Phenotypic diversity and relationships of fruit quality traits in peach and nectarine [ Prunus persica (L.) Batsch] breeding progenies

Page 1

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

Page 2

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

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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.

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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

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76.5

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24.5

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55.2

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118.0

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11

16

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210.5

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23.2

258.2

15.3

24.4

84.3

212.5

20.0

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21

36

48.5

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17.6

66

5.2

55.6

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23.6

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94.3

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816.0

4

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21

57

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7.6

18.2

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25.2

665.5

95.1

13.9

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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

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Euphytica

123

Page 6

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

Page 7

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Euphytica

123

Page 8

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)

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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

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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

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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

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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*

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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*

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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*

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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

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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

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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)

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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.

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