Evidence map›Paper›PMID 40394140›Full record

ArticleScientific reports2025

Genetic diversity and agro-morphological characterization of cassava varieties provides insight for breeding and crop improvement.

Shamal Shasang Kumar, Shalendra Prasad, Owais Ali Wani, Salah El-Hendawy, Mohamed A Mattar, Ali Salem

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shamal Shasang KumarCrop Research Division, Ministry of Agriculture & Waterways (MOA & W), P.O. Box 77, Nausori, Fiji.
Shalendra PrasadCrop Research Division, Ministry of Agriculture & Waterways (MOA & W), P.O. Box 77, Nausori, Fiji.
Owais Ali WaniDivision of Agronomy, Faculty of Agriculture, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Wadura, Sopore, 193201, India. owaisaliwani@gmail.com.
Salah El-HendawyDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, P.O. Box 2460, 11451, Riyadh, Saudi Arabia.
Mohamed A MattarPrince Sultan Bin Abdulaziz International Prize for Water Chair, Prince Sultan Institute for Environmental, Water and Desert Research, King Saud University, P.O. Box 2454, Riyadh 11451, Saudi Arabia. mmattar@ksu.edu.sa.ORCID http://orcid.org/0000-0002-7506-3036
Ali SalemCivil Engineering Department, Faculty of Engineering, Minia University, Minia 61111, Egypt. salem.ali@mik.pte.hu.ORCID http://orcid.org/0000-0001-6176-8345

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lack of knowledge about genetic variation in cassava is a problem for Fiji's efforts to improve its genetics. Using agro-morphological features, this study aimed to assess the genetic diversity and interrelationships among 33 cassava cultivars. A field investigation was conducted at the Dobuilevu Research Station using a randomized complete block design. Morphological analysis, based on qualitative and quantitative characteristics, divided the germplasm into three groups. In both the qualitative and quantitative trait datasets, two principal components were found to account for 36.31% and 43.45% of the total genetic variance, respectively. Qualitative features, such as branching habit and stem cortex color (r = 0.19), petiole color and root cortex color (r = 0.32), and leaf color and root shape (r = 0.40) were shown to have significant positive correlations. Similarly, quantitative parameters like starch content (r = 0.25) and the number of leaf lobes with yield (r = 0.17) showed significant associations. Based on morphological and genetic similarities, hierarchical clustering grouped the cultivars into three qualitative and five quantitative clusters. While the quantitative traits emphasized variability in yield, starch content, and iron content. The qualitative traits' descriptive statistics revealed diverse phenotypic expressions, with dark green leaf color and cylindrical root form being the most common. These results demonstrate significant genetic variation across cassava cultivars, which can be used for genetic improvement initiatives, germplasm conservation, and short-term varietal release programs. To facilitate the development of more resilient and productive cassava cultivars, targeted breeding efforts aimed at improving yield, quality, and stress tolerance are recommended based on the significant phenotypic and genetic variation observed.

Indexed as

Crops, AgriculturalGenetic VariationManihotPlant BreedingPhenotypePlant LeavesPlant RootsAgro-morphological traitsBreeding programsCassava varietiesCorrelation analysisGenetic variabilityHierarchical clusteringPrincipal component analysis

Identifiers

PMID40394140
PMCPMC12092572

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