Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis

This study leverages multivariate analysis, including principal component analysis (PCA) and cluster analysis, to select peanut genotypes with resistance to thrips and desirable agronomic traits. The focus is on progenies derived from the cross between the cultivar IAC 503 4x and an interspecific sy...

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Main Authors: Melina Zacarelli Pirotta, Marcos Doniseti Michelotto, Ignácio José de Godoy, Claudenir Facincani Franco, Jardel da Silva Souza, Sandra Helena Unêda-Trevisoli
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:International Journal of Agronomy
Online Access:http://dx.doi.org/10.1155/ioa/6173160
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author Melina Zacarelli Pirotta
Marcos Doniseti Michelotto
Ignácio José de Godoy
Claudenir Facincani Franco
Jardel da Silva Souza
Sandra Helena Unêda-Trevisoli
author_facet Melina Zacarelli Pirotta
Marcos Doniseti Michelotto
Ignácio José de Godoy
Claudenir Facincani Franco
Jardel da Silva Souza
Sandra Helena Unêda-Trevisoli
author_sort Melina Zacarelli Pirotta
collection DOAJ
description This study leverages multivariate analysis, including principal component analysis (PCA) and cluster analysis, to select peanut genotypes with resistance to thrips and desirable agronomic traits. The focus is on progenies derived from the cross between the cultivar IAC 503 4x and an interspecific synthetic amphidiploid (A. magna x A. cardenasii) 4x. Analyzing F4 generation progenies using Federer’s augmented block scheme with intercalary checks, the study evaluates resistance to thrips based on natural infestation and damage symptoms, alongside agronomic traits indicating proximity to the cultivated variety. The multivariate techniques applied are PCA and hierarchical cluster analysis using Euclidean distance and Ward’s method, and the nonhierarchical K-means method. PCA identifies two principal components explaining 78.39% of the variance, focusing on pod and grain yield, number of pods and grains, number of thrips, and visual symptom scores. This allows for the discrimination of 24 progenies based on crucial agronomic characteristics. Cluster analysis forms nine groups, with selected progenies clustering together, indicating consistency between multivariate analysis methods. These analyses effectively select segregating progenies from initial generations of peanuts, emphasizing traits related to thrips resistance and production components. The agreement between PCA and cluster analysis results highlights the efficiency of these methods in genotype selection for improved pest resistance and agronomic performance, contributing to the sustainability and economic viability of peanut production.
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spelling doaj-art-0f3cf0ca0ff5425c950e4021f9a8c8e72025-08-20T03:01:07ZengWileyInternational Journal of Agronomy1687-81672025-01-01202510.1155/ioa/6173160Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate AnalysisMelina Zacarelli Pirotta0Marcos Doniseti Michelotto1Ignácio José de Godoy2Claudenir Facincani Franco3Jardel da Silva Souza4Sandra Helena Unêda-Trevisoli5Laboratory of Biotechnology and Plant BreedingAgência Paulista de Tecnologia Dos Agronegócios/APTACenter for Analysis and Technological Research of Grain and Fiber AgribusinessFaculdade de Tecnologia de JaboticabalLaboratory of Biotechnology and Plant BreedingLaboratory of Biotechnology and Plant BreedingThis study leverages multivariate analysis, including principal component analysis (PCA) and cluster analysis, to select peanut genotypes with resistance to thrips and desirable agronomic traits. The focus is on progenies derived from the cross between the cultivar IAC 503 4x and an interspecific synthetic amphidiploid (A. magna x A. cardenasii) 4x. Analyzing F4 generation progenies using Federer’s augmented block scheme with intercalary checks, the study evaluates resistance to thrips based on natural infestation and damage symptoms, alongside agronomic traits indicating proximity to the cultivated variety. The multivariate techniques applied are PCA and hierarchical cluster analysis using Euclidean distance and Ward’s method, and the nonhierarchical K-means method. PCA identifies two principal components explaining 78.39% of the variance, focusing on pod and grain yield, number of pods and grains, number of thrips, and visual symptom scores. This allows for the discrimination of 24 progenies based on crucial agronomic characteristics. Cluster analysis forms nine groups, with selected progenies clustering together, indicating consistency between multivariate analysis methods. These analyses effectively select segregating progenies from initial generations of peanuts, emphasizing traits related to thrips resistance and production components. The agreement between PCA and cluster analysis results highlights the efficiency of these methods in genotype selection for improved pest resistance and agronomic performance, contributing to the sustainability and economic viability of peanut production.http://dx.doi.org/10.1155/ioa/6173160
spellingShingle Melina Zacarelli Pirotta
Marcos Doniseti Michelotto
Ignácio José de Godoy
Claudenir Facincani Franco
Jardel da Silva Souza
Sandra Helena Unêda-Trevisoli
Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis
International Journal of Agronomy
title Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis
title_full Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis
title_fullStr Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis
title_full_unstemmed Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis
title_short Selection of Interspecific Peanut Arachis hypogaea L. Genotypes for Thrips Resistance Using Multivariate Analysis
title_sort selection of interspecific peanut arachis hypogaea l genotypes for thrips resistance using multivariate analysis
url http://dx.doi.org/10.1155/ioa/6173160
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