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Transcript of Phenotypic diversity and relationships of fruit quality traits in peach and nectarine [Prunus...
Phenotypic diversity and relationships of fruit quality traitsin inter-specific almond 3 peach backcrosses breedingprogenies
Hamid Yaghini • Maryam Shirani • Azin Archangi •
Karim Sorkheh • Sajad Badfar Chaleshtori • Seyed Ehsan Sangi •
Mahmood Khodambashi • Farahnaz Tavakoli
Received: 9 December 2012 / Accepted: 14 February 2013
� Springer Science+Business Media Dordrecht 2013
Abstract Nineteen agrochemical traits of 20 almond
inter-specific backcrosses progenies were evaluated and
compared for three consequence years to find out their
phenotypic diversity and determine the relationships
of fruit quality traits in almond 9 peach backcrosses
breeding progenies. The variation was observed for
traits of phenology parameters (blooming time, ripening
time), Physical parameters (fruit weight, width, height,
shape, thickness, skin pubescences, colour and flower
type), chemical parameters (total sugar content, soluble
solids content and acidity) and sensory parameters
(attractiveness, taste, and flavor) and yield. Many fruit
characteristics that are important to breeders are present
in this collection. A high variability was found in the
evaluated almond progenies and significant differences
were found among them in all studied quality attributes.
Year-by-year variations were observed for majority of
traits. A significant correlation was found among the
fruit height, fruit width, skin pubescences and yield.
Fruit height showed a significant positive correlation
with fruit weight and fruit thickness and some other
traits and a negative correlation with the titratable
acidity, skin pubescences and fruit flavour. A high
negative correlation was found between the fruit weight
and titratable acidity (-0.8). Low coefficients were got
between the flower colour and skin pubescences. In
addition, principal component analysis it possible to
established similar groups of genotypes depending on
their quality characteristics and to study relationships
among pomological traits in almond progenies
evaluated.
Keywords Almond 9 Peach backcrosses �Fruit quality � Principal component analysis �Prunus dulcis L.
Introduction
Almond [Prunus dulcis (L.) Batsch] is the most
important fruit crop in the South of Iran (158,050 tons
with shell almond) (FAOSTAT 2010), and the most
important in the genus Prunus. Among temperate fruit
crops, the almond breeding industry is one of the most
dynamic and new cultivars are released every year
(Moradi 2006; Sorkheh et al. 2009, 2010). Iran, due to
a diverse variability in geographical regions such as
mountain ranges and deserts spreading throughout the
country and therefore diverse kinds of climates, is one
of the origins of almond (Sorkheh et al. 2007;
Nikoumanesh et al. 2011).
H. Yaghini � M. Shirani � A. Archangi �K. Sorkheh (&) � S. E. Sangi � M. Khodambashi �F. Tavakoli
Department of Agronomy and Plant Breeding, Faculty
of Agriculture, Shahrekord University, P.O. Box 115,
Shahrekord, Iran
e-mail: [email protected]
S. B. Chaleshtori
Department of Agronomy and Plant Biotechnology,
Faculty of Agriculture, Payame Nor-e-Tehran University,
Tehran, Iran
123
Euphytica
DOI 10.1007/s10681-013-0893-3
The efficiency of cross-breeding programs mainly
depends on the choice of the progenitors and knowl-
edge of the trait’s transmission we want to improve.
A high efficiency is especially important in fruit
breeding, because of the high cost and time consuming
of breeding programs of these species (Sanchez-Perez
et al. 2007).
The kernel is the edible part of the nut and is
considered an important food crop, with a high
nutritional value. It may be consumed raw or cooked,
blanched or unblanched, combined and mixed with
other nuts. It can also be transformed into other
products or to produce marzipan and nougat (Kodak
and Socias Company 2008). Almond kernel quality
has so far been defined only by physical parameters:
size, shape, double kernels, etc. however, the different
uses of almond may require kernels with a specific
composition, depending on each commodity. The high
nutritive value of almond kernels arises mainly from
their high lipid content (Sabate and Hook 1996). So,
oil stability and fatty acid composition are considered
an important criterion to evaluate kernel quality
(Kodad and Socias Company 2008).
To day, the most common method for producing
new cultivars is through cross of chosen parents. The
resulting full-sib families are planted in trials from,
which the best genotypes that share the most proper
combination of traits after evaluation, are selected
(Kester et al. 1991; Scorza and Sherman 1996; Nicotra
et al. 2002; Martınez-Calvo et al. 2006; Cantin et al.
2010). The selected seedlings are budded for clonal
testing (Brown 1975; Brown and Walker 1990). This
is the method used in the present work that deals with
15 progenies derived from crosses between commer-
cial and/or pre-selected peach cultivars, reaching up to
one thousand seedlings. We search for superior
almond cultivars for the Iranian almond industry with
good adaptation to South of Iran conditions. Besides
lowering the production costs and improving pest and
disease resistance, breeding objectives of this program
also include extension of the harvest season, a new
fruit types for areas with mild-winter climate areas,
and improvement of fruit quality (shape, flesh and skin
colour, firmness, flavour, etc.). Like other temperate
fruits, almond has chilling and heat requirements for
flowering. Early flowering is a desirable characteristic
in many breeding programs in South of Iran areas to
get the earliest yield (Moradi 2006; Sorkheh et al.
2009) although spring frosts may reduce production in
some years. Extension of the harvest season with
early, also late-maturing almond genotypes is of
considerable interest for the almond industry in this
area, to supply the market for a longer period of time
(Sorkheh et al. 2010).
The quality parameters may not be independent of
each other, and therefore relationships among them
should be studied to improve the choice of production
objectives for fruit quality and to improve character-
izing fruit quality by using a few number independent
parameters. This could be used in breeding programs
and orchard management because the knowledge of
the relationships among fruit quality parameters
would it possible to reduced pomological traits for
study. In this sense, multivariate analysis is a useful
tool, which used to establish genetic relationship
among cultivars and to study correlations among
variables (Hilling and Iezzoni 1988; Brown and
Walker 1990; Iezzoni and Pritts 1991; Genard and
Bruchou 1992; Perez-Gonzalez 1992; Esti et al. 1997;
Badenes et al. 1998). A good knowledge of any trait
and its relationships with other interesting traits is
essential in a breeding program (Wu et al. 2003). In the
other word, the knowledge of these relationships is
important because improvement for an objective may
positively or negatively influence other traits depend-
ing on their correlations.
Kramer and Twigg (1966) defined quality as being
constituted of those chemical and physical character-
istics that give a product consumer appeal and
acceptability. The shape and proportions of the fruit
are also of interest to the consumers (Badenes et al.
2006). Some important agronomic and fruit quality
traits are controlled by major genes transmitted to the
offspring over Mendelian inheritance (Cantin et al.
2010). But, quantitatively inherited characters consti-
tute the bulk of the variability selected during the
breeding process in fruit trees as in most cultivated
species. Characters related with plant growth and
architecture, yield, blooming and harvesting times,
and fruit quality, are usually of quantitative nature
(Dirlewanger et al. 1999; Etienne et al. 2002). The
quality parameters may not be independent of each
other, and therefore, relationships among them should
be studied to improve the choice of production
objectives (Cantin et al. 2010).
In this work, we investigated physical parameters
(weight, size, flesh and skin colour, firmness and
percentage of dry matter), chemical parameters (total
Euphytica
123
soluble solids content and acidity) and sensory
parameters (attractiveness, taste, aroma and texture).
The aims of this study were to evaluate the phenotypic
diversity among and within the breeding progenies,
and study the relationships among agronomic and fruit
quality parameters, including qualitative pomological
traits linked to the fruit quality. In addition, principal
component analysis (PCA) was carried out to study
correlations among variables and to establish relation-
ships among breeding crosses for fruit quality attri-
butes. The materials evaluated are representative of
the germplasm available for almond breeding in the
South of Iran area. The high number of genotypes,
with large genetic variability for many fruit quality
traits, will improve the knowledge of the genetic
studies on this crop and will make up a helpful tool to
be applied in P. dulcis (Mill.) breeding programs.
Materials and methods
Plant material
The plant material tested included 20 inter-specific
almond 9 peach genotypes generated by forming
several backcrosses with almond genotypes were made
during 2007, 2008 and 2009 in collaboration with
ANRRC (Tehran-Karaj, Iran). The assayed progeni-
tors belonged to four different categories of fruit type:
soft shell, hard shell, semi-hard and paper. The
resulting seedlings were budded on the same rootstock
and established (one tree for each genotype) in an
experimental orchard at the Experimental Station of
Karaj Botany Orchard (Tehran, Karaj, Iran,) in 2002.
Trees were trained to the standard open vase system
and planted at a spacing of 4 9 2.5 m according to
Sorkheh et al. (2009) and Cantin et al. (2010). Trees
were grown under standard conditions of irrigation,
fertilization and pest and disease control. Vegetative
and fruit quality traits evaluated in a total of genotypes
over three consecutive years (2007–2009). All traits
were measured and scored for each seedling tree
separately over the 3-year period and means of 3 years
were calculated. Finally, superior genotypes were
selected by independent culling of the most important
agronomic (Ripening date and yield) and fruit quality
traits (fruit weight, soluble solids content, acidity, skin
blush,) evaluated. The pedigree of the almond proge-
nies assayed is shown in Table 1.
Agronomic characters and fruit quality traits
evaluation
During the 2007, 2008 and 2009 seasons, the follow-
ing characteristics were measured individually in each
seedling tree using the IPGRI descriptor for Rosaceae
family (Table 2): Blooming date (in Julian days) was
recorded for each progeny according to Felipe (1975,
1984, 1999) and Fleckinger (1945) that is the average
date for bloom beginning (E stage), full bloom (F
stage) and bloom end (G stage) was scored in each
progeny. The mean harvesting date was also calcu-
lated for each progeny. Fruits were considered ripe in
the tree when their growth had stopped. Harvesting
date ranged from late-May to mid-September, depend-
ing on the genotypes. Yield (kg/tree) was determined
for each seedling tree and the total of fruits was also
recorded. Furthermore, the total average fruit weight
was calculated. For assaying fruit quality parameters a
representative sample is made up of 50 fruits for each
tree was selected.
Fruit colour represented by four categories: 1 =
white; 2 = pale rose; 3 = pink and 4 = dark pink.
Fruit type: 1 = rosaceous and 2 = campanulate. Skin
ground colour: 1 = green, 2 = greenish-cream, 3 =
cream, 4 = cream yellow, 5 = yellow. Skin pubes-
cence: 6 = intermediate, 7 = high. Fruit shape: 1 =
very flat, 2 = slightly flat, 3 = rounded, 4 = ovate,
5 = oblong, 6 = elongated.
Fruit height, width and thickness were measured by
caliper in cm, respectively. In additions, Fruit and
stone weight were measured by scale in g, respec-
tively.
A trained panel of five experts evaluated the fruit
attractiveness, fruit taste and fruit flavour from each
inter-specific backcrosses. Score from 1 (extremely
poor) to 10 (extremely good).
Evaluation of biochemical quality parameters
The soluble solids content was measured with a
temperature compensated refractometer (model
ATC-1, Atago Co., Tokyo, Japan); and data are given
as Brix. The titratable acidity was determined by
titration with NaOH 0.1 N to pH 8.1 (AOAC 1984).
Data are given as g/L of malic acid according to
Nikolic et al. (2010) with some modification adapted
for almond genotypes.
Euphytica
123
Evaluation of sensory attribute
All samples were collected at the same maturity stage;
the end of the harvest season, when skin-opening is
complete and the abscission layer between the fruit and
the peduncle has formed, making easier the dropping-
off of the fruits. After harvesting, the almonds were
subjected to different treatments. The nuts were cleaned
in a cleaner air screen to remove foreign matter and, after
being cracked, the kernels were separated from the shell
by hand. To obtain the tegument, the kernel was scalded
with water at 80–90 �C and then peeled and dried. To
determine the shell, tegument, and kernel moisture
contents, a representative amount of almonds (10 whole
almonds) was separated. After being cracked, the
tegument was separated from the kernel by hand. The
initial moisture contents of shell, tegument, and kernel
were determined by drying the samples in an air-
ventilated oven at 105 �C for at least 2 h until they
reached constant weight according to Valverde et al.
(2006) with some modification.
Linear dimensions (length (L), width (W), and
thickness (T)) were established by using a digital
vernier caliper with a sensitivity of 0.01 mm accord-
ing to Valverde et al. (2006). The indices about form,
I1 and I2, (Berenguer 1972; Saura et al. 1988;
Valverde et al. 2006), were calculated as:
I1 ¼ T� 100 ¼ L and I2 ¼W� 100 ¼ L:
The geometric mean diameter (Dp) and degree of
sphericity (U) of the fruit were calculated by using the
following formulae (Mohsenin 1970) and adapted
using Valverde et al. (2006):
DP ¼ LWTð Þ1=3and U ¼ LWTð Þ1=3�100 ¼ L:
To determine the fruit surface color, a representa-
tive amount of almonds (10 whole almonds) was
separated. To determine the surface color for the
tegument, nuts were cracked and to measure that of the
kernel without tegument, the kernel was scalded,
peeled, and dried. The fruit surface color was analyzed
by measuring showed color with chroma meter (L*,
Table 1 Pedigree, flowering and self-incompatibility of inter-specific almond 9 peach genotypes assayed
Progeny Pedigreea Floweringb Compatibility
K1 Almond 9 Peach Early (-6 and earlier) Self-compatibility
K2 Almond 9 Peach Early (-6 and earlier) Self-compatibility
K3 Almond 9 Peach Early (-6 and earlier) Self-compatibility
K4 Almond 9 Peach Early (-6 and earlier) Self-compatibility
K5 Almond 9 Peach Middle (0 to ?2) Self-compatibility
K6 Almond 9 Peach Middle (0 to ?2) Self-compatibility
K7 Almond 9 Peach Middle (0 to ?2) Self-compatibility
K8 Almond 9 Peach Middle (0 to ?2) Self-compatibility
K9 Almond 9 Peach Late (?5 to ?7) Self-compatibility
K10 Almond 9 Peach Late (?5 to ?7) Self-compatibility
K11 Almond 9 Peach Late (?5 to ?7) Self-compatibility
K12 Almond 9 Peach Late (?5 to ?7) Self-compatibility
K13 Almond 9 Peach Late (?5 to ?7) Self-compatibility
K14 Almond 9 Peach Very late (?8 and later) Self-compatibility
K15 Almond 9 Peach Very late (?8 and later) Self-compatibility
K16 Almond 9 Peach Very late (?8 and later) Self-compatibility
K17 Almond 9 Peach Very late (?8 and later) Self-compatibility
K18 Almond 9 Peach Very late (?8 and later) Self-compatibility
K19 Almond 9 Peach Very late (?8 and later) Self-compatibility
K20 Almond 9 Peach Very late (?8 and later) Self-compatibility
a The inter-specific almond 9 peach genotypes generated by forming several backcrosses with almond genotypesb The number in the parentheses indicate the days before (-) or after (?) peak Nonpareil’’ bloom (Sorkheh et al. 2010; Asai et al.
1996, Almond Production Manual. University of California. ANR Publication)
Euphytica
123
Ta
ble
2A
gro
no
mic
and
fru
itq
ual
ity
trai
tsfo
ral
mo
nd
bre
edin
gp
rog
enie
ssu
bje
cted
toas
sess
men
t
Gen
oty
pe
Flo
wer
colo
ur
Flo
wer
type
Skin
gro
und
colo
ur
Skin
pubes
cence
Fru
it
shap
e
Tota
l
sugar
conte
nt
Tit
atab
le
acid
ity
Solu
ble
soli
d
conte
nt
Fru
it
flav
or
Fru
it
tast
e
Fru
it
attr
acti
ven
ess
Yie
ldS
tone
wei
ght
Fru
it
wei
ght
Fru
it
thic
knes
s
Fru
it
wid
th
Fru
it
hei
ght
Har
ves
ting
dat
e
Blo
om
ing
dat
e
K1
11
26
37.2
511
13.4
85
76.5
33.1
24.5
954.6
55.2
15.0
34.2
223.0
118.0
4
K2
11
16
37.3
210.5
15.2
46
7.9
833.1
23.2
258.2
15.3
24.4
84.3
212.5
20.0
1
K3
21
36
48.5
8.4
17.6
66
5.2
55.6
654.2
23.6
480.1
94.3
64.3
25.2
216.0
816.0
4
K4
21
57
510.1
7.6
18.2
74.3
97.1
520.2
25.2
665.5
95.1
13.9
84.0
23.0
915.0
2
K5
21
57
610.2
75.9
17.6
86.8
8.3
551.9
4.8
855.0
44.5
14.1
4.7
816.2
219.0
5
K6
32
56
69.0
69.8
16.2
10
7.9
9.2
531.2
5.0
959
4.6
74.3
53.9
811.0
621.0
7
K7
32
47
49.0
611
14.3
10
8.2
4.8
8.2
66.2
264.3
54.7
14.6
44.5
225.0
619.0
5
K8
32
47
58.5
53.8
12.5
47
4.5
948.5
74.7
475.3
44.2
34.2
25.3
515.3
017.0
2
K9
32
57
37.6
54.6
14.6
66
5.6
854.7
84.6
548.6
95.9
54.2
35.1
514.0
922.0
3
K10
41
17
36.4
86.7
13
75.8
5.9
865.2
5.6
982.6
44.3
95.1
54.2
613.2
221.0
1
K11
41
17
410.2
87.9
12
84.3
4.8
829.8
5.1
288.2
54.8
75.1
84.3
922.0
616.3
2
K12
31
37
69.2
45.8
16.9
95
6.2
633.2
15.5
699.8
4.6
54.6
94.9
710.0
824.0
2
K13
31
37
78.2
97.9
17
67.2
520.7
4.8
681.5
44.2
24.8
84.3
49.8
523.0
5
K14
22
26
57.8
76.6
16
87.9
819.3
55.9
548.9
84.1
54.8
75.1
115.0
421.0
9
K15
22
26
59.7
14.4
15.2
10
8.3
59.1
224.5
6.3
352.6
54.1
94.9
34.3
614.0
618.0
9
K16
22
57
47.6
15.3
15.4
10
5.2
7.4
817.6
4.5
864.3
24.8
74.8
55.2
218.0
919.0
6
K17
22
57
39.0
68.6
14.6
94.6
7.9
815.6
56.6
561.2
54.9
54.9
74.3
913.0
220.0
4
K18
31
47
38.0
54.9
13.8
69.2
929.3
5.2
259.8
44.6
54.3
54.7
517.0
222.0
3
K19
31
47
410.4
58.9
18.6
88.7
928.2
44.3
766.3
54.5
54.2
14.4
916.0
324.0
9
K20
32
36
39.6
45.6
17.6
77.9
88.3
34.0
690.2
84.0
25.6
44.7
822.0
320.0
3
*F
or
expla
nat
ion
of
char
acte
rsy
mbols
,se
e‘‘
Mat
eria
lsan
dm
ethods’
’se
ctio
n
Euphytica
123
a*, b*) according to Valverde et al. (2006) and Ruiz
and Egea (2008) to measure two representative
different areas of the surfaces of randomly selected
fruit, from which the mean value was calculated.
Three readings were taken at each point, the screen
showing their mean. The chromatic attributes chroma
(C* = ((a*)2 ? (b*)2)1/2), hue angle (H* = arc
tanb*/a*), and metric saturation (S* = (a*2 ? b*2)/
L*) were also determined.
Data analysis
All the statistical analyses were performed using the
SAS program (SAS Institute 2000). When the data was
denoted through percentages of proportions, an arc-
sine transformation was conducted to ensure a normal
distribution. The analysis of variance with the PROC
GLM procedure was applied to distinguish the effect
of the genotype and the year on the analyses traits.
To get basic statistics for the entire plant material
studied, number of observed seedlings, maximum and
minimum value, mean, mean standard error and
standard deviation for each trait were calculated.
Results were analyzed by considering cross and year
as fixed factors, and seedling within crosses and the
interaction of seedling with year, as the residual term.
Differences between crosses for each trait were
analyzed by Duncan’s multiple range test (P \ 0.05).
When comparing different fruit type t test (P \ 0.05)
was used. Correlation between traits to reveal possible
associations was calculated with raw data based on
single plant estimates over the 3 years, using Pearson
correlation coefficient at P \ 0.05 using PROC CORR
procedure was used to determine the coefficient values
of phenotypical correlation between all the character-
istics for each year. Principal components analysis
(PCA) was performed with family means to determine
the relationships among progenies and to obtain an
overview of correlation among fruit quality traits.
Results and discussion
Maturity date
All selections used were harvested between mid-May
and late June (Table 1); there were large variations in
harvest season among the tested genotypes. The
earliest almond seedling trees were ‘K1’ and ‘K2’,
which were harvested in mid-May. Most of almond
seedling selections were harvested in late May and
early June. The latest selections were cultivars ‘K3’
and ‘K4’ and selections ‘K7’ and ‘K10’, which had
maturity date in late June. Significant differences
between years were found for evaluated almond
seedling prognosis trees (Table 3), which could be
because of the influence of environmental conditions.
Grasselly (1972) and Kester and Asay (1975)
established that this trait was characteristic of each
cultivar, quantitative and easily transmitted to the
offspring. In addition, Dicenta and Garcıa (1993a) got
high values of heritability for this trait, and suggested
non-additive factors, which would allow breeders to
hasten the ripening date, which coincides with our
results. The ability to obtain earlier ripening descen-
dants than progenitors is interesting for breeders, as
this characteristic is important in cold areas to
accelerate the harvest.
Blooming and harvesting dates
Blooming and harvesting dates for the 20 breeding
progenies averaged over the 3 years are shown in
Fig. 1. Early flowering is a desirable character in
South of Iran to obtain earliest yields (Sorkheh et al.
2007, 2010) even though spring frosts may reduce
production in some years. Although no significant
differences were found among progenies for the
beginning of the bloom, higher differences were
observed for the full bloom and end of the bloom,
caused by the differences on the length of the
blooming period for different progenies. Blooming
date is considered as a quantitative trait in peach and
other Prunus species (Dirlewanger et al. 1999; Vargas
and Romero 2001). Thus, the differences for the
blooming date observed among the seedlings within
any progeny from the 20 breeding populations studied
(data not shown) were somehow expected. Regarding
harvesting time (Fig. 1), significant variations were
found in the harvest season among the tested geno-
types ranging from late-May to mid-September. The
earliest seedlings to be harvested (late-May) belonged
to the ‘K1’, ‘K2’, ‘K3’ and ‘K4’ progeny. The latest
seedlings were those from the ‘K9’, ‘K10’, ‘K11’,
‘K12’ and K13’ progeny, which were harvested from
mid-August to mid-September. The harvesting time
showed a normal distribution within each progeny
for all the crosses (data not shown), showing a
Euphytica
123
Ta
ble
3A
NO
VA
anal
ysi
so
fth
eef
fect
of
gen
oty
pe
and
yea
ro
nfr
uit
qu
alit
ytr
aits
ina
20
alm
on
dk
ern
elg
eno
typ
e
So
urc
ed
fB
loo
min
gti
me
Rip
pin
gti
me
Fru
ith
eig
ht
Fru
itw
idth
Fru
itth
ick
nes
sF
ruit
wei
gh
tS
ton
ew
eig
ht
Gen
oty
pe
19
0.2
3*
*0
.03
0*
*3
.18
**
1.3
5*
*0
.75
*0
.71
**
35
.2*
*
Yea
r2
0.6
1*
*0
.03
3*
*4
.18
**
3.2
6*
*0
.50
*0
.61
**
4.6
3*
*
Gen
oty
pe
9Y
ear
38
0.0
9*
0.0
07
*8
.92
ns
3.0
6*
0.0
7*
0.0
5*
0.0
46
ns
Err
or
11
80
.03
0.0
03
4.3
52
.21
0.0
20
.02
0.2
5
So
urc
eY
ield
Fru
itat
trac
tiv
enes
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Euphytica
123
quantitative genetic control. This trait established as
characteristic of each cultivar, and quantitatively
inherited (Dirlewanger et al. 1999; Vargas and
Romero 2001). This variability allows selecting the
most interesting harvesting date among the genotypes
to cover market demands (Byrne 2002).
Although blooming and harvesting time may
change every year depending on the environmental
conditions, especially temperature (Sanchez-Perez
et al. 2007; Mounzer et al. 2008; Ruiz and Egea
2008), the fruit development period (a days from full
bloom to maturity) remained more or less stable for
each seedling over the 3 years of study (data not
shown). The almond fruit development period is highly
dependent on cultivar (Arteaga and Socias i Company
2001; Sanchez-Perez et al. 2007), however, previous
research has shown an influence of spring temperatures
on the harvest date of almond cultivars (Kester 1965;
Dicenta and Garcıa 1992, 1993a, b; Sorkheh et al.
2010). Very early-maturing, as well as very late-
maturing almond genotypes, are of considerable inter-
est for the almond industry in the South of Iran (Moradi
2006), and the main difference among these genotypes
is the length of their fruit development period (Sorkheh
et al. 2007). In the present work, the fruit development
period ranged from 80 to 130 days for all the proge-
nies, except for ‘K9’–‘K13’, which showed the longest
period (approximately 165 days). Therefore, this was
the latest progeny to be harvested (Fig. 1). The shortest
fruit development period (data not shown), and the
earliest harvest season, was found in ‘K1’, ‘K2’, ‘K3’
and ‘K4’ progenies. This interesting trait, among
others, was valued in the selection of eleven genotypes
from these three progenies.
Kester (1965), Grasselly (1978), and Socias i
Company (1999), studying some descendants of
‘Tardy Nonpareil’ also observed a bimodal distribu-
tion for this trait what was explained by the presence of
a late blooming major gene, quantitatively modified
by other minor genes. On the other hand, Ballester and
Socias i Company (2001) studied a population from
‘Tardy Nonpareil’, identified three molecular markers
associated with this ‘‘late blooming gene’’, and
located this trait in the linkage group four of the
‘Felisia’ 9 ‘Bertina’ genetic map.
Despite this case of descendants of ‘Tardy Nonpa-
reil’, in general, blooming date was considered as a
quantitative trait by several authors (Grasselly 1972;
Vargas and Romero 2001) with a high heritability
(Kester et al. 1977; Dicenta et al. 1993, 2005). Dicenta
et al. (2005) established that the best strategy to get
late-blooming descendants is to cross progenitors as
late-blooming as possible. When the offspring show a
bimodal distribution we must select the latest-bloom-
ing, probably carrying the late-blooming allele, which
could be transmitted to its descendants. Even though
we did not find any descendant blooming later than the
progenitors, this has indeed happened in other crosses,
being used by the breeders to delay the blooming date
of the descendants even more. Finally, early maturity
and its short duration are interesting in dry-farming
conditions, because the water and nutritional needs of
the plant during hot periods are reduced and because
they limit the risk of damage to fruit before harvesting.
3 May
28 April
20 April
17 April
14 April
11 April
8 April
5 April
2 April
30 March
27 March
24 March
21 March
17 March
14 March
Date & Progeny
K1 K2 K3 K4 K5 K6 K7 K8 K9
K10 K11 K12 K13 K14 K15 K16 K17 K18 K19 K20
Fig. 1 Flowering period (red colour) and full bloom (black colour) of 20 inter-specific backcrosses of almond during the year 2007,
Julian days when 50 % of flowers were opened according to Moradi (2006) and Sanchez-Perez et al. (2007). (Color figure online)
Euphytica
123
Evaluation of physical attributes
Mean values and mean ranges of genotypes for each
trait are reported in Table 4. Results reflected signif-
icant diversity in the assayed almond genotypes. It was
considered that the blooming time reflected the highest
standard deviation (6.3 %), followed by the deviation
shown by the traits of total sugar content (5.6 %), fruit
width (4.4 %) and ripening time (4.3 %). The mean
values of the blooming time were high, varying from
33 to 72. The mean yield was almost 2.46 and it varied
from 0.2 to 4.8. The trait of the fruit weight and skin
ground colour showed the lowest value of standard
deviation among all flowering traits. Standard mean
values were obtained for kernel weight, length, width
and thickness. All the other traits related with the shape
of the nut and the kernel reflected less variable mean
values. The value of the fruit flavor, soluble solid
content and fruit shape did not show significant
differences along the 3 years. The value of the fruit
width did not significant along 2007 and 2006 although
in 2009, the fruit width lighter than in the other years,
thus showing stability in the value of this trait in the
growth conditions. The mean value of ripening time of
all the genotypes was 213.3. But, the fruit height in
most of the genotypes was noted to be between
3.98 cm (for ‘K6’) and 5.35 cm (for ‘K8’). Mean value
of the fruit thickness was between 4.02 cm (for ‘K20’)
and 5.95 cm (for ‘K9’). Conducting the Duncan
multiple range tests on the stone weight showed some
differences in the values along the 3 years. There were
significant differences among accessions concerning
the stone weight (Table 4). Values ranged between
13.22 and 25.2 (Table 4). Genotype ‘K2’ showed the
lowest value (3.22), while the highest percentage dry
matter (6.65) occurred for selection ‘K17’. The mean
value of the fruit attractiveness of the kernel varied
from 1.2 to 5.2. A significant variation was also
observed in the fruit test and fruit flavor, with values
ranging respectively from 1.0 to 3.0 and 0.9 to 3.2. The
mean values of the genotypes reflected significant
differences with regard to the soluble solid content,
revealing values from 1 to 3.2. Intensity of the flower
colour was noted to be similar in all the studied
genotypes, wherein, the values ranged from 1.3 to
5.31, however, many genotypes revealed a compara-
tively lighter flower color.
As expected, the analysis of variance revealed
significant differences in the values of all the measured
traits among the genotypes. However, the interaction
value of genotype 9 year was not significant for the
fruit height, the stone weight, the flower type and
flower colour and it was significant for the other
variables. This significant difference among the
genotypes and along the years reveals the influence
of both variables on the measured parameters; how-
ever, the low interaction value of the measure of
genotype 9 year for some variables also facilitates
the establishment of a range of classifications for the
main characteristics of the almond genotypes, which
would be maintained over the years. Colour has a
significant impact on consumer perception of almond
quality especially about fruit attractiveness. The
results show a large variability in the set of evaluated
almond genotypes, and significant differences were
observed among them (Table 4). The soluble solids
content is a important quality attribute, influencing
notably the fruit taste. The acidity of almond geno-
types is given in Table 4. Values got ranged from 1.2
(‘K8’) to 4.0 (‘K1’, ‘K7’) g malic acid/100 ml, with
significant differences among genotypes. No year-by-
year variation was observed by titratable acidity. The
fruit weight ranged from 1.0 g (‘K20’) to 3.2 g (‘K9’)
(Table 4) and differences among genotypes were
highly significant (Table 4). Previous work on apricot
also reported a high variability among cultivars
regarding this parameter (Perez-Gonzalez 1992; Led-
better et al. 1996; Badenes et al. 1998a, b). Year-by-
year variations were significant according to the
statistical analysis. Sensory analysis of attractiveness
and taste is shown in Table 5. The application of
sensory analysis using a panel of selected and trained
tasters is a reliable and effective method for the
evaluation of the organoleptic quality of almond
(Aydin 2003; Egea et al. 2006) and peach (Bassi and
Selli 1990; Colaric et al. 2005).
The highest value for the coordinate brightness (L*)
was obtained in the almond nut with values of around
68.32 for ‘K17’ while the lowest value related to ‘K10’
with 50.24. L* values ranged from 50.24 to 68.32,
48.25 to 58.25 and 90.34 to 96.46 in almond nut,
tegument and kernel respectively. The red component/
yellow component (a*/b*) values of the almond kernel
were negative in all genotypes from -0.15 in ‘K5’ and
‘K15’ to -0.1 in ‘K12’ and ‘K20’. Chroma (C*) had
quiet similar range in almond nut and tegument. Hue
angle (H*) ranged from maxima of 73.48 in ‘K2’,
‘K13’ in almond nut, 68.95 for ‘K1’ in tegument and
Euphytica
123
98.63 for ‘K5’ in almond kernel to minimum of 71.35
in ‘K6’ and ‘K9’ for almond nut, 65.13 in ‘K12’ for
tegument and 95.49 in ‘K12’ for almond kernel. The
lowest metric saturation (S*) values were around 6.18
in ‘K14’ for almond kernel and the highest was 43.65
in ‘K5’ for tegument (Table 5), these traits were
measured for almond by difference in Effect of the
irrigation regime by Valverde et al. (2006).
Correlation among variables
Significant correlations were found among pomolog-
ical traits related to the fruit quality (Table 6). Fruit
height was highly correlated with fruit width
(r = 0.82), fruit weight (r = 0.85), stone weight
(r = 0.91), fruit taste (r = 0.71) and yield
(r = 0.81). In addition, fruit width was correlated
strongly with fruit thickness (r = 0.91), fruit weight
(r = 0.95), stone weight (r = 0.72) and yield
(r = 0.83). Other assays of fruit quality mentioned
in Table 6. Although significant relationships were
observed between the colour measurements and
acidity (Table 6), the correlation coefficients were
quite low. In general, high hue angle (H*) values could
indicate low acidity, while low H* could be related
with a higher acidity. But, the coefficient correlations
were not enough high to prove this relationship (result
not shown). On the other hand, there was no relation-
ship between colour and firmness or taste (Table 6), in
agreement with previous work in peach (Genard et al.
1994). The tristimulus colour variables have been
related to the types and quantities of pigments present
in foods. Good correlations found between the Hunter
a* and H* (hue) values and the carotenoid concentra-
tion in apricot (Ruiz et al. 2005; Ruiz and Egea 2008).
The colour variables have also been recommended for
prediction of chemical and quality changes in food
products (Lozano and Ibarz 1997).
Our results show a high correlation between fruit
weight and stone weight (r = 0.91); therefore, both
parameters can be used to predict each other. This
relationship reported also by other authors in Prunus
species (Biondi et al. 1991; Okut and Akca 1995).
Correlation between fruit weight and soluble solid
Table 4 Evaluation of quantitative fruit traits in the 20 almond genotypes assayed
Years
2007 2008 2009 Mean Standard dev. Min Max
Blooming time 46b 44a 62c 50.7 6.3 33 72
Ripping time 211a 213b 216c 213.3 4.3 203 254
Fruit height 22a 31b 26c 26.3 2.7 21.6 28.6
Fruit width 18a 18.6a 24.3b 20.3 4.4 17.3 25.2
Fruit thickness 14.3b 12.2a 20.3c 15.6 2.45 10.0 22.2
Fruit weight 1.1a 2.0b 2.5b 1.86 0.25 1.0 3.2
Stone weight 16.3a 20.5b 24.6c 20.5 2.3 13.2 25.2
Yield 0.2a 3.0b 4.2c 2.46 0.49 0.2 4.8
Fruit attractiveness 3.0b 2.2a 3.4b 2.86 0.54 1.2 5.0
Fruit test 1.8a 2.7b 2.0b 2.16 0.89 1.0 3.0
Fruit flavor 1.2a 1.5a 1.8a 1.5 3.41 0.9 3.2
Soluble solid content 3.2a 3.3a 3.2a 3.23 1.75 1.0 3.2
Titratable acidity 3.4a 3.4a 3.6a 3.46 1.80 1.2 4.0
Total sugar content 33a 34b 37c 34.6 5.60 18.6 63
Fruit shape 1.0a 1.0a 1.0a 1.0 0.52 1.0 2.5
Skin pubescence 1.8a 2.7b 1.8a 2.1 0.50 1.2 3.2
Skin ground colour 1.8a 2.7b 2.0a 2.16 0.28 1.0 5.0
Flower type 1.3a 2.4b 2.0b 1.9 1.24 1.1 2.5
Flower colour 1.7a 2.6b 1.8a 2.03 1.35 1.3 5.3
Mean value for each year and mean, minimum, standard deviation and maximum for the 3 years. Values with different letters showed
statistically significant differences between years at the 5 % level according to the Duncan multiple tests
Euphytica
123
content or titratable acidity was not observed, in
agreement with previous work in other species
(Badenes et al. 1998; Asma and Ozturk 2005).
Conversely, only a limited relationship was found
between ripening time and soluble solid content
(r = -0.15), and there was low correlation with the
acidity (Table 6). Badenes et al. (1998), did not find a
correlation between harvest date and fruit weight,
while a significant correlation was observed between
ripening time and acidity. The differences between our
results and those of Badenes et al. (1998) could be
explained by differences in the plant material and in
the size of the group of cultivars studied.
There was no correlation between firmness and
other quality attributes such as colour, fruit weight
(Table 6), in agreement with previous studies
(Ledbetter et al. 1996; Badenes et al. 1998). Fruit
with the same hue angle had greatly differing fruit
taste (Lewallen and Marini 2003). However, Byrne
et al. (1991) found correlations between fruit taste,
soluble solid content, titratable acidity and colour
attributes among peach cultivars. They are reported that
soluble solid content was highly correlated with the dry
matter (r = 0.93), while no relationship between
soluble solid content and titratable acidity was found,
as reported previously by Badenes et al. (1998). But,
Asma and Ozturk (2005) found a significant correlation
between soluble solid content and titratable acidity in a
group of Turkish apricot cultivars. The differences
between our results and those of Asma and Ozturk
(2005) could be caused by the different ecogeograph-
ical groups of apricot cultivars.
Blooming and ripening time were not high signif-
icantly correlated. This fact implies that the number of
days from blossom to maturity is highly variable in
this collection, which was almost similar to other
research in almond that no correlation was observed
between the blooming and the ripening dates in the
genotypes (Sorkheh et al. 2010). It is mentioned the
most important significant correlation Because of
wide range of date. In the Table 6, correlations were
found among most of the traits, but in several traits it
Table 5 Results of colour value in almond progenies nut, tegument and kernel, according to L*, a* and b*and chroma (c*), hue
angle (H) and metric saturation (S) according to Valverde et al. (2006)
Almond kernel Almond tegument Almond nut
Genotype S* H* C* a*/b* L* S* H* C* a*/b* L* S* H* C* a*/b* L*
K1 8.46 98.01 25.07 -0.12 93.57 41.56 68.95 49.12 0.39 57.5 25.64 72.65 46.7 0.32 66.35
K2 7.49 97.96 26.01 -0.11 94.56 40.38 67.12 47.95 0.43 58.2 25.89 73.48 43.28 0.3 60.22
K3 8.28 97.48 27.05 -0.13 93.48 41.09 66.32 46.87 0.42 57.96 25.72 72.89 44.35 0.3 60.87
K4 8.39 98 28.09 -0.14 92.78 42.56 67.44 48.46 0.43 55.96 26.23 72.44 45.28 0.29 62.12
K5 8.02 98.63 24.06 -0.15 91.64 43.65 68.36 49.35 0.38 55.19 24.55 72.31 46.98 0.31 65.89
K6 7.18 98.46 25.08 -0.11 90.38 41.35 68.12 48.29 0.41 57.39 24.32 71.35 46.56 0.32 62.45
K7 7.36 97.66 27.08 -0.12 91.28 40.25 67.35 48.12 0.39 57.15 25.49 71.48 44.65 0.33 60.28
K8 7.15 96.15 27.012 -0.14 93.45 40.15 67.35 47.19 0.40 56.88 25.47 72.44 45.26 0.3 61.45
K9 8.23 96.66 29.08 -0.13 92.35 36.98 66.12 46.38 0.43 48.25 25.88 71.35 45.32 0.32 60.38
K10 8.45 97.48 25.06 -0.12 96.46 36.55 65.44 45.39 0.42 51.36 24.32 72.99 40.25 0.33 50.24
K11 7.36 96.36 27.08 -0.11 95.34 37.48 66.89 44.28 0.41 50.24 25.65 72.68 41.56 0.32 55.12
K12 7.25 95.49 27.02 -0.1 92.44 35.65 65.13 44.25 0.42 55.24 25.44 72.55 41.45 0.33 59.45
K13 7.88 98 27.08 -0.13 93.78 39.78 68.28 46.86 0.43 56.82 25.97 73.48 41.25 0.28 66
K14 6.18 96.35 26.05 -0.14 92.35 40.39 67.22 48.72 0.42 57.46 24.68 72.36 41.36 0.32 65.46
K15 7.69 97.64 27.62 -0.15 93.48 40.38 67.86 48.69 0.41 58.25 24.78 72 41.89 0.33 66.79
K16 6.48 98 28.25 -0.14 94.56 41.82 67.44 47.04 0.4 57.45 25.78 71.38 40.25 0.3 65.34
K17 8.35 98.48 26.05 -0.13 92 41.25 69.12 46.35 0.38 56.96 25.87 72.45 41.38 0.29 68.32
K18 8.26 96.35 27.41 -0.12 92.77 40.48 68.13 47.75 0.36 56.78 25.48 72.14 41.39 0.32 66.78
K19 7.82 97.68 27.05 -0.11 90.34 38.44 67.12 46.14 0.39 55.68 25.68 72.35 40.15 0.3 64.55
K20 7.28 96.54 25.65 -0.1 91.48 35.36 67.44 45.48 0.38 55.48 24.54 72.12 40.36 0.31 67.12
Euphytica
123
Table 6 Pearson’s correlation coefficient between fruit traits in inter-specific almond backcrosses assayed
Years
2007 2008 2009 Mean
Blooming time/Ripening time 0.13* 0.11* 0.1 n.s 0.11*
Blooming time/Fruit height -0.24* -0.2* -0.18* -0.21*
Blooming time/Fruit width -0.23* -0.18* -0.19* -0.2*
Blooming time/Fruit thickness -0.33* -0.28* -0.3* -0.3*
Blooming time/Fruit weight -0.22* -0.28* -0.33* -0.27*
Blooming time/Stine weight -0.38* -0.4* -0.45* -0.41*
Blooming time/Yield -0.05n.s -0.04 n.s -0.03 n.s -0.04n.s
Blooming time/Fruit attractiveness -0.03 n.s -0.03 n.s -0.05 n.s -0.03 n.s
Blooming time/Fruit attractiveness -0.28* -0.3* -0.35* -0.31*
Blooming time/Fruit flavor -0.34* -0.28* -0.22* -0.28*
Blooming time/Soluble solid content -0.61* -0.63* -0.6* -0.61*
Blooming time/Titratable acidity 0.24* 0.2* 0.25* 0.23*
Blooming time/Total sugar content -0.14* -0.17* -0.14* -0.15*
Blooming time/Fruit shape 0.05 n.s 0.08 n.s 0.1 n.s 0.07 n.s
Blooming time/Skin pubescences 0.28* 0.3* 0.32* 0.3*
Blooming time/Skin ground colour -0.09 n.s -0.05 n.s -0.03 n.s -0.05 n.s
Blooming time/Flower type -0.07 n.s -0.03 n.s -0.08 n.s -0.06 n.s
Blooming time/Flower colour -0.13* -0.12* -0.16* -0.14*
Ripening time/Fruit height -0.2* -0.19* -0.15* -0.18*
Ripening time/Fruit width -0.18* -0.1 n.s -0.15* -0.14*
Ripening time/Fruit thickness -0.08 n.s -0.05 n.s -0.06 n.s -0.06n.s
Ripening time/Fruit wieght -0.14* -0.12* -0.15* -0.14*
Ripening time/Stone weight -0.17* -0.15* -0.13* -0.15*
Ripening time/Yield -0.33* -0.31* -0.35* -0.33*
Ripening time/Fruit attractiveness -0.28* -0.25* -0.26* -0.26*
Ripening time/Fruit attractiveness 0.05 n.s 0.05 n.s 0.03 n.s 0.04 n.s
Ripening time/Fruit flower 0.18* 0.11* 0.1 n.s 0.13*
Ripening time/Soluble solid content -0.16* -0.13* -0.15* -0.15*
Ripening time/Titratable acidity 0.25* 0.23* 0.28* 0.25*
Ripening time/Total sugar content 0.08 n.s 0.1 n.s 0.11* 0.09 n.s
Stone weight/Yield 0.22* 0.18* 0.22* 0.21*
Stone weight/Fruit attractiveness -0.18* -0.17* -0.14* -0.16*
Stone weight/Fruit test 0.19* 0.32* 0.28* 0.26*
Stone weight/Fruit flavor 0.08 n.s 0.06 n.s 0.08 n.s 0.07 n.s
Stone weight/Soluble solid content -0.18* -0.22* -0.18* -0.19*
Stone weight/Titratable acidity -0.52* -0.45* -0.46* -0.48*
Stone weight/Total sugar content -0.09 n.s -0.06 n.s -0.11* -0.09 n.s
Stone weight/Fruit shape 0.65* 0.64* 0.7* 0.66*
Stone weight/Skin pubescences 0.39* 0.42* 0.55* 0.45*
Stone weight/Skin ground colour 0.11* 0.13* 0.12* 0.12*
Stone weight/Flower type 0.22* 0.28* 0.36* 0.29*
Stone weight/Flower colour 0.05 n.s 0.02 n.s 0.01 n.s 0.03 n.s
Yield/Fruit attractiveness 0.46* 0.56* 0.52* 0.51*
Yield/Fruit test 0.23* 0.24* 0.22* 0.23*
Euphytica
123
Table 6 continued
Years
2007 2008 2009 Mean
Yield/Fruit flavor -0.82* -0.69* -0.75* -0.75*
Yield/Soluble solid content 0.44* 0.38* 0.48* 0.43*
Yield/Titratable acidity -0.2* -0.18* -0.19* -0.19*
Yield/Total sugar content -0.1 n.s -0.15* -0.12* -0.12*
Yield/Fruit shape -0.04 n.s -0.02 n.s -0.01 n.s -0.02 n.s
Yield/Skin pubescences -0.55* -0.56* -0.64* -0.58*
Yield/Skin ground colour 0.02 n.s 0.08 n.s 0.03 n.s 0.04 n.s
Yield/Flower type 0.19* 0.14* 0.19* 0.17*
Yield/Flower colour -0.08 n.s -0.09 n.s -0.03 n.s -0.07 n.s
Fruit attractiveness/Fruit test 0.63* 0.71* 0.68* 0.67*
Fruit attractiveness/Fruit flavor 0.35* 0.3* 0.32* 0.32*
Fruit attractiveness/Soluble solid content -0.22* -0.21* -0.26* -0.23*
Fruit attractiveness/Titratable acidity -0.18* -0.23* -0.26* -0.22*
Fruit attractiveness/Total sugar content 0.11* 0.16* 0.19* 0.15*
Fruit attractiveness/Fruit shape 0.35* 0.42* 0.43* 0.4*
Fruit attractiveness/Skin pubescences -0.18* -0.32* -0.42* -0.31*
Ripening time/Fruit shape -0.03 n.s -0.02 n.s -0.02 n.s -0.02 n.s
Ripening time/SP 0.12* 0.13* 0.12* 0.12*
Ripening time/Skin ground colour 0.54* 0.59* 0.61* 0.58 *
Ripening time/Flower type -0.02 n.s -0.01 n.s -0.06 n.s -0.03 n.s
Ripening time/Flower colour 0.32* 0.35* 0.32* 0.33*
Fruit height/Fruit width 0.78* 0.82* 0.85* 0.82*
Fruit height/Fruit thickness 0.18* 0.11* 0.09 n.s 0.13*
Fruit height/Fruit weight 0.77* 0.88* 0.89* 0.85*
Fruit height/Stone weight 0.9* 0.96* 0.86* 0.91*
Fruit height/Yield 0.78* 0.8* 0.85* 0.81*
Fruit height/Fruit attractiveness 0.11* 0.14* 0.15* 0.13*
Fruit height/Fruit test 0.74* 0.68* 0.71* 0.71*
Fruit height/Fruit flavor 0.44* 0.47* 0.55* 0.49*
Fruit height/Soluble solid content 0.48* 0.42* 0.39* 0.43*
Fruit height/Titratable acidity -0.31* -0.13* -0.11* -0.18*
Fruit height/Total sugar content 0.05 n.s 0.04 n.s 0.03 n.s 0.04 n.s
Fruit height/Fruit shape -0.29* -0.31* -0.35* -0.32*
Fruit height/Skin pubescences 0.22* 0.25* 0.2* 0.22*
Fruit height/Skin ground colour -0.48* -0.62* -0.63* -0.58*
Fruit height/Flower type -0.04 n.s -0.07 n.s -0.03 n.s -0.05 n.s
Fruit height/Flower colour 0.38* 0.4* 0.44* 0.41*
Fruit width/Fruit thickness 0.87* 0.9* 0.95* 0.91*
Fruit width/Fruit weight 0.98* 0.9* 0.96* 0.95*
Fruit width/Stone weight 0.81* 0.75* 0.59* 0.72*
Fruit width/Yield 0.85* 0.87* 0.78* 0.83*
Fruit width/Fruit attractiveness 0.33* 0.22* 0.25* 0.27*
Fruit width/Fruit test 0.84* 0.8* 0.85* 0.83*
Fruit width/Fruit flavor 0.54* 0.62* 0.74* 0.63*
Euphytica
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Table 6 continued
Years
2007 2008 2009 Mean
Fruit width/Soluble solid content 0.55* 0.54* 0.45* 0.51*
Fruit width/Titratable acidity -0.45* -0.54* -0.56* -0.52*
Fruit width/Total sugar content -0.01 n.s -0.03 n.s -0.02 n.s -0.02 n.s
Fruit attractiveness/Skin ground colour 0.04 n.s 0.03 n.s 0.08 n.s 0.05 n.s
Fruit attractiveness/Flower type 0.09 n.s 0.11* 0.15* 0.12*
Fruit attractiveness/Flower colour 0.16* 0.19* 0.22* 0.19*
Fruit test/Fruit flavor 0.72* 0.78* 0.87* 0.79*
Fruit test/Soluble solid content 0.14* 0.13* 0.12* 0.13*
Fruit test/Titratable acidity 0.11* 0.16* 0.13* 0.13*
Fruit test/Total sugar content -0.22* -0.22* -0.29* -0.24*
Fruit test/Fruit shape -0.68* -0.72* -0.78* -0.73*
Fruit test/Skin pubescences -0.17* -0.18* -0.16* -0.17*
Fruit test/Skin ground colour 0.22* 0.21* 0.28* 0.24*
Fruit test/Flower type -0.08 n.s -0.06 n.s -0.03 n.s -0.06 n.s
Fruit test/Flower colour 0.18* 0.15* 0.18* 0.17*
Fruit flavor/Soluble solid content 0.38* 0.35* 0.31* 0.35*
Fruit flavor/Titratable acidity 0.28* 0.47* 0.59* 0.45*
Fruit flavor/Total sugar content -0.72* -0.82* -0.89* -0.81*
Fruit flavor/Fruit shape -0.54* -0.52* -0.56* -0.54*
Fruit flavor/Skin pubescences -0.14* -0.17* -0.12* -0.14*
Fruit flavor/Skin ground colour -0.24* -0.25* -0.22* -0.24*
Fruit flavor/Flower type -0.3* -0.34* -0.39* -0.34*
Fruit flavor/Flower colour -0.06 n.s -0.05 n.s -0.04 n.s -0.05 n.s
Soluble solid content/Titratable acidity 0.15* 0.19* 0.22* 0.19*
Soluble solid content/Total sugar content 0.15* 0.17* 0.32* 0.21*
Soluble solid content/Fruit shape -0.61* -0.68* -0.67* -0.65*
Soluble solid content/Skin pubescences -0.29* -0.39* -0.44* -0.37*
Soluble solid content/Skin ground colour -0.16* -0.16* -0.14* -0.15*
Soluble solid content/Flower type 0.22* 0.27* 0.29* 0.26*
Soluble solid content/Flower colour 0.05 n.s 0.03 n.s 0.02 n.s 0.03 n.s
Titratable acidity/Total sugar content 0.12* 0.13* 0.17* 0.14*
Titratable acidity/Fruit shape -0.17* -0.18* -0.11* -0.15*
Titratable acidity/Skin pubescences 0.1 n.s 0.11* 0.17* 0.13*
Titratable acidity/Skin ground colour -0.18* -0.14* -0.12* -0.15*
Fruit width/Fruit shape -0.34* -0.35* -0.33* -0.34*
Fruit width/Skin pubescences -0.35* -0.38* -0.34* -0.36*
Fruit width/Skin ground colour -0.05 n.s -0.04 n.s -0.02 n.s -0.04 n.s
Fruit width/Flower type 0.02 n.s 0.06 n.s 0.05 n.s 0.04 n.s
Fruit width/Flower colour -0.44* -0.48* -0.45* -0.46*
Fruit thickness/Fruit weight 0.91* 0.87* 0.8* 0.86*
Fruit thickness/Stone weight 0.65* 0.63* 0.58* 0.62*
Fruit thickness/Yield 0.9* 0.93* 0.91* 0.91*
Fruit thickness/Fruit attractiveness 0.43* 0.52* 0.68* 0.54*
Fruit thickness/Fruit test 0.77* 0.77* 0.69* 0.74*
Euphytica
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Table 6 continued
Years
2007 2008 2009 Mean
Fruit thickness/Fruit flavor 0.66* 0.61* 0.58* 0.62*
Fruit thickness/Soluble solid content 0.64* 0.66* 0.6* 0.63*
Fruit thickness/Titratable acidity -0.37* -0.65* -0.69* -0.57*
Fruit thickness/Total sugar content -0.02 n.s -0.01 n.s -0.08 n.s -0.04 n.s
Fruit thickness/Fruit shape 0.14* 0.13* 0.11* 0.13*
Fruit thickness/Skin pubescences -0.04 n.s -0.03 n.s -0.09 n.s -0.05 n.s
Fruit thickness/Skin ground colour 0.06 n.s 0.09 n.s 0.04 n.s 0.06 n.s
Fruit thickness/Flower type 0.01 n.s 0.07 n.s 0.02 n.s 0.03 n.s
Fruit thickness/Flower colour 0.23* 0.18* 0.12* 0.18*
Fruit weight/Stone weight 0.62* 0.62* 0.63* 0.62*
Fruit weight/Yield 0.41* 0.39* 0.4* 0.4*
Fruit weight/Fruit test -0.22* -0.18* -0.19* -0.2*
Fruit weight/Fruit test 0.49* 0.41* 0.54* 0.48*
Fruit weight/Fruit flavor -0.53* -0.52* -0.61* -0.55*
Fruit weight/Soluble solid content 0.35* 0.32* 0.39* 0.35*
Fruit weight/Titratable acidity -0.49* -0.94* -0.98* -0.8*
Fruit weight/Total sugar content -0.03 n.s -0.09 n.s -0.03 n.s -0.05 n.s
Fruit weight/Fruit shape -0.28* -0.22* -0.28* -0.26*
Fruit weight/Skin pubescences -0.8* -0.05 n.s -0.03 n.s -0.29*
Fruit weight/Skin ground colour 0.09 n.s 0.1 0.18* 0.12*
Fruit weight/Flower type 0.25* 0.3* 0.46* 0.34*
Fruit weight/Flower colour 0.11* 0.13* 0.1 n.s 0.11*
Titratable acidity/Flower type -0.54* -0.6* -0.78* -0.64*
Titratable acidity/Flower colour -0.04 n.s -0.07 n.s -0.03 n.s -0.05 n.s
Total sugar content/Fruit shape -0.13* -0.12* -0.19* -0.15*
Total sugar content/Skin pubescences 0.12* 0.13* 0.12* 0.12*
Total sugar content/Skin ground colour 0 n.s 0.01 n.s 0.11* 0.04 n.s
Total sugar content/Flower type -0.08 n.s -0.06 n.s -0.05 n.s -0.06 n.s
Total sugar content/Flower colour -0.23* -0.32* -0.44* -0.33*
Fruit shape/Skin pubescences 0.25* 0.16* 0.22* 0.21*
Fruit shape/Skin ground colour 0.12* 0.15* 0.12* 0.13*
Fruit shape/Flower type 0.21* 0.3* 0.44* 0.32*
Fruit shape/Flower colour -0.05 n.s -0.04 n.s -0.02 n.s -0.04 n.s
Skin pubescences/Skin ground colour -0.08 n.s -0.04 n.s -0.03 n.s -0.05 n.s
Skin pubescences/Flower type 0.06 n.s 0.03 n.s 0.06 n.s 0.05 n.s
Skin pubescences/Flower colour 0.02 n.s 0.01 n.s 0 n.s 0.01 n.s
Skin ground colour/Flower type 0.14* 0.12* 0.14* 0.13*
Skin ground colour/Flower colour -0.08 n.s -0.03 n.s -0.05 n.s -0.05 n.s
Flower type/Flower colour 0.23* 0.25* 0.42* 0.3*
Years 2007–2009 and all years combined
ns not significant
* significant at 0.05 level
Euphytica
123
contained high significantly. Very high correlation
values were recorded for the fruit height with each of
fruit width, fruit weight, stone weight, Yield and fruit
taste. Another high significant correlation was found
for the fruit width with each of the following traits:
fruit thickness, fruit weight, stone weight, yield and
fruit test. The third high correlation was obtained for
the fruit thickness versus stone weight, Yield and fruit
taste. There was a high negative correlation between
fruit weight and titratable acidity (-0.80). Results
were similar in some cases with Nikolic et al. (2010)
research. Small and no value of correlation were found
between the other traits.
The coefficients of correlation (Table 6) show
that the fruit height/stone weight, fruit width/fruit
thickness, fruit width/fruit weight and fruit thick-
ness/yield ratios are highly significant as compared
with all other ratios (more than 0.90). Significant
correlations were found among most of the pomo-
logical traits related to the fruit quality (Table 6).
Good correlation founded between the fruit taste
with fruit attractive and fruit flavour. Furthermore,
high correlation values were recorded for stone
weight and fruit shape. Some high negative values
Table 7 Eigen values and proportion of total variability
among almond genotypes as explained by the first 9 principal
components
PC Eigen values Percent var. Cumulative var.
1 6.524 30.03 30.03
2 5.122 20.22 50.25
3 4.215 18.47 68.72
4 3.101 8.45 77.17
5 2.228 6.30 83.47
6 1.874 5.12 88.59
7 1.748 4.14 92.73
8 1.658 3.22 95.95
9 1.054 2.22 98.17
Table 8 Component loadings for quality variables and component scores for 20 almond genotypes Table 3: Correlation between the
original variables and the first three principal components (PC)
Variable Component loading Progeny Component scores
PC1 PC2 PC3 PC1 PC2 PC3
Blooming time 0.39 -0.35 0.08 K1 -2.04 1.43 1.28
Ripening time 0.38 0.68 -0.03 K2 -1.32 1.87 -0.63
Fruit height -0.81 0.32 0.12 K3 -2.64 -0.74 0.74
Fruit width -0.93 0.47 -0.1 K4 0.36 0.52 0.45
Fruit thickness -0.9 0.16 -0.25 K5 1.54 0.48 1.37
Fruit weight -0.82 0.12 -0.3 K6 -0.11 1.98 -1.32
Stone weight -0.73 -0.11 -0.06 K7 1.78 0.19 0.22
Yield -0.24 -0.02 0.44 K8 1.65 1.43 -2.08
Fruit attractive -0.71 0.03 -0.55 K9 -2.35 0.18 -0.65
Fruit test -0.82 0.25 -0.02 K10 0.43 0.48 0.87
Fruit flavor -0.83 0.35 -0.03 K11 3.76 2.12 -1.32
Soluble solid content -0.53 0.48 -0.04 K12 0.75 0.76 0.53
Titratable acidity 0.59 0.51 0.24 K13 0.87 1.32 -1.76
Total sugar content 0.48 0.6 0.06 K14 1.97 0.76 1.23
Fruit shape 0.43 -0.38 0.55 K15 1.53 0.83 0.13
Skin pubescences 0.12 -0.38 -0.68 K16 2.17 2.54 -2.32
Skin ground colour -0.06 -0.6 0.01 K17 0.48 0.44 1.38
Flower type -0.8 -0.34 -0.45 K18 -2.14 1.22 1.14
Flower colour -0.6 -0.2 0.29 K19 -1.86 0.99 -0.34
K20 -1.34 -0.14 0.49
Euphytica
123
of correlation coefficients were got for yield, total
sugar content and fruit flavour (Table 6).
PCA and grouping of progenies
Principal component analysis, one of the multivariate
statistical procedures, used previously to establish
genetic relationships among cultivars and to study
correlations among fruit traits in almond genotypes
(Brown and Walker 1990; Badenes et al. 1998;
Gurrieri et al. 2001; Azodanlou et al. 2003) and peach
genotypes (Wu et al. 2003; Esti et al. 1997). Associ-
ations between traits emphasized by this method may
correspond to genetic linkage between loci controlling
traits or a pleiotropic effect (Iezzoni and Pritts 1991).
The PCA carried out in our work showed more than
68.72 % of the variability observed was explained by
the first five components (Table 7). PC1, PC2 and PC3
accounted for 30.03, 20.22 and 18.47 % respectively
of the variability. Table 8 shows the correlation
between the original variables and the first 3 principal
components: PC1 represents mainly fruit height, fruit
width, Fruit thickness, fruit weight and fruit flavour;
PC2 explains ripening time, total sugar content and
skin ground colour date; PC3 represents mainly fruit
attractive, fruit shape and skin pubescences. Figure 2
represents PC1 and PC2 plotted on a bi dimensional
plane. Component scores for the accessions evaluated
are shown in Table 8.
Component scores for the accessions evaluated are
shown in Table 8. Negative values for PC1 indicate
varieties with higher contents of total soluble solids
and better taste as well as lower colour intensity.
Varieties such as ‘K1’, ‘K2, ‘K3’, ‘K18’, ‘K19’ and
‘K20’ belong to this group (Fig. 2). The highest
positive values for PC1 indicate varieties with high
acidity and orange fruits (‘K5’, ‘K7’, ‘K8’, K9’,
‘K14’, ‘K15’, ‘K16’), as shown in Fig. 2. The highest
PC2 values correspond to varieties with later harvest
date and larger fruits, such as ‘K1’, ‘K2’, ‘K6’, ‘K8’,
‘K11’, K13, K16 and ‘K18’ (Fig. 2). The group of
Fig. 2 Segregation of 20
inter-specific
almond 9 peach progenies
formed by several
backcrosses according to
their fruit quality
characteristics determined
by principal component
analysis (PCA)
Euphytica
123
varieties with the lowest negative PC2 values stands
out especially because of their early harvest date and
low fruit weight (‘K3’ and ‘K4/17’). The highest PC3
values show the firmest varieties and a higher
percentage of blushes on the skin. Varieties such as
‘K1’, ‘K5’, ‘K17 ‘and K18’ belong to this group.
Conclusions
A high variability founded in inter-specific
almond 9 peach backcrosses progenies evaluated
with regard to the studied pomological traits related
to fruit quality, and significant differences among
selections were observed for studied quality attributes.
The inter-specific almond 9 peach backcrosses prog-
enies of evaluated, coming from different genetic
origins and with a large phenotypic variability, could
provide valuable information about the cultivated
genotypes of almond, regarding the parameters, which
influence almond quality.
Significant year-by-year variation showed for stud-
ied attribute. These interactions were particularly
important for the duration of maturity. A close
relationship between traits could facilitate or hinder
the breeding process, since the selection for a given
trait, could favour the presence of another desirable or
undesirable characteristics for this fruit tree. However,
an effect of the year was not observed for fruit height,
stone weight, flower type and flower colour, which
could be due to a greater genetic determination of
these pomological traits.
A high correlation was found among some almond
inter-specific selection quality attributes, which could
reduce the number of pomological traits which need to
be studied in breeding programmes and orchard
management. In addition, PCA it possible to establish
similar groups of genotypes, according to their quality
characteristics, as well as to study relationships among
pomological traits. This study also emphasizes the
usefulness of PCA in evaluating the fruit quality of
new breeding releases and studying relationships
among pomological traits.
Finally, it is important to point to the early
flowering, which permits to obtain earliest yields
because spring frosts may reduce production in some
years that can be consider in breeding programs.
Evaluated crosses in inter-specific almond 9 peach
backcrosses showed a good performance regarding
fruit quality aspects such as fruit height, fruit width,
fruit weight, stone weight, fruit taste and yield are
considered the most important for discriminating
pomological attributes in our studied cultivars as
showed by high correlation, which of resulted in the
inter-specific backcrosses for selection of new high
fruit quality accessions in the sought of Iran.
Acknowledgments The authors are gratefully thank
Shahrekord University for their financial support, the section
of Horticulture, ANRRC of Shahrekord and Karaj collection for
providing and access to the progenies at the station. We wish to
thank Kh. Chenaneh Hanoni for technical assistance and critical
review of the manuscript.
References
AOAC (1984) Official methods of analysis, 14th edn. Associa-
tion of Official Analytical Chemists, Arlington, pp 414–420
Arteaga N, Socias i Company R (2001) Heritability of fruit and
kernel traits in almond. Acta Hortic 591:269–274
Asai WK, Micke WC, Kester DE, Rough D (1996) The evalu-
ation and selection of current varieties; almond production
manual, University of California (system). Division of
Agriculture and Natural Resources. ANR Publications,
California, p 52
Asma BM, Ozturk K (2005) Analysis of morphological, pomo-
logical and yield characteristics of some apricot germplasm
in Turkey. Genet Resour Crop Evol 52:305–313
Aydin C (2003) Physical properties of almond nut and kernel.
J Food Eng 60:315–320
Azodanlou R, Darbellay C, Luisier JL, Villettaz JC, Amado R
(2003) Development of a model for quality assessment of
tomatoes and apricots. Food Sci Technol 36:223–233
Badenes ML, Martınez-Calvo J, Llacer G (1998a) Analysis of
apricot germplasm from the European ecogeographical
group. Euphytica 102:93–99
Badenes ML, Martınez-Calvo J, Llacer G (1998b) Estudio
comparativo de la calidad de los frutos de 26 cultivares de
melocotonero de origen norteamericano y dos variedades
poblacıon de origen espa0nol. Invest Agr Prod Prot Veg
13:56–70
Badenes ML, LLacer G, Crisosto CH (2006) Mejora de la
Calidad de Frutales de Hueso. In: Llacer G, Dı0ez MJ,
Carrillo JM, Badenes ML (eds) Mejora genetica de la
calidad en plantas. Sociedad Espanola de Ciencias Hortı0colas y Sociedad Espanola de Genetica, Valencia,
pp 551–578
Ballester J, Socias i Company R (2001) Genetic mapping of a
major gene delaying blooming time in almond. Plant Breed
120:268–270
Bassi D, Selli R (1990) Evaluation of fruit quality in peach and
apricot. Adv Hortic Sci 4:107–112
Berenguer T (1972) Caracteres de interes para la seleccio0n de
variedades de almendro. Inst. Agron. Medit, Zaragoza
Biondi G, Pratella GC, Bassi R (1991) Maturity indexes as a
function of quality in apricot harvesting. Acta Hortic
293:667–674
Euphytica
123
Brown AG (1975) Apples. In: Jannick J, Moore JN (eds)
Advances in fruit breeding. Purdue University Press, West
Lafayette, pp 3–38
Brown GS, Walker TD (1990) Indicators of maturity in apricots
using biplot multivariate analysis. J Sci Food Agric
53:321–331
Byrne DH (2002) Peach breeding trends. Acta Hortic 592:49–59
Byrne DH, Nikolic AN, Burns EE (1991) Variability in sugars,
acids, firmness, and color characteristics of 12 peach
genotypes. J Am Soc Hortic Sci 116:1004–1006
Cantin CM, Gogorcena Y, Moreno MA (2010) Phenotypic
diversity and relationships of fruit quality traits in peach
and nectarine [Prunus persica (L.) Batsch] breeding
progenies. Euphytica 171:211–226
Colaric M, Veberic R, Stampar F, Hudina M (2005) Evaluation
of peach and nectarine fruit quality and correlations
between sensory and chemical attributes. J Sci Food Agric
85:2611–2616
Dicenta F, Garcıa JE (1992) Phenotypical correlations among
some traits in almond. J Genet Breed 46:241–246
Dicenta F, Garcıa JE (1993a) Inheritance of self-compatibility
in almond. Heredity 70:313–317
Dicenta F, Garcıa JE (1993b) Inheritance of the kernel flavour in
almond. Heredity 70:308–312
Dicenta F, Garcıa JE, Carbonell E (1993) Heritability of flow-
ering, productivity and maturity in almond. J Hortic Sci
68:113–120
Dicenta F, Garcıa-Gusano M, Ortega E, Martınez-Go0mez P
(2005) The possibilities of early selection of late flowering
almonds as a function of seed germination or leafing time
of seedlings. Plant Breed 124:305–309
Dirlewanger E, Moing A, Rothan C, Svanella L, Pronier V,
Guye A, Plomion C, Monet R (1999) Mapping QTLs
controlling fruit quality in peach [P. persica (L.) Batsch].
Theor Appl Genet 98:18–31
Egea J, Romojaro F, Pretel MT, Martinez-Madrid MC, Costell
E, Cascales A (2006) Application of sensory analysis to the
determination of the determination of the optimum quality
and harvesting moment in apricots. Acta Hortic
701:529–532
Esti M, Messia MC, Sinesio F, Nicotra A, Conte L (1997)
Quality evaluation of peaches and nectarines by electro-
chemical and multivariate analyses: relationships between
analytical measurements and sensory attributes. Food
Chem 60:659–666
Etienne C, Rothan C, Moing A, Plomion C, Bodenes C,
Svanella-Dumas L, Cosson P, Pronier V, Monet R,
Dirlewanger E (2002) Candidate genes and QTLs for sugar
organic acid content in peach [P. persica (L.) Batsch].
Theor Appl Genet 105:145–159
FAOSTAT (2010) FAO statistical database. http://www.fao.
org/corp/statistics/en/. Accessed February 2010
Felipe AJ (1975) F1 hybrids of peach and almond trees as a
model for both species. Agricultura 44:661–663
Felipe AJ (1984) Etat de l’arboretum des espe‘ces sauvages
d’amandier a Saragose. Options Mediterr 84/I:203–204
Felipe AJ (1999). El cultivo del almendro. SECH. Boletın In-
formativo XII, No (1), pp 65–69
Fleckinger J (1945) Notations phenologiques et representations
graphiques du development des bourgeons de Poirier.
Congres de Paris de l’Association francaise pour
l’avancement des Sciencies, Paris, p 118
Genard M, Bruchou C (1992) Multivariate analysis of within
tree factors accounting for the variation of peach fruit
quality. Sci Hortic 52:37–51
Genard M, Souty M, Holmes S, Reich M, Breuils L (1994)
Correlations among quality parameters of peach fruit. J Sci
Food Agric 66:241–245
Grasselly C (1972) L’amandier caracte‘ res morphologiques et
physiologiques des variete s, modalite de leurs transmis-
sions chez les hybrides de premie‘re gene ration. The se,
Universite de Bordeaux I
Grasselly Ch (1978) Observations sur l’utilisation d’un mutant
d’Amandier a‘ floraison tardive dans un programme
d’hybridation. Ann Ame l Plantes 28:695
Gurrieri F, Audergon JM, Albagnac G, Reich M (2001) Soluble
sugars and carboxylic acids in ripe apricot fruit as param-
eters for distinguishing different cultivars. Euphytica
117:183–189
Hilling KW, Iezzoni A (1988) Multivariate analysis in a sour
cherry germplasm collection. J Am Soc Hortic Sci
113:928–934
Iezzoni AF, Pritts MP (1991) Applications of principal com-
ponents analysis to horticultural research. Hortic Sci
26:334–338
Institute SAS (2000) SAS/STAT user’s guide. SAS Institute,
Cary
Kester DE (1965) Inheritance of time of bloom in certain
progenies of almond. Proc Am Soc Hortic Sci 87:214–221
Kester DE, Asay RN (1975) Almonds. In: Janick y J, Moore JN
(eds) Advances in fruit breeding. Purdue University Press,
West Lafayette, pp 387–419
Kester DE, Rady P, Asay R (1977) Correlations of chilling
requirements for germination blooming and leafing within
and among seedling population of almond. J Am Soc
Hortic Sci 102:145–148
Kester DE, Gradziel TM, Grasselly C (1991) Almonds (Prunus).
In: Moore JM, Ballington JR (eds) Genetic resources of
temperate fruit and nut crops. The International Society for
Horticultural Science, Wageningen, pp 701–758
Kodad K, Socias i Company R (2008) Fruit set evaluation for
self-compatibility selection in almond. Sci Hortic
118:260–265
Kramer A, Twigg BA (1966) Fundamentals of quality control
for the food industry, 2nd edn. Avi Publishing, Westport
Ledbetter CA, Go0mez E, Burgos L, Peterson S (1996) Evalu-
ation of fruit quality of apricot cultivars and selections.
J Tree Fruit Prod 1:73–86
Lewallen KS, Marini RP (2003) Relationship between flesh
firmness and ground color in peach as influenced by light
and canopy position. J Am Soc Hortic Sci 128:163–170
Lozano JE, Ibarz A (1997) Colour changes in concentrated fruit
pulp during heating at high temperatures. J Food Eng
31:365–373
Martınez-Calvo J, Llacer G, Cunill M, Duran S, Badenes ML
(2006) Programa de mejora de melocotonero del IVIA.
Actas Hortic 45:221–222
Mohsenin NN (1970) Physical properties of plant and animal
materials. Gordon and Breach Science Publishers, New
York
Euphytica
123
Moradi H (2006) Study of quantitative and qualitative charac-
teristics of some almond cultivars in Shahrekord. Acta
Hortic 726:283–288
Mounzer OH, Conejero W, Nicolas E E, Abrisqueta I, Garcıa-
Orellana YV, Tapia LM, Vera J, Abrisqueta JM, Ruiz-
Sanchez MC (2008) Growth pattern and phonological
stages of early-maturing peach trees under a Mediterranean
climate. Hortic Sci 43:1813–1818
Nicotra A, Conte L, Moser L, Fantechi P (2002) New types of
high quality peaches: flat peaches (P. persica var. Plati-
carpa) and Ghiaccio peach series with long on tree fruit life.
Acta Hortic 1–2:131–135
Nikolic D, Rakonjac V, Milatovic D, Fotiric M (2010) Multi-
variate analysis of vineyard peach [Prunus persicaL. Batsch] germplasm collection. Euphytica 171:227–234
Nikoumanesh K, Ebadia A, Zeinalabedinib M, Gogorcenac Y
(2011) Morphological and molecular variability in some
Iranian almond genotypes and related Prunus species and
their potentials for rootstock breeding. Sci Hortic
129:108–118
Okut H, Akca Y (1995) Study to determine the causal relations
between fruit weight and certain important fruit charac-
teristics with using a path analysis. Acta Hortic 384:97–102
Perez-Gonzalez S (1992) Associations among morphological
and phenological characters representing apricot germ-
plasm in Central Mexico. J Am Soc Hortic Sci 117:486–490
Ruiz D, Egea J (2008) Phenotypic diversity and relationships of
fruit quality traits in apricot (Prunus armeniace L.) ger-
mpasm. Euphytica 163:143–158
Ruiz D, Egea J, Tomas-Barberan FA, Gil MI (2005) Carotenoids
from new apricot (Prunus armeniaca L.) varieties and their
relationship with flesh and skin color. J Agric Food Chem
53:6368–6374
Sabate J, Hook DG (1996) Almonds, walnuts and serum lipids.
In: Spiller GA (ed) Lipids in human nutrition. CRC Press,
Boca Raton, pp 137–144
Sanchez-Perez R, Ortega E, Duval H, Martınez-Go0mez P,
Dicenta F (2007) Inheritance and relationships of impor-
tant agronomic traits in almond. Euphytica 155:381–391
Saura F, Canellas J, Soler L (1988) La almendra. In: I.N.I.A (ed)
Composicion, variedades, desarrollo y maduracion.
Madrid, Spain
Scorza R, Sherman WB (1996) Peaches. In: Janick J, Moore JN
(eds) Fruit breeding. Tree and tropical fruits, vol 1. Wiley,
New York, p 325
Socias i Company R (1999) A major gene for flowering time in
almond. Plant Breed 118:443–448
Sorkheh K, Shiran B, Gradziel TM, Epperson BK, Martinez-
Gomez P, Asadi E (2007) Amplified Fragment Length
Polymorphism as a tool for molecular characterization of
almond germplasm: genetic diversity among cultivated
genotypes and related wild species of almond. Euphytica
156:327–344
Sorkheh K, Shiran B, Rouhi V, Asadi E, Jahanbazi H, Moradi H,
Gradziel TM, Martınez-Go0mez P (2009) Phenotypic
diversity within native Iranian almond (Prunus spp.) spe-
cies and their breeding potential. Genet Resour Crop Evol
56:947–961
Sorkheh K, Shiran B, Khodambashi M, Moradi H, Gradziel TM,
Martinez-Gomez P (2010) Correlations between quantita-
tive tree and fruit almond traits and their implications for
breeding. Sci Hortic 125:323–331
Valverde M, Madrid R, Garcia AL (2006) Effect of the irrigation
regime, type of fertilization, and culture year on the
physical properties of almond (cv. Guara). J Food Eng
78:584–593
Vargas FJ, Romero MA (2001) Blooming time in almond
progenies. Options Mediterr 56:29–34
Wu B, Quilot B, Kervella J, Genard M, Li S (2003) Analysis of
genotypic variation of sugar and acid contents in peaches
and nectarines through the principle component analysis.
Euphytica 132:375–384
Euphytica
123