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Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions
Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255084/ https://www.ncbi.nlm.nih.gov/pubmed/37299146 http://dx.doi.org/10.3390/plants12112165 |
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author | Ljubičić, Nataša Popović, Vera Kostić, Marko Pajić, Miloš Buđen, Maša Gligorević, Kosta Dražić, Milan Bižić, Milica Crnojević, Vladimir |
author_facet | Ljubičić, Nataša Popović, Vera Kostić, Marko Pajić, Miloš Buđen, Maša Gligorević, Kosta Dražić, Milan Bižić, Milica Crnojević, Vladimir |
author_sort | Ljubičić, Nataša |
collection | PubMed |
description | Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes grown in field trials; one control trial without nitrogen, and three applying different levels of nitrogen (0, 70, 140, and 210 kg ha(−1), respectively). Across two growing seasons, both the phenotypic variability and GEI for yield traits over four maize genotypes (P0725, P9889, P9757 and P9074) grown in four different fertilization treatments were studied. The additive main effects and multiplicative interaction (AMMI) models were used to estimate the GEI. The results revealed that genotype and environmental effects, such as the GEI effect, significantly influenced yield, as well as revealing that maize genotypes responded differently to different conditions and fertilization measures. An analysis of the GEI using the IPCA (interaction principal components) analysis method showed the statistical significance of the first source of variation, IPCA1. As the main component, IPCA1 explained 74.6% of GEI variation in maize yield. Genotype G3, with a mean grain yield of 10.6 t ha(−1), was found to be the most stable and adaptable to all environments in both seasons, while genotype G1 was found to be unstable, following its specific adaptation to the environments. |
format | Online Article Text |
id | pubmed-10255084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102550842023-06-10 Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions Ljubičić, Nataša Popović, Vera Kostić, Marko Pajić, Miloš Buđen, Maša Gligorević, Kosta Dražić, Milan Bižić, Milica Crnojević, Vladimir Plants (Basel) Article Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes grown in field trials; one control trial without nitrogen, and three applying different levels of nitrogen (0, 70, 140, and 210 kg ha(−1), respectively). Across two growing seasons, both the phenotypic variability and GEI for yield traits over four maize genotypes (P0725, P9889, P9757 and P9074) grown in four different fertilization treatments were studied. The additive main effects and multiplicative interaction (AMMI) models were used to estimate the GEI. The results revealed that genotype and environmental effects, such as the GEI effect, significantly influenced yield, as well as revealing that maize genotypes responded differently to different conditions and fertilization measures. An analysis of the GEI using the IPCA (interaction principal components) analysis method showed the statistical significance of the first source of variation, IPCA1. As the main component, IPCA1 explained 74.6% of GEI variation in maize yield. Genotype G3, with a mean grain yield of 10.6 t ha(−1), was found to be the most stable and adaptable to all environments in both seasons, while genotype G1 was found to be unstable, following its specific adaptation to the environments. MDPI 2023-05-30 /pmc/articles/PMC10255084/ /pubmed/37299146 http://dx.doi.org/10.3390/plants12112165 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ljubičić, Nataša Popović, Vera Kostić, Marko Pajić, Miloš Buđen, Maša Gligorević, Kosta Dražić, Milan Bižić, Milica Crnojević, Vladimir Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions |
title | Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions |
title_full | Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions |
title_fullStr | Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions |
title_full_unstemmed | Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions |
title_short | Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions |
title_sort | multivariate interaction analysis of zea mays l. genotypes growth productivity in different environmental conditions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255084/ https://www.ncbi.nlm.nih.gov/pubmed/37299146 http://dx.doi.org/10.3390/plants12112165 |
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