[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126450-en":3,"doc-seo-126450-105":31,"detail-sidebar-cat-0-en-105":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126450,8796095027276,"Valentina","https://avatar.qwps.com/avatar/d3BzX2FwX3Rlc3RfMjUxMTI2XzAxODA=",8,"Research & Report","INTEGRATIVE APPROACHES TO UNDERSTANDING AND IDENTIFYING LACTUCA SPECIES - PHYLOGENETICS, MORPHOLOGY, AND MACHINE LEARNING - Applications at a Genebank Level","The USDA National Plant Germplasm System (NPGS) faces a major barrier: many plant accessions remain inaccurately identified due to time and resource limits, limiting downstream research and breeding. This dissertation clarifies Lactuca taxonomy by building a robust phylogeny of 26 Lactuca species with Hyb-Seq, conducting detailed morphological examinations, and testing supervised machine learning for species identification from Hyb-Seq data. Results enable more economical, higher-throughput genebank characterization and improved understanding of species relationships within the genus.","INTEGRATIVE APPROACHES TO UNDERSTANDING AND IDENTIFYING LACTUCA SPECIES: PHYLOGENETICS, MORPHOLOGY, AND MACHINE LEARNING  \nAPPLICATIONS AT A GENEBANK LEVEL  \nALEXANDER CORNWALL  \nA dissertation submitted in partial fulfillment of  \nthe requirements for the degree of  \nDOCTOR OF PHILOSOPHY  \nWASHINGTON STATE UNIVERSITY  \nDepartment of Horticulture  \nDECEMBER 2025  \n© 2025 ALEXANDER CORNWALL  \nAll Rights Reserved  \nTo the Faculty of Washington State University:  \nThe members of the Committee appointed to examine the dissertation of ALEXANDER CORNWALL find it satisfactory and recommend that it be accepted.  \nCarol A. Miles, Ph.D., Chair  \nEric Roalson, Ph.D.  \nDeven See, Ph.D.  \nStephen Ficklin, Ph.D.  \nCameron Peace, Ph.D.  \nINTEGRATIVE APPROACHES TO UNDERSTANDING AND IDENTIFYING LACTUCA SPECIES: PHYLOGENETICS, MORPHOLOGY, AND MACHINE LEARNING  \nAPPLICATIONS AT A GENEBANK LEVEL  \nAbstract  \nAlexander Cornwall, Ph.D.  \nWashington State University  \nDecember 2025  \nChair: Carol A. Miles  \nThe USDA National Plant Germplasm System (NPGS) faces a significant challenge inaccurately identifying and characterizing its vast collection of plant germplasm, with hundreds of accessions remaining unidentified due to time and resource constraints. For example, 65 accessions of lettuce (Lactuca) lack species designations, limiting their utility for research and breeding. This study aimed to address this issue by providing increased clarity on the taxonomy of the genus Lactuca. The research utilized hybrid-exome capture sequencing (Hyb-Seq) to create a robust phylogeny of 26 Lactuca species, compiled a thorough morphological examination of these species, and explored the potential of supervised machine learning to accurately identify species using Hyb-Seq data. The first study established a robust phylogeny of 26 Lactuca species, clarified crop breeding pools and proposed the name Maculospermae for the North American and Azorean lettuce species. The second study reviewed the history of the genus and its complex morphology, presenting a consolidated monograph and a dichotomous key for  \nspecies identification. The third study tests the potential of a supervised machine learning model being utilized for high throughput species identification at a genebank level and provided a preliminary model for future work. This research offers new, more economical methods for species identification, enabling genebanks to enhance the accuracy of their characterization data for Lactuca accessions and improve the understanding of species interrelatedness within the  \ngenus.  \nACKNOWLEDGEMENT  \nThe opportunity to pursue this degree is a dream I thought I had lost forever. I’d like to acknowledge Barbara Hellier for the support she has given me over the last 15 years and for her trust in me to take over the curation of the Horticultural Crops Collection for the NPGS. She helped me navigate all the bureaucracy and paperwork to make this dream a reality while continuing to be a technician and support my family financially. I can also never express enough thanks to Carol Miles and her unflinching support of me through five long and hard years of balancing work, school, and family life. I could not have done it without her stalwart belief in me. I would also like to acknowledge my other committee members. Dr. Eric Roalson for his patience and advice as I navigated the realms of phylogenetics and systematics. Dr. Deven See and Dr. Marlowe for their time and attention to assist me with my DNA extractions and hybridizations. Dr. Stephen Ficklin for his expertise and encouragement to learn python and supervised machine learning and Dr. Cameron Peace for his support and knowledge of germplasm and genetic biodiversity.  \nI’d also like to express my gratitude to the members of the Western Regional Plant Introduction Station for funding my program and for your patience with me as I balanced the work of several people on top of school and family. Especially to Dr. Marilyn Warbu","cbCailSjled5XaVK","https://ap.wps.com/l/cbCailSjled5XaVK","pdf",3233185,5,1,164,"English","en",105,"# TABLE OF CONTENTS\n## ABSTRACT\n## ACKNOWLEDGEMENT\n## LIST OF TABLES\n## LIST OF FIGURES\n## CHAPTERS\n## CHAPTER 1: INTRODUCTION\n## CHAPTER 2: RESOLVING PHYLOGENETIC RELATIONSHIPS IN LACTUCA (ASTERACEAE) USING 1061 NGS HYB-SEQ EXOME MARKERS\n## CHAPTER 3 MORPHOLOGY AND HISTORICAL STRUCTURE OF THE GENUS LACTUCA\n## LITERATURE CITED","[{\"question\":\"What problem does the dissertation address in the USDA NPGS?\",\"answer\":\"Inaccurate identification and characterization of germplasm, with many accessions lacking species designations because time and resources are limited.\"},{\"question\":\"How does the study generate a phylogeny for Lactuca species?\",\"answer\":\"It uses hybrid-exome capture sequencing (Hyb-Seq) markers to construct a robust phylogeny covering 26 Lactuca species.\"},{\"question\":\"What role does supervised machine learning play?\",\"answer\":\"It evaluates the feasibility of using Hyb-Seq data to accurately identify Lactuca species at a high-throughput genebank level, providing a preliminary model for future work.\"}]","INTEGRATIVE APPROACHES TO UNDERSTANDING AND IDENTIFYING LACTUCA SPECIES - PHYLOGENETICS, MORPHOLOGY, AND MACHINE LEARNING - Applications at a Genebank Level | PDF",1785905119,413,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"integrative-approaches-to-understanding-and-identifying-lactuca-species-phylogenetics-morphology-and-machine-learning-applications-at-a-genebank-level","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/integrative-approaches-to-understanding-and-identifying-lactuca-species-phylogenetics-morphology-and-machine-learning-applications-at-a-genebank-level/126450/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"What problem does the dissertation address in the USDA NPGS?","Question",{"text":77,"@type":78},"Inaccurate identification and characterization of germplasm, with many accessions lacking species designations because time and resources are limited.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"How does the study generate a phylogeny for Lactuca species?",{"text":82,"@type":78},"It uses hybrid-exome capture sequencing (Hyb-Seq) markers to construct a robust phylogeny covering 26 Lactuca species.",{"name":84,"@type":75,"acceptedAnswer":85},"What role does supervised machine learning play?",{"text":86,"@type":78},"It evaluates the feasibility of using Hyb-Seq data to accurately identify Lactuca species at a high-throughput genebank level, providing a preliminary model for future work.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":20,"slug":139},19,"General","general"]