Integrating Image-Based Phenotyping: A Comprehensive Analysis Using PCA, Cluster Analysis, and Path Coefficient Analysis

Yıl 2025, Cilt: 1 Sayı: 2, 51 - 60, 26.12.2025

Muhammad Waqas Ashiq , Muhammad Sheraz , Muhammad Shahnawaz , Sidra Zahoor , Aamir Aziz , Sidra Razzaq , Muhammad Taimoor Farrukh Khan , Tayyab Nawaz Khan , Muhammad Yasir Malik , Muhammad Muzamil

https://doi.org/10.5281/zenodo.17976793

Öz

Field pea (Pisum sativum L.) is a significant legume crop in Pakistan, and the development of high-yielding varieties is essential for enhancing productivity. This study aimed to evaluate the morphological diversity of 25 pea genotypes using both image-based phenotyping and field-based traits. A total of 21 traits were analyzed. Principal Component Analysis (PCA) revealed a strong positive correlation among pod area, pod perimeter, pod length, pod weight, pod aspect ratio, number of seeds per pod, seed weight per pod, and number of nodes, with pod area showing the highest eigenvalue of 9.715. Cluster analysis identified four major clusters and six sub-clusters, highlighting significant genetic diversity in the germplasm. Correlation analysis revealed a highly significant positive correlation between pod weight and pod factor from density (r = 0.91), seed weight per pod (r = 0.88), and number of seeds per pod (r = 0.85). Path coefficient analysis indicated that pod area had the highest direct positive effect on pod weight (0.010), while pod length exhibited a negative direct effect (-0.002). Genetic variance estimates ranged from 41,108,350 for pod area to 0.00 for pod roundness, with phenotypic variance ranging from 50,332,040 for pod area to 0.00 for pod roundness. Broad-sense heritability was high for traits such as pod weight (0.80), pod area (0.82), seed weight per pod (0.81), and number of pods per plant (0.81). These findings highlight the strong genetic influence on pea yield-related traits and provide a foundation for future breeding programs aimed at improving productivity.

Anahtar Kelimeler

Peas , High-throughput phenotyping , PCA , Cluster and Correlation

Görüntü Tabanlı Fenotiplemenin Entegrasyonu: PCA, Kümeleme Analizi ve Yol Katsayısı Analizi Kullanılarak Kapsamlı Bir Analiz

Öz

Tarla bezelyesi (Pisum sativum L.), Pakistan’da önemli bir baklagil ürünüdür ve yüksek verimli çeşitlerin geliştirilmesi, verimliliğin artırılması açısından kritik öneme sahiptir. Bu çalışma, 25 bezelye genotipinin morfolojik çeşitliliğini hem görüntü tabanlı fenotipleme hem de tarla temelli özellikler kullanarak değerlendirmeyi amaçlamıştır. Toplam 21 özellik analiz edilmiştir. Temel Bileşen Analizi (PCA), bakla alanı, bakla çevresi, bakla uzunluğu, bakla ağırlığı, bakla en-boy oranı, bakla başına tohum sayısı, bakla başına tohum ağırlığı ve boğum sayısı arasında güçlü pozitif korelasyon olduğunu ortaya koymuştur; en yüksek özdeğer ise bakla alanında 9,715 olarak tespit edilmiştir. Kümeleme analizi, gen havuzunda önemli genetik çeşitliliği ortaya koyarak dört ana küme ve altı alt küme belirlemiştir. Korelasyon analizi, bakla ağırlığı ile yoğunluk faktörü (r = 0,91), bakla başına tohum ağırlığı (r = 0,88) ve bakla başına tohum sayısı (r = 0,85) arasında yüksek düzeyde anlamlı pozitif korelasyon göstermiştir. Yol katsayısı analizi, bakla alanının bakla ağırlığı üzerinde en yüksek doğrudan pozitif etkiye (0,010) sahip olduğunu, bakla uzunluğunun ise negatif doğrudan etki (-0,002) gösterdiğini ortaya koymuştur. Genetik varyans tahminleri bakla alanı için 41.108.350 ile bakla yuvarlaklığı için 0,00 arasında değişirken, fenotipik varyans bakla alanı için 50.332.040 ile bakla yuvarlaklığı için 0,00 arasında değişmiştir. Geniş anlamda kalıtım derecesi ise bakla ağırlığı (0,80), bakla alanı (0,82), bakla başına tohum ağırlığı (0,81) ve bitki başına bakla sayısı (0,81) gibi özelliklerde yüksek bulunmuştur. Bu bulgular, bezelyede verimle ilişkili özellikler üzerinde güçlü genetik etkinin varlığını vurgulamakta ve verimliliği artırmaya yönelik ıslah programları için sağlam bir temel sunmaktadır.

Anahtar Kelimeler

Bezelye , Yüksek Verimli Fenotipleme , PCA , Kümeleme ve Korelasyon

Kaynakça

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