{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:11:32Z","timestamp":1788876692732,"version":"build-2803163510"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Plant Sci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Faba bean cultivation in northern Europe is challenged by high variability in yield performance due to strong genotype \u00d7 environment interaction (GEI). Appropriate GEI modeling and interpretation is essential for both cultivar recommendation and breeding for Nordic conditions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Grain yield data from fifteen spring faba bean cultivars evaluated in eleven Norwegian environments during four growing seasons (2022\u20132025) were analyzed using the Additive Main Effects and Multiplicative Interaction (AMMI) model. Climatic drivers of GEI were investigated using factorial regression, while genome-wide SNP markers were used to assess the relationship between molecular diversity and adaptive differentiation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Environment, genotype, and GEI significantly influenced grain yield. The AMMI model with three GEI principal components (AMMI3) represented the biologically meaningful GEI signal and explained 83.4% of the GEI variation. The predictive accuracy of this model closely approached that of BLUP and GBLUP. Factorial regression showed that maximum and mean September temperatures explained 38.5% of the GEI variation, indicating that late-season thermal conditions are the principal environmental drivers of cultivar adaptation. We identified three top-yielding genotypes (Ketu, Birgit, and Vire) that can be object of site-specific recommendation. Two sub-regions emerged as possibly distinct breeding targets, namely, a major one, and a smaller one featuring cooler late-cycle temperatures and specific adaptation of very early material. A significant Mantel correlation between genomic and adaptive dissimilarity (r = 0.40, P\u00a0=\u00a00.029) suggested that differences in environmental adaptation have a measurable genetic basis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study identified elite cultivars for recommendation and generated crucial information for future crop breeding and variety testing in Norway. Breeding for wide adaptation across climatically diversified environments is justified by the modest size of the smaller sub-region and its expected decreasing importance due to climate change. The relationship between genomic and adaptive dissimilarity, if confirmed for a larger genotype set, could be exploited for a preliminary screening of regional breeding material and novel plant introductions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpls.2026.1936638","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T13:55:47Z","timestamp":1788875747000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptation of faba bean cultivars across Norwegian environments: identification of elite material and definition of optimal breeding and cultivar testing procedures"],"prefix":"10.3389","volume":"17","author":[{"given":"Stefano","family":"Zanotto","sequence":"first","affiliation":[{"name":"Department of Plant Science, Faculty of Biosciences, Norwegian University of Life Sciences (NMBU)","place":["\u00c5s, Norway"]},{"name":"Council for Agricultural Research and Economics (CREA), Research Centre for Animal Production and Aquaculture","place":["Lodi, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jon Arne","family":"Dieseth","sequence":"additional","affiliation":[{"name":"Graminor AS","place":["Hamar, Norway"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wendy","family":"Waalen","sequence":"additional","affiliation":[{"name":"Division of Food Production and Society, Norwegian Institute for Bioeconomy Research (NIBIO)","place":["\u00c5s, Norway"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Annicchiarico","sequence":"additional","affiliation":[{"name":"Council for Agricultural Research and Economics (CREA), Research Centre for Animal Production and Aquaculture","place":["Lodi, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne Kjersti","family":"Uhlen","sequence":"additional","affiliation":[{"name":"Department of Plant Science, Faculty of Biosciences, Norwegian University of Life Sciences (NMBU)","place":["\u00c5s, Norway"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"key":"B1","volume-title":"Muligheter for \u00d8kt Proteinproduksjon P\u00e5 Kornarealene","author":"Abrahamsen","year":"2018"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2021.744259","article-title":"Conventional and Molecular Breeding Tools for Accelerating Genetic Gain in Faba Bean (Vicia Faba L.)","volume":"12","author":"Adhikari","year":"2021","journal-title":"Front. 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