{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:56:33Z","timestamp":1792788993057,"version":"4.5.0"},"reference-count":202,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T00:00:00Z","timestamp":1789948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deutsche Forschungsgemeinschaft","award":["YO 304\/4-1"],"award-info":[{"award-number":["YO 304\/4-1"]}],"id":[{"id":"https:\/\/ror.org\/018mejw64","id-type":"ROR","asserted-by":"crossref"}]},{"award":["YO 304\/4-1"],"award-info":[{"award-number":["YO 304\/4-1"]}],"id":[{"id":"https:\/\/ror.org\/018mejw64","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biology"],"abstract":"<jats:p>Genome-wide association studies (GWASs) have become a central tool in plant genomics, providing high-resolution access to the genetic architecture of complex traits in cereal crops. This review observes the application of GWASs to biotic and abiotic stress responses and nutritional quality in rice (Oryza sativa), wheat (Triticum aestivum), maize (Zea mays), and barley (Hordeum vulgare). However, conventional SNP-based GWASs may overlook structural and presence\u2013absence variation, and significant associations do not by themselves identify the causal gene or variant. Recent methodological developments, including multi-locus and environment-aware models, can improve the detection of complex genetic effects, while pan-genomic and graph-based references broaden the range of genomic variation available for association analysis. Integrating GWASs with transcriptomics, metabolomics, and proteomics provides additional functional evidence for candidate-gene prioritization and interpretation of associated loci. Fine mapping and functional validation, including genome-editing approaches, further help to test candidate-gene function. Together, these advances strengthen the progression from statistical association to biological interpretation and breeding-relevant genetic variation. This review discusses their current applications, limitations, and potential for improving cereal breeding.<\/jats:p>","DOI":"10.3390\/biology15181673","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:50:03Z","timestamp":1789995003000},"page":"1673","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["From Association to Causality: Next-Generation GWAS, Pangenomes, and Multi-Omics Driving Gene Discovery and Precision Breeding in Cereal Crops"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4957-4040","authenticated-orcid":false,"given":"Helmy M.","family":"Youssef","sequence":"first","affiliation":[{"name":"Centre for Converging Science and Emerging Technology (CoSET), Benha National University, Al Obour 13518, Egypt"},{"name":"Department of Botany, Faculty of Agriculture, Cairo University, Giza 12613, Egypt"},{"name":"Chair of Plant Breeding, Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Betty-Heimann-Str. 3, D-06120 Halle (Saale), Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2010-2798","authenticated-orcid":false,"given":"Radwa Y.","family":"Helmi","sequence":"additional","affiliation":[{"name":"Genetics and Cytology Department, Biotechnology Research Institute, National Research Centre, Giza 12622, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3301-9026","authenticated-orcid":false,"given":"Andreas","family":"B\u00f6rner","sequence":"additional","affiliation":[{"name":"Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, OT Gatersleben, D-06466 Seeland, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahmoud M.","family":"Sakr","sequence":"additional","affiliation":[{"name":"Centre for Converging Science and Emerging Technology (CoSET), Benha National University, Al Obour 13518, Egypt"},{"name":"Plant Biotechnology Department, Biotechnology Research Institute, National Research Centre, Giza 12622, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6930-5246","authenticated-orcid":false,"given":"Mohamed","family":"El-Soda","sequence":"additional","affiliation":[{"name":"Department of Genetics, Faculty of Agriculture, Cairo University, Giza 12613, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Garutti, M., Nevola, G., Mazzeo, R., Cucciniello, L., Totaro, F., Bertuzzi, C.A., Caccialanza, R., Pedrazzoli, P., and Puglisi, F. (2022). The Impact of Cereal Grain Composition on the Health and Disease Outcomes. Front. Nutr., 9.","DOI":"10.3389\/fnut.2022.888974"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zenda, T., Liu, S., Dong, A., Li, J., Wang, Y., Liu, X., Wang, N., and Duan, H. (2021). Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value. Front. Plant Sci., 12.","DOI":"10.3389\/fpls.2021.774994"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Jadhav, Y., and Jumbo, M.B. (2024). Genomic Selection in Plant Breeding. Plant Molecular Breeding in Genomics Era: Applications, Springer.","DOI":"10.1007\/978-3-031-68598-9_6"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1002\/csc2.20377","article-title":"Genetic Diversity Is Indispensable for Plant Breeding to Improve Crops","volume":"61","author":"Swarup","year":"2021","journal-title":"Crop Sci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cort\u00e9s, A., and L\u00f3pez-Hern\u00e1ndez, F. (2021). Harnessing Crop Wild Diversity for Climate Change Adaptation. Genes, 12.","DOI":"10.3390\/genes12050783"},{"key":"ref_6","unstructured":"Miedaner, T., and Korzun, V. (2018). Applications of Genetic and Genomic Research in Cereals, Woodhead Publishing."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1038\/nature08800","article-title":"Genome-Wide Association Study of 107 Phenotypes in Arabidopsis Thaliana Inbred Lines","volume":"465","author":"Atwell","year":"2010","journal-title":"Nature"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/ng1702","article-title":"A Unified Mixed-Model Method for Association Mapping That Accounts for Multiple Levels of Relatedness","volume":"38","author":"Yu","year":"2006","journal-title":"Nat. Genet."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1111\/j.1365-313X.2005.02591.x","article-title":"Maize Association Population: A High-Resolution Platform for Quantitative Trait Locus Dissection","volume":"44","author":"Thuillet","year":"2005","journal-title":"Plant J."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1007\/s00122-014-2444-2","article-title":"Genetic Characterization of the Wheat Association Mapping Initiative (Wami) Panel for Dissection of Complex Traits in Spring Wheat","volume":"128","author":"Lopes","year":"2015","journal-title":"Theor. Appl. Genet."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1126\/science.1174320","article-title":"Genetic Properties of the Maize Nested Association Mapping Population","volume":"325","author":"McMullen","year":"2009","journal-title":"Science"},{"key":"ref_12","unstructured":"(2014). The 3, 000 rice genomes project. The 3000 Rice Genomes Project. GigaScience, 3, 7."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1146\/annurev-arplant-050213-035715","article-title":"Natural Variations and Genome-Wide Association Studies in Crop Plants","volume":"65","author":"Huang","year":"2014","journal-title":"Annu. Rev. Plant Biol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e70217","DOI":"10.1002\/tpg2.70217","article-title":"Introgression of Wild Barley Alleles Improves Seedlings Salinity Tolerance in the Nested Association Mapping Heb-400 Population","volume":"19","author":"Schierenbeck","year":"2026","journal-title":"Plant Genome"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1038\/ng.695","article-title":"Genome-Wide Association Studies of 14 Agronomic Traits in Rice Landraces","volume":"42","author":"Huang","year":"2010","journal-title":"Nat. Genet."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4089","DOI":"10.1093\/jxb\/erx214","article-title":"The Roles of Pleiotropy and Close Linkage as Revealed by Association Mapping of Yield and Correlated Traits of Wheat (Triticum aestivum L.)","volume":"68","author":"Schulthess","year":"2017","journal-title":"J. Exp. Bot."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wallace, J.G., Bradbury, P.J., Zhang, N., Gibon, Y., Stitt, M., and Buckler, E.S. (2014). Association Mapping across Numerous Traits Reveals Patterns of Functional Variation in Maize. PLoS Genet., 10.","DOI":"10.1101\/010207"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Thakral, V., Yadav, H., Padalkar, G., Kumawat, S., Raturi, G., Kumar, V., Mandlik, R., Rajora, N., and Singh, M. (2022). Recent Advances and Applicability of Gbs, Gwas, and Gs in Polyploid Crops. Genotyping by Sequencing for Crop Improvement, John Wiley & Sons, Inc.","DOI":"10.1002\/9781119745686.ch15"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1086","DOI":"10.1111\/pbi.12456","article-title":"Understanding and Utilizing Crop Genome Diversity Via High-Resolution Genotyping","volume":"14","author":"Snowdon","year":"2016","journal-title":"Plant Biotechnol. J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"giy154","DOI":"10.1093\/gigascience\/giy154","article-title":"Blink: A Package for the Next Level of Genome-Wide Association Studies with Both Individuals and Markers in the Millions","volume":"8","author":"Huang","year":"2019","journal-title":"GigaScience"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1016\/j.molp.2022.02.012","article-title":"A Compressed Variance Component Mixed Model for Detecting Qtns and Qtn-by-Environment and Qtn-by-Qtn Interactions in Genome-Wide Association Studies","volume":"15","author":"Li","year":"2022","journal-title":"Mol. Plant"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Liu, X., Huang, M., Fan, B., Buckler, E.S., and Zhang, Z. (2016). Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies. PLoS Genet., 12.","DOI":"10.1371\/journal.pgen.1005767"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1038\/s41586-020-2947-8","article-title":"The Barley Pan-Genome Reveals the Hidden Legacy of Mutation Breeding","volume":"588","author":"Jayakodi","year":"2020","journal-title":"Nature"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"uhaf213","DOI":"10.1093\/hr\/uhaf213","article-title":"Epigenetic Crop Improvement: Integrating Encode Strategies into Horticultural Breeding","volume":"12","author":"Yang","year":"2025","journal-title":"Hortic. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1111\/tpj.13515","article-title":"The Pangenome of Hexaploid Bread Wheat","volume":"90","author":"Montenegro","year":"2017","journal-title":"Plant J."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"102658","DOI":"10.1016\/j.pbi.2024.102658","article-title":"New Perspectives of Post-Gwas Analyses: From Markers to Causal Genes for More Precise Crop Breeding","volume":"82","author":"Kanovska","year":"2024","journal-title":"Curr. Opin. Plant Biol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.molp.2016.06.016","article-title":"Distant Eqtls and Non-Coding Sequences Play Critical Roles in Regulating Gene Expression and Quantitative Trait Variation in Maize","volume":"10","author":"Liu","year":"2017","journal-title":"Mol. Plant"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1038\/s42003-023-05279-y","article-title":"Transcriptome-Wide Association Studies: Recent Advances in Methods, Applications and Available Databases","volume":"6","author":"Mai","year":"2023","journal-title":"Commun. Biol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"e79348","DOI":"10.7554\/eLife.79348","article-title":"Integrative Analysis of Metabolite Gwas Illuminates the Molecular Basis of Pleiotropy and Genetic Correlation","volume":"11","author":"Smith","year":"2022","journal-title":"eLife"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1111\/pbi.70032","article-title":"Taft-D1 Positively Regulates Grain Weight by Acting as a Coactivator of Tafdl2 in Wheat","volume":"23","author":"Zhang","year":"2025","journal-title":"Plant Biotechnol. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1016\/j.tplants.2017.08.011","article-title":"Genomic Selection in Plant Breeding: Methods, Models, and Perspectives","volume":"22","author":"Crossa","year":"2017","journal-title":"Trends Plant Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1016\/j.tplants.2021.03.010","article-title":"Designing Future Crops: Genomics-Assisted Breeding Comes of Age","volume":"26","author":"Varshney","year":"2021","journal-title":"Trends Plant Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.tplants.2018.02.001","article-title":"Translating High-Throughput Phenotyping into Genetic Gain","volume":"23","author":"Araus","year":"2018","journal-title":"Trends Plant Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Montesinos-L\u00f3pez, A., Montesinos-L\u00f3pez, O.A., Ramos-Pulido, S., Mosqueda-Gonz\u00e1lez, B.A., Guerrero-Arroyo, E.A., Crossa, J., and Ortiz, R. (2025). Artificial Intelligence Meets Genomic Selection: Comparing Deep Learning and Gblup across Diverse Plant Datasets. Front. Genet., 16.","DOI":"10.3389\/fgene.2025.1568705"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"diaf012","DOI":"10.1093\/insilicoplants\/diaf012","article-title":"Rare Variants in Crops: Theoretical Insights and Emerging Detection Strategies","volume":"7","author":"Floriani","year":"2025","journal-title":"Silico Plants"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1186\/1746-4811-9-29","article-title":"The Advantages and Limitations of Trait Analysis with Gwas: A Review","volume":"9","author":"Korte","year":"2013","journal-title":"Plant Methods"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"bbac547","DOI":"10.1093\/bib\/bbac547","article-title":"A Fast and Powerful Linear Mixed Model Approach for Genotype-Environment Interaction Tests in Large-Scale Gwas","volume":"24","author":"Zhong","year":"2023","journal-title":"Brief. Bioinform."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"De Walsche, A., Vergne, A., Rincent, R., Roux, F., Nicolas, S., Welcker, C., Mezmouk, S., Charcosset, A., and Mary-Huard, T. (2025). Metage: Investigating Genotype X Environment Interactions through Gwas Meta-Analysis. PLoS Genet., 21.","DOI":"10.1371\/journal.pgen.1011553"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"e20077","DOI":"10.1002\/tpg2.20077","article-title":"Status and Prospects of Genome-Wide Association Studies in Plants","volume":"14","author":"Cortes","year":"2021","journal-title":"Plant Genome"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3542","DOI":"10.1016\/j.cell.2021.04.046","article-title":"Pan-Genome Analysis of 33 Genetically Diverse Rice Accessions Reveals Hidden Genomic Variations","volume":"184","author":"Qin","year":"2021","journal-title":"Cell"},{"key":"ref_41","first-page":"123","article-title":"The Research Progress on Crop Genomics and Genome-Wide Association Studies: A Review","volume":"5","author":"Xue","year":"2025","journal-title":"Adv. Resour. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1038\/ng.3596","article-title":"Genome-Wide Association Study Using Whole-Genome Sequencing Rapidly Identifies New Genes Influencing Agronomic Traits in Rice","volume":"48","author":"Yano","year":"2016","journal-title":"Nat. Genet."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/hdy.2015.113","article-title":"Genome-Wide Prediction Models That Incorporate De Novo Gwas Are a Powerful New Tool for Tropical Rice Improvement","volume":"116","author":"Spindel","year":"2016","journal-title":"Heredity"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"153352","DOI":"10.1016\/j.jplph.2020.153352","article-title":"Integrating Multi-Omics Data for Crop Improvement","volume":"257","author":"Scossa","year":"2021","journal-title":"J. Plant Physiol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e70135","DOI":"10.1111\/jac.70135","article-title":"Harnessing Omics Technologies to Mitigate Drought Stress in Crop Plants","volume":"212","author":"Rautela","year":"2026","journal-title":"J. Agron. Crop Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"8622","DOI":"10.1038\/s41467-025-63642-5","article-title":"Integrative Omics of the Genetic Basis for Wheat Wue and Drought Resilience Reveal the Function of Tamyb7-A1","volume":"16","author":"Zhou","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1038\/s41586-024-08187-1","article-title":"Structural Variation in the Pangenome of Wild and Domesticated Barley","volume":"636","author":"Jayakodi","year":"2024","journal-title":"Nature"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2831","DOI":"10.1038\/s41588-025-02378-w","article-title":"A Pangenome of Maize Provides Genetic Insights into Drought Resistance","volume":"57","author":"Yang","year":"2025","journal-title":"Nat. Genet."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3171","DOI":"10.1038\/s41467-025-58081-1","article-title":"Gwas Meta-Analysis Using a Graph-Based Pan-Genome Enhanced Gene Mining Efficiency for Agronomic Traits in Rice","volume":"16","author":"Yang","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Sahito, J.H., Zhang, H., Ghulam Nabi Gishkori, Z., Ma, C., Wang, Z., Ding, D., Zhang, X., and Tang, J. (2024). Advancements and Prospects of Genome-Wide Association Studies (Gwas) in Maize. Int. J. Mol. Sci., 25.","DOI":"10.3390\/ijms25031918"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1007\/978-3-031-28146-4_15","article-title":"Genome-Wide Association Study: A Powerful Approach to Map Qtls in Crop Plants","volume":"Volume 1","author":"Desaint","year":"2023","journal-title":"Advanced Crop Improvement"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Mu\u00f1oz-Amatria\u00edn, M., Cuesta-Marcos, A., Endelman, J.B., Comadran, J., Bonman, J.M., Bockelman, H.E., Chao, S., Russell, J., Waugh, R., and Hayes, P.M. (2014). The Usda Barley Core Collection: Genetic Diversity, Population Structure, and Potential for Genome-Wide Association Studies. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0094688"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Pasam, R.K., Sharma, R., Malosetti, M., van Eeuwijk, F.A., Haseneyer, G., Kilian, B., and Graner, A. (2012). Genome-Wide Association Studies for Agronomical Traits in a World Wide Spring Barley Collection. BMC Plant Biol., 12.","DOI":"10.1186\/1471-2229-12-16"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1038\/s41437-020-0336-6","article-title":"Multi-Parent Populations in Crops: A Toolbox Integrating Genomics and Genetic Mapping with Breeding","volume":"125","author":"Scott","year":"2020","journal-title":"Heredity"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.jare.2019.10.013","article-title":"Gwas: Fast-Forwarding Gene Identification and Characterization in Temperate Cereals: Lessons from Barley\u2013a Review","volume":"22","author":"Alqudah","year":"2020","journal-title":"J. Adv. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2083","DOI":"10.1105\/tpc.19.00951","article-title":"Ten Years of the Maize Nested Association Mapping Population: Impact, Limitations, and Future Directions","volume":"32","author":"Gage","year":"2020","journal-title":"Plant Cell"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1038\/ng.1018","article-title":"Genome-Wide Association Study of Flowering Time and Grain Yield Traits in a Worldwide Collection of Rice Germplasm","volume":"44","author":"Huang","year":"2012","journal-title":"Nat. Genet."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Panagea, I.S., Dangol, A., Olijslagers, M., Diels, J., and Wyseure, G. (2025). A Database Schema for Standardized Data and Metadata Collection in Agricultural Experiments. Land, 14.","DOI":"10.3390\/land14091816"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s10681-007-9449-8","article-title":"Blup for Phenotypic Selection in Plant Breeding and Variety Testing","volume":"161","author":"Piepho","year":"2008","journal-title":"Euphytica"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1111\/j.0006-341X.2001.01138.x","article-title":"Analyzing Variety by Environment Data Using Multiplicative Mixed Models and Adjustments for Spatial Field Trend","volume":"57","author":"Smith","year":"2001","journal-title":"Biometrics"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"e20120","DOI":"10.1002\/ael2.20120","article-title":"The Landscape Data Commons: A System for Standardizing, Accessing, and Applying Large Environmental Datasets for Agroecosystem Research and Management","volume":"8","author":"McCord","year":"2023","journal-title":"Agric. Environ. Lett."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1007\/s00122-016-2691-5","article-title":"Envirotyping for Deciphering Environmental Impacts on Crop Plants","volume":"129","author":"Xu","year":"2016","journal-title":"Theor. Appl. Genet."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Keeble-Gagn\u00e8re, G., Pasam, R., Forrest, K.L., Wong, D., Robinson, H., Godoy, J., Rattey, A., Moody, D., Mullan, D., and Walmsley, T. (2021). Novel Design of Imputation-Enabled Snp Arrays for Breeding and Research Applications Supporting Multi-Species Hybridization. Front. Plant Sci., 12.","DOI":"10.3389\/fpls.2021.756877"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Elshire, R.J., Glaubitz, J.C., Sun, Q., Poland, J.A., Kawamoto, K., Buckler, E.S., and Mitchell, S.E. (2011). A Robust, Simple Genotyping-by-Sequencing (Gbs) Approach for High Diversity Species. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0019379"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Glaubitz, J.C., Casstevens, T.M., Lu, F., Harriman, J., Elshire, R.J., Sun, Q., and Buckler, E.S. (2014). Tassel-Gbs: A High Capacity Genotyping by Sequencing Analysis Pipeline. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0090346"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"gix134","DOI":"10.1093\/gigascience\/gix134","article-title":"Construction of the Third-Generation Zea Mays Haplotype Map","volume":"7","author":"Bukowski","year":"2018","journal-title":"GigaScience"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"lantgenome2014.05.0023","DOI":"10.3835\/plantgenome2014.05.0023","article-title":"Novel Methods to Optimize Genotypic Imputation for Low-Coverage, Next-Generation Sequence Data in Crop Plants","volume":"7","author":"Swarts","year":"2014","journal-title":"Plant Genome"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1711","DOI":"10.1038\/s41588-026-02641-8","article-title":"A K-Mer-Based Genome-Wide Association Study Approach Empowering Gene Mining in Polyploids","volume":"58","author":"Chen","year":"2026","journal-title":"Nat. Genet."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Karikari, B., Lemay, M.-A., and Belzile, F. (2023). K-Mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives. Genes, 14.","DOI":"10.3390\/genes14071439"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1186\/gb-2011-12-10-232","article-title":"Genome-Wide Association Studies in Plants: The Missing Heritability Is in the Field","volume":"12","author":"Brachi","year":"2011","journal-title":"Genome Biol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1038\/ng.546","article-title":"Mixed Linear Model Approach Adapted for Genome-Wide Association Studies","volume":"42","author":"Zhang","year":"2010","journal-title":"Nat. Genet."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Hayes, B. (2013). Overview of Statistical Methods for Genome-Wide Association Studies (GWAS). Genome-Wide Association Studies and Genomic Prediction, Springer.","DOI":"10.1007\/978-1-62703-447-0_6"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"19444","DOI":"10.1038\/srep19444","article-title":"Improving Power and Accuracy of Genome-Wide Association Studies Via a Multi-Locus Mixed Linear Model Methodology","volume":"6","author":"Wang","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Zhou, X., Carbonetto, P., and Stephens, M. (2013). Polygenic Modeling with Bayesian Sparse Linear Mixed Models. PLoS Genet., 9.","DOI":"10.1371\/journal.pgen.1003264"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Sandhu, K.S., Burke, A.B., Merrick, L.F., Pumphrey, M.O., and Carter, A.H. (2024). Comparing Performances of Different Statistical Models and Multiple Threshold Methods in a Nested Association Mapping Population of Wheat. Front. Plant Sci., 15.","DOI":"10.3389\/fpls.2024.1460353"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1066","DOI":"10.1038\/ng.2376","article-title":"A Mixed-Model Approach for Genome-Wide Association Studies of Correlated Traits in Structured Populations","volume":"44","author":"Korte","year":"2012","journal-title":"Nat. Genet."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"lantgenome2016.07.0064","DOI":"10.3835\/plantgenome2016.07.0064","article-title":"A Comprehensive Image-Based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa)","volume":"10","author":"Campbell","year":"2017","journal-title":"Plant Genome"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"101230","DOI":"10.1016\/j.xplc.2024.101230","article-title":"The Developments and Prospects of Plant Super-Pangenomes: Demands, Approaches, and Applications","volume":"6","author":"He","year":"2025","journal-title":"Plant Commun."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.molp.2018.12.016","article-title":"Exploring and Exploiting Pan-Genomics for Crop Improvement","volume":"12","author":"Tao","year":"2019","journal-title":"Mol. Plant"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1038\/s41588-020-0612-7","article-title":"Identifying Genetic Variants Underlying Phenotypic Variation in Plants without Complete Genomes","volume":"52","author":"Voichek","year":"2020","journal-title":"Nat. Genet."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1038\/s41588-024-02029-6","article-title":"Pangenome Graphs and Their Applications in Biodiversity Genomics","volume":"57","author":"Secomandi","year":"2025","journal-title":"Nat. Genet."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.1038\/s41588-026-02678-9","article-title":"A Pangenome of Tetraploid Wheat Reveals the Genetic Architecture Underlying Domestication and Genomic Diversity for Breeding","volume":"58","author":"Bian","year":"2026","journal-title":"Nat. Genet."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1146\/annurev-arplant-090823-015358","article-title":"What Are We Learning from Plant Pangenomes?","volume":"76","author":"Jayakodi","year":"2025","journal-title":"Annu. Rev. Plant Biol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"7634","DOI":"10.1038\/s41467-025-62887-4","article-title":"Pangenome Analysis of Transposable Element Insertion Polymorphisms Reveals Features Underlying Cold Tolerance in Rice","volume":"16","author":"Qian","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"N\u2019Diaye, A., Walkowiak, S., and Pozniak, C. (2023). Wheat Sequencing: The Pan-Genome and Opportunities for Accelerating Breeding. The Wheat Genome, Springer.","DOI":"10.1007\/978-3-031-38294-9_14"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1038\/s41586-020-2961-x","article-title":"Multiple Wheat Genomes Reveal Global Variation in Modern Breeding","volume":"588","author":"Walkowiak","year":"2020","journal-title":"Nature"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s13059-020-02224-8","article-title":"How the Pan-Genome Is Changing Crop Genomics and Improvement","volume":"22","author":"Qiu","year":"2021","journal-title":"Genome Biol."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1126\/science.abg5289","article-title":"De Novo Assembly, Annotation, and Comparative Analysis of 26 Diverse Maize Genomes","volume":"373","author":"Hufford","year":"2021","journal-title":"Science"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1038\/s41586-025-08883-6","article-title":"A Pangenome Reference of Wild and Cultivated Rice","volume":"642","author":"Guo","year":"2025","journal-title":"Nature"},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Tsakirpaloglou, N., Septiningsih, E.M., and Thomson, M.J. (2023). Guidelines for Performing Crispr\/Cas9 Genome Editing for Gene Validation and Trait Improvement in Crops. Plants, 12.","DOI":"10.3390\/plants12203564"},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Thomson, M.J., Biswas, S., Tsakirpaloglou, N., and Septiningsih, E.M. (2022). Functional Allele Validation by Gene Editing to Leverage the Wealth of Genetic Resources for Crop Improvement. Int. J. Mol. Sci., 23.","DOI":"10.3390\/ijms23126565"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s41065-023-00304-w","article-title":"A Guide to Barley Mutants","volume":"161","author":"Hansson","year":"2024","journal-title":"Hereditas"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1007\/s10930-020-09913-0","article-title":"Heterologous Expression of the Barley (Hordeum Vulgare L.) Xantha-F,-G and-H Genes That Encode Magnesium Chelatase Subunits","volume":"39","author":"Mahdi","year":"2020","journal-title":"Protein J."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1186\/s41065-026-00693-8","article-title":"Targeted Knockout of Barley Ycf54 Demonstrates Its Essential Function in the Mg-Protoporphyrin Ix Monomethyl Ester Cyclase Involved in Chlorophyll Biosynthesis","volume":"163","author":"Youssef","year":"2026","journal-title":"Hereditas"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"1717","DOI":"10.1007\/s00122-022-04065-4","article-title":"Gwas and Transcriptome Analysis Reveal Mads26 Involved in Seed Germination Ability in Maize","volume":"135","author":"Ma","year":"2022","journal-title":"Theor. Appl. Genet."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Fan, B.-L., Chen, L.-H., Chen, L.-L., and Guo, H. (2025). Integrative Multi-Omics Approaches for Identifying and Characterizing Biological Elements in Crop Traits: Current Progress and Future Prospects. Int. J. Mol. Sci., 26.","DOI":"10.3390\/ijms26041466"},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Milek, J.J., Michel, S., Buchelt, A., Holzinger, A., and Molin, E.M. (2026). Applying Traditional and Machine Learning-Based Gwas Approaches for Marker-Trait Identification in Wheat. Front. Plant Sci., 16.","DOI":"10.3389\/fpls.2025.1734247"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1146\/annurev.arplant.043008.092114","article-title":"Quantitative Genomics: Analyzing Intraspecific Variation Using Global Gene Expression Polymorphisms or Eqtls","volume":"60","author":"Kliebenstein","year":"2009","journal-title":"Annu. Rev. Plant Biol."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"7501","DOI":"10.1038\/s41467-023-43077-6","article-title":"Transcriptome-Wide Association Analyses Reveal the Impact of Regulatory Variants on Rice Panicle Architecture and Causal Gene Regulatory Networks","volume":"14","author":"Ming","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1186\/s12284-023-00672-x","article-title":"Genome-and Transcriptome-Wide Association Studies to Discover Candidate Genes for Diverse Root Phenotypes in Cultivated Rice","volume":"16","author":"Wei","year":"2023","journal-title":"Rice"},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1105\/tpc.113.119982","article-title":"Insights into the Maize Pan-Genome and Pan-Transcriptome","volume":"26","author":"Hirsch","year":"2014","journal-title":"Plant Cell"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.cell.2020.05.021","article-title":"Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato","volume":"182","author":"Alonge","year":"2020","journal-title":"Cell"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1186\/s13059-021-02377-0","article-title":"Using High-Throughput Multiple Optical Phenotyping to Decipher the Genetic Architecture of Maize Drought Tolerance","volume":"22","author":"Wu","year":"2021","journal-title":"Genome Biol."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Phua, D.Y.Z., Li, X., and Nolan, T.M. (2026). Single-Cell and Spatial Transcriptomics in Plants: From Cell States to Inter-Tissue Coordination. J. Exp. Bot., erag241.","DOI":"10.1093\/jxb\/erag241"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"101300","DOI":"10.1016\/j.stress.2026.101300","article-title":"Decoding Spatial Heterogeneity in Plants: Advances and Challenges in Spatial Transcriptomics for Stress Responses and Crop Resilience","volume":"20","author":"Shao","year":"2026","journal-title":"Plant Stress"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"2605","DOI":"10.1093\/jxb\/erz116","article-title":"Breeding Drought-Resistant Crops: G\u00d7E Interactions, Proteomics and Pqtls","volume":"70","year":"2019","journal-title":"J. Exp. Bot."},{"key":"ref_107","doi-asserted-by":"crossref","unstructured":"Sharma, V., Gupta, P., Priscilla, K., Kumar, S., Hangargi, B., Veershetty, A., Pandurang Ramrao, D., Suresh, S., Narasanna, R., and Naik, G.R. (2021). Metabolomics Intervention Towards Better Understanding of Plant Traits. Cells, 10.","DOI":"10.3390\/cells10020346"},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Amin, A., Zaman, W., and Park, S. (2025). Harnessing Multi-Omics and Predictive Modeling for Climate-Resilient Crop Breeding: From Genomes to Fields. Genes, 16.","DOI":"10.3390\/genes16070809"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1111\/pbi.13634","article-title":"Mining Novel Kernel Size-Related Genes by Pqtl Mapping and Multi-Omics Integrative Analysis in Developing Maize Kernels","volume":"19","author":"Zhou","year":"2021","journal-title":"Plant Biotechnol. J."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1038\/s41576-026-00968-w","article-title":"Translating Functional Molecular Knowledge into Crop-Breeding Success","volume":"27","author":"Ramstein","year":"2026","journal-title":"Nat. Rev. Genet."},{"key":"ref_111","doi-asserted-by":"crossref","unstructured":"Houston, K., Russell, J., Schreiber, M., Halpin, C., Oakey, H., Washington, J.M., Booth, A., Shirley, N., Burton, R.A., and Fincher, G.B. (2014). A Genome Wide Association Scan for (1,3;1,4)-\u03b2-Glucan Content in the Grain of Contemporary 2-Row Spring and Winter Barleys. BMC Genom., 15.","DOI":"10.1186\/1471-2164-15-907"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1534\/g3.113.006148","article-title":"Genome-Wide Association Study and Pathway-Level Analysis of Tocochromanol Levels in Maize Grain","volume":"3","author":"Lipka","year":"2013","journal-title":"G3 Genes Genomes Genet."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1038\/ng.1033","article-title":"Genomic and Metabolic Prediction of Complex Heterotic Traits in Hybrid Maize","volume":"44","author":"Riedelsheimer","year":"2012","journal-title":"Nat. Genet."},{"key":"ref_114","doi-asserted-by":"crossref","unstructured":"Kaur, B., Sandhu, K.S., Kamal, R., Kaur, K., Singh, J., R\u00f6der, M.S., and Muqaddasi, Q.H. (2021). Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects. Plants, 10.","DOI":"10.20944\/preprints202104.0531.v1"},{"key":"ref_115","doi-asserted-by":"crossref","unstructured":"Ramakrishnan, M., Zhang, Z., Mullasseri, S., Kalendar, R., Ahmad, Z., Sharma, A., Liu, G., Zhou, M., and Wei, Q. (2022). Epigenetic Stress Memory: A New Approach to Study Cold and Heat Stress Responses in Plants. Front. Plant Sci., 13.","DOI":"10.3389\/fpls.2022.1075279"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"3041","DOI":"10.1016\/j.cell.2021.04.014","article-title":"A Cis-Regulatory Atlas in Maize at Single-Cell Resolution","volume":"184","author":"Marand","year":"2021","journal-title":"Cell"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"2720","DOI":"10.1105\/tpc.18.00375","article-title":"Genome-Wide Association Studies Reveal the Genetic Basis of Ionomic Variation in Rice","volume":"30","author":"Yang","year":"2018","journal-title":"Plant Cell"},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"3438","DOI":"10.1038\/ncomms4438","article-title":"Metabolome-Based Genome-Wide Association Study of Maize Kernel Leads to Novel Biochemical Insights","volume":"5","author":"Wen","year":"2014","journal-title":"Nat. Commun."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"101668","DOI":"10.1016\/j.xplc.2025.101668","article-title":"Decoding Plant Physiology through Systems Biology: Integrative Multi-Omics and Computational Perspectives for Next-Generation Crop Design","volume":"7","author":"Kundu","year":"2026","journal-title":"Plant Commun."},{"key":"ref_120","doi-asserted-by":"crossref","unstructured":"Mahmood, U., Li, X., Fan, Y., Chang, W., Niu, Y., Li, J., Qu, C., and Lu, K. (2022). Multi-Omics Revolution to Promote Plant Breeding Efficiency. Front. Plant Sci., 13.","DOI":"10.3389\/fpls.2022.1062952"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"4427","DOI":"10.1038\/s41467-026-71035-5","article-title":"Leveraging Weighted Embedding and Transformer Architecture to Improve Phenotype Prediction of Complex Traits for Crops","volume":"17","author":"Li","year":"2026","journal-title":"Nat. Commun."},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Wang, T., Tong, R., Yuan, Z., and Li, Y. (2026). Beyond Qtl and Gwas: How Deep Learning, Graph Models, and Multi-Omics Are Reshaping Plant Genomic Prediction Analysis. Front. Genet., 17.","DOI":"10.3389\/fgene.2026.1783939"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1007\/s11032-024-01454-z","article-title":"Multi-Omics Assists Genomic Prediction of Maize Yield with Machine Learning Approaches","volume":"44","author":"Wu","year":"2024","journal-title":"Mol. Breed."},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Mora-Poblete, F., Maldonado, C., Henrique, L., Uhdre, R., Scapim, C.A., and Mangolim, C.A. (2023). Multi-Trait and Multi-Environment Genomic Prediction for Flowering Traits in Maize: A Deep Learning Approach. Front. Plant Sci., 14.","DOI":"10.3389\/fpls.2023.1153040"},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.tplants.2022.09.008","article-title":"Charting Plant Gene Functions in the Multi-Omics and Single-Cell Era","volume":"28","author":"Depuydt","year":"2023","journal-title":"Trends Plant Sci."},{"key":"ref_126","doi-asserted-by":"crossref","unstructured":"Diakite, S., Norman, P.E., Kamara, L., Pehlivan, N., and Zargar, M. (2026). Genetic Enhancement of Root, Tuber and Cereal Crops Via Pangenomics, Multi-Omics Integration and Ai-Driven Prediction. Front. Plant Sci., 17.","DOI":"10.3389\/fpls.2026.1793924"},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"276","DOI":"10.3390\/crops3040025","article-title":"Speed Breeding for Crop Improvement and Food Security","volume":"3","author":"Potts","year":"2023","journal-title":"Crops"},{"key":"ref_128","doi-asserted-by":"crossref","unstructured":"Sayed, M.A., Allam, M., Kalby Heck, Q., Urbanavi\u010di\u016bt\u0117, I., Rutten, T., Stuart, D., Zakhrabekova, S., B\u00f6rner, A., Pillen, K., and Hansson, M. (2021). Analyses of Mads-Box Genes Suggest Hvmads56 to Regulate Lateral Spikelet Development in Barley. Plants, 10.","DOI":"10.3390\/plants10122825"},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"100549","DOI":"10.1016\/j.xplc.2023.100549","article-title":"Fast Integration and Accumulation of Beneficial Breeding Alleles through an Ab\u2013Namic Strategy in Wheat","volume":"4","author":"Jiao","year":"2023","journal-title":"Plant Commun."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"1266","DOI":"10.1038\/s42003-021-02782-y","article-title":"Features and Applications of Haplotypes in Crop Breeding","volume":"4","author":"Bhat","year":"2021","journal-title":"Commun. Biol."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"bbaf355","DOI":"10.1093\/bib\/bbaf355","article-title":"A Technical Review of Multi-Omics Data Integration Methods: From Classical Statistical to Deep Generative Approaches","volume":"26","author":"Cai","year":"2025","journal-title":"Brief. Bioinform."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1016\/j.tplants.2024.12.009","article-title":"Expanding Genomic Prediction in Plant Breeding: Harnessing Big Data, Machine Learning, and Advanced Software","volume":"30","author":"Crossa","year":"2025","journal-title":"Trends Plant Sci."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2135\/cropsci2008.08.0512","article-title":"Genomic Selection for Crop Improvement","volume":"49","author":"Heffner","year":"2009","journal-title":"Crop Sci."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"68","DOI":"10.2135\/cropsci2013.05.0315","article-title":"Genomewide Selection When Major Genes Are Known","volume":"54","author":"Bernardo","year":"2014","journal-title":"Crop Sci."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"1530","DOI":"10.1038\/s41588-019-0496-6","article-title":"Improving Grain Yield, Stress Resilience and Quality of Bread Wheat Using Large-Scale Genomics","volume":"51","author":"Juliana","year":"2019","journal-title":"Nat. Genet."},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1534\/genetics.112.144246","article-title":"Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy","volume":"192","author":"Jia","year":"2012","journal-title":"Genetics"},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"1062","DOI":"10.1038\/s41598-024-51792-3","article-title":"Genomic Prediction in Multi-Environment Trials in Maize Using Statistical and Machine Learning Methods","volume":"14","author":"Barreto","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Guo, J., Khan, J., Pradhan, S., Shahi, D., Khan, N., Avci, M., Mcbreen, J., Harrison, S., Brown-Guedira, G., and Murphy, J.P. (2020). Multi-Trait Genomic Prediction of Yield-Related Traits in Us Soft Wheat under Variable Water Regimes. Genes, 11.","DOI":"10.3390\/genes11111270"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1111\/jipb.13425","article-title":"Plant Base Editing and Prime Editing: The Current Status and Future Perspectives","volume":"65","author":"Li","year":"2023","journal-title":"J. Integr. Plant Biol."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"e13969","DOI":"10.1111\/ppl.13969","article-title":"Recent Advances in Artificial Intelligence, Mechanistic Models, and Speed Breeding Offer Exciting Opportunities for Precise and Accelerated Genomics-Assisted Breeding","volume":"175","author":"Bhat","year":"2023","journal-title":"Physiol. Plant."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.tibtech.2021.08.009","article-title":"Reap the Crop Wild Relatives for Breeding Future Crops","volume":"40","author":"Bohra","year":"2022","journal-title":"Trends Biotechnol."},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1038\/s41586-024-07713-5","article-title":"Promises and Challenges of Crop Translational Genomics","volume":"636","author":"Mascher","year":"2024","journal-title":"Nature"},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1270\/jsbbs.23046","article-title":"Global Regulatory Trends of Genome Editing Technology in Agriculture and Food","volume":"74","author":"Tachikawa","year":"2024","journal-title":"Breed. Sci."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1038\/ng.3518","article-title":"Osspl13 Controls Grain Size in Cultivated Rice","volume":"48","author":"Si","year":"2016","journal-title":"Nat. Genet."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"5665","DOI":"10.1038\/s41467-022-33318-5","article-title":"Genome-Wide Association Study Identifies a Gene Responsible for Temperature-Dependent Rice Germination","volume":"13","author":"Yoshida","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1038\/ng.3636","article-title":"Genetic Variation in Zmvpp1 Contributes to Drought Tolerance in Maize Seedlings","volume":"48","author":"Wang","year":"2016","journal-title":"Nat. Genet."},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"8326","DOI":"10.1038\/ncomms9326","article-title":"A Transposable Element in a Nac Gene Is Associated with Drought Tolerance in Maize Seedlings","volume":"6","author":"Mao","year":"2015","journal-title":"Nat. Commun."},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"2702","DOI":"10.1038\/s41598-019-38570-2","article-title":"Genome-Wide Association Study Revealed That the Tagw8 Gene Was Associated with Kernel Size in Chinese Bread Wheat","volume":"9","author":"Yan","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_149","doi-asserted-by":"crossref","unstructured":"Hazzouri, K.M., Khraiwesh, B., Amiri, K.M., Pauli, D., Blake, T., Shahid, M., Mullath, S.K., Nelson, D., Mansour, A.L., and Salehi-Ashtiani, K. (2018). Mapping of Hkt1; 5 Gene in Barley Using Gwas Approach and Its Implication in Salt Tolerance Mechanism. Front. Plant Sci., 9.","DOI":"10.3389\/fpls.2018.00156"},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1038\/ng.745","article-title":"Intermedium-C, a Modifier of Lateral Spikelet Fertility in Barley, Is an Ortholog of the Maize Domestication Gene Teosinte Branched 1","volume":"43","author":"Ramsay","year":"2011","journal-title":"Nat. Genet."},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/s13353-025-01034-7","article-title":"Accelerating Genetic Gain through Integrated Genomic Selection in Crop Plants","volume":"67","author":"Edukondalu","year":"2026","journal-title":"J. Appl. Genet."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1038\/s41559-018-0793-y","article-title":"The Global Burden of Pathogens and Pests on Major Food Crops","volume":"3","author":"Savary","year":"2019","journal-title":"Nat. Ecol. Evol."},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"3885","DOI":"10.1007\/s11033-023-08309-4","article-title":"Recent Advances on Genome-Wide Association Studies (Gwas) and Genomic Selection (Gs); Prospects for Fusarium Head Blight Research in Durum Wheat","volume":"50","author":"Mir","year":"2023","journal-title":"Mol. Biol. Rep."},{"key":"ref_154","doi-asserted-by":"crossref","unstructured":"Fan, Y., Ma, L., Pan, X., Tian, P., Wang, W., Liu, K., Xiong, Z., Li, C., Wang, Z., and Wang, J. (2024). Genome-Wide Association Study Identifies Rice Panicle Blast-Resistant Gene Pb4 Encoding a Wall-Associated Kinase. Int. J. Mol. Sci., 25.","DOI":"10.3390\/ijms25020830"},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"1540","DOI":"10.1038\/s41588-019-0503-y","article-title":"Natural Variation in Zm Fbl41 Confers Banded Leaf and Sheath Blight Resistance in Maize","volume":"51","author":"Li","year":"2019","journal-title":"Nat. Genet."},{"key":"ref_156","doi-asserted-by":"crossref","first-page":"1995","DOI":"10.1007\/s42976-026-00824-x","article-title":"Multi-Omics and Precision Breeding Strategies for Enhancing Biotic and Abiotic Stress Resilience in Rice","volume":"54","author":"Jamali","year":"2026","journal-title":"Cereal Res. Commun."},{"key":"ref_157","doi-asserted-by":"crossref","unstructured":"Alemu, A., Brazauskas, G., Gaikpa, D.S., Henriksson, T., Islamov, B., Nistrup J\u00f8rgensen, L., Koppel, M., Koppel, R., Liatukas, \u017d., and Svensson, J.T. (2021). Genome-Wide Association Analysis and Genomic Prediction for Adult-Plant Resistance to Septoria Tritici Blotch and Powdery Mildew in Winter Wheat. Front. Genet., 12.","DOI":"10.3389\/fgene.2021.661742"},{"key":"ref_158","doi-asserted-by":"crossref","unstructured":"Oyebamiji, O.Y., Adigun, B.A., Shamsudin, N.A.A., Ikmal, A.M., Salisu, M.A., Malike, F.A., and Lateef, A.A. (2024). Recent Advancements in Mitigating Abiotic Stresses in Crops. Horticulturae, 10.","DOI":"10.3390\/horticulturae10020156"},{"key":"ref_159","doi-asserted-by":"crossref","unstructured":"Dwivedi, S.L., Scheben, A., Edwards, D., Spillane, C., and Ortiz, R. (2017). Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes. Front. Plant Sci., 8.","DOI":"10.3389\/fpls.2017.01461"},{"key":"ref_160","doi-asserted-by":"crossref","unstructured":"Rai, K.K. (2025). Machine Learning-Driven Precision Plant Breeding. Machine Learning for Plant Biology, John Wiley & Sons.","DOI":"10.1002\/9781394329649.ch13"},{"key":"ref_161","first-page":"1","article-title":"Biochemical and Physiological Response of Egyptian Wheat Genotypes to Drought Stress","volume":"66","author":"Hanafy","year":"2023","journal-title":"Egypt. J. Chem."},{"key":"ref_162","doi-asserted-by":"crossref","first-page":"6265","DOI":"10.1093\/jxb\/eru363","article-title":"Breeding High-Yielding Drought-Tolerant Rice: Genetic Variations and Conventional and Molecular Approaches","volume":"65","author":"Kumar","year":"2014","journal-title":"J. Exp. Bot."},{"key":"ref_163","doi-asserted-by":"crossref","first-page":"10085","DOI":"10.1038\/s41598-025-94175-y","article-title":"Gwas Identifies Novel Loci Linked to Seedling Growth Traits in Highly Diverse Barley Population under Drought Stress","volume":"15","author":"Badr","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_164","doi-asserted-by":"crossref","first-page":"6563","DOI":"10.1038\/s41467-025-61943-3","article-title":"An Elite Allele Tadt1-a Hapi Enhances Drought Tolerance Via Mediating Autophagic Pathways in Wheat","volume":"16","author":"Liu","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_165","doi-asserted-by":"crossref","unstructured":"Sayed, M.A., Maurer, A., Schmutzer, T., Schnurbusch, T., B\u00f6rner, A., Hansson, M., Pillen, K., and Youssef, H.M. (2022). Genome-Wide Association Study of Salt Tolerance-Related Traits during Germination and Seedling Development in an Intermedium-Spike Barley Collection. Int. J. Mol. Sci., 23.","DOI":"10.3390\/ijms231911060"},{"key":"ref_166","doi-asserted-by":"crossref","unstructured":"Helmi, R.Y., Sayed, M.A., Abdelhadi, A.A., Maurer, A., B\u00f6rner, A., Elarabi, N.I., Halema, A.A., Schierenbeck, M., Sakr, M.M., and Pillen, K. (2026). Decoding the Genetic Basis of Salinity Tolerance at Germination and Seedling Traits in Heb-25 Barley Nam Population. Plants, 15.","DOI":"10.3390\/plants15121886"},{"key":"ref_167","doi-asserted-by":"crossref","unstructured":"Thingujam, D., Gouli, S., Cooray, S.P., Chandran, K.B., Givens, S.B., Gandhimeyyan, R.V., Tan, Z., Wang, Y., Patam, K., and Greer, S.A. (2025). Climate-Resilient Crops: Integrating Ai, Multi-Omics, and Advanced Phenotyping to Address Global Agricultural and Societal Challenges. Plants, 14.","DOI":"10.20944\/preprints202506.2364.v1"},{"key":"ref_168","doi-asserted-by":"crossref","unstructured":"Chachar, Z., Fan, L., Chachar, S., Ahmed, N., Narejo, M.-U.-N., Ahmed, N., Lai, R., and Qi, Y. (2024). Genetic and Genomic Pathways to Improved Wheat (Triticum aestivum L.) Yields: A Review. Agronomy, 14.","DOI":"10.3390\/agronomy14061201"},{"key":"ref_169","doi-asserted-by":"crossref","first-page":"2743","DOI":"10.1093\/jxb\/eraf478","article-title":"Genetic Modulation of Yield and Phenotypic Plasticity of Yield in Winter Wheat","volume":"77","author":"Giordano","year":"2026","journal-title":"J. Exp. Bot."},{"key":"ref_170","doi-asserted-by":"crossref","unstructured":"Gasparis, S., and Mi\u0142oszewski, M.M. (2023). Genetic Basis of Grain Size and Weight in Rice, Wheat, and Barley. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms242316921"},{"key":"ref_171","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1038\/ng.746","article-title":"Genome-Wide Association Study of Leaf Architecture in the Maize Nested Association Mapping Population","volume":"43","author":"Tian","year":"2011","journal-title":"Nat. Genet."},{"key":"ref_172","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1111\/jipb.13633","article-title":"Orchestrating Seed Storage Protein and Starch Accumulation toward Overcoming Yield\u2013Quality Trade-Off in Cereal Crops","volume":"66","author":"Cao","year":"2024","journal-title":"J. Integr. Plant Biol."},{"key":"ref_173","doi-asserted-by":"crossref","unstructured":"Tadesse, W., Amri, A., Ogbonnaya, F.C., Sanchez-Garcia, M., Sohail, Q., and Baum, M. (2016). Wheat. Genetic and Genomic Resources for Grain Cereals Improvement, Elsevier.","DOI":"10.1016\/B978-0-12-802000-5.00002-2"},{"key":"ref_174","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1038\/ng.2484","article-title":"Genome-Wide Association Study Dissects the Genetic Architecture of Oil Biosynthesis in Maize Kernels","volume":"45","author":"Li","year":"2013","journal-title":"Nat. Genet."},{"key":"ref_175","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1002\/ppp3.10120","article-title":"Genome-Wide Association Mapping and Comparative Genomics Identifies Genomic Regions Governing Grain Nutritional Traits in Finger Millet (Eleusine coracana L. Gaertn.)","volume":"2","author":"Puranik","year":"2020","journal-title":"Plants People Planet"},{"key":"ref_176","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Wang, R., Tu, K., Hong, Y., Wang, F., Zhu, J., Lv, C., Xu, R., and Guo, B. (2025). Gwas Reveals Stable Genetic Loci and Candidate Genes for Grain Protein Content in Wheat. Curr. Issues Mol. Biol., 47.","DOI":"10.3390\/cimb47120981"},{"key":"ref_177","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1186\/s13059-023-03137-y","article-title":"Metabolic Gwas-Based Dissection of Genetic Basis Underlying Nutrient Quality Variation and Domestication of Cassava Storage Root","volume":"24","author":"Ding","year":"2023","journal-title":"Genome Biol."},{"key":"ref_178","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1023\/A:1020668100330","article-title":"Breeding Crops for Enhanced Micronutrient Content","volume":"245","author":"Welch","year":"2002","journal-title":"Plant Soil"},{"key":"ref_179","doi-asserted-by":"crossref","unstructured":"Gaikwad, K.B., Rani, S., Kumar, M., Gupta, V., Babu, P.H., Bainsla, N.K., and Yadav, R. (2020). Enhancing the Nutritional Quality of Major Food Crops through Conventional and Genomics-Assisted Breeding. Front. Nutr., 7.","DOI":"10.3389\/fnut.2020.533453"},{"key":"ref_180","doi-asserted-by":"crossref","first-page":"7037","DOI":"10.1038\/s41598-022-10618-w","article-title":"Genome-Wide Association Study Identifies Loci and Candidate Genes for Grain Micronutrients and Quality Traits in Wheat (Triticum aestivum L.)","volume":"12","author":"Rathan","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_181","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1104\/pp.108.131888","article-title":"Epistatic Interactions between Opaque2 Transcriptional Activator and Its Target Gene Cyppdk1 Control Kernel Trait Variation in Maize","volume":"150","author":"Manicacci","year":"2009","journal-title":"Plant Physiol."},{"key":"ref_182","doi-asserted-by":"crossref","first-page":"1298","DOI":"10.1126\/science.1133649","article-title":"A Nac Gene Regulating Senescence Improves Grain Protein, Zinc, and Iron Content in Wheat","volume":"314","author":"Uauy","year":"2006","journal-title":"Science"},{"key":"ref_183","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s11032-022-01277-w","article-title":"Pyramiding of Genes for Grain Protein Content, Grain Quality, and Rust Resistance in Eleven Indian Bread Wheat Cultivars: A Multi-Institutional Effort","volume":"42","author":"Gupta","year":"2022","journal-title":"Mol. Breed."},{"key":"ref_184","doi-asserted-by":"crossref","unstructured":"Bollinedi, H., Yadav, A.K., Vinod, K.K., Krishnan, S.G., Bhowmick, P.K., Nagarajan, M., Neeraja, C.N., Ellur, R.K., and Singh, A.K. (2020). Genome-Wide Association Study Reveals Novel Marker-Trait Associations (Mtas) Governing the Localization of Fe and Zn in the Rice Grain. Front. Genet., 11.","DOI":"10.3389\/fgene.2020.00213"},{"key":"ref_185","doi-asserted-by":"crossref","first-page":"4847","DOI":"10.1038\/ncomms5847","article-title":"Osaap6 Functions as an Important Regulator of Grain Protein Content and Nutritional Quality in Rice","volume":"5","author":"Peng","year":"2014","journal-title":"Nat. Commun."},{"key":"ref_186","doi-asserted-by":"crossref","unstructured":"Swamy, M.B.P., Marathi, B., Ribeiro-Barros, A.I., Calayugan, M.I.C., and Ricachenevsky, F.K. (2021). Iron Biofortification in Rice: An Update on Quantitative Trait Loci and Candidate Genes. Front. Plant Sci., 12.","DOI":"10.3389\/fpls.2021.647341"},{"key":"ref_187","doi-asserted-by":"crossref","first-page":"9797","DOI":"10.1038\/s41598-021-89276-3","article-title":"Genome-Wide Association Studies of Grain Quality Traits in Maize","volume":"11","author":"Zheng","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_188","doi-asserted-by":"crossref","first-page":"1049","DOI":"10.1534\/g3.117.300511","article-title":"Genetic Loci Controlling Carotenoid Biosynthesis in Diverse Tropical Maize Lines","volume":"8","author":"Azmach","year":"2018","journal-title":"G3 Genes Genomes Genet."},{"key":"ref_189","doi-asserted-by":"crossref","unstructured":"Dinsa, F.G., Russell, J., Steffenson, B., Halpin, C., and Waugh, R. (2025). Variation at the Major Facilitator Superfamily Zifl1 Gene Influences Zinc Concentration of Barley Grain. Front. Plant Sci., 16.","DOI":"10.3389\/fpls.2025.1539029"},{"key":"ref_190","doi-asserted-by":"crossref","first-page":"14796","DOI":"10.15835\/nbha53414796","article-title":"Artificial Intelligence for Climate-Smart Agriculture: Enhancing Food Security and Plant Adaptation","volume":"53","author":"Mandour","year":"2025","journal-title":"Not. Bot. Horti Agrobot. Cluj-Napoca"},{"key":"ref_191","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1038\/ng1337","article-title":"The Effects of Human Population Structure on Large Genetic Association Studies","volume":"36","author":"Marchini","year":"2004","journal-title":"Nat. Genet."},{"key":"ref_192","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/nmeth.2848","article-title":"Efficient Multivariate Linear Mixed Model Algorithms for Genome-Wide Association Studies","volume":"11","author":"Zhou","year":"2014","journal-title":"Nat. Methods"},{"key":"ref_193","doi-asserted-by":"crossref","first-page":"5743","DOI":"10.1007\/s00018-021-03868-w","article-title":"Genome-Wide Association Studies: Assessing Trait Characteristics in Model and Crop Plants","volume":"78","author":"Alseekh","year":"2021","journal-title":"Cell. Mol. Life Sci."},{"key":"ref_194","doi-asserted-by":"crossref","unstructured":"Sul, H.J., Martin, L.S., and Eskin, E. (2018). Population Structure in Genetic Studies: Confounding Factors and Mixed Models. PLoS Genet., 14.","DOI":"10.1371\/journal.pgen.1007309"},{"key":"ref_195","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1093\/pcp\/pcae079","article-title":"Beyond the Standard Gwas\u2014A Guide for Plant Biologists","volume":"66","author":"Clauw","year":"2025","journal-title":"Plant Cell Physiol."},{"key":"ref_196","doi-asserted-by":"crossref","unstructured":"Angidi, S., Madankar, K., Tehseen, M.M., and Bhatla, A. (2025). Advanced High-Throughput Phenotyping Techniques for Managing Abiotic Stress in Agricultural Crops\u2014A Comprehensive Review. Crops, 5.","DOI":"10.3390\/crops5020008"},{"key":"ref_197","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1111\/tpj.14139","article-title":"Crop Genome-Wide Association Study: A Harvest of Biological Relevance","volume":"97","author":"Liu","year":"2019","journal-title":"Plant J."},{"key":"ref_198","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1002\/cppb.20041","article-title":"A Guide to Genome-Wide Association Mapping in Plants","volume":"2","author":"Burghardt","year":"2017","journal-title":"Curr. Protoc. Plant Biol."},{"key":"ref_199","doi-asserted-by":"crossref","first-page":"103418","DOI":"10.1016\/j.copbio.2025.103418","article-title":"Functional Cereal Pan-Genomics: Harnessing Structural and Regulatory Variation for Precision Crop Design","volume":"97","author":"Zhu","year":"2026","journal-title":"Curr. Opin. Biotechnol."},{"key":"ref_200","doi-asserted-by":"crossref","first-page":"6641","DOI":"10.1038\/s41598-025-91199-2","article-title":"Identification of Quantitative Trait Nucleotides for Grain Quality in Bread Wheat under Heat Stress","volume":"15","author":"Bashir","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_201","doi-asserted-by":"crossref","unstructured":"Morales, F., Anc\u00edn, M., Fakhet, D., Gonz\u00e1lez-Torralba, J., G\u00e1mez, A.L., Seminario, A., Soba, D., Ben Mariem, S., Garriga, M., and Aranjuelo, I. (2020). Photosynthetic Metabolism under Stressful Growth Conditions as a Bases for Crop Breeding and Yield Improvement. Plants, 9.","DOI":"10.3390\/plants9010088"},{"key":"ref_202","doi-asserted-by":"crossref","unstructured":"Molinari, C.M.D., Pagliarini, R.F., Florentino, L.H., Lima, R.N., Arraes, F.B.M., Abbad, S.V., de Farias, M.P., Mertz-Henning, L.M., Rech, E., and Nepomuceno, A.L. (2024). Navigating the Path from Lab to Market: Regulatory Challenges and Opportunities for Genome Editing Technologies for Agriculture. Plant Genome Editing Technologies: Speed Breeding, Crop Improvement and Sustainable Agriculture, Springer.","DOI":"10.1007\/978-981-99-9338-3_2"}],"container-title":["Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-7737\/15\/18\/1673\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T04:41:13Z","timestamp":1790138473000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-7737\/15\/18\/1673"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,21]]},"references-count":202,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["biology15181673"],"URL":"https:\/\/doi.org\/10.3390\/biology15181673","relation":{},"ISSN":["2079-7737"],"issn-type":[{"value":"2079-7737","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,21]]}}}