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Morphological and pomological characterization of edible fig (Ficus carica L.) to select the superior trees
Scientia Horticulturae 238 (2018) 66–74
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Scientia Horticulturae journal homepage: www.elsevier.com/locate/scihorti
Morphological and pomological characterization of edible fig (Ficus carica L.) to select the superior trees
T
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Ali Khadivi , Rahim Anjam, Karim Anjam Department of Horticultural Sciences, Faculty of Agriculture and Natural Resources, Arak University, 38156-8-8349 Arak, Iran
A R T I C LE I N FO
A B S T R A C T
Keywords: Fig (Ficus carica) Morphological and pomological diversity Dried fruits Germplasm Breeding Fruit quality
Fig (Ficus carica L.) is one of the oldest traditional crops and sacred fruit tree widely present in the world. In the present investigation, the morphological and pomological variability of edible fig genotypes belonging to the Smyrna-type was evaluated from Estahban region located in Fars province in Iran. The studied genotypes exhibited significant variability in the characteristics analyzed and most of the measured traits showed the coefficient of variations (CV) more than 20.00%, revealing a high level of phenotypic diversity among the genotypes. Leaf length varied from 62.20 to 138.00 mm, while leaf width ranged from 41.00 to 153.00 mm. Ripening time ranged between very-early and late. The dried fruit weight ranged from 1.86 to 7.15 g and most of the genotypes showed high fruit quality. Simple correlation coefficient analysis revealed significant correlations among the variables measured. Dried fruit weight was positively correlated with leaf density, leaf dimensions, dried fruit length and dried fruit width. Cluster analysis revealed grouping of genotypes into two main clusters, where cluster II contained a large number of genotypes. While most of the genotypes studied showed high potential, nine genotypes were superior in terms of the fruit characters and are valuable gene pools. Further and future breeding programs with these genotypes can provide the better-quality cultivars. The results of the current work are framed in the context of a proper management of fig genetic resource.
1. Introduction Fig (Ficus carica L., 2n = 26, Moraceae) is native to western Asia and later was spread to the Mediterranean region. According to Kislev et al. (2006), fig trees are probably the first domesticated trees of the Neolithic Revolution, about a thousand years before the cereals. Hirst (1996) reported that the fig was domesticated “five thousand years earlier” than millet and wheat. Based on this historical context, scientists have been attended to detect and study the genetic variability of fig. Fig fruit species is widespread in many regions since it has high adaptation to different climate and soils (Mars, 2003). The genetic diversity of fig trees is rich, because this species has not been subjected to intensive breeding programs. In addition, 600 cultivars are locally cultivated and called varieties (Condit, 1955). They contain the selected genotypes with high-quality fruits and the cutting is used for their propagation. Nowadays, the fresh or dried fig fruits are consumed and also used for spirit beverage and jam. The fig is a gynodioecious species and pollinated by Blastophaga psenes L. wasp (Beck and Lord, 1988; Kislev et al., 2006). This species contains caprifigs (bisexual with functional male trees) and edible figs (unisexual female trees) (Valdeyron and
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Corresponding author. E-mail address: [email protected] (A. Khadivi).
https://doi.org/10.1016/j.scienta.2018.04.031 Received 13 March 2018; Received in revised form 13 April 2018; Accepted 16 April 2018 0304-4238/ © 2018 Elsevier B.V. All rights reserved.
Lloyd, 1979). Three types of female figs have been described for their cropping. Common figs produce their fruit parthenocarpically without pollination, which can produce one (unifera varieties) or two (bifera varieties) crops. The Smyrna-type figs need pollination with pollen of caprifigs. In addition, San Pedro-type figs produce their first crop (breba) parthenocarpically, while their second main crop requires pollination with pollen of caprifigs (Flaishman et al., 2008). A caprifig tree produces three fruit crop each year: profichi fruit in summer, mammoni fruit in autumn and mamme fruit in winter (Anjam et al., 2017). The profichi, as the main crop of caprifig, coincides with the main summer crop of edible female figs. Caprifig trees provide a pollen source for caprification, which is the transfer of pollen from caprifigs to female edible figs by Blastophaga psenes wasp (Condit, 1947). The propagation of figs is usually done through stem-cutting, and this method contributes to homonymy and synonymy; because the misidentification and soma-clonal variation are common occurrences in asexual propagated plant species such as fig (do Val et al., 2013). The long period of domestication, the usefulness of the perpetuation of certain traits through asexual propagation, and the exchange of
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which were quantitative and nine of which were qualitative traits. For each genotype, 30 leaves and 30 dried fruits were used for the morphological and pomological analyses. Some variables were measured by using laboratory equipment. Variable including leaf dimensions, petiole length, petiole thickness, central lobe depth, lateral lobe depth, dried fruit length, dried fruit width, ostiole width, fruit stalk length, fruit stalk diameter and fruit cracking width were measured with a digital caliper. Traits including dried fruit weight and seed weight were measured by electronic balance with 0.01 g precision. Also, some characteristics such as leaf density, leaf color, ripening time, fruit fall type, fruit skin color, fruit pulp internal color, fruit basal status, fruit skin wrinkle status and fruit quality were measured based on rating, panel test, and coding.
materials are also contributed to synonymy (Aradhya et al., 2010). Moreover, in recent decades, the intensive urbanization leads to severe genetic erosions. The most important fig characters that are of interest to consumers are the flesh quality and its very sweet taste. Growers and breeders also pay attention to some of the pomological traits such as fruit size, fruit weight, and fruit stalk shape, as well as adaptation to environmental conditions and high commercial values (Trad et al., 2013). The genetic variation of fruit species needs to preserve existing genetic resources more urgent (Esquinas Alcazar, 2005). Phenotype traits should be used for conserving and using the gene pools in the related programs. To better conserve and utilize genetic resources, the proper traits should be carefully selected and the morphological diversity in the collections should be accurately investigated (Giraldo et al., 2010). The collection and study of the phenotypic and genotypic variations of the gene pool of fig species are needed for the establishment of breeding programs to improve its landraces. Several earlier studies have reported the morphological diversity of edible fig accessions and suggested the use of morphological traits to characterize accessions in the world (Caliskan and Polat, 2008; Saddoud et al., 2008; Giraldo et al., 2010; Podgornik et al., 2010). In addition, rare studies on the morphological variation of caprifig germplasm and its potential for caprification of edible figs have been done (Condit, 1955; Khadivi-Khub and Anjam, 2014). The fig landrace ‘Sabz’, the main dried fig in Iran, belongs to the Smyrna type figs which bear only pistillate flowers and requires the wasp pollinator for the pollination of its fruit. The fruit crop of ‘Sabz’ ripens and partially dries on the tree. The fruit crops of ‘Sabz’ landrace are dried directly on the tree and do not fall until they are perfectly ripened. They are gathered after fallen and left in the sun for a few hours before being conditioned for sale. Caprifigs are the only type of figs that possess both staminate and pistillate flowers. The caprifig fruits containing the pollen (profichi) are harvested by growers before emerging B. psenes wasp, in June and are subjected in cans and hanged onto the Smyrna type ‘Sabz’ landrace trees so that the emerged wasps from profichi enter to the female flowers of the edible cultivar and pollinate the pistillate flowers. In Iran, fig species is represented by a large number of cultivars and genotypes which are facing genetic erosion. Thus, the aims of the current work were to evaluate the morphological and pomological diversity of edible fig genotypes grown in Estahban, which is the most important region of fig production in Iran that presents an interesting fig genetic resource; and to identify superior trees with high fruit quality.
2.3. Statistical analysis The average values of phenotypic data were used for statistical analysis. The parameters including mean, minimum value, maximum value, standard deviation (SD) and coefficient of variation (CV%) were calculated for the measured traits. The variance was analyzed for all the characters using SAS software (SAS Inst., 1990). Pearson correlation coefficients between the traits were determined using SPSS software. Principal component analysis (PCA) was used to determine the relationships among the genotypes using the SPSS software. A distance matrix generated from phenotypic data was used for cluster analysis based on Ward method to better understand the patterns of variability among the genotypes using PAST statistics software. In addition, a scatter plot was created according to the PC1 and PC2 using PAST software (Hammer et al., 2001). 3. Results and discussion 3.1. Morphological and pomological characteristics The studied genotypes exhibited significant variability in the characteristics analyzed. The highest CVs were recorded in fruit cracking width (77.78%), fruit skin color (70.92%) and fruit cracking percentage (66.38%), respectively. In addition, the least CVs were observed for the fruit pH (6.75%) and also the dried fruit width (7.79%). Nineteen out of the 29 measured traits showed CVs more than 20.00%, revealing a high level of phenotypic diversity among the genotypes (Table 1). High variabilities were detected in the traits related to leaves such as leaf dimensions, leaf lobe depth, and the leaf lobe number. The traits related to leaves are important for the assessment of landrace as well as in taxonomic investigations (Papadopoulou et al., 2002). Leaf density was high for most of the genotypes (46 genotypes, 52.90%), and followed by intermediate (23 genotypes, 26.40%) and low (18 genotypes, 20.70%). Leaf color was most frequently classified as green in 65 genotypes, while leaf color was silver for 19 genotypes. Leaf length varied from 62.20 to 138.00 mm, while leaf width ranged from 41.00 to 153.00 mm. Most of the genotypes had five lobes per leaf. Central lobe depth ranged from 16.80 to 62.00 mm, while lateral lobe depth ranged from 16.80 to 92.00 mm. Petiole length ranged from 16.80 to 58.00 mm and petiole thickness ranged between 1.70 and 6.30 mm (Table 1). The differences between Slovenian figs have been reported in the degrees of leaf lobation (the central lobe length/the leaf length) (Podgornik et al., 2010). The most frequent tree vigor observed was intermediate. Majority of the studied trees had an open and spreading habit. Podgornik et al. (2010) reported intermediate tree vigor and spreading habit for Slovenian figs. Ripening time was early in 66 genotypes, late in 15 genotypes, veryearly in three genotypes, and intermediate in three genotypes (Table 2). Dried fruit fall type was predominant (79 genotypes, 89.90%). Fruit yield ranged from 7.00 to 80.00 kg per/tree. Dried fruit length ranged from 19.80 to 36.20 mm and dried fruit width ranged from 15.70 to 25.20 mm (Table 1). Fruit dimensions are of great importance in
2. Material and methods 2.1. Plant materials In the present investigation, a total of 87 edible fig genotypes belonging to the Smyrna-type were selected from Estahban region located in Fars province in Iran. Among them, 80 genotypes belong to ‘Sabz’ landrace, two genotypes from ‘Siah’, three from ‘Shahanjir’, one from ‘Mati’ and one from ‘Choopani’, respectively. Estahaban is the main region of the fig fruit production in Iran with 28˚50′33″N latitude, 53˚35′16″E longitude and 1731 m height above sea level. This area has 17.20 °C annual average temperature and 181.81 mm annual precipitation. 2.2. Morphological and pomological characterization The characterization of plant materials was carried out using the IPGRI (International Plant Genetic Resources Institute) and CIHEAM descriptors for Ficus carica (IPGRI and CIHEAM, 2003). In total, 29 morphological and pomological characteristics were evaluated, 20 of 67
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Table 1 Descriptive statistics for the morphological and pomological traits among the studied edible fig genotypes. No.
Character
Abbreviation
Unit
Min
Max
Mean
SD
CV (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight
LDe LLe LWi LCo VeNo LoNo CeLoD LaLoD PeLe PeTh RiTi FrFaTy Yi FrLe FrWi FrWe OsWi FrStLe FrStDi FrCrWi FrCrPer FrSkCo FrPuInCo FrBaSta FrSkWrSta FrQu pH SeNo SeWe
Code mm mm Code Number Number mm mm mm mm Code Code kg mm mm g mm mm mm mm % Code Code Code Code Code – Number g
1 62.20 41.00 1 2 2 16.80 16.80 16.80 1.70 1 1 7.00 19.80 15.70 1.86 0.00 5.80 1.50 0.00 0.00 1 1 1 1 1 3.84 0.00 0.02
5 138.00 153.00 5 5 10 62.00 92.00 58.00 6.30 7 3 80.00 36.20 25.20 7.15 10.82 20.10 2.95 9.10 70.00 7 5 5 5 11 6.13 575.00 0.47
3.64 98.02 97.41 4.06 3.57 5.32 34.85 36.10 35.45 4.30 3.69 1.18 38.62 25.09 21.47 4.75 6.33 8.83 2.02 3.62 25.05 2.61 3.32 4.84 3.76 8.26 5.14 217.49 0.22
1.60 14.48 14.87 1.67 0.58 1.16 7.93 11.25 7.44 0.78 1.61 0.58 19.06 2.65 1.67 0.87 2.62 1.97 0.29 2.82 16.63 1.85 1.01 0.70 1.07 2.90 0.35 80.86 0.08
43.93 14.78 15.27 41.03 16.24 21.77 22.77 31.16 20.99 18.25 43.60 49.24 49.34 10.58 7.79 18.33 41.48 22.33 14.22 77.78 66.38 70.92 30.30 14.40 28.38 35.05 6.75 37.18 35.00
from 0.00 to 70.00%. The seven genotypes including ‘Siah-1′, ‘Siah-2′, ‘Sabz-22′, ‘Sabz-40′, ‘Sabz-60′, ‘Choopani’ and ‘Mati’ had no fruit cracking. The highest width of the cracked section of fruit was 9.10 mm and was observed in ‘Sabz-71’ genotype, while the lowest value of this trait was 0.00 mm. Cracking around ostiole is an undesirable trait, because the pathogens and pests enter to fruit via these cracks (Can, 1993). Fruit skin color was most often yellow (40 genotypes, 46.00%) and followed by dark yellow (31 genotypes, 35.60%), and also the fruit pulp internal color was yellow in most of the genotypes (63 genotypes, 72.40%) (Table 2). It is well known that the type of caprifig can have a significant effect on the color of both the fruit skin and its interior edible flesh (Janick and Moore, 1975). The colors of fruit skin and fruit flesh are used together with other features in determining the promising fig genotypes in breeding studies (Sacks and Shaw, 1994). Fruit quality was excellent in 28 genotypes, very-good in 31 genotypes, good in 11 genotypes, intermediate in seven genotypes, bad in five genotypes and very-bad in five genotypes. The range of pH was 3.84–6.13 and agreed with others (Aksoy et al., 1992; Koyuncu et al., 1998; Mars et al., 1998). ‘Mati’ genotype was seedless, while the range of seed number in other genotypes ranged from 24 (in ‘Siah-1’ and ‘Siah-2’ genotypes) to 575 (in ‘Sabz-11’ genotype). Pictures of tree, leaf, and fruit of the studied genotypes are shown in Fig. 1.
packing and transportation in fig (Condit, 1947). Dried fruit weight ranged from 1.86 to 7.15 g. Fruit weight is very important for marketing, sales, and consumption of figs (Aksoy et al., 1992). Fruit ostiole width ranged from 0.00 to 10.82 mm. Fruit ostiole width has been previously reported as 0.60–9.10 mm (Aksoy et al., 1992), 1.50–4.00 mm (Koyuncu et al., 1998), and 1.00–9.40 mm (Polat and Ozkaya, 2005). The highest values of fruit stalk length and fruit stalk diameter were 20.10 mm and 2.95 mm, respectively. Fruit cracking percentage varied
Table 2 Frequency distribution of the measured qualitative characters among the studied edible fig genotypes. Qualitative trait
Leaf density Leaf color Ripening time Fruit fall type Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality
Distribution
Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%)
Code 1
3
5
7
9
11
18 20.70 19 21.80 3 3.40 79 90.80 40 46.00 5 5.70 2 2.30 2 2.30 5 5.70
23 26.40 3 3.40 66 75.90 8 9.20 31 35.60 63 72.40 3 3.40 50 57.50 5 5.70
46 52.90 65 74.70 3 3.40 – – 9 10.30 19 21.80 82 94.30 35 40.20 7 8.00
– – – – 15 17.20 – – 7 8.00 – – – – – – 11 12.60
– – – – – – – – – – – – – – – – 31 35.60
– – – – – – – – – – – – – – – – 28 32.20
3.2. Correlations among the characters Simple correlation coefficient analysis revealed significant correlations among the variables measured (Table 3). Leaf length showed positive correlations with leaf width (r = 0.78), lobe number (r = 0.46), central lobe depth (r = 0.60), lateral lobe depth (r = 0.54), petiole length (r = 0.48) and petiole thickness (r = 0.46), and agreed with the finding of Khadivi-Khub and Anjam (2014) in caprifig. The existence of close positive correlations among leaf traits indicates that more leaf expansion leads to stronger aerial growth (Khadivi-Khub and Anjam, 2014, 2016; Anjam et al., 2017). Fruit yield showed positive 68
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Fig. 1. Tree, leaf, and fruit of the studied edible fig genotypes.
are very important to evaluate genotypes (Norman et al., 2011; Khadivi-Khub, 2014).
correlations with leaf density (r = 0.31), dried fruit width (r = 0.34) and dried fruit weight (r = 0.39). Also, dried fruit weight was positively correlated with leaf density (r = 0.22), leaf length (r = 0.35), leaf width (r = 0.45), leaf color (r = 0.34), vein number (r = 0.32), central lobe depth (r = 0.29) and lateral lobe depth (r = 0.23), and also highly correlated with dried fruit length (r = 0.51), and dried fruit width (r = 0.85), in accordance with the results of Khadivi-Khub and Anjam (2014, 2016) in caprifig. Fruit cracking percentage showed negative correlations with leaf color (r = −0.27), fruit fall type (r = −0.21) and fruit skin color (r = −0.20), while it showed positive collations with fruit yield (r = 0.27), ostiole width (r = 0.68), fruit cracking width (r = 0.65), seed number (r = 0.33) and seed weight (r = 0.30). In addition, fruit cracking width was negatively correlated with fruit fall type (r = −0.25), while this trait indicated positive correlations with ostiole width (r = 0.93), seed number (r = 0.32) and seed weight (r = 0.32). Fruit quality was positively correlated with leaf density (r = 0.31), dried fruit width (r = 0.25), dried fruit weight (r = 0.30), ostiole width (r = 0.58), fruit cracking width (r = 0.46), and fruit cracking percentage (r = 0.54). These traits may be used to predict each other and also can be regarded to characterize genotypes. In addition, it can be concluded that the evaluated traits have a similar effect in determining the cultivars with planting potential as well as the germplasm assessment. The correlation coefficient can provide information on the traits that
3.3. Principal component analysis (PCA) The PCA was used to identify patterns of variability among the genotypes studied (Iezzoni and Pritts, 1991). The PCA has been widely used to analyze the phenotypic diversity of edible figs (Saddoud et al., 2008; Caliskan and Polat, 2008; Giraldo et al., 2010; Podgornik et al., 2010) and caprifig (Khadivi-Khub and Anjam, 2014, 2016). For PCA, components with eigenvalues more than 1.00 were retained to uphold reliability of the final output. Thus, seven PCs were observed which contributed 69.86% of the total variance and the first three PCs explained 39.53% of the variance (Table 4). A plot of the variance extracted by seven PCs showed that the variance explained was decreased between PC1 and PC2, but the variance decrease became slow from PC2 onward (Fig. 2). Values above 0.58 were considered to be significant for the studied traits. PC1 explained 16.70% of the total variance and was represented by leaf length (0.80), leaf width (0.87), central lobe depth (0.82), lateral lobe depth (0.75), petiole length (0.75) and petiole thickness (0.72) with positive correlations. PC2 explained 11.86% of the total variance and was constituted by ostiole width (0.91), fruit cracking width (0.90), fruit cracking percentage (0.81) and fruit quality (0.65) with positive correlations. PC3 explained 10.98% of the total 69
LDe
1.00 −0.09 0.07 0.21* −0.11 0.09 −0.22* −0.04 0.05 −0.02 0.06 −0.18 0.31** 0.08 0.14 0.22* 0.16 0.01 −0.01 0.08 0.19 −0.35** −0.09 0.41** 0.39** 0.31** −0.08 0.17 0.19
FrWi
1.00 0.85** 0.33** −0.23* 0.51** 0.20 0.18
Varible
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight
Varible
70
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage 1.00 0.22* −0.21* 0.50** 0.06 0.09
FrWe
1.00 0.78** 0.14 0.44** 0.46** 0.60** 0.54** 0.48** 0.46** 0.29** 0.00 0.10 0.30** 0.35** 0.35** 0.04 0.04 0.37** −0.01 −0.01 0.09 0.13 −0.05 0.25* 0.02 0.02 0.04 0.10
LLe
1.00 0.12 −0.07 0.93** 0.68**
OsWi
1.00 0.12 0.38** 0.45** 0.66** 0.57** 0.52** 0.63** 0.19 0.07 0.16 0.27** 0.46** 0.45** 0.09 0.03 0.42** 0.01 0.07 0.08 0.14 0.05 0.268* 0.10 0.03 0.06 0.08
LWi
1.00 −0.25* 0.16 0.17
FrStLe
1.00 0.01 0.07 0.12 0.06 0.16 0.03 0.11 0.06 0.17 0.33** 0.26* 0.34** −0.10 0.02 0.20* −0.19 −0.27** 0.03 0.15 0.12 0.26* −0.02 0.05 0.09 0.19
LCo
1.00 −0.10 −0.14
FrStDi
1.00 0.57** 0.50** 0.46** 0.59** 0.34** 0.38** 0.14 −0.02 0.34** 0.36** 0.32** 0.05 0.07 0.263* 0.03 −0.04 0.10 0.16 −0.11 0.14 −0.10 0.14 −0.14 −0.04
VeNo
1.00 0.65**
FrCrWi
1.00 0.34** 0.39** 0.45** 0.35** 0.39** 0.16 0.13 0.41** 0.17 0.19 −0.02 0.36** 0.06 −0.05 0.05 0.05 0.09 0.13 0.18 0.02 0.13 0.15 0.12
LoNo
Table 3 Bivariate correlations among the morphological and pomological traits in the studied edible fig genotypes.
1.00
FrCrPer
FrSkCo
1.00 0.71** 0.58** 0.46** 0.20 0.25* 0.00 0.30** 0.36** 0.29** −0.12 0.02 0.48** −0.11 −0.14 0.25* 0.22* −0.29** 0.09 −0.12 0.09 −0.16 −0.14
CeLoD
FrBaSta
1.00 0.49** 0.27* 0.01 0.04 0.21* 0.28** 0.29** 0.04 0.08 0.25* 0.00 −0.07 −0.07 −0.01 0.09 0.21* 0.01 0.05 0.01 0.03
PeLe
FrPuInCo
1.00 0.55** 0.36** 0.19 0.23* 0.08 0.26* 0.26* 0.23* −0.02 0.16 0.34** −0.01 −0.04 0.21 0.21* −0.16 0.05 −0.05 0.23* −0.01 0.02
LaLoD
FrSkWrSta
1.00 0.29** 0.00 −0.01 0.06 0.37** 0.30** 0.14 0.05 0.28** 0.05 0.11 −0.01 0.05 0.05 0.21* 0.13 0.04 0.21 0.13
PeTh
FrQu
1.00 0.18 0.14 0.22* 0.14 0.21 −0.07 0.10 0.05 −0.08 −0.04 −0.04 0.03 0.14 0.21* −0.17 0.10 0.06 0.12
RiTi
pH
1.00 −0.13 0.28** −0.03 −0.11 −0.38** 0.30** 0.23* −0.25* −0.21* 0.61** 0.33** −0.28** −0.16 −0.51** 0.24* −0.05 −0.13
FrFaTy
SeWe
1.00 0.42** 0.51** −0.06 0.25* 0.43** −0.10 −0.12 0.31** 0.44** −0.04 0.13 −0.07 0.25* 0.06 0.10
FrLe
(continued on next page)
SeNo
1.00 0.12 0.34** 0.39** 0.23* 0.00 0.14 0.19 0.27* −0.08 −0.05 0.24* 0.30** 0.20 0.12 0.27* 0.31**
Yi
A. Khadivi et al.
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Table 4 Loading factor of variation in the principal components (PCs) in the studied edible fig genotypes.
1.00
SeWe
A. Khadivi et al.
1.00 0.32** 0.30** 1.00 0.04 0.30** 0.35** 1.00 0.30** −0.22* 0.09 0.19 1.00 −0.20 −0.17 0.04 0.36** 0.07 0.09 1.00 0.51** −0.40** −0.21* −0.39** 0.29** 0.05 0.04
1.00 0.27** 0.31** 0.11 0.36** 0.38**
pH FrSkWrSta FrPuInCo
−0.20 −0.05 0.29** 0.12 0.54** 0.04 0.33** 0.30** −0.18 −0.09 0.20 −0.02 0.46** 0.17 0.32** 0.32** 0.32 0.38** −0.26* 0.11 0.03 0.23* 0.05 0.07 0.21 0.05 0.21* −0.08 −0.01 0.21* 0.26* 0.16
FrCrWi
* **
FrStDi FrStLe
*
FrCrPer
FrSkCo
FrBaSta
FrQu
SeNo
1.00 0.81**
Component Variable
1
2
3
4
5
6
7
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight Total % of variance Cumulative %
−0.07 0.80** 0.87** 0.08 0.55 0.53 0.82**
0.12 −0.02 0.04 −0.33 0.11 0.03 −0.10
−0.18 0.05 0.05 0.18 0.18 0.12 0.25
0.72** 0.09 0.17 0.58** 0.00 0.21 −0.08
0.04 0.05 0.06 0.17 −0.24 0.01 −0.17
−0.18 0.08 0.08 0.07 0.03 −0.39 0.13
−0.10 0.09 −0.03 −0.06 0.59** 0.45 0.04
0.75**
0.01
0.27
−0.03
−0.06
−0.10
0.02
0.75** 0.72** 0.21 0.05 −0.01 0.21
−0.01 0.06 −0.14 −0.35 0.22 −0.04
−0.08 −0.13 −0.04 0.62** 0.03 0.65**
0.12 −0.05 0.11 −0.19 0.47 0.45
−0.03 0.27 0.17 −0.03 0.25 −0.11
−0.07 0.13 −0.02 −0.19 0.15 −0.03
0.22 0.12 0.79** 0.20 0.16 0.24
0.36 0.32
0.30 0.18
0.27 0.21
0.40 0.60**
0.07 0.06
0.59** 0.54
0.18 0.18
0.03 0.09 0.41
0.91** 0.14 −0.08
−0.07 0.29 0.47
0.08 0.02 0.16
0.21 0.14 0.03
0.05 −0.79** 0.52
0.01 0.10 −0.10
−0.03
0.90**
−0.02
−0.09
0.15
−0.02
0.03
−0.01
**
0.81
−0.09
0.05
0.14
−0.11
−0.01
0.05 0.10
−0.24 −0.01
0.76** 0.75**
−0.28 0.05
0.10 0.02
0.03 0.08
−0.01 −0.13
−0.06 0.21
0.19 0.03
−0.34 −0.25
0.43 0.66**
0.41 0.04
−0.38 0.16
0.07 0.15
0.07 0.03 0.02 0.01 4.84 16.70 16.70
0.65** 0.16 0.25 0.25 3.44 11.86 28.55
−0.18 0.55 0.10 0.09 3.18 10.98 39.53
0.36 −0.09 0.12 0.22 2.90 9.99 49.52
0.14 0.38 0.87** 0.83** 2.21 7.63 57.15
0.05 −0.10 −0.08 0.02 2.06 7.12 64.27
−0.32 0.10 −0.01 0.05 1.62 5.60 69.86
−0.25 −0.09 0.31** 0.14 0.58** 0.17 0.38** 0.40**
* Correlation is significant at the 0.05 level. ** Correlation is significant at the 0.01 level.
0.08 0.21* −0.06 0.37** 0.25* 0.12 0.19 0.26* Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight
0.00 0.21 0.04 0.52** 0.30** 0.07 0.18 0.26*
FrWi Varible
Table 3 (continued)
FrWe
OsWi
*
** Eigenvalues ≥ 0.58 are significant.
Fig. 2. Variance percentage accounted by seven principal components (PCs) in PCA in the studied edible fig genotypes.
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Fig. 3. Cluster analysis of the studied edible fig genotypes based on the morphological and pomological traits using Euclidean distances.
tool for selecting genotypes or new cultivars with superior traits. The present findings were in agreement with the previously reported results in edible figs (Caliskan and Polat, 2008; Podgornik et al., 2010) and caprifig (Khadivi-Khub and Anjam, 2014).
variability and was represented by fruit fall type (0.62), dried fruit length (0.65), fruit skin color (0.76), and fruit pulp internal color (0.75) with positive correlations. These characters were the most effective traits for separating and identifying the studied genotypes. In addition, these traits are economically important and can also be used as a useful 72
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Fig. 4. The scatter plot for the first two principal components (PC1/PC2, 28.55% of total variance) for the studied edible fig genotypes based on the morphological and pomological characters.
The current findings support the view that pomological and leaf characteristics are reliable in estimating genetic relationships among fig genotypes and can be used efficiently for discrimination. Similarly, many studies (Condit, 1955; Mars et al., 1998; Oukabli et al., 2002; Papadopoulou et al., 2002; Mars, 2003; Aljane and Ferchichi, 2005) revealed that morphological traits are very helpful in identification and evaluation of fig germplasm.
3.4. Phenotypic variability The Ward dendrogram reflected the similarities and dissimilarities among the genotypes based on the qualitative and quantitative variables measured. The most significant result was represented by the identification of two separate main clusters of genotypes based on morphological characteristics (Fig. 3). Cluster I included 18 genotypes that genotypes ‘Mati’, ‘Siah-1′, ‘Siah-2′, ‘Shahanjir-3′ along 14 genotypes of ‘Sabz’ landrace were placed in this cluster. Cluster II included 69 genotypes forming three sub-clusters. Sub-cluster II-A contained one genotype and Sub-cluster II-B consisted of 18 genotypes; while remaining 50 genotypes formed sub-cluster II-C. In addition, a scatter plot was prepared according to the PC1 and PC2 (28.55% of total variance) that reflected the relationship among the genotypes in terms of phenotypic characteristics. The plot distributed genotypes into four sides and showed significant differences for some traits (Fig. 4). Starting from negative to positive values of PC1, the studied genotypes indicated an increase in leaf length, leaf width, central lobe depth, lateral lobe depth, petiole length and petiole thickness. Starting from negative values to the positive values of PC2, the genotypes were characterized by higher values for ostiole width, fruit cracking width, fruit cracking percentage and fruit quality. The most of genotypes were placed in the central area of the plot. The results showed that the studied fig germplasm have high phenotypic variation. Because the genotypes were studied in the same region with an equal climate condition, the observed variation is probably more related to their genetics. Ideally, this characterization should be made under the same edaphoclimatic conditions. Phenotypic characterization is always needed and it should be included in any program of conservation and use of genetic resources (Giraldo et al., 2010). Similarly, high phenotypic variability was reported in fig collections from different countries such as Tunisia (Mars et al., 1998; Chatti et al., 2003), Turkey (Caliskan and Polat, 2008), Morroco (Oukabli et al., 2002), Spain (Sanches et al., 2002), Lebanon (Chalack et al., 2005) and Jordan (Almajalia et al., 2012). These studies indicated that high diversity in pomological and leaf-related traits could be used as an efficient marker system to discriminate between fig genotypes.
4. Conclusions The selection of highly discriminant variables is important to optimize resources for a feasible morphological characterization. This is especially important in a crop such as fig fruit with hundreds of genotypes described worldwide in which many synonymies and homonymies may be observed. As the first report in Estahban region in Iran, here edible fig genotypes were studied that some of them showed high fruit quality and can be directly used for cultivation or indirectly in breeding programs. One of the most important aims is to expand the sales time thanks to the cultivation of genotypes/cultivars with different ripening time. The ripening time of the fruits in the studied genotypes was variable and ranged between very-early and late. This study also demonstrates broad pomological diversity existing among fig genotypes. Further breeding with these genotypes may provide fig cultivars with the highest quality. To fulfill that, the superior genotypes such as 'Sabz-39′, 'Sabz-61′, 'Sabz-65′, 'Sabz-67′, 'Sabz-18′, 'Sabz-34′, 'Sabz-59′, 'Shahanjir-1′ and 'Shahanjir-2′ should be tested through the repeated assessments for multi-locations with high fig production. The results of the present study are framed in the context of a proper management and conservation of fig genetic resource. References Aksoy, U., Seferoglu, G., Mısirli, A., Kara, S., S¸ahin, N., Bulbul, S., Duzbastılar, M., 1992. Selection of the table fig genotypes suitable for Aegean Region. Proceedings of the First National Horticultural Congress. pp. 545–548 in Turkish. Aljane, F., Ferchichi, A., 2005. Morphological, chemical and sensory characterization of Tunisian fig (Ficus carica L.) cultivars based on dry fruits. Acta Hortic. 741, 60–68. Almajalia, D., Abdel-Ghanib, A.H., Migdadia, H., 2012. Evaluation of genetic diversity
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A. Khadivi et al. among Jordanian fig germplasm accessions by morphological traits and ISSR markers. Sci. Hortic. 147, 8–19. Anjam, K., Khadivi-Khub, A., Sarkhosh, A., 2017. The potential of caprifig genotypes for sheltering Blastophaga psenes L. for caprification of edible figs. Erwerbs-Obstbau 59, 45–49. Aradhya, M.K., Stover, E., Velasco, D., Koehmstedt, A., 2010. Genetic structure and differentiation in cultivated fig (Ficus carica L.). Genetica 138, 681–694. Beck, N.G., Lord, E.M., 1988. Breeding system in Ficus carica, the common fig. I. Floral diversity. Am. J. Bot. 75, 1904–1912. Caliskan, O., Polat, A., 2008. Fruit characteristics of fig cultivars and genotypes grown in Turkey. Sci. Hortic. 115, 360–367. Can, H.Z., 1993. The Investigation of Some Horticultural Characteristics of Some Selected Fig Genotypes in Aegean Region. Master Thesis. Ege University, Izmir, Turkey. Chalack, L., Chehade, A., Mattar, E., Khadari, B., 2005. Morphological characterization of fig accessions cultivated in Lebanon. Acta Hortic. 798, 54–61. Chatti, K., Salhi-Hannachi, A., Mars, M., Marrakchi, M., Trifi, M., 2003. Analysis of genetic diversity of Tunisian fig tree cultivars (Ficus carica L.) using morphological characteristics. Fruits 59, 49–61. Condit, I.J., 1947. The fig. Waltham, Mass. Cronica Botanica, USA. p. 222. . Condit, I.J., 1955. Fig varieties: a monograph. Hilgardia 23, 323–538. do Val, A.D., Souza, C.S., Ferreira, E.A., Salgado, S.M., Pasqual, M., Cançado, G.M., 2013. Evaluation of genetic diversity in fig accessions by using microsatellite markers. Genet. Mol. Res. 12, 1383–1391. Esquinas Alcazar, J., 2005. Protecting crop genetic diversity for food security political, ethical and technical challenges. Nat. Rev. Genet. 6, 519–526. Flaishman, M.A., Rodov, V., Stover, E., 2008. The fig: botany, horticulture, and breeding. Hortic. Rev. 34, 113–197. Giraldo, E., Lopez Corrales, M., Hormaza, J.I., 2010. Selection of the most discriminating morphological qualitative variables for characterization of fig germplasm. J. Am. Soc. Hortic. Sci. 135, 240–249. Hammer, Ø, Harper, D.A.T., Ryan, P.D., 2001. PAST: paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4 (1), 9. http:// palaeoelectronica.org/2001_1/past/issue1_01.htm. Hirst, K., 1996. Fig trees and archaeology. The history of the domestication of fig trees. About.com Archaeology. http://archaeology.about.com/od/domestications/a/fig_ trees.htm. Iezzoni, A.F., Pritts, M.P., 1991. Applications of principal component analysis to horticultural research. HortScience 26, 334–338. IPGRI and CIHEAM, 2003. Descriptors for figs. International Plant Genetic Resources Institute, Rome, Italy, and International Centre for Advanced Mediterranean Agronomic Studies, Paris, France. Janick, J., Moore, J.N., 1975. Advances in Fruit Breeding. Purdue University Press, West Lafayette, IN, USA p. 623.
Khadivi-Khub, A., 2014. Genetic divergence in seedling trees of Persian walnut for morphological characters in Markazi province from Iran. Braz. J. Bot. 37, 273–281. Khadivi-Khub, A., Anjam, K., 2014. Characterization and evaluation of male fig (caprifig) accessions in Iran. Plant Syst. Evol. 10, 2177–2189. Khadivi-Khub, A., Anjam, K., 2016. The relationship of fruit size and light condition with number, activity and price of Blastophaga psenes wasp in caprifigs. Trees 30, 1855–1862. Kislev, M.E., Hartmann, A., Bar-Yosef, O., 2006. Early domesticated fig in the Jordan Valley. Science 312, 1372–1374. Koyuncu, M.A., Bostan, S.Z., I˙slam, A., Koyuncu, F., 1998. Investigation on physical and chemical characteristics in fig cultivars grown in Ordu. Acta Hortic. 480, 87–89. Mars, M., 2003. Conservation of fig (Ficus carica L.) and pomegranate (Prunica granatum L.) varieties in Tunisia. In: Lemons, J., Victor, R., Schaffer, D. (Eds.), Conserving Biodiversity in Arid Regions. Kluwer, pp. 433–442. Mars, M., Chebli, T., Marrakchi, M., 1998. Multivariate analysis of fig (Ficus carica L.) germplasm in southern Tunisia. Acta Hortic. 480, 75–78. Norman, P.E., Tongoona, P., Shanahan, P.E., 2011. Determination of interrelationships among agr-morphological traits of yams (Discorea spp.) using correlation and factor analyses. J. Appl. Biosci. 45, 3059–3070. Oukabli, A., Mamouni, A., Laghezali, R., Khadari, B., Roger, J.P., Kjellberg, F., Ater, M., 2002. Genetic variability in Morrocan fig cultivars (Ficus carica) based on morphological and pomological data. Acta Hortic. 605, 54–60. Papadopoulou, K., Ehaliotis, C., Tourna, M., Kastanis, P., Karydis, I., Zervakis, G., 2002. Genetic relatedness among dioecious (Ficus carica L.) cultivars by random amplified polymorphic DNA analysis, and evaluation of agronomic and morphological characters. Genetica 114, 183–194. Podgornik, M., Vuk, I., Vrhovnik, I., Mavsar, D.B., 2010. A survey and morphological evaluation of fig (Ficus carica L.) genetic resources from Slovenia. Sci. Hortic. 125, 380–389. Polat, A.A., Ozkaya, M., 2005. Selection studies on fig in the Mediterranean region of Turkey. Pak. J. Bot. 37 (3), 567–574. Sacks, E.J., Shaw, D.V., 1994. Optimum allocation of subjective color measurements for evaluating fresh strawberries. J. Am. Soc. Hortic. Sci. 119, 330–334. Saddoud, O., Baraket, G., Chatti, K., Trifi, M., Marrakchi, M., Salhi-Hannachi, A., Mars, M., 2008. Morphological variability of fig (Ficus carica L.) cultivars. Int. J. Fruit Sci. 8, 35–51. Sanches, J., Melgarejo, P., Hemandz, F., Martienz, J.J., 2002. Acta Hortic. 605, 43–53. SAS® Procedures, Version 6, 3rd ed. SAS Institute, Cary, NC. Trad, M., Gaaliche, B., Renard, C.M.G.C., Mars, M., 2013. Plant natural resources and fruit characteristics of fig (Ficus carica L.) change from coastal to continental areas of Tunisia. J. Agric. Res. Dev. 3 (2), 022–025. Valdeyron, G., Lloyd, D.G., 1979. Sex differences and flowering phenology in the common Fig, Ficus carica L. Evolution 33, 673–685.
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Morphological and pomological characterization of edible fig (Ficus carica L.) to select the superior trees
T
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Ali Khadivi , Rahim Anjam, Karim Anjam Department of Horticultural Sciences, Faculty of Agriculture and Natural Resources, Arak University, 38156-8-8349 Arak, Iran
A R T I C LE I N FO
A B S T R A C T
Keywords: Fig (Ficus carica) Morphological and pomological diversity Dried fruits Germplasm Breeding Fruit quality
Fig (Ficus carica L.) is one of the oldest traditional crops and sacred fruit tree widely present in the world. In the present investigation, the morphological and pomological variability of edible fig genotypes belonging to the Smyrna-type was evaluated from Estahban region located in Fars province in Iran. The studied genotypes exhibited significant variability in the characteristics analyzed and most of the measured traits showed the coefficient of variations (CV) more than 20.00%, revealing a high level of phenotypic diversity among the genotypes. Leaf length varied from 62.20 to 138.00 mm, while leaf width ranged from 41.00 to 153.00 mm. Ripening time ranged between very-early and late. The dried fruit weight ranged from 1.86 to 7.15 g and most of the genotypes showed high fruit quality. Simple correlation coefficient analysis revealed significant correlations among the variables measured. Dried fruit weight was positively correlated with leaf density, leaf dimensions, dried fruit length and dried fruit width. Cluster analysis revealed grouping of genotypes into two main clusters, where cluster II contained a large number of genotypes. While most of the genotypes studied showed high potential, nine genotypes were superior in terms of the fruit characters and are valuable gene pools. Further and future breeding programs with these genotypes can provide the better-quality cultivars. The results of the current work are framed in the context of a proper management of fig genetic resource.
1. Introduction Fig (Ficus carica L., 2n = 26, Moraceae) is native to western Asia and later was spread to the Mediterranean region. According to Kislev et al. (2006), fig trees are probably the first domesticated trees of the Neolithic Revolution, about a thousand years before the cereals. Hirst (1996) reported that the fig was domesticated “five thousand years earlier” than millet and wheat. Based on this historical context, scientists have been attended to detect and study the genetic variability of fig. Fig fruit species is widespread in many regions since it has high adaptation to different climate and soils (Mars, 2003). The genetic diversity of fig trees is rich, because this species has not been subjected to intensive breeding programs. In addition, 600 cultivars are locally cultivated and called varieties (Condit, 1955). They contain the selected genotypes with high-quality fruits and the cutting is used for their propagation. Nowadays, the fresh or dried fig fruits are consumed and also used for spirit beverage and jam. The fig is a gynodioecious species and pollinated by Blastophaga psenes L. wasp (Beck and Lord, 1988; Kislev et al., 2006). This species contains caprifigs (bisexual with functional male trees) and edible figs (unisexual female trees) (Valdeyron and
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Corresponding author. E-mail address: [email protected] (A. Khadivi).
https://doi.org/10.1016/j.scienta.2018.04.031 Received 13 March 2018; Received in revised form 13 April 2018; Accepted 16 April 2018 0304-4238/ © 2018 Elsevier B.V. All rights reserved.
Lloyd, 1979). Three types of female figs have been described for their cropping. Common figs produce their fruit parthenocarpically without pollination, which can produce one (unifera varieties) or two (bifera varieties) crops. The Smyrna-type figs need pollination with pollen of caprifigs. In addition, San Pedro-type figs produce their first crop (breba) parthenocarpically, while their second main crop requires pollination with pollen of caprifigs (Flaishman et al., 2008). A caprifig tree produces three fruit crop each year: profichi fruit in summer, mammoni fruit in autumn and mamme fruit in winter (Anjam et al., 2017). The profichi, as the main crop of caprifig, coincides with the main summer crop of edible female figs. Caprifig trees provide a pollen source for caprification, which is the transfer of pollen from caprifigs to female edible figs by Blastophaga psenes wasp (Condit, 1947). The propagation of figs is usually done through stem-cutting, and this method contributes to homonymy and synonymy; because the misidentification and soma-clonal variation are common occurrences in asexual propagated plant species such as fig (do Val et al., 2013). The long period of domestication, the usefulness of the perpetuation of certain traits through asexual propagation, and the exchange of
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which were quantitative and nine of which were qualitative traits. For each genotype, 30 leaves and 30 dried fruits were used for the morphological and pomological analyses. Some variables were measured by using laboratory equipment. Variable including leaf dimensions, petiole length, petiole thickness, central lobe depth, lateral lobe depth, dried fruit length, dried fruit width, ostiole width, fruit stalk length, fruit stalk diameter and fruit cracking width were measured with a digital caliper. Traits including dried fruit weight and seed weight were measured by electronic balance with 0.01 g precision. Also, some characteristics such as leaf density, leaf color, ripening time, fruit fall type, fruit skin color, fruit pulp internal color, fruit basal status, fruit skin wrinkle status and fruit quality were measured based on rating, panel test, and coding.
materials are also contributed to synonymy (Aradhya et al., 2010). Moreover, in recent decades, the intensive urbanization leads to severe genetic erosions. The most important fig characters that are of interest to consumers are the flesh quality and its very sweet taste. Growers and breeders also pay attention to some of the pomological traits such as fruit size, fruit weight, and fruit stalk shape, as well as adaptation to environmental conditions and high commercial values (Trad et al., 2013). The genetic variation of fruit species needs to preserve existing genetic resources more urgent (Esquinas Alcazar, 2005). Phenotype traits should be used for conserving and using the gene pools in the related programs. To better conserve and utilize genetic resources, the proper traits should be carefully selected and the morphological diversity in the collections should be accurately investigated (Giraldo et al., 2010). The collection and study of the phenotypic and genotypic variations of the gene pool of fig species are needed for the establishment of breeding programs to improve its landraces. Several earlier studies have reported the morphological diversity of edible fig accessions and suggested the use of morphological traits to characterize accessions in the world (Caliskan and Polat, 2008; Saddoud et al., 2008; Giraldo et al., 2010; Podgornik et al., 2010). In addition, rare studies on the morphological variation of caprifig germplasm and its potential for caprification of edible figs have been done (Condit, 1955; Khadivi-Khub and Anjam, 2014). The fig landrace ‘Sabz’, the main dried fig in Iran, belongs to the Smyrna type figs which bear only pistillate flowers and requires the wasp pollinator for the pollination of its fruit. The fruit crop of ‘Sabz’ ripens and partially dries on the tree. The fruit crops of ‘Sabz’ landrace are dried directly on the tree and do not fall until they are perfectly ripened. They are gathered after fallen and left in the sun for a few hours before being conditioned for sale. Caprifigs are the only type of figs that possess both staminate and pistillate flowers. The caprifig fruits containing the pollen (profichi) are harvested by growers before emerging B. psenes wasp, in June and are subjected in cans and hanged onto the Smyrna type ‘Sabz’ landrace trees so that the emerged wasps from profichi enter to the female flowers of the edible cultivar and pollinate the pistillate flowers. In Iran, fig species is represented by a large number of cultivars and genotypes which are facing genetic erosion. Thus, the aims of the current work were to evaluate the morphological and pomological diversity of edible fig genotypes grown in Estahban, which is the most important region of fig production in Iran that presents an interesting fig genetic resource; and to identify superior trees with high fruit quality.
2.3. Statistical analysis The average values of phenotypic data were used for statistical analysis. The parameters including mean, minimum value, maximum value, standard deviation (SD) and coefficient of variation (CV%) were calculated for the measured traits. The variance was analyzed for all the characters using SAS software (SAS Inst., 1990). Pearson correlation coefficients between the traits were determined using SPSS software. Principal component analysis (PCA) was used to determine the relationships among the genotypes using the SPSS software. A distance matrix generated from phenotypic data was used for cluster analysis based on Ward method to better understand the patterns of variability among the genotypes using PAST statistics software. In addition, a scatter plot was created according to the PC1 and PC2 using PAST software (Hammer et al., 2001). 3. Results and discussion 3.1. Morphological and pomological characteristics The studied genotypes exhibited significant variability in the characteristics analyzed. The highest CVs were recorded in fruit cracking width (77.78%), fruit skin color (70.92%) and fruit cracking percentage (66.38%), respectively. In addition, the least CVs were observed for the fruit pH (6.75%) and also the dried fruit width (7.79%). Nineteen out of the 29 measured traits showed CVs more than 20.00%, revealing a high level of phenotypic diversity among the genotypes (Table 1). High variabilities were detected in the traits related to leaves such as leaf dimensions, leaf lobe depth, and the leaf lobe number. The traits related to leaves are important for the assessment of landrace as well as in taxonomic investigations (Papadopoulou et al., 2002). Leaf density was high for most of the genotypes (46 genotypes, 52.90%), and followed by intermediate (23 genotypes, 26.40%) and low (18 genotypes, 20.70%). Leaf color was most frequently classified as green in 65 genotypes, while leaf color was silver for 19 genotypes. Leaf length varied from 62.20 to 138.00 mm, while leaf width ranged from 41.00 to 153.00 mm. Most of the genotypes had five lobes per leaf. Central lobe depth ranged from 16.80 to 62.00 mm, while lateral lobe depth ranged from 16.80 to 92.00 mm. Petiole length ranged from 16.80 to 58.00 mm and petiole thickness ranged between 1.70 and 6.30 mm (Table 1). The differences between Slovenian figs have been reported in the degrees of leaf lobation (the central lobe length/the leaf length) (Podgornik et al., 2010). The most frequent tree vigor observed was intermediate. Majority of the studied trees had an open and spreading habit. Podgornik et al. (2010) reported intermediate tree vigor and spreading habit for Slovenian figs. Ripening time was early in 66 genotypes, late in 15 genotypes, veryearly in three genotypes, and intermediate in three genotypes (Table 2). Dried fruit fall type was predominant (79 genotypes, 89.90%). Fruit yield ranged from 7.00 to 80.00 kg per/tree. Dried fruit length ranged from 19.80 to 36.20 mm and dried fruit width ranged from 15.70 to 25.20 mm (Table 1). Fruit dimensions are of great importance in
2. Material and methods 2.1. Plant materials In the present investigation, a total of 87 edible fig genotypes belonging to the Smyrna-type were selected from Estahban region located in Fars province in Iran. Among them, 80 genotypes belong to ‘Sabz’ landrace, two genotypes from ‘Siah’, three from ‘Shahanjir’, one from ‘Mati’ and one from ‘Choopani’, respectively. Estahaban is the main region of the fig fruit production in Iran with 28˚50′33″N latitude, 53˚35′16″E longitude and 1731 m height above sea level. This area has 17.20 °C annual average temperature and 181.81 mm annual precipitation. 2.2. Morphological and pomological characterization The characterization of plant materials was carried out using the IPGRI (International Plant Genetic Resources Institute) and CIHEAM descriptors for Ficus carica (IPGRI and CIHEAM, 2003). In total, 29 morphological and pomological characteristics were evaluated, 20 of 67
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Table 1 Descriptive statistics for the morphological and pomological traits among the studied edible fig genotypes. No.
Character
Abbreviation
Unit
Min
Max
Mean
SD
CV (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight
LDe LLe LWi LCo VeNo LoNo CeLoD LaLoD PeLe PeTh RiTi FrFaTy Yi FrLe FrWi FrWe OsWi FrStLe FrStDi FrCrWi FrCrPer FrSkCo FrPuInCo FrBaSta FrSkWrSta FrQu pH SeNo SeWe
Code mm mm Code Number Number mm mm mm mm Code Code kg mm mm g mm mm mm mm % Code Code Code Code Code – Number g
1 62.20 41.00 1 2 2 16.80 16.80 16.80 1.70 1 1 7.00 19.80 15.70 1.86 0.00 5.80 1.50 0.00 0.00 1 1 1 1 1 3.84 0.00 0.02
5 138.00 153.00 5 5 10 62.00 92.00 58.00 6.30 7 3 80.00 36.20 25.20 7.15 10.82 20.10 2.95 9.10 70.00 7 5 5 5 11 6.13 575.00 0.47
3.64 98.02 97.41 4.06 3.57 5.32 34.85 36.10 35.45 4.30 3.69 1.18 38.62 25.09 21.47 4.75 6.33 8.83 2.02 3.62 25.05 2.61 3.32 4.84 3.76 8.26 5.14 217.49 0.22
1.60 14.48 14.87 1.67 0.58 1.16 7.93 11.25 7.44 0.78 1.61 0.58 19.06 2.65 1.67 0.87 2.62 1.97 0.29 2.82 16.63 1.85 1.01 0.70 1.07 2.90 0.35 80.86 0.08
43.93 14.78 15.27 41.03 16.24 21.77 22.77 31.16 20.99 18.25 43.60 49.24 49.34 10.58 7.79 18.33 41.48 22.33 14.22 77.78 66.38 70.92 30.30 14.40 28.38 35.05 6.75 37.18 35.00
from 0.00 to 70.00%. The seven genotypes including ‘Siah-1′, ‘Siah-2′, ‘Sabz-22′, ‘Sabz-40′, ‘Sabz-60′, ‘Choopani’ and ‘Mati’ had no fruit cracking. The highest width of the cracked section of fruit was 9.10 mm and was observed in ‘Sabz-71’ genotype, while the lowest value of this trait was 0.00 mm. Cracking around ostiole is an undesirable trait, because the pathogens and pests enter to fruit via these cracks (Can, 1993). Fruit skin color was most often yellow (40 genotypes, 46.00%) and followed by dark yellow (31 genotypes, 35.60%), and also the fruit pulp internal color was yellow in most of the genotypes (63 genotypes, 72.40%) (Table 2). It is well known that the type of caprifig can have a significant effect on the color of both the fruit skin and its interior edible flesh (Janick and Moore, 1975). The colors of fruit skin and fruit flesh are used together with other features in determining the promising fig genotypes in breeding studies (Sacks and Shaw, 1994). Fruit quality was excellent in 28 genotypes, very-good in 31 genotypes, good in 11 genotypes, intermediate in seven genotypes, bad in five genotypes and very-bad in five genotypes. The range of pH was 3.84–6.13 and agreed with others (Aksoy et al., 1992; Koyuncu et al., 1998; Mars et al., 1998). ‘Mati’ genotype was seedless, while the range of seed number in other genotypes ranged from 24 (in ‘Siah-1’ and ‘Siah-2’ genotypes) to 575 (in ‘Sabz-11’ genotype). Pictures of tree, leaf, and fruit of the studied genotypes are shown in Fig. 1.
packing and transportation in fig (Condit, 1947). Dried fruit weight ranged from 1.86 to 7.15 g. Fruit weight is very important for marketing, sales, and consumption of figs (Aksoy et al., 1992). Fruit ostiole width ranged from 0.00 to 10.82 mm. Fruit ostiole width has been previously reported as 0.60–9.10 mm (Aksoy et al., 1992), 1.50–4.00 mm (Koyuncu et al., 1998), and 1.00–9.40 mm (Polat and Ozkaya, 2005). The highest values of fruit stalk length and fruit stalk diameter were 20.10 mm and 2.95 mm, respectively. Fruit cracking percentage varied
Table 2 Frequency distribution of the measured qualitative characters among the studied edible fig genotypes. Qualitative trait
Leaf density Leaf color Ripening time Fruit fall type Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality
Distribution
Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%) Frequency Percent (%)
Code 1
3
5
7
9
11
18 20.70 19 21.80 3 3.40 79 90.80 40 46.00 5 5.70 2 2.30 2 2.30 5 5.70
23 26.40 3 3.40 66 75.90 8 9.20 31 35.60 63 72.40 3 3.40 50 57.50 5 5.70
46 52.90 65 74.70 3 3.40 – – 9 10.30 19 21.80 82 94.30 35 40.20 7 8.00
– – – – 15 17.20 – – 7 8.00 – – – – – – 11 12.60
– – – – – – – – – – – – – – – – 31 35.60
– – – – – – – – – – – – – – – – 28 32.20
3.2. Correlations among the characters Simple correlation coefficient analysis revealed significant correlations among the variables measured (Table 3). Leaf length showed positive correlations with leaf width (r = 0.78), lobe number (r = 0.46), central lobe depth (r = 0.60), lateral lobe depth (r = 0.54), petiole length (r = 0.48) and petiole thickness (r = 0.46), and agreed with the finding of Khadivi-Khub and Anjam (2014) in caprifig. The existence of close positive correlations among leaf traits indicates that more leaf expansion leads to stronger aerial growth (Khadivi-Khub and Anjam, 2014, 2016; Anjam et al., 2017). Fruit yield showed positive 68
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Fig. 1. Tree, leaf, and fruit of the studied edible fig genotypes.
are very important to evaluate genotypes (Norman et al., 2011; Khadivi-Khub, 2014).
correlations with leaf density (r = 0.31), dried fruit width (r = 0.34) and dried fruit weight (r = 0.39). Also, dried fruit weight was positively correlated with leaf density (r = 0.22), leaf length (r = 0.35), leaf width (r = 0.45), leaf color (r = 0.34), vein number (r = 0.32), central lobe depth (r = 0.29) and lateral lobe depth (r = 0.23), and also highly correlated with dried fruit length (r = 0.51), and dried fruit width (r = 0.85), in accordance with the results of Khadivi-Khub and Anjam (2014, 2016) in caprifig. Fruit cracking percentage showed negative correlations with leaf color (r = −0.27), fruit fall type (r = −0.21) and fruit skin color (r = −0.20), while it showed positive collations with fruit yield (r = 0.27), ostiole width (r = 0.68), fruit cracking width (r = 0.65), seed number (r = 0.33) and seed weight (r = 0.30). In addition, fruit cracking width was negatively correlated with fruit fall type (r = −0.25), while this trait indicated positive correlations with ostiole width (r = 0.93), seed number (r = 0.32) and seed weight (r = 0.32). Fruit quality was positively correlated with leaf density (r = 0.31), dried fruit width (r = 0.25), dried fruit weight (r = 0.30), ostiole width (r = 0.58), fruit cracking width (r = 0.46), and fruit cracking percentage (r = 0.54). These traits may be used to predict each other and also can be regarded to characterize genotypes. In addition, it can be concluded that the evaluated traits have a similar effect in determining the cultivars with planting potential as well as the germplasm assessment. The correlation coefficient can provide information on the traits that
3.3. Principal component analysis (PCA) The PCA was used to identify patterns of variability among the genotypes studied (Iezzoni and Pritts, 1991). The PCA has been widely used to analyze the phenotypic diversity of edible figs (Saddoud et al., 2008; Caliskan and Polat, 2008; Giraldo et al., 2010; Podgornik et al., 2010) and caprifig (Khadivi-Khub and Anjam, 2014, 2016). For PCA, components with eigenvalues more than 1.00 were retained to uphold reliability of the final output. Thus, seven PCs were observed which contributed 69.86% of the total variance and the first three PCs explained 39.53% of the variance (Table 4). A plot of the variance extracted by seven PCs showed that the variance explained was decreased between PC1 and PC2, but the variance decrease became slow from PC2 onward (Fig. 2). Values above 0.58 were considered to be significant for the studied traits. PC1 explained 16.70% of the total variance and was represented by leaf length (0.80), leaf width (0.87), central lobe depth (0.82), lateral lobe depth (0.75), petiole length (0.75) and petiole thickness (0.72) with positive correlations. PC2 explained 11.86% of the total variance and was constituted by ostiole width (0.91), fruit cracking width (0.90), fruit cracking percentage (0.81) and fruit quality (0.65) with positive correlations. PC3 explained 10.98% of the total 69
LDe
1.00 −0.09 0.07 0.21* −0.11 0.09 −0.22* −0.04 0.05 −0.02 0.06 −0.18 0.31** 0.08 0.14 0.22* 0.16 0.01 −0.01 0.08 0.19 −0.35** −0.09 0.41** 0.39** 0.31** −0.08 0.17 0.19
FrWi
1.00 0.85** 0.33** −0.23* 0.51** 0.20 0.18
Varible
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight
Varible
70
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage 1.00 0.22* −0.21* 0.50** 0.06 0.09
FrWe
1.00 0.78** 0.14 0.44** 0.46** 0.60** 0.54** 0.48** 0.46** 0.29** 0.00 0.10 0.30** 0.35** 0.35** 0.04 0.04 0.37** −0.01 −0.01 0.09 0.13 −0.05 0.25* 0.02 0.02 0.04 0.10
LLe
1.00 0.12 −0.07 0.93** 0.68**
OsWi
1.00 0.12 0.38** 0.45** 0.66** 0.57** 0.52** 0.63** 0.19 0.07 0.16 0.27** 0.46** 0.45** 0.09 0.03 0.42** 0.01 0.07 0.08 0.14 0.05 0.268* 0.10 0.03 0.06 0.08
LWi
1.00 −0.25* 0.16 0.17
FrStLe
1.00 0.01 0.07 0.12 0.06 0.16 0.03 0.11 0.06 0.17 0.33** 0.26* 0.34** −0.10 0.02 0.20* −0.19 −0.27** 0.03 0.15 0.12 0.26* −0.02 0.05 0.09 0.19
LCo
1.00 −0.10 −0.14
FrStDi
1.00 0.57** 0.50** 0.46** 0.59** 0.34** 0.38** 0.14 −0.02 0.34** 0.36** 0.32** 0.05 0.07 0.263* 0.03 −0.04 0.10 0.16 −0.11 0.14 −0.10 0.14 −0.14 −0.04
VeNo
1.00 0.65**
FrCrWi
1.00 0.34** 0.39** 0.45** 0.35** 0.39** 0.16 0.13 0.41** 0.17 0.19 −0.02 0.36** 0.06 −0.05 0.05 0.05 0.09 0.13 0.18 0.02 0.13 0.15 0.12
LoNo
Table 3 Bivariate correlations among the morphological and pomological traits in the studied edible fig genotypes.
1.00
FrCrPer
FrSkCo
1.00 0.71** 0.58** 0.46** 0.20 0.25* 0.00 0.30** 0.36** 0.29** −0.12 0.02 0.48** −0.11 −0.14 0.25* 0.22* −0.29** 0.09 −0.12 0.09 −0.16 −0.14
CeLoD
FrBaSta
1.00 0.49** 0.27* 0.01 0.04 0.21* 0.28** 0.29** 0.04 0.08 0.25* 0.00 −0.07 −0.07 −0.01 0.09 0.21* 0.01 0.05 0.01 0.03
PeLe
FrPuInCo
1.00 0.55** 0.36** 0.19 0.23* 0.08 0.26* 0.26* 0.23* −0.02 0.16 0.34** −0.01 −0.04 0.21 0.21* −0.16 0.05 −0.05 0.23* −0.01 0.02
LaLoD
FrSkWrSta
1.00 0.29** 0.00 −0.01 0.06 0.37** 0.30** 0.14 0.05 0.28** 0.05 0.11 −0.01 0.05 0.05 0.21* 0.13 0.04 0.21 0.13
PeTh
FrQu
1.00 0.18 0.14 0.22* 0.14 0.21 −0.07 0.10 0.05 −0.08 −0.04 −0.04 0.03 0.14 0.21* −0.17 0.10 0.06 0.12
RiTi
pH
1.00 −0.13 0.28** −0.03 −0.11 −0.38** 0.30** 0.23* −0.25* −0.21* 0.61** 0.33** −0.28** −0.16 −0.51** 0.24* −0.05 −0.13
FrFaTy
SeWe
1.00 0.42** 0.51** −0.06 0.25* 0.43** −0.10 −0.12 0.31** 0.44** −0.04 0.13 −0.07 0.25* 0.06 0.10
FrLe
(continued on next page)
SeNo
1.00 0.12 0.34** 0.39** 0.23* 0.00 0.14 0.19 0.27* −0.08 −0.05 0.24* 0.30** 0.20 0.12 0.27* 0.31**
Yi
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Table 4 Loading factor of variation in the principal components (PCs) in the studied edible fig genotypes.
1.00
SeWe
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1.00 0.32** 0.30** 1.00 0.04 0.30** 0.35** 1.00 0.30** −0.22* 0.09 0.19 1.00 −0.20 −0.17 0.04 0.36** 0.07 0.09 1.00 0.51** −0.40** −0.21* −0.39** 0.29** 0.05 0.04
1.00 0.27** 0.31** 0.11 0.36** 0.38**
pH FrSkWrSta FrPuInCo
−0.20 −0.05 0.29** 0.12 0.54** 0.04 0.33** 0.30** −0.18 −0.09 0.20 −0.02 0.46** 0.17 0.32** 0.32** 0.32 0.38** −0.26* 0.11 0.03 0.23* 0.05 0.07 0.21 0.05 0.21* −0.08 −0.01 0.21* 0.26* 0.16
FrCrWi
* **
FrStDi FrStLe
*
FrCrPer
FrSkCo
FrBaSta
FrQu
SeNo
1.00 0.81**
Component Variable
1
2
3
4
5
6
7
Leaf density Leaf length Leaf width Leaf color Vein number Lobe number Central lobe depth Lateral lobe depth Petiole length Petiole thickness Ripening time Fruit fall type Yield Dried fruit length Dried fruit width Dried fruit weight Ostiole width Fruit stalk length Fruit stalk diameter Fruit cracking width Fruit cracking percentage Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight Total % of variance Cumulative %
−0.07 0.80** 0.87** 0.08 0.55 0.53 0.82**
0.12 −0.02 0.04 −0.33 0.11 0.03 −0.10
−0.18 0.05 0.05 0.18 0.18 0.12 0.25
0.72** 0.09 0.17 0.58** 0.00 0.21 −0.08
0.04 0.05 0.06 0.17 −0.24 0.01 −0.17
−0.18 0.08 0.08 0.07 0.03 −0.39 0.13
−0.10 0.09 −0.03 −0.06 0.59** 0.45 0.04
0.75**
0.01
0.27
−0.03
−0.06
−0.10
0.02
0.75** 0.72** 0.21 0.05 −0.01 0.21
−0.01 0.06 −0.14 −0.35 0.22 −0.04
−0.08 −0.13 −0.04 0.62** 0.03 0.65**
0.12 −0.05 0.11 −0.19 0.47 0.45
−0.03 0.27 0.17 −0.03 0.25 −0.11
−0.07 0.13 −0.02 −0.19 0.15 −0.03
0.22 0.12 0.79** 0.20 0.16 0.24
0.36 0.32
0.30 0.18
0.27 0.21
0.40 0.60**
0.07 0.06
0.59** 0.54
0.18 0.18
0.03 0.09 0.41
0.91** 0.14 −0.08
−0.07 0.29 0.47
0.08 0.02 0.16
0.21 0.14 0.03
0.05 −0.79** 0.52
0.01 0.10 −0.10
−0.03
0.90**
−0.02
−0.09
0.15
−0.02
0.03
−0.01
**
0.81
−0.09
0.05
0.14
−0.11
−0.01
0.05 0.10
−0.24 −0.01
0.76** 0.75**
−0.28 0.05
0.10 0.02
0.03 0.08
−0.01 −0.13
−0.06 0.21
0.19 0.03
−0.34 −0.25
0.43 0.66**
0.41 0.04
−0.38 0.16
0.07 0.15
0.07 0.03 0.02 0.01 4.84 16.70 16.70
0.65** 0.16 0.25 0.25 3.44 11.86 28.55
−0.18 0.55 0.10 0.09 3.18 10.98 39.53
0.36 −0.09 0.12 0.22 2.90 9.99 49.52
0.14 0.38 0.87** 0.83** 2.21 7.63 57.15
0.05 −0.10 −0.08 0.02 2.06 7.12 64.27
−0.32 0.10 −0.01 0.05 1.62 5.60 69.86
−0.25 −0.09 0.31** 0.14 0.58** 0.17 0.38** 0.40**
* Correlation is significant at the 0.05 level. ** Correlation is significant at the 0.01 level.
0.08 0.21* −0.06 0.37** 0.25* 0.12 0.19 0.26* Fruit skin color Fruit pulp internal color Fruit basal status Fruit skin wrinkle status Fruit quality Fruit pH Seed number Seed weight
0.00 0.21 0.04 0.52** 0.30** 0.07 0.18 0.26*
FrWi Varible
Table 3 (continued)
FrWe
OsWi
*
** Eigenvalues ≥ 0.58 are significant.
Fig. 2. Variance percentage accounted by seven principal components (PCs) in PCA in the studied edible fig genotypes.
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Fig. 3. Cluster analysis of the studied edible fig genotypes based on the morphological and pomological traits using Euclidean distances.
tool for selecting genotypes or new cultivars with superior traits. The present findings were in agreement with the previously reported results in edible figs (Caliskan and Polat, 2008; Podgornik et al., 2010) and caprifig (Khadivi-Khub and Anjam, 2014).
variability and was represented by fruit fall type (0.62), dried fruit length (0.65), fruit skin color (0.76), and fruit pulp internal color (0.75) with positive correlations. These characters were the most effective traits for separating and identifying the studied genotypes. In addition, these traits are economically important and can also be used as a useful 72
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Fig. 4. The scatter plot for the first two principal components (PC1/PC2, 28.55% of total variance) for the studied edible fig genotypes based on the morphological and pomological characters.
The current findings support the view that pomological and leaf characteristics are reliable in estimating genetic relationships among fig genotypes and can be used efficiently for discrimination. Similarly, many studies (Condit, 1955; Mars et al., 1998; Oukabli et al., 2002; Papadopoulou et al., 2002; Mars, 2003; Aljane and Ferchichi, 2005) revealed that morphological traits are very helpful in identification and evaluation of fig germplasm.
3.4. Phenotypic variability The Ward dendrogram reflected the similarities and dissimilarities among the genotypes based on the qualitative and quantitative variables measured. The most significant result was represented by the identification of two separate main clusters of genotypes based on morphological characteristics (Fig. 3). Cluster I included 18 genotypes that genotypes ‘Mati’, ‘Siah-1′, ‘Siah-2′, ‘Shahanjir-3′ along 14 genotypes of ‘Sabz’ landrace were placed in this cluster. Cluster II included 69 genotypes forming three sub-clusters. Sub-cluster II-A contained one genotype and Sub-cluster II-B consisted of 18 genotypes; while remaining 50 genotypes formed sub-cluster II-C. In addition, a scatter plot was prepared according to the PC1 and PC2 (28.55% of total variance) that reflected the relationship among the genotypes in terms of phenotypic characteristics. The plot distributed genotypes into four sides and showed significant differences for some traits (Fig. 4). Starting from negative to positive values of PC1, the studied genotypes indicated an increase in leaf length, leaf width, central lobe depth, lateral lobe depth, petiole length and petiole thickness. Starting from negative values to the positive values of PC2, the genotypes were characterized by higher values for ostiole width, fruit cracking width, fruit cracking percentage and fruit quality. The most of genotypes were placed in the central area of the plot. The results showed that the studied fig germplasm have high phenotypic variation. Because the genotypes were studied in the same region with an equal climate condition, the observed variation is probably more related to their genetics. Ideally, this characterization should be made under the same edaphoclimatic conditions. Phenotypic characterization is always needed and it should be included in any program of conservation and use of genetic resources (Giraldo et al., 2010). Similarly, high phenotypic variability was reported in fig collections from different countries such as Tunisia (Mars et al., 1998; Chatti et al., 2003), Turkey (Caliskan and Polat, 2008), Morroco (Oukabli et al., 2002), Spain (Sanches et al., 2002), Lebanon (Chalack et al., 2005) and Jordan (Almajalia et al., 2012). These studies indicated that high diversity in pomological and leaf-related traits could be used as an efficient marker system to discriminate between fig genotypes.
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