Morphological Characterization of Fig Accessions Cultivated in Lebanon

Chalak, L.; Chehade, Ali; Mattar, Eduardo Pacca Luna; Khadari, Bouchaïb

doi:10.17660/actahortic.2008.798.5

Cited by 8 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our results are similar with other reports in of fig collections from different countries, i.e., Tunisia (Chatti et al, 2003), Turkey (Calis xkan and Polat, 2008), Morocco (Oukabli et al, 2002), Spain (Sanches et al, 2002), Lebanon (Chalack et al, 2005), and Jordan (Almajalia et al, 2012), which reported high diversity in pomological and leaf-related traits, and these could be useful as an efficient marker system to discriminate between fig genotypes.…”

Section: Two-way Hierarchical Morphological Cluster Analysissupporting

confidence: 92%

Morphological, Pomological, and Specific Molecular Marker Resources for Genetic Diversity Analyses in Fig (Ficus carica L.)

Abdelsalam¹,

Awad²,

Ali³

et al. 2019

horts

View full text Add to dashboard Cite

Fig (Ficus carica L.) considers the original cultivated fruit trees and currently has become extinct. Such genetic resources should be identified, documented, and conserved. Morphology, pomology, and molecular markers are successful tools in assessing genetic diversity and classifying fig accessions. Twenty-one cultivated fig (F. carica L.) accessions were collected from Egypt and Libya. In Egypt, fig accessions are dispersed from Sinai in the east to El-Saloom in the west and from Alexandria in the north to Aswan in the south, whereas Libyan accessions were collected from Tubryq, Bengazi, and AlKufrah. Seventeen morphological, pomological, and fruit traits were used to characterize the fig accessions. Moreover, frozen young leaves were used to extract genomic DNA; 13 expressed sequence tag (EST) common fig primer pairs with 12 intersimple sequence repeat (ISSR)-anchored primers were used to detect the genetic diversity. Analysis of variance for fig accessions showed highly significant differences concerning morphological traits, i.e., the leaf length (centimeters) and width (centimeters) ranged from 5.4 and 6 cm to 23 and 23.5 cm, for Komesrey-El-Hammam, Abodey-Giza, and Black_Mission accessions, respectively. Also, fig accessions showed different shapes of leaf edge and fruits; they were categorized into four groups: straight, waved, zigzag, and serrated. The number of leaf lobes data ranged from one lobe for the ‘Green-yellow’, ‘Sultani Red Siwa’, and ‘Sultany Red Amria’ accessions to 10 lobes in the Aswany accession. The two-way hierarchical morphological cluster analysis distributed fig accessions into two main groups. The results detected high genetic diversity for the fig accessions that could be useful in the future breeding programs. Concerning molecular data, the EST markers showed highly polymorphism and informative (r = 0.61; 90.0%), with a total number of identified alleles of 78. We proved that a relatively greater number of alleles per locus characterizes the targeted loci among fig accessions, for which only one and two alleles per locus have been revealed, respectively, although ISSR showed a clear pattern and bands of the primers UBC807, UBC811, UBC812, UBC814, UBC815, UBC817, UBC818, and UBC823. In conclusion, a great range of variability was detected within the fig accessions. This diversification could enrich the genetic base of this genus, and more experiments are needed to reach its full potential.

show abstract

Section: Two-way Hierarchical Morphological Cluster Analysissupporting

confidence: 92%

Morphological, Pomological, and Specific Molecular Marker Resources for Genetic Diversity Analyses in Fig (Ficus carica L.)

Abdelsalam¹,

Awad²,

Ali³

et al. 2019

horts

View full text Add to dashboard Cite

show abstract

“…To evaluate similarity among cultivars, principal component analysis (PCA) and a hierarchical canonical analysis (HCA) were carried out using Statbox 5.40 software. These statistical analyses are commonly used for the cha- (Mars et al, 1998;Salhi-Hannachi et al, 2003;Chatti et al, 2004;Chalak et al, 2008;Aljane et al, 2007a).…”

Section: Discussionmentioning

confidence: 99%

“…Some works have focused on Tunisian cultivars (Ben Salah et al, 1995;Mars et al, 1998;Aljane et al, 2004Aljane et al, , 2007a. Many studies are interested on the germplasm resources of fig in the world on the basis of its morphological, chemical and molecular characteristics (Valisadeh & Valdeyron, 1979;Kadhari et al, 1995;Aksoy et al, 2003;Salhi-Hannachi et al, 2003;Chalak et al, 2008;Oukabli & Khadari, 2005;Saddoud et al, 2006;Aljane et al, 2007a). In this context our study is integrated.…”

mentioning

confidence: 99%

Assessment of genetic diversity of Tunisian fig (Ficus caricaL.) cultivars using morphological and chemical characters

Aljane¹,

Ferchichi²

2010

Acta Botanica Gallica

View full text Add to dashboard Cite

Résumé.-Une étude a été réalisée pour évaluer et identifier quatorze cultivars de figuier tunisien basée sur des caractères morphologiques, chimiques et les composés minéraux des fruits. Les résultats ont été soumis à une analyse de variance et des analyses multivariées afin d'évaluer la diversité entre les cultivars et les corrélations entre les caractères étudiés. Les cultivars sont identifiés sur la base de la couleur de la peau (Nemri, Bouholi, etc.), la forme des fruits (Boukhobza, Garghi, etc.) et le goût des fruits (Bouharrag, etc.). Une grande variabilité pour le poids et les dimensions des fruits a été observée entre les cultivars. Le fructose, le glucose, le potassium et le calcium sont les principaux sucres et minéraux dans les figues. Certains caractères morphologiques et chimiques montrent une grande diversité entre les cultivars. À l'issue de la présen-te étude, certains cultivars tunisiens sont particulièrement recommandés pour de futurs programmes de sélection et de culture.

show abstract

“…The Jaccard's distance approach (Hartigan 1975;Chalak et al 2006;Zahn 1971) which is based on Boolean algebra to find the distance between the tasks i.e., the columns of the matrix given in table 1. The Jaccard's distance is defined by Table 1.…”

Section: Examplementioning

confidence: 99%

Complex networks and SOA: Mathematical modelling of granularity based web service compositions

Chatla¹,

Kadam²,

Kolluru³

et al. 2011

Sadhana

View full text Add to dashboard Cite

Service Oriented Architecture (SOA) can be defined as a way of defining and implementing enterprise applications that deals with the intercommunication of loosely coupled, coarse grained (business level), reusable artifacts (services). In this paper, we attempt to mathematically model the preliminary steps in the larger problem of providing an optimal architecture. The problem is treated as a complex network, particularly a process-task-network. We employ statistical and graph-theoretic methods namely, Jaccard's distance analysis, Multiple Correspondence method and the Minimum Spanning Tree method, to find appropriate clusters. These methods are used to cluster tasks across business processes to propose services. Additional properties and features of these clusters are discussed. We propose a leverage factor which demonstrates the importance of a task within the service and its impact on service composition.

show abstract

Morphological Characterization of Fig Accessions Cultivated in Lebanon

Cited by 8 publications

References 0 publications

Morphological, Pomological, and Specific Molecular Marker Resources for Genetic Diversity Analyses in Fig (Ficus carica L.)

Morphological, Pomological, and Specific Molecular Marker Resources for Genetic Diversity Analyses in Fig (Ficus carica L.)

Assessment of genetic diversity of Tunisian fig (Ficus caricaL.) cultivars using morphological and chemical characters

Complex networks and SOA: Mathematical modelling of granularity based web service compositions

Contact Info

Product

Resources

About