{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T11:56:02Z","timestamp":1790682962512,"version":"4.1.0"},"reference-count":64,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LP200200927"],"award-info":[{"award-number":["LP200200927"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["IC230100016"],"award-info":[{"award-number":["IC230100016"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["acsess.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Plant Genome"],"published-print":{"date-parts":[[2026,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Climate change poses a significant threat to cereal production, making it increasingly important to understand the role of genotype\u2010by\u2010environment interactions (GEIs) in crops. Traditional breeding approaches consider GEIs at a whole genotype level missing valuable breeding potential that can be dissected by exploring this relationship at a chromosome segment level. A robust commercial dataset consisting of 961 spring barley (\n                    <jats:italic>Hordeum vulgare<\/jats:italic>\n                    L.) genotypes grown across 12 sites was used to explore these questions and to co\u2010locate haplotypes under GEIs with key physiology genes to better understand the drivers of GEIs. A genomic best linear unbiased prediction model for barley yield was fitted to the data, where the GEI term had a factor analytic 4 (FA4) variance structure. Using the first three factor loadings from the FA4 model, the 12 sites were grouped into four environmental clusters. The barley single nucleotide polymorphisms were partitioned into 1741 haploblocks based on linkage disequilibrium and the local genomic estimated breeding values were calculated for each haplotype in each environmental cluster. The GEIs of each haploblock across the environmental clusters were explored, and those under large GEIs were identified across several chromosomes and found to vastly vary in size. Further analysis of a few key haploblocks revealed that for some blocks the best haplotypes were similar across clusters, but for others they were vastly different. This study provides a novel framework for investigating GEIs at a haplotype level, which can be utilized in a range of breeding applications across traits and crops.\n                  <\/jats:p>","DOI":"10.1002\/tpg2.70310","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T11:00:11Z","timestamp":1790679611000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A haplotype\u2010based approach to explore genotype\u2010by\u2010environment interactions for barley yield"],"prefix":"10.1002","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3916-1238","authenticated-orcid":false,"given":"Stephanie M.","family":"Brunner","sequence":"first","affiliation":[{"name":"Queensland Alliance for Agriculture and Food Innovation The University of Queensland  St Lucia Queensland 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Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8303-8076","authenticated-orcid":false,"given":"Hannah","family":"Robinson","sequence":"additional","affiliation":[{"name":"Queensland Alliance for Agriculture and Food Innovation The University of Queensland  St Lucia Queensland Australia"},{"name":"Department of Plant Breeding Hochschule Geisenheim University  Geisenheim Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.1974.1100705"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/tpg2.70088"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btad445"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1534\/genetics.107.071068"},{"key":"e_1_2_11_6_1","unstructured":"Brunner 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