Scholarlink

Context <p>Accurate identification of cultivars is essential for effective breeding, germplasm conservation, and varietal protection. In sesame, traditional morphological descriptors often lack the precision required for clear differentiation, highlighting the need to integrate molecular markers for more reliable identification.</p> Aims <p>This study aimed to establish a robust and rapid approach for sesame cultivar identification by integrating Distinctness, Uniformity, and Stability (DUS) descriptors with molecular markers.</p> Methods <p>A total of 43 sesame genotypes were evaluated using 20 DUS descriptors and 34 simple sequence repeat (SSR) markers, of which nine were found to be polymorphic. Morphological diversity was assessed using Mahalanobis’s D<sup>2</sup> analysis while molecular diversity was assessed through DARwin software based on allelic scoring of polymorphic SSR markers. Genetic relationships and population structure were determined using STRUCTURE software. The integrated data of from DUS traits and allele codes of markers were subsequently encoded into Quick Response (QR) codes to enable easy and efficient access.</p> Key results <p>DUS characterization of sesame genotypes revealed substantial diversity across the evaluated traits. Based on morphological data, the genotypes were grouped into seven distinct clusters, whereas molecular analysis using SSR markers classified them into three major clusters. Population structure analysis further divided the genotypes into two primary groups, mainly based on seed color. By integrating data from nine polymorphic SSR markers and 12 essential DUS descriptors, all 43 genotypes could be distinctly identified, in contrast to only 17 genotypes distinguishable using molecular markers alone.</p> Conclusions <p>The integration of morphological and molecular data significantly enhances the accuracy and efficiency of varietal identification in sesame.</p> Implications <p>The QR code system enables rapid data retrieval, thereby supporting breeding programs, germplasm management, and varietal protection, with promising potential for application in other crop species.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of QR codes for rapid identification of sesame cultivars using DUS descriptors and molecular markers

  • 期刊论文

  • 发表日期：

    2025年6月6日

查看全文
  • Amidala Manasa,
  • Duddu Bharathi,
  • Roja Veeraghattapu,
  • Shanthi Priya Mallapuram,
  • Lavanya Kumari Padherla,
  • Bhanu Prakash Vulusala,
  • Anil Kumar Gangireddy,
  • Girish Kumar Killada,
  • K. S. SaiVenkat,
  • Lakshminarayana R. Vemieddy

摘要

Context

Accurate identification of cultivars is essential for effective breeding, germplasm conservation, and varietal protection. In sesame, traditional morphological descriptors often lack the precision required for clear differentiation, highlighting the need to integrate molecular markers for more reliable identification.

Aims

This study aimed to establish a robust and rapid approach for sesame cultivar identification by integrating Distinctness, Uniformity, and Stability (DUS) descriptors with molecular markers.

Methods

A total of 43 sesame genotypes were evaluated using 20 DUS descriptors and 34 simple sequence repeat (SSR) markers, of which nine were found to be polymorphic. Morphological diversity was assessed using Mahalanobis’s D2 analysis while molecular diversity was assessed through DARwin software based on allelic scoring of polymorphic SSR markers. Genetic relationships and population structure were determined using STRUCTURE software. The integrated data of from DUS traits and allele codes of markers were subsequently encoded into Quick Response (QR) codes to enable easy and efficient access.

Key results

DUS characterization of sesame genotypes revealed substantial diversity across the evaluated traits. Based on morphological data, the genotypes were grouped into seven distinct clusters, whereas molecular analysis using SSR markers classified them into three major clusters. Population structure analysis further divided the genotypes into two primary groups, mainly based on seed color. By integrating data from nine polymorphic SSR markers and 12 essential DUS descriptors, all 43 genotypes could be distinctly identified, in contrast to only 17 genotypes distinguishable using molecular markers alone.

Conclusions

The integration of morphological and molecular data significantly enhances the accuracy and efficiency of varietal identification in sesame.

Implications

The QR code system enables rapid data retrieval, thereby supporting breeding programs, germplasm management, and varietal protection, with promising potential for application in other crop species.