HORTSCIENCE 43(3):655–660. 2008.

Storability in Cold Temperatures Can
Be Evaluated Based on Changes in
Fruit Quality in Apple Genotypes
Under Shelf Life Conditions
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, storage, cultivar difference, firmness, titratable
acidity, regression
Abstract. To compare changes in fruit quality during cold storage with those during shelf
life conditions, flesh firmness and titratable acidity (TA) were measured during storage in
20 apple (Malus ·domestica Borkh.) cultivars. Fruit of each cultivar were divided into
two groups and stored in chambers controlled at 20 ± 2 8C and 85 ± 5% relative humidity(RH) (shelf life conditions) or 0.5 ± 0.3 8C and 95 ± 5% RH (cold storage). Five of thestored fruit were removed for measurements at 5- or 10-d intervals for 40 d and at
1-month intervals until 10 months after harvest at 20 8C and 0.5 8C, respectively. Data
for firmness and TA were subjected to a linear regression and a nonlinear regression,respectively. Moreover, to determine the advantages of 0.5 8C storage over 20 8C storage
for retaining firmness and TA, the effect of storage type on extending the storage period
was introduced as a parameter. The estimate of the effect of storage type showed thatfirmness and TA could be retained 8.9 and 3.7 times, respectively, longer at 0.5 8C than
20 8C, independently of the cultivar. Therefore, firmness and TA after cold storage could
be predicted by the change in firmness and TA during shelf life conditions. Moreover,cultivar differences regarding quality change under cold storage could be determined ina short period after harvest because the cultivar differences under shelf life conditions
were detected within 1 month after harvest.
Storage potential is generally evaluatedby measuring fruit quality before and after
storage. A cultivar with the smallest change
in fruit quality between at harvest and after
storage or a cultivar with acceptable levels of
quality as evaluated by sensory analysis after
storage was determined to have a goodstorage potential. Because apples can be
stored and are marketed year-round, theevaluation of fruit quality requires a longtime and a large amount of fruit because
measurements should be made several times
during storage. This means that it is difficult
to evaluate the storage potential and selectcultivars for their storage potential in apple
breeding programs. For this reason, Iwanami
et al. (2004) measured changes in fruit firmness during shelf life conditions at 20 C andproposed a regression parameter that could
be used as an indicator of storage potential in
breeding programs. Changes in fruit quality
in shelf life conditions were rapid, andcultivar differences regarding the changes
could be determined shortly after harvest.
However, the differences among cultivars
regarding the degradation of fruit quality inshelf life conditions were not assumed to be

Received for publication 29 Oct. 2007. Acceptedfor publication 8 Jan. 2008.
1
To whom reprint requests should be addressed;
e-mail hiwanami@affrc.go.jp

HORTSCIENCE VOL. 43(3) JUNE 2008

the same as those in cold storage, which is the
typical method of storage.
Fruit quality is defined comprehensively
by appearance, texture, flavor, and theabsence of physiological disorders. Delayed
loss of firmness and titratable acidity (TA)are the most important indicators for evaluating apple storage practices. Therefore, theobjectives of this study were 1) to measurechanges in firmness and acidity during storage at 0.5 C (cold storage) and 20 C (shelf
life conditions), 2) to reveal cultivar differences regarding the changes, and 3) to determine whether evaluation and selection werepossible for storage potential on the basis of
the quality changes occurring in shelf life
conditions in apple breeding situations.
Materials and Methods
Fruit materials and storage conditions.
Twenty apple cultivars from an orchard at
the Apple Research Station at the National
Institute of Fruit Tree Science, Japan, wereselected on the basis of diversity of theharvest date. Eighty-five fruit from each
cultivar were picked randomly from a tree
when most of the fruit was determined to bemature on the basis of ground color, texture,
flavor, and starch staining from August to
Nov. 2004 (Table 1). After weighing the fruit,
five apples were immediately used for measurements of firmness and TA at harvest. The
remaining fruit were divided into groups of
30 and 50 and stored in chambers controlled
at 20 ± 2 C and 85 ± 5% relative humidity(RH) and at 0.5 ± 0.3 C and 95 ± 5% RH,
respectively. Five of the stored fruit were
removed for the measurements of fruit
weight, firmness, and TA from the chamber
at 20 C at 5, 10, 15, 20, 30, and 40 d after
harvest and from the chamber at 0.5 C at
1-month intervals until 10 months after harvest. Fruit displaying rot were immediately
removed from the chamber during storage
and when more than half of the stored fruit
displayed rot or internal browning, measurements for the cultivar were discontinued.
Measurements of firmness and titratable
acidity. Flesh firmness was measured using a
fruit pressure tester (FT327; McCormick
Fruit Technology, WA) mounted on a drillpress and fitted with an 11.1-mm probe on thepared surfaces of the sunny and shady sides

Table 1. Starch index, firmness, and titratable acidity at harvest in 20 cultivars evaluated in this study.
HarvestStarchFirmness
Titratable acidity
Cultivardate
indexz(N)(g/100 mL)
American Summer
Pearmain
26 Aug.
3.2
65.1
0.682
Sansa
9 Sept.
1.0
53.4
0.358
Akane
15 Sept.
0.7
59.0
0.665
Tsugaru
15 Sept.
2.0
65.1
0.437
McIntosh24 Sept.
1.5
56.9
0.866
Silken24 Sept.
2.0
58.3
0.430
Santaro30 Sept.
0.6
61.4
0.504
Hatsuaki
30 Sept.
0.0
48.8
0.582
Redgold
8 Oct.
3.4
57.8
0.430
Senshu8 Oct.
0.7
52.2
0.408
Kitaro14 Oct.
0.8
61.0
0.432
Jonathan14 Oct.
1.3
57.9
0.827
Starking Delicious
14 Oct.
2.1
55.0
0.291
Jonagold
21 Oct.
1.4
58.4
0.509
Golden Delicious
21 Oct.
2.3
57.0
0.620
Kotaro28 Oct.
1.5
60.0
0.346
Shinano Gold28 Oct.
1.4
53.1
0.497
Orin
4 Nov.
2.3
65.5
0.324
Fuji
11 Nov.
1.3
63.5
0.487
Ralls Janet
19 Nov.
1.4
71.3
0.715
z
The starch index by iodine solution was rated from 0 = 0% staining to 5 = 100% staining.

655

of each fruit. Three of the five fruit were used
for the measurement of TA. Crude juice was
extracted with a juicer (MJ-C68; National,
Osaka, Japan) from each fruit, which had
been peeled and cored. After filtration, 2 mLof the juice was titrated with an autotitrator(AUT-301; TOA Electronics, Tokyo) to pH
8.0 with 0.1 N NaOH. Titration results were
calculated as malic acid (in grams) per 100
mL of sample juice.
Statistical analysis. Firmness measurements of individual fruit sampled were subjected to a linear regression as described by
Iwanami et al. (2004) (Fig. 1A) expressed as
yijlm = b0ij + b1ij  xijlm + eijlm[1]where yijlm is the firmness measurement as
the dependent variable of mth fruit at lth daysof storage under jth storage condition in ith
cultivar, b0ij is an intercept of ith cultivar
under jth storage condition, b1ij is a regression coefficient of ith cultivar under jth
storage condition, which expresses the firmness reduction rate, xijlm is the days of storageas the independent variable of mth fruit at lth
days of storage under jth storage condition in
ith cultivar, and eijlm is the residual of theregression line.
Measurements of TA were subjected to anonlinear regression (Fig. 1B). The nonlinear
regression model that was proposed by Johnston et al. (2001) was modified slightly to fit
our data and was expressed as

regression coefficient of ith cultivar at 0.5 C,
ki is the effect of a storage condition as aparameter that fits the regression line at
0.5 C to that at 20 C by extending theperiod of storage at 20 C, and aj is a dummy
variable for jth storage condition: a = 1 at
0.5 C (j = 1) and a = 0 at 20 C (j = 2).
The effect of cold storage on retaining TA
was estimated in the same way using Eq. [2].
"where b2i is a common initial TA asymptote
of ith cultivar for both storage conditions, b3i
is a final TA asymptote of ith cultivar under
0.5 C storage, b4i is the rate of change in the
TA of ith cultivar at 0.5 C, and ki is the effectof a storage condition as a parameter that fits
the regression curve at 0.5 C to that at 20 C
by extending the period of storage at 20 C.
Estimations of all the parameters were
performed using the REG and NLIN procedures of SAS (SAS Institute, Cary, NC). To
determine whether the effects of the storage
condition (ki) were different (ki 6¼ k) or thesame (ki = k) among cultivars, Eqs. [3] and [4]were compared with the models in which
ki was substituted for k in the equations on
the basis of Akaike’s information criterion
3167
yijlm = b2ij  ðb2ij  b3ij Þ  41  hnoi0:2 5+ eijlm [2]1=0:2
1+ exp b4ij  xijlm  5:2 + lnð2
 1Þyijlm = b0i + ð1  aj Þ  b1i  k i  xijlm+ aj  b1i  xijlm + eijlm[3]

where b0i is a common intercept of ith
cultivar for both storage conditions, b1i is a

656

1

#

yijlm = b2i  ð1  aj Þ  ðb2i  b3i Þ  1  0:2
1+ exp b4i  k i  xijlm  5:2 + lnð21=0:2  1Þ
"
#
1
[4]
 aj  ðb2i  b3i Þ  1  0:2 + eijlm
1+ exp b4i  xijlm  5:2 + lnð21=0:2  1Þ2

where yijlm is the measurement of TA as thedependent variable of mth fruit at lth days ofstorage under jth storage condition in ith
cultivar, b2ij is an initial TA asymptote as aparameter of ith cultivar under jth storage
condition, b3ij is a final TA asymptote as aparameter of ith cultivar under jth storage
condition, b4ij is the rate of change in TA as aparameter of ith cultivar under jth storage
condition, xijlm is the days of storage as theindependent variable of mth fruit at lth daysof storage under jth storage condition in ith
cultivar, and eijlm is the residual of theregression curve.
To estimate the degree to which cold
storage retains firmness compared with thatat shelf life temperature, we made a regression model that is expressed in the subsequent equation. A parameter that expressed
the effect of storage conditions on extending
the storage period was introduced, and thelinear regressions for a reduction in firmness
under each condition were combined toconsider the magnitude of the estimation
error for all cultivars.

tions. Firmness at 20 d of storage at 20 C did
not significantly differ from that at 180 d ofstorage at 0.5 C in those cultivars. Thismeans that the minimum firmness is not
influenced by the storage conditions anddepends on the cultivar.
To evaluate the differences in the decrease of firmness between at 20 and 0.5 C, alinear regression was applied to the change in(AIC). AIC can lead to an adequate regression model by comparing the number ofparameters with the magnitude of the error
in the model. The model with the smaller AIC
is better.
Results
Weight loss of fruit continued to the endof the storage periods. The daily weight loss
was correlated between 20 and 0.5 C storage
among cultivars tested and was approximately seven times greater for the former
than for the latter (data not shown).
Most cultivars lost firmness rapidly at
20 C (Fig. 2), but no difference occurredfor ‘Senshu’, ‘Kitaro’, ‘Shinano Gold’, and‘Fuji’. Softening at 0.5 C was slower than at
20 C. The softening slowed during storage,
and firmness seldom changed until the end ofstorage under either condition in most cultivars. The fruit of ‘American Summer Pearmain’ and ‘Silken’ showed severe breakdownof the flesh after 20 d on the shelf, and noslow phase in the decrease of firmness wasobserved. The values of minimum firmness
during storage differed among cultivars. The
values of minimum firmness, however, were
nearly identical under the two storage conditions in cultivars in which the decrease infirmness slowed during both storage condi-

firmness and parameters of the regression
equation was compared. Because firmness
did not always decease uniformly throughout
the storage periods, the linear regression was
adapted from the harvest date until firmness
decreased just below 20% of harvest firmness(Fig. 1A). When firmness did not decrease
more than 20% within 20 d at 20 C or within
150 d at 0.5 C, the regression lines were
calculated using data from the harvest dateuntil 20 d and 150 d at 20 and 0.5 C, respectively. On the other hand, although eachparameter is estimated with error, the magnitude of the estimation error is entirely
ignored if the parameter is compared andanalyzed using analysis of variance or correlation between the two storage conditions. To
compare the parameters, it is better to consider the magnitude of the estimation error.
Therefore, Eq. [3] was constructed to calculate the magnitude of the estimation error,
estimated parameters, and compared models.
The estimates of the effect of the storage
condition (ki) in firmness changes widely
varied among cultivars, from 4.7 to 16.8
(Table 2). Because the firmness of ‘Senshu’,‘Kitaro’, ‘Shinano Gold’, and ‘Fuji’ did notdecrease at 20 C, the four cultivars were
excluded for the estimation. ‘Tsugaru’ had
the least difference in the firmness reduction
rate under either condition and ‘Kotaro’ had
the largest. This means that the reduction ratein the firmness of ‘Tsugaru’ is 4.7 times andthat of ‘Kotaro’ is 16.8 times slower at 0.5 Cthan at 20 C. However, a comparison of amodel in which the effect of storage conditions differed among cultivars with one inwhich the outcome was identical indicatedthat the latter was better on the basis of AIC
and that the effect of storage conditions
produced the same value (8.9 ± 0.5) amongcultivars (Table 2). This means that the
reduction rate in firmness was 8.9 times
slower at 0.5 C than 20 C independentlyof the cultivar. When the number of days at
20 C is multiplied by 8.9, the regression
lines of firmness change in both conditions fit
well overall (Fig. 2).
Fruit of the four cultivars, ‘Senshu’,‘Kitaro’, ‘Shinano Gold’, and ‘Fuji’, in whichfirmness did not decrease at 20 C, softened
at 0.5 C, and firmness reduction rates of
those cultivars at 0.5 C were 0.08, 0.05, 0.06,
and 0.05 Nd–1, respectively. The firmness
HORTSCIENCE VOL. 43(3) JUNE 2008

Fig. 1. Cultivar differences regarding change in (A) firmness and (B) titratable acidity under shelf life
conditions (20 C, 85% relative humidity) in apple and applications of regression Eqs. [1] and [2],respectively, to the changes.

reduction rates were small in comparison
with softening rates of the other cultivars
tested in our study, which were all higher
than 0.1 Nd–1, except for ‘Kotaro’ (0.07Nd–1) (data not shown).
The TA of all cultivars decreased rapidly
after harvest under both storage conditions(Fig. 3). The decrease in TA became slow
after a rapid reduction during storage, especially at 20 C, showing a typical sigmoid
curve (Fig. 1B). Although the decrease in TA
was slower at 0.5 C than 20 C, the values ofthe minimum TA during storage were smaller
at 0.5 C than 20 C.
To estimate the differences in thedecrease of TA between at 20 and 0.5 C, anonlinear regression was applied to thechange in TA, and parameters of the regression equation were compared in the same
way as the change in firmness. The degree ofthe decrease in TA was larger at 0.5 C than at
20 C, and the estimates of the final TA
asymptote were largely different between
both storage conditions, which resulted in
misfits of both regression curves after anadjustment using the data of full-term storage. Therefore, data for 120 d were used forthe estimation in storage at 0.5 C.
The estimates of the effect of the storage
condition (ki) in TA changes under bothstorage conditions also varied widely amongcultivars, from 1.4 to 7.2 (Table 2). The
reduction rate in TA of ‘Kotaro’ was 1.4
times and that of ‘McIntosh’ was 7.2 times
slower at 0.5 C than at 20 C. However, acomparison of a model with effects thatdiffered among cultivars with one with identical effects indicated that the latter was
better on the basis of AIC and the effectproduced the same value (3.7 ± 0.2) amongcultivars (Table 2). This means that the lossof TA was 3.7 times slower at 0.5 C than at
20 C independently of the cultivar. When
HORTSCIENCE VOL. 43(3) JUNE 2008

the days of storage at 20 C were multipliedby 3.7, the regression curves of the TAchange under both storage conditions fit well(Fig. 3).
Discussion
Fruit of four cultivars (‘Senshu’, ‘Kitaro’,‘Shinano Gold’, and ‘Fuji’) did not soften at
20 C (Fig. 2). Johnston et al. (2001, 2002a)
also observed that fruit softened slowly or
increased in firmness when stored at 20 C in‘Granny Smith’ and ‘Pacific Rose’, although
fruit of both cultivars softened rapidly duringstorage at 0.5 C. They concluded that a cold
treatment was necessary for these cultivars tostimulate autocatalytic ethylene production
and subsequent rapid softening at ambient
temperatures. However, rates of firmnesschange during storage at 0 C for ‘Granny
Smith’ and ‘Pacific Rose’ were slower thanthose for the other cultivars tested in the study
by Johnston et al. (2001). In our study, fruit of
the four cultivars in which firmness did notdecrease at 20 C softened more slowly thanthose of the other cultivars under storage
at 0.5 C. Therefore, it is useful for apple
breeders to measure changes in firmness after
harvest under shelf life conditions for selecting a cultivar in which firmness decreases
slowly under cold storage.
Excluding these four cultivars, firmness
was retained 8.9 times longer under cold
storage than shelf life conditions independently of the cultivar (Table 2; Fig. 2). We
chose various types of cultivars for this study,
including ones in which mealiness could
develop during storage. ‘American Summer
Pearmain’, ‘Sansa’, ‘McIntosh’, ‘Silken’,‘Redgold’, ‘Jonagold’, and ‘Starking Delicious’ were reported to be cultivars in which
mealiness developed and firmness decreased
rapidly during storage at 20 C (Iwanami

et al., 2005b). Therefore, firmness after cold
storage is predictable based on changes infirmness under shelf life conditions regardless of occurrence of mealiness when someharvest fruit were stored under shelf life conditions and measurements of the firmness
were made at 5- or 10-d intervals duringstorage until 20 to 30 d after harvest. Several
studies have attempted to predict firmness
after storage using regression equations(Blankenship et al., 1997; Evensen et al.,
1993; Ingle et al., 2000; Johnson and Ridout,1998). The regression equations, however,required the measurement of several fruit
characteristics at harvest, and the coefficientof determination was not always high. Ingle
and Morris (1989) observed a significant correlation between the firmness change at 20
and 0 C in ‘Rome’ apples harvested from10 orchards in 2 years and proposed equations to predict the softening rate at 0 Cusing the firmness at harvest and softening
rate at 20 C as parameters. However, theysuggested that the procedure developed for‘Rome’ to predict softening could not beapplied to ‘Delicious’.
Loss of TA was 3.7 times slower at 0.5 Cthan 20 C independently of the cultivar(Table 2; Fig. 3). The estimate of the effectof storage conditions in TA was less than
one-half of that in firmness. Moreover, theminimum TA during storage was smaller at
0.5 C than at 20 C in most cultivars. These
results indicated that cold temperatures do
not suppress a reduction in TA postharvest as
efficiently as they suppress softening. The
decrease in TA could be a critical factor of
unacceptable change in quality in a cultivar
in which a decrease in firmness occurs slowly
under cold storage. A decrease in firmness of‘Fuji’ occurred slowly under cold storage,
and the effect of a controlled atmosphere(CA) or 1-methylcyclopropene treatment on
suppressing softening was nonexistent or
only slight (Drake, 1993; Fan et al., 1999).
However, CA storage is recommended forproviding a good-quality apple even after
short-term storage to suppress the TA reduction in ‘Fuji’ (Drake, 1993), although acceptable firmness could be retained under cold
storage in this cultivar.
TA after cold storage can also be predicted based on changes in TA under shelf
life conditions. The prediction of TA after
cold storage by regression equations wasreported in ‘Starkspur Golden Delicious’(Fallahi et al., 1985). The regression equations also required measurements of mineralcontents in leaves and fruit.
The nonlinear regression model, which
was applied for the change in TA in thisstudy, was originally proposed for the change
in firmness during storage by Johnston et al.
(2001). However, the model requires a phasechange from a slow reduction at first to a
rapid reduction later to fit the model tochanges in measurement during storage, andthey could not fit the model to the curves forthe firmness reduction of some cultivars inwhich firmness decreased gradually. Moreover, because the model also requires a phase657

Fig. 2. Changes in firmness during storage at 20 and 0.5 C, and prediction of the changes at 0.5 C based on the changes at 20 C in 20 apple cultivars.
The prediction was made by multiplying the days of storage at 20 C by 8.9 in each cultivar.

change from the rapid to a final slow reduction, the changes in firmness of ‘American
Summer Pearmain’ and ‘Silken’ at 20 C, inwhich softening continued, were not fitted by
the model. Therefore, we did not apply thenonlinear regression model to the change infirmness and applied the linear model to the
reduction period in firmness. Although thesimple linear model was applied, the curves
for the firmness change under both storage658

conditions fitted well overall (Fig. 2). On theother hand, changes in TA, which differ
greatly among cultivars, were described wellby the nonlinear regression model (Fig. 1B).
Because the degree of the change infirmness during storage can fluctuate depending on environmental factors such as harvest
year (Ingle and Morris, 1989), orchard, andharvest date (Johnston et al., 2002b), theprediction of fruit quality after cold storage

may not be accurate if each fruit under coldand shelf temperature is sampled under different environmental conditions. However,environmental variances of the firmness
reduction rate such as those associated withgenotype · year, year · tree, tree and harvest
date were all reported to be very small bycomparison with variance associated withgenotype (Iwanami et al., 2005a). Therefore,
the estimate of the effect of the storage
HORTSCIENCE VOL. 43(3) JUNE 2008

Table 2. Comparison of the regression model, in which the response to storage conditions varies amongcultivars (ki 6¼ k) with the model in which the response is the same (ki = k) using Akaike’s information
criterion (AIC) for the decrease in firmness and decrease in titratable acidity during storage.
Regression model
Decrease in firmness
ki = k1  k16 in Eq. [3]ki = k in Eq. [3]Decrease in titratable acidity
ki = k1  k20 in Eq. [4]ki = k in Eq. [4]nMean squares ofresidual

k value (effect ofstorage condition)

AIC

478
478

287,547
326,986

ki = 4.7  16.8
k = 8.9

1,426.5
1,423.2

701
701

1.26201.4275ki = 1.4  7.2
k = 3.7–1,762.0–1,762.5

condition (k) is reliable because genotypes
with a wide range of softening rate were used
for the estimation.
The most worthy result in this study is thatthe storage potential under cold storage canbe evaluated from changes in quality undershelf life conditions. The change in fruit
quality under shelf life conditions is rapid,
and cultivar differences regarding qualitychange can be detected within 1 month ofFig. 3. Changes in titratable acidity during storage at 20 and 0.5 C, and prediction of the changes at 0.5 C based on the changes at 20 C in 20 apple cultivars.
The prediction was made by multiplying the days of storage at 20 C by 3.7 in each cultivar.

HORTSCIENCE VOL. 43(3) JUNE 2008659

harvest. Because young seedlings do not
produce enough fruit to permit extensive
sampling for storage tests, seedling screening
for storage potential is neglected in many
breeding programs (Alston, 1988). In ourstudy, storage potential could be evaluatedfrom 35 fruit: five of each harvested fruit
were used for the measurements of firmness
and TA at 5-d intervals from harvest until
30 d postharvest. When the firmness of acultivar does not significantly decrease undershelf life conditions, the cultivar is determined to have a hard fruit after cold storage,
although the value of the firmness cannot be
predicted.
Incidence of physiological disorders suchas low-temperature breakdown, soft scald,and soggy breakdown, which are thought tobe developed especially during cold storage,
could also limit storage potential and somecultivars are reported to be susceptible tothese disorders (Autio et al., 1986; Johnson
and Ridout, 1998; Tong et al., 2003; Watkins
et al., 2005). Therefore, it would be better toinvestigate the incidence of these disorders
during cold storage if there are enough fruit
for the long-term storage test.
In conclusion, most cultivars softenedat both 0.5 and 20 C. ‘Senshu’, ‘Kitaro’,‘Shinano Gold’, and ‘Fuji’ did not soften
at 20 C, but did soften at 0.5 C. Softening
at 0.5 C slowed after the initial softening
phase. The TA of all cultivars decreased
rapidly postharvest under both storage conditions. A comparison of a model in which
the effect of storage condition on keeping
quality was different among cultivars with
one in which that was the same indicated thatthe latter was better on the basis of AIC and

660

that the effect of storage condition produced
the same values among cultivars for firmnesschange and TA change. Firmness and TA
could be retained 8.9 and 3.7 times longer,
respectively, at 0.5 C than 20 C, independently of the cultivar.
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