with a high and a
low degree of mealiness, the progenies tended to be distributed
not around the midparent value, but segregated to the extreme,i.e., below 10% and above 50% in the degree of mealiness at
30 d of storage. Therefore, progenies in which mealiness hardly
occurred at 30 d of storage could be judged as nonmealy andqualitatively different from progenies with a high degree of
mealiness at 30 d of storage.
Softening is a process primarily associated with the changes
in the cell walls of parenchyma cells, which result in tissue
failure. Tissue failure, which is observed when mechanicalforces are applied to the flesh tissue, can be explained by threeprincipal modes: cell fracture, cell rupture, and cell-to-celldebonding (cell separation; Harker et al., 1997). The ratio of thecells that fracture, rupture, and separate continuously changes
according to the tissue conditions during storage (Harker et al.,2002, 2006). The method used in our study for measuring
mealiness can only detect the contribution of cell separation
to tissue failure (cell-to-cell bonding). Cell fracture and cell
rupture could also occur, and the contributions of those to tissue
failure could continuously change, irrespective of the occurrence of mealiness (cell separation). In this study, the softening
rates of mealy progenies tended to be higher than those of
nonmealy progenies and were distributed relatively widely(Fig. 2). Therefore, the softening rates were continuously
distributed in every family when mealy and nonmealy progenies were combined, although Iwanami et al. (2005b) observedthat the softening rates of mealy genotypes were all high, with
about the same values.
The heritability estimated using data from all progenies washigh, at 0.93 (Fig. 3A). Although the estimate of the heritability
depends on the population tested, the environmental circumstances to which the individuals are subjected, and the way inwhich the phenotype is measured (Falconer and Mackay,1996), the heritability of the ripening date of apple was also
reported to be high (h2 = 0.94 by Tancred et al., 1995; h2 = 0.6 to
0.9 by Oraguzie et al., 2003). Ripening date is not usually a trait
highly selected for in fruit breeding. Early, middle-, and lateripening cultivars are all useful and desirable for growers
because cultivars with various ripening dates can help spreadthe harvest. Therefore, the ripening date of parents used in fruit
breeding has a wide range, thus contributing to the highheritability for this trait in many crops. For example, it is0.87 to 1.0 in japanese pear (Pyrus pyrifolia Nakai; Abe et al.,1993), 0.94 and 0.84 in peach (de Souza et al., 1998
and Hansche et al., 1972, respectively), 0.99 in persimmon(Diospyros kaki Thunb.; Yamada et al., 1995), and 0.88 insweet cherry (Hansche et al., 1966). The high heritability for thesoftening rate in our study also suggests that little selection has
been applied to this trait in apple, and genetic diversity is
considered to be large regarding the softening rate.
On the other hand, the heritability estimated by sib analysis
using data from nonmealy progenies was moderately high, at
0.55, but lower than that estimated using all progenies (Table
983). The family means for the softening rate of nonmealy
progeny were lower than those for all progeny in every family(Fig. 3). The lower variation of the family mean could raise
the magnitude of environmental variance, resulting in lower
heritability. Alspach and Oraguzie (2002) estimated the heritability of fruit traits in apple, with the estimates generally low
and varying between 0.1 and 0.6. They suggested that themagnitude of environmental variance caused by the yearly
effect in each fruit trait could have contributed to the low anddiffering heritability estimates.
To produce progeny with good storage potential or shelf life,
it is necessary to predict the softening rate in the nonmealy
progeny of the next generation from the phenotype of thepresent genotypes used as parents. However, the softening rate
as the phenotype value in mealy parents was biased by theoccurrence of mealiness and was not expected to be a goodpredictor. Therefore, the breeding value that expressed thecontribution of mealy parents to the softening rate of nonmealy
progeny was estimated by sib analysis using nonmealy progenies. Because year · family interaction was not significant, sib
analysis was performed using 2 years of data combined. The
lack of interaction could be attributed to the softening rates ofindividual progenies not being significantly different from year
to year. This observation was consistent with the results of
Iwanami et al. (2005a), which showed that the softening rate,
represented by a linear regression coefficient, was stable against
environmental conditions.
The variance of the SCA was not significant and was small(Table 3). This result indicates that the family means of thesoftening rate in the nonmealy progeny of future crosses within
the parental set used in this study can be readily predicted by
GCA estimates alone. Moreover, a significant correlation wasobserved between the phenotypic values and the breedingvalues of the parental genotypes (Fig. 4). This correlation
indicates that genotypes with a high softening rate will tend to
produce progenies with a high softening rate, irrespective ofoccurrence of mealiness. The reason that the heritability
estimated by sib analysis was almost the same as that estimatedby parent-offspring regression (Table 3 and Fig. 3B) could be
because the phenotypic value and the breeding value weresignificantly correlated, although the softening rates of mealy
parents were expected to be quite high. On the other hand, thesoftening rate of mealy genotypes was not significantly correlated with the breeding value (Fig. 4). Moreover, softening rates
and breeding values showed wide variations in mealy genotypes. In our study, two-thirds of parental genotypes werenonmealy and resulted in the significant correlation between
phenotypic values and breeding values of all parental genotypes. When many mealy genotypes have been used forbreeding programs, a significant correlation would not havebeen observed between the phenotypic values and the breedingvalues. In Japan, many nonmealy cultivars have been produced,
particularly from ‘Fuji’ or other nonmealy cultivars because
Japanese consumers are very sensitive to the mealy texture ofapples (Iwanami et al., 2005b). Therefore, nonmealy cultivars
will be exclusively used for breeding programs in Japan, withthe result that the breeding values of parental cultivars could be
evaluated based on their phenotypic values. Finn and Luby
(1992) also observed low correlation between breeding values(GCA) and parental phenotype scores for fruit color, picking
scar, and firmness in a population of blueberry from interspecific crossings.
J. AMER. SOC. HORT. SCI. 133(1):92–99. 2008.

In conclusion, the softening rates in the progeny populations
were distributed continuously around the softening rates ofparents, although segregation of the degree of mealiness at 30 dof storage was observed. The heritability estimate of thesoftening rate was high, suggesting that storage and shelf life
traits have been sparingly characterized and selected for inbreeding programs. This also means that selection of a parent
based on its softening rate can contribute to the improvement ofsoftening rate in the next generation. The variance of the SCA
was small and nonsignificant, indicating that the family meansof nonmealy progeny of future crosses within the parental set
used in this study can be readily predicted from GCA estimatesalone. Moreover, a significant correlation was observed
between the phenotypic values and the breeding values of theparental genotypes. However, the softening rate of mealy
genotypes was not significantly correlated with the breedingvalue, indicating that contribution of a mealy genotype to thesoftening rate of nonmealy progenies cannot be predicted by its
phenotypic value.
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