Determining the genetic relationships between cultivated type olives using ISSR and morphological markers

WOS: 000413107700021Aim: The study aimed to compare morphological characters and Inter-simple sequence repeat (ISSR) data based trees, and examine the genetic relations in ten olive varieties among cultivated type olives grown commonly in different regions of Turkey. Methodology: Ten olive varieties were evaluated with some morphologic markers and ISSR marker. All analyses were conducted with Numerical Taxonomy System (NTSYS). The cluster analysis was performed with unweighted pair group method with arithmetic average (UPGMA) clustering algorithm. Results: The results showed that there was a moderate correlation between pairwise distances estimated from ISSR data and distances from morphological characters (0.511). The Euclidean Distance matrix represented that the lowest value was between Taysan Yuregi and Cilli (1.62), while the highest value was between Manzanilla and Cekiste (7.91). According to Jaccard coefficient, the samples closest to each other were (Memecik and Gemlik); and the samples farthest to each other were (Halhali and Manzanilla). Interpretation: Determining the genetic relations in agriculturally economic plants is valuable in terms of protecting the gene sources, determining the homonyms and synonyms, and developing breeding programs. Morphological and molecular markers may be used in the identification of genetic variability. Mutually complementary information can be obtained by using morphological and molecular markers together.Scientific Research Projects Coordination Unit of Celal Bayar University, Manisa, TurkeyCelal Bayar UniversityThis study has been supported by the Scientific Research Projects Coordination Unit of Celal Bayar University, Manisa, Turkey

UPGMA and artificial neural networks applications on wild type olives

WOS: 000413107700026Aim: Plant genetic sources are important to study genetic variability and richness of hereditary knowledge of plant species in gene pool. Local varieties, rural populations, wild types and old varieties are the primary ones. In this respect, wild type olives (Olea europaea oleaster) are valuable in terms of olive breeding, cultivation and ecosystem. The aim of the study was to determine genetic distances between olive varieties. Methodology: Artificial Neural Networks intuitive algorithm application was performed on seven wild type olives grown in different regions of Turkey by using data obtained from twenty-two ISSR primers. Results: UPGMA dendrograms were developed through Jaccard, simple matching coefficients, and similarity matrices; and genetic similarities and dissimilarities were exhibited. Interpretation: It was concluded that Artificial Neural Networks would be beneficial for estimating olive types accurately based on the results obtained from earlier studies performed with genetic markers.Scientific Research Projects Coordination Unit of Manisa Celal Bayer University, Manisa, TurkeyThis study has been supported by the Scientific Research Projects Coordination Unit of Manisa Celal Bayer University, Manisa, Turkey