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    Assessment of genetic diversity and population structure in local alfalfa genotypes using iPBS molecular markers
    (Springer, 2023) Eren, Barış; Keskin, Bilal; Demirel, Fatih; Demirel, Serap; Türkoğlu, Aras; Yılmaz, Abdurrahim
    iPBS retrotransposon markers, in other words, inter-primer binding site markers based on retrotransposon, have been helpful for the determination of genetic diversity in several plants. The study was evaluated using 10 iPBS molecular markers on the level of genetic diversity and genetic structure of alfalfa genotypes. A total of 280 alleles in 50 alfalfa genotypes (48 local genotypes and 2 commercial varieties) were obtained by 267 polymorphic markers with an average of 28 per locus, ranging from 9 to 41 alleles. The rate of polymorphism of the markers ranged from 86.36 to 100% with an average of 93.71%. The average number of polymorphic bands per marker was detected as 26.7. The mean PIC value and Dice's similarity index were calculated as 0.14 and 0.50 respectively. The results of UPGMA analysis, principal coordinate analysis (PCoA), and STRUCTURE demonstrated that the 50 alfalfa genotypes could be classified into 4 subpopulations, namely the Q1, Q2, Q3, and Q4. The Nei's genetic distances ranged from 0.0121 to 0.0359. iPBS markers and alfalfa genotypes used in this study may be used in studies of alfalfa breeding and germplasm conservation.
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    Genetic relationships of salep orchid species and gene flow among Serapias vomeracea × Anacamptis morio hybrids
    (Springer, 2023) Palaz, Esra Bulunuz; Demirel, Fatih; Adalı, Sümeyye; Demirel, Serap; Yılmaz, Abdurrahim
    Orchids are naturally grown in many countries of the Eastern Mediterranean. Salep, produced from orchid tubers via grinding and used as a hot drink, is an essential ingredient of ice cream. Salep orchid species are in danger of extinction due to the absence of cultivation and over-harvesting from nature. In this study, the genetic diversity and population structure between salep orchid species, their hybrids, and commercial species of Phalenopsis sp. were first investigated using inter-Primer Binding Site (iPBS) Retrotransposon markers. A total of 854 bands were scored with a 100% polymorphism rate. Neighbor-joining, model-based structure, and PCoA (Principal Coordinate Analysis) algorithms clustered the 30 salep orchids into three main populations. The analysis of molecular variance revealed variations within and among the populations as 71% and 29%, respectively. Anacamptis morio and Serapias vomeracea had the furthest genetic distances, and F-1 hybrids of S. vomeracea and A. morio had great genetic diversity. The study results will provide helpful information for orchid breeding by eliciting the genetic distances of salep orchids.
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    Prediction of grain yield in wheat by CHAID and MARS algorithms analyses
    (MDPI, 2023) Demirel, Fatih; Eren, Barış; Yılmaz, Abdurrahim; Türkoğlu, Aras; Haliloğlu, Kamil; Niedbala, Gniewko
    Genetic information obtained from ancestral species of wheat and other registered wheat has brought about critical research, especially in wheat breeding, and shown great potential for the development of advanced breeding techniques. The purpose of this study was to determine correlations between some morphological traits of various wheat (Triticum spp.) species and to demonstrate the application of MARS and CHAID algorithms to wheat-derived data sets. Relationships among several morphological traits of wheat were investigated using a total of 26 different wheat genotypes. MARS and CHAID data mining methods were compared for grain yield prediction from different traits using cross-validation. In addition, an optimal CHAID tree structure with minimum RMSE was obtained and cross-validated with nine terminal nodes. Based on the smallest RMSE of the cross-validation, the eight-element MARS model was found to be the best model for grain yield prediction. The MARS algorithm proved superior to CHAID in grain yield prediction and accounted for 95.7% of the variation in grain yield among wheats. CHAID and MARS analyses on wheat grain yield were performed for the first time in this research. In this context, we showed how MARS and CHAID algorithms can help wheat breeders describe complex interaction effects more precisely. With the data mining methodology demonstrated in this study, breeders can predict which wheat traits are beneficial for increasing grain yield. The adaption of MARS and CHAID algorithms should benefit breeding research.