Genotype–Environment Interaction in Shaping the Agronomic Performance of Silage Maize Varieties Cultivated in Organic Farming Systems

cris.virtual.author-orcid0000-0001-8841-9970
cris.virtual.author-orcid0000-0002-8514-5449
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid0000-0002-9670-3231
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcidd0990805-e440-4a16-9390-ca702683f45e
cris.virtualsource.author-orcid0e58100d-9317-4213-93ad-a314751fcd69
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcidd5bc5072-424b-49a4-92ce-2da11fa5d021
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.abstract.enOrganic production systems impose strong environmental constraints on silage maize, yet the relative contributions of genotype, environment and their interaction (G × E) to key performance traits remain insufficiently resolved. This study evaluated six maize cultivars across 11 organically managed environments (location × year combinations) in Poland, assessing weed infestation, plant height, fresh matter yield, dry matter content and dry matter yield. Genotype × environment interaction was explicitly analyzed using AMMI-based models, and cultivar adaptability and stability were evaluated using complementary indices. Environmental effects consistently dominated all traits, explaining 78–91% of total variation, while G × E interactions, though smaller, were significant and altered cultivar rankings. Weed infestation ranged widely across environments, from below 10% to over 90%, and was almost entirely environment-driven. Yield-related traits followed a strong precipitation gradient, with Pawłowice and Śrem showing the highest biomass potential. SM Perseus produced the greatest dry matter yields (13.53 t·ha−1), whereas SM Mieszko combined high dry matter content (37.73%) with outstanding stability. Mega-environment analysis identified distinct adaptive niches, confirming that no genotype performed consistently best across all conditions. These findings close a key knowledge gap regarding cultivar performance under organic management and demonstrate the necessity of multi-environment evaluation that integrates performance, stability and adaptability analyses to support site-specific cultivar recommendations that enhance biomass productivity and silage quality in ecologically managed maize systems.
dc.affiliationWydział Rolnictwa, Ogrodnictwa i Biotechnologii
dc.affiliation.instituteKatedra Metod Matematycznych i Statystycznych
dc.affiliation.instituteKatedra Agronomii
dc.contributor.authorMarcinkowska, Katarzyna
dc.contributor.authorKolańska, Karolina
dc.contributor.authorBanaś, Konrad
dc.contributor.authorŁacka, Agnieszka
dc.contributor.authorLenartowicz, Tomasz
dc.contributor.authorSzulc, Piotr
dc.contributor.authorBujak, Henryk
dc.date.access2026-01-07
dc.date.accessioned2026-01-07T08:27:09Z
dc.date.available2026-01-07T08:27:09Z
dc.date.copyright2026-01-03
dc.date.issued2026
dc.description.abstract<jats:p>Organic production systems impose strong environmental constraints on silage maize, yet the relative contributions of genotype, environment and their interaction (G × E) to key performance traits remain insufficiently resolved. This study evaluated six maize cultivars across 11 organically managed environments (location × year combinations) in Poland, assessing weed infestation, plant height, fresh matter yield, dry matter content and dry matter yield. Genotype × environment interaction was explicitly analyzed using AMMI-based models, and cultivar adaptability and stability were evaluated using complementary indices. Environmental effects consistently dominated all traits, explaining 78–91% of total variation, while G × E interactions, though smaller, were significant and altered cultivar rankings. Weed infestation ranged widely across environments, from below 10% to over 90%, and was almost entirely environment-driven. Yield-related traits followed a strong precipitation gradient, with Pawłowice and Śrem showing the highest biomass potential. SM Perseus produced the greatest dry matter yields (13.53 t·ha−1), whereas SM Mieszko combined high dry matter content (37.73%) with outstanding stability. Mega-environment analysis identified distinct adaptive niches, confirming that no genotype performed consistently best across all conditions. These findings close a key knowledge gap regarding cultivar performance under organic management and demonstrate the necessity of multi-environment evaluation that integrates performance, stability and adaptability analyses to support site-specific cultivar recommendations that enhance biomass productivity and silage quality in ecologically managed maize systems.</jats:p>
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.if3,6
dc.description.number1
dc.description.points100
dc.description.versionfinal_published
dc.description.volume16
dc.identifier.doi10.3390/agriculture16010123
dc.identifier.issn2077-0472
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/6609
dc.identifier.weblinkhttps://www.mdpi.com/2077-0472/16/1/123
dc.languageen
dc.relation.ispartofAgriculture (Switzerland)
dc.relation.pagesart. 123
dc.rightsCC-BY
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.subject.enAMMI analysis
dc.subject.encultivar adaptability
dc.subject.endry matter yield
dc.subject.enmega-environment analysis
dc.subject.ensilage yield stability
dc.subject.enweed infestation
dc.titleGenotype–Environment Interaction in Shaping the Agronomic Performance of Silage Maize Varieties Cultivated in Organic Farming Systems
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue1
oaire.citation.volume16