本研究使用50個SSR標誌和來自不同區域的23個大豆品種，初步探討大豆性狀與SSR標誌之間的相關性。從SSR標記獲得的條帶進行統計分析，並應用聚類生成之樹狀圖以區分大豆品種之間的基因關係。結果顯示，來自哥倫比亞的大豆品種和台南5號親緣關係接近。另一方面，對28個栽培試驗中大豆性狀的調查數據進行主成分分析（PCA）。結果表明，在抗病和感病條件下，23個品種在9個連續性狀的調查結果中沒有顯著差異。進行統計分析篩選具有與相同性狀相關的SSR標記的條帶，並評估分子標記與植物性狀之間的相關性。研究表明，與性狀更高相關性的SSR標誌主要集中在大豆的第12、13、14和16條染色體上，與先前有關大豆生長、發育和產量的QTL報告一致。研究結果強調了一個關鍵點，即僅從單一性狀或SSR標誌生成的條帶不能有效區分大豆品種。因此，未來收穫來自不同地區的更多大豆基因種原，數據分析將整合來自栽培試驗的農藝性狀和SSR標記，進行比對統計。這種方法旨在掌握大豆性狀的基因因素，對於推動大豆育種和提高產量至關重要。

This study involved 50 SSR markers and 23 soybean cultivars, encompassing different cultivars and breeding types from various regions, to preliminarily explore the correlation between soybean traits and SSR markers. Statistical analysis of the bands obtained from SSR markers and the application of cluster analysis was used to generate a dendrogram to distinguish the genetic relationships among soybean cultivars. The results suggest a close genetic relationship between soybean cultivars from Colombia and Tainan No. 5. In addition, principal component analysis (PCA) was conducted on the survey data of soybean traits from 28 cultivation experiments. The results indicate no significant differences in the investigation outcomes of 9 consecutive traits among 23 cultivars under disease-resistant and susceptible conditions. Statistical analysis was performed to identify SSR markers with bands correlated to the same traits and further assess the correlation between molecular markers and plant traits. The study demonstrated that SSR markers with higher correlation to traits were mainly concentrated on soybean chromosomes 12, 13, 14, and 16, consistent with QTL reported in previous studies on soybean growth, development, and yield. The research findings emphasize a crucial point that bands generated solely from single traits or SSR markers cannot effectively distinguish soybean cultivars. Therefore, in the future, as more soybean germplasms from different regions will be available, data analysis will integrate agronomic traits from cultivation experiments with SSR markers for comparative analysis.

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