<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The aim of this study was to identify the molecular and morphological characteristics of Turkish pea accessions (<italic>Pisum sativum</italic> L.). The genetic diversity among 130 Turkish landraces and 2 commercial varieties in a total of 132 pea accessions was assessed with 14 simple sequence repeat (SSR) markers. Forty-eight (48) polymorphic alleles were identified using 14 SSR markers. The pairwise Dice coefficients of similarity between accessions ranged from 0.091 to 0.960. The polymorphism information content (PIC) value ranged from 0.585 to 0.861. Overall, 50 morphological traits were evaluated. Cluster analysis was carried out on a matrix of Euclidean distances. The accessions were divided into three main groups. Principal component analysis (PCA) was used to identify the weight of each morphological characteristic. According to the results, the highest eigenvalue was observed in PC-I (13.88) followed by PC-II (11.42), and PC-III (7.32). The first fifteen PCs with eigenvalues > 1 explained 74.08% of the variability. The results showed that the molecular markers were useful and polymorphic, sufficient to allocate all the evaluated accessions. This research has provided significant insights into the genetic variability of Turkish pea accessions.</p></abstract>

The aim of this study was to identify the molecular and morphological characteristics of Turkish pea accessions (Pisum sativum L.). The genetic diversity among 130 Turkish landraces and 2 commercial varieties in a total of 132 pea accessions was assessed with 14 simple sequence repeat (SSR) markers. Forty-eight (48) polymorphic alleles were identified using 14 SSR markers. The pairwise Dice coefficients of similarity between accessions ranged from 0.091 to 0.960. The polymorphism information content (PIC) value ranged from 0.585 to 0.861. Overall, 50 morphological traits were evaluated. Cluster analysis was carried out on a matrix of Euclidean distances. The accessions were divided into three main groups. Principal component analysis (PCA) was used to identify the weight of each morphological characteristic. According to the results, the highest eigenvalue was observed in PC-I (13.88) followed by PC-II (11.42), and PC-III (7.32). The first fifteen PCs with eigenvalues > 1 explained 74.08% of the variability. The results showed that the molecular markers were useful and polymorphic, sufficient to allocate all the evaluated accessions. This research has provided significant insights into the genetic variability of Turkish pea accessions.

Genetic variability in peas (<italic>Pisum sativum</italic> L.) from Turkey asssessed with molecular and morphological markers

Folia Horticulturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Genetic variability in peas ( L.) from Turkey asssessed with molecular and morphological markers

The aim of this study was to identify the molecular and morphological characteristics of Turkish pea accessions (Pisum sativum L.). The genetic diversity among...

Genetic variability in peas (Pisum sativum L.) from Turkey asssessed with molecular and morphological markers

Online veröffentlicht: 30. Juni 2019

Seitenbereich: 101 - 116

Eingereicht: 26. Juli 2018

Akzeptiert: 03. Okt. 2018

DOI: https://doi.org/10.2478/fhort-2019-0007

Schlüsselwörter
breeding, cluster analysis, diversity, pea, polymorphism

© 2019 Fatih Hanci, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Genetic variability in peas (Pisum sativum L.) from Turkey asssessed with molecular and morphological markers

Online veröffentlicht: 30. Juni 2019

Seitenbereich: 101 - 116

Eingereicht: 26. Juli 2018

Akzeptiert: 03. Okt. 2018

DOI: https://doi.org/10.2478/fhort-2019-0007

Schlüsselwörterbreeding, cluster analysis, diversity, pea, polymorphism

© 2019 Fatih Hanci, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
breeding, cluster analysis, diversity, pea, polymorphism