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Paketli gıda ürün etiketleri kullanılarak görüntü işleme ve optik karakter tanıma (OKT) tekniklerine dayalı uzman sistemin geliştirilmesi

2024
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Advisor: Dr. Öğr. Üyesi Tolga Hayıt ; Dr. Öğr. Üyesi Fatma Hayıt

Abstract (TR)

Apple (Malus domestica) is a significant pome fruit, and its genotypes are essential for breeding programs. Molecular markers, particularly the SSR (Simple Sequence Repeats) technique, are highly reliable for identifying genetic diversity and relationships among plant genotypes within a population. This study utilized SSR markers to quickly and reliably determine genetic diversity in apple genotypes. The analyses identified a total of 187 alleles across SSR loci, with allele numbers per locus ranging from 2 to 16 and an average of 8. The BC226-SCAR locus had the highest number of alleles. The number of effective alleles (Ne) varied between 1.17 (MD-EXP7SSR) and 9.11 (CH02C06), with an average of 4.67. Observed heterozygosity (Ho) among genotypes ranged from 0.16 to 1.00, with an average of 0.70, and the highest values (1.00) were found at the CH01H10, EMPC116, and HI02D04 loci. Expected heterozygosity (He) was highest at the CH02C06 and BC226-SCAR loci, with an average of 0.72. Polymorphism Information Content (PIC) values, indicating genetic diversity and marker discrimination power, ranged from 0.14 (MD-EXP7SSR) to 0.88 (CH02C06, BC226-SCAR). The UPGMA dendrogram and PCoA graph indicated that apple varieties and genotypes clustered into two main groups, further divided into four subclusters. Genetic similarity coefficients ranged from 0.14 to 0.88. The results of the dendrogram and STRUCTURE analysis were very similar, showing consistent genetic differentiation patterns across UPGMA, structure analysis, and PCoA. This study effectively characterized the genetic diversity and relationships of apple genotypes in the Yozgat region, highlighting the richness of apple genetic resources in the area and the potential for breeding programs. 2024, 40 Pages Keywords: Apple, Malus domestica, SSR

Author

Dr. Canan Akça Ertürk

How to Cite

Canan Akça Ertürk (Yüksek Lisans Tezi). Paketli gıda ürün etiketleri kullanılarak görüntü işleme ve optik karakter tanıma (OKT) tekniklerine dayalı uzman sistemin geliştirilmesi, 2024, Yozgat Bozok University.

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