Despite the fact that mangoes of India exhibit a considerable diversity, barring only a few genotypes, majority of them are not adequate for commercialisation. Thus, outstanding new varieties are required to meet the market demand, which necessitates assessment of genetic variability, authentic identification and population structuring. We examined 30 different fruit traits and utilized 63 RAPD primers in an attempt to perform population structuring and genetic diversity analysis of 58 selected Indian mango genotypes, including commercial cultivars as selections, hybrids and landraces. The higher average values for % polymorphism (85.82%), PIC(> 0.6), EMR(> 12), MI (8.65), RP (13), I (0.40) and a wide range of similarity 0.38 to 0.87 (averaging 0.59) indicated a high degree of genetic diversity and affirmed effectiveness of RAPD as a reliable informative marker. Forty-eight genotype-specific unique fingerprints were detected which enabled identification of 27 different genotypes out of all genotypes audited. Compared to markers associated with fruit features, RAPD markers proved relatively more resolute, being able to portray higher similarity and discrimination among closely related genotypes. A low correlation was noticed between clustering pattern and matrices of fruit-specific and molecular markers. Ten local genotypes were identified based on morphological features related to low similarity coefficient, outliers and pairing with superior genotypes that have been already used as breeding partners. Besides, based on RAPD data on diversity index, presence of unique fingerprints and outlier clustering pattern, 13 most diverse genotypes were identified including three local genotypes, namely ‘Kancha Mitha’, ‘Hunkagaja’, and ‘Hamilton Sundari’, which could be employed as suitable candidates in breeding programs. Efficient grouping of mango genotypes in UPGMA and Bayesian model-based population structuring and admixture analysis, mostly based on genotypic status (selection, hybrid or landrace), substantiated RAPD’s efficacy, not only for estimating genetic divergence/associations but also structuring mango populations. Information generated through this investigation will facilitate characterization, conservation and breeding for genetic improvement of this valuable fruit crop.

尽管印度的芒果表现出相当大的多样性，除了少数基因型外，其中大多数还不足以商业化。因此，需要优秀的新品种来满足市场需求，这需要对遗传变异性、真实性鉴定和种群结构进行评估。我们检查了 30 种不同的果实性状并使用了 63 种 RAPD 引物，试图对 58 种选定的印度芒果基因型进行群体结构和遗传多样性分析，包括作为选择、杂交品种和地方品种的商业品种。% 多态性 (85.82%)、PIC(> 0.6)、EMR(> 12)、MI (8.65)、RP (13)、I (0.40) 和广泛的相似性 0.38 到 0.87（平均 0 . 59）表明高度的遗传多样性，并肯定了 RAPD 作为可靠信息标记的有效性。检测到 48 个基因型特异性独特指纹，从而能够在所有审核的基因型中识别出 27 种不同的基因型。与与水果特征相关的标记相比，RAPD 标记相对更明确，能够在密切相关的基因型之间描绘更高的相似性和区分性。聚类模式与水果特异性和分子标记的矩阵之间的相关性较低。基于与低相似系数、异常值和与已用作育种伙伴的优良基因型配对相关的形态特征，鉴定了十个局部基因型。此外，基于多样性指数的 RAPD 数据，由于存在独特的指纹和异常值聚类模式，鉴定了 13 个最多样化的基因型，其中包括 3 个本地基因型，即“Kancha Mitha”、“Hunkagaja”和“Hamilton Sundari”，可作为育种计划的合适候选者。在 UPGMA 和基于贝叶斯模型的种群结构和混合分析中对芒果基因型进行有效分组，主要基于基因型状态（选择、杂交或地方品种），证实了 RAPD 的功效，不仅用于估计遗传差异/关联，还用于构建芒果种群。通过这项调查产生的信息将有助于对这种有价值的水果作物进行遗传改良的表征、保护和育种。即“Kancha Mitha”、“Hunkagaja”和“Hamilton Sundari”，它们可以用作育种计划中的合适候选者。在 UPGMA 和基于贝叶斯模型的种群结构和混合分析中对芒果基因型进行有效分组，主要基于基因型状态（选择、杂交或地方品种），证实了 RAPD 的功效，不仅用于估计遗传差异/关联，还用于构建芒果种群。通过这项调查产生的信息将有助于对这种有价值的水果作物进行遗传改良的表征、保护和育种。即“Kancha Mitha”、“Hunkagaja”和“Hamilton Sundari”，它们可以用作育种计划中的合适候选者。在 UPGMA 和基于贝叶斯模型的种群结构和混合分析中对芒果基因型进行有效分组，主要基于基因型状态（选择、杂交或地方品种），证实了 RAPD 的功效，不仅用于估计遗传差异/关联，还用于构建芒果种群。通过这项调查产生的信息将有助于对这种有价值的水果作物进行遗传改良的表征、保护和育种。主要基于基因型状态（选择、杂交或地方品种），证实了 RAPD 的功效，不仅用于估计遗传差异/关联，还用于构建芒果种群。通过这项调查产生的信息将有助于对这种有价值的水果作物进行遗传改良的表征、保护和育种。主要基于基因型状态（选择、杂交或地方品种），证实了 RAPD 的功效，不仅用于估计遗传差异/关联，还用于构建芒果种群。通过这项调查产生的信息将有助于对这种有价值的水果作物进行遗传改良的表征、保护和育种。