Evaluating genetic diversity of morpho-physiological traits in sweet cherry (Prunus avium L.) cultivars using multivariate analysis

• Published in: Genetic resources and crop evolution 2024-10, Vol.71 (7), p.3267-3302
• Main Authors: Dangi, Girish, Singh, Dinesh, Chauhan, Neena, Dogra, R. K., Verma, Pramod, Chauhan, Akriti
• Format: Article
• Language: English
• Subjects: Agriculture; Biomedical and Life Sciences; Cluster analysis; Correlation coefficient; Correlation coefficients; Cultivars; Evaluation; Fruit juices; Fruits; Genetic analysis; Genetic diversity; Genotypes; Germplasm; Hybridization; Leaf area; Leaves; Life Sciences; Multivariate analysis; Parameter identification; Physiology; Plant breeding; Plant Genetics and Genomics; Plant Physiology; Plant Sciences; Plant Systematics/Taxonomy/Biogeography; Principal components analysis; Prunus avium; Qualitative analysis; Research Article; Sweetness
• ISSN: 0925-9864; 1573-5109
• DOI: 10.1007/s10722-023-01809-z

The current research focused on the examination of 20 distinct sweet cherry cultivars after analyzing 34 qualitative and 39 quantitative morpho-physiological attributes encompassing tree, leaf, flower, fruit, and stone characteristics. The findings highlighted a notable spectrum of diversity within the assessed array of sweet cherry cultivars. The analysis of correlation coefficients revealed noteworthy positive and negative correlations among the morpho-physiological traits under investigation. Predominantly, these significant correlation coefficients were identified between attributes reflecting both the size and quality of the fruit. The application of principal component analysis (PCA) on both quantitative and qualitative morphological parameters elucidated a substantial portion of the total variability, accounting for 85.29% and 89.18% across the initial eight and nine axes, respectively. In this PCA, specific traits such as leaf width, fruit sweetness, fruit juice color, fruit juiciness, and fruit flesh colorstood out as dominant factors within the realm of qualitative characteristics. Meanwhile, within the realm of quantitative traits, attributes including leaf area, leaf length, TSS, TSS: acid ratio, pulp-to-stone ratio, and yield efficiency emerged as primary contributors within the first components of PCA. This underscores their significance in the evaluation and characterization of sweet cherry germplasm. Ward's agglomeration, employing Euclidean's distance method, yielded a hierarchical cluster analysis that classified assorted sweet cherry cultivars into two primary clusters, each containing several secondary sub-clusters. This classification indicates a significant potential within the characterized sweet cherry collection for targeted breeding objectives. Notably, sweet cherry cultivars spanning various clusters hold promise as potential parent candidates for hybridization, enabling the development of novel genotypes. The dendrogram depicting the assessed traits visually portrays notable differentiation among sweet cherry cultivars, thus indicating clear distinctions. Moreover, it also hints at the presence of synonymous traits within the evaluated sweet cherry group.