Diversity of morpho-physiological traits in worldwide sweet cherry cultivars of GeneBank collection using multivariate analysis

Ganopoulos, Ioannis; Moysiadis, Theodoros; Xanthopoulou, Aliki; Ganopoulou, Maria; Avramidou, Evangelia V.; Aravanopoulos, Filippos A.; Tani, Eleni; Madesis, Panagiotis; Tsaftaris, Athanasios; Kazantzis, Konstantinos

doi:10.1016/j.scienta.2015.09.061

Cited by 33 publications

(32 citation statements)

References 22 publications

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“…The multivariate analysis method has been used to study various germplasm collections of Prunus spp. (Ganopoulos et al, 2015;Ganopoulos et al, 2016;Font i Forcada et al, 2014;Khadivi-Khub et al, 2016;Khadivi-Khub et al, 2012;Nikolić et al, 2010;Rakonjac et al, 2010;Ruiz and Egea, 2008) and Malus × domestica (Gaši et al, 2011;Pereira-Lorenzo et al, 2003;Reig et al, 2015). Here, the PCA testing revealed that all variables examined showed high scores regarding the first eight principal components.…”

Section: Multivariate Analysis Of Qualitative Variables: Pca and Ahc mentioning

confidence: 63%

“…The most important traits that were included in our developed database were identified by the PCA analysis, which, in this case, allows the multivariate statistical analysis of a large number of variables (Ganopoulos et al, 2015;Ganopoulos et al, 2011). The initial variables were transformed to a decreased number of uncorrelated ones in order to reduce the data, allowing relationships between the individuals and variables to be sufficiently revealed.…”

Section: Multivariate Analysis Of Qualitative Variables: Pca and Ahc mentioning

confidence: 99%

“…In turn, germplasm characterization facilitates the identification of important phenotypic traits. These traits are commonly linked to genetic data and their use is crucial for breeding programs (Ganopoulos et al, 2015;Ganopoulos et al, 2011). Therefore, the clustering analysis and PCA are key tools to group and evaluate cultivars preserved in GeneBank collections (Iezzoni and Pritts, 1991).…”

Section: Multivariate Analysis Of Qualitative Variables: Pca and Ahc mentioning

confidence: 99%

“…Traditionally, genetic diversity in apple species or varieties was assessed with morphological descriptors (Reig et al, 2015), commonly produced by the International Board for Plant Genetic Resources (IBPGR, 1983) and later by the International Union for the Protection of New Varieties of Plants (UPOV, 2005). The multivariate data analysis is an efficient approach to analyze large data of apple qualitative phenotypic traits and is considered the most suitable to identify patterns and relationships among powerful statistical techniques, such as the principal component analysis (PCA) and the cluster analysis (Oliveira et al, 2012;Furones-Pérez and Fernández-López, 2009;Ganopoulos et al, 2015;Mehmood et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Phenotypic and molecular characterization of apple (Malus × domestica Borkh) genetic resources in Greece

Ganopoulos¹,

Tourvas

Xanthopoulou

et al. 2018

Sci. agric. (Piracicaba, Braz.)

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ABSTRACT:The phenotypic and genetic analysis of apple (Malus × domestica Borkh) genotypes is essential for breeding species. Information on the morphology and genetic structure of apple offers significant help for germplasm maintenance and selection of suitable material to breed superior cultivars. This study shows the results of an investigation on the morphology and the genetic diversity for 19 apple cultivars, which are preserved in an ex situ collection in Naoussa, Central Macedonia, Greece. Information was recorded over a 5-year period for 47 traits describing plant morphology and phenotype, as well as leaf and fruit quality. Data were analyzed using the principal component analysis (PCA) method. The Euclidean distance metric and the Ward's agglomeration method were used in an unsupervised hierarchical cluster analysis of all cultivars. The cultivars were grouped into four main clusters, suggesting that the characterized apple collection has a high potential for specific breeding goals. Furthermore, the cultivars were genotyped using seven microsatellite primers. Moderate levels of polymorphism were detected, and 38 distinctive alleles (5.4 alleles per primer pair) were identified. Both multivariate clustering approach (phenotypic data) and the genetic distance clustering approach (genetic data) grouped the apple cultivars according to their type. Hence, these data could be used for protection or patenting processes of existing or new apple cultivars carried out by the EU-Community Plant Variety Office.

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Section: Multivariate Analysis Of Qualitative Variables: Pca and Ahc mentioning

confidence: 63%

Section: Multivariate Analysis Of Qualitative Variables: Pca and Ahc mentioning

confidence: 99%

Section: Multivariate Analysis Of Qualitative Variables: Pca and Ahc mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Phenotypic and molecular characterization of apple (Malus × domestica Borkh) genetic resources in Greece

Ganopoulos¹,

Tourvas

Xanthopoulou

et al. 2018

Sci. agric. (Piracicaba, Braz.)

Self Cite

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“…Multivariate techniques such as Principal Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC) analysis have been previously used for morphological assessment of genetic variability in sweet cherry (Prunus avium L.) cultivars (Ganopoulos et al, 2015) and in maize (Alves, Cargnelutti Filho, Toebe, Burin, & Silva, 2014).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Elite Open-Pollinated Maize Lines in Two Contrasting Environments

Greveniotis¹,

Bouloumpasi²,

Tsakiris³

et al. 2017

JAS

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Selection environment affects plant behavior and response to selection. The objective of the present study was the evaluation of 17 quality and quantity phenotypic characteristics of six open-pollinated maize lines of fifth cycle of selection (C4), which was performed by the implementation of honeycomb breeding, in two contrasting environments (A and B) The soil chemical analysis revealed that the two environments were very diverse (A: SL, pH = 6.25, organic matter: 1.29%, B: SCL, pH = 8, organic matter: 2.4%). Our data suggest that moisture content, seed oil content, ear length, ear diameter, number of grain rows, spindle diameter and seed thickness exhibit inter-location high broad-sense heritability (over 0.9). Heritability estimations were highly depended on the environment, since GEI interaction was high indicating environmental interaction with genotype, especially environment B, which seems to favor heritability. Location affects strongly variation and genotype by environment interaction is significant in many cases. Seed width was the only characteristic to be depended on genetic variability. Descriptive statistics revealed a broad range of mean fluctuations, indicating satisfactory variability in many characteristics to be exploited by breeders. Some characteristics showed low CV (Coefficient of Variation) values (1.6 to 5.3), indicating stability of performance and low environmental effects. Significant correlations between the 17 quantity and quality traits found in our study may be a useful tool for indirect selection of certain characteristics, otherwise difficult to be selected due to non-additive effects. Cluster analysis and PCA showed contrasting results in classification of open-pollinated lines and this was attributed to strong environmental effects that distorted phenotypic expression of the characteristics studied.

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Applications of Biotechnological Tools for Developing Abiotic Stress Tolerant Cherries

Lal

Verma

2022

Genomic Designing for Abiotic Stress Resistant Fruit Crops

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Diversity of morpho-physiological traits in worldwide sweet cherry cultivars of GeneBank collection using multivariate analysis

Cited by 33 publications

References 22 publications

Phenotypic and molecular characterization of apple (Malus × domestica Borkh) genetic resources in Greece

Phenotypic and molecular characterization of apple (Malus × domestica Borkh) genetic resources in Greece

Evaluation of Elite Open-Pollinated Maize Lines in Two Contrasting Environments

Applications of Biotechnological Tools for Developing Abiotic Stress Tolerant Cherries

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