{"id":792,"date":"2026-04-23T10:32:56","date_gmt":"2026-04-23T14:32:56","guid":{"rendered":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/?page_id=792"},"modified":"2026-04-23T10:40:21","modified_gmt":"2026-04-23T14:40:21","slug":"predicting-sweetpotato-parent-compatibility-using-machine-learning","status":"publish","type":"page","link":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/predicting-sweetpotato-parent-compatibility-using-machine-learning\/","title":{"rendered":"Predicting Sweetpotato Parent Compatibility Using Machine Learning"},"content":{"rendered":"\n\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignright size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1001\" height=\"760\" src=\"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-content\/uploads\/sites\/24\/2026\/04\/Untitled-design-1.png\" alt=\"\" class=\"wp-image-793\" srcset=\"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-content\/uploads\/sites\/24\/2026\/04\/Untitled-design-1.png 1001w, https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-content\/uploads\/sites\/24\/2026\/04\/Untitled-design-1-600x456.png 600w, https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-content\/uploads\/sites\/24\/2026\/04\/Untitled-design-1-768x583.png 768w\" sizes=\"auto, (max-width: 1001px) 100vw, 1001px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">Sweetpotato breeding programs rely on resource-intensive, trial-and-error crossing with high failure rates to create new varieties. To address this, we propose a novel machine learning approach using Graph Neural Networks (GNN)<strong> <\/strong>and ensemble methods<strong> <\/strong>to predict parental compatibility. This predictive tool aims to optimize breeding efficiency, reducing costs and accelerating the development of improved sweetpotato varieties for both farmers and consumers.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Sweetpotato breeding programs rely on resource-intensive, trial-and-error crossing with high failure rates to create new varieties. To address this, we propose a novel machine learning approach using Graph Neural Networks&hellip;<\/p>\n","protected":false},"author":567,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_tec_requires_first_save":true,"ncst_dynamicHeaderBlockName":"ncst\/default-header","ncst_dynamicHeaderData":"{\"pageIntro\":\"Project Leads: Amelia Loeb, Audrey Fahey, Annelise Intemann<br>Project Mentor: Dr. Dave Roberts\"}","ncst_content_audit_freq":"","ncst_content_audit_date":"","_EventAllDay":false,"_EventTimezone":"","_EventStartDate":"","_EventEndDate":"","_EventStartDateUTC":"","_EventEndDateUTC":"","_EventShowMap":false,"_EventShowMapLink":false,"_EventURL":"","_EventCost":"","_EventCostDescription":"","_EventCurrencySymbol":"","_EventCurrencyCode":"","_EventCurrencyPosition":"","_EventDateTimeSeparator":"","_EventTimeRangeSeparator":"","_EventOrganizerID":[],"_EventVenueID":[],"_OrganizerEmail":"","_OrganizerPhone":"","_OrganizerWebsite":"","_VenueAddress":"","_VenueCity":"","_VenueCountry":"","_VenueProvince":"","_VenueState":"","_VenueZip":"","_VenuePhone":"","_VenueURL":"","_VenueStateProvince":"","_VenueLat":"","_VenueLng":"","_VenueShowMap":false,"_VenueShowMapLink":false,"_tribe_blocks_recurrence_rules":"","_tribe_blocks_recurrence_description":"","_tribe_blocks_recurrence_exclusions":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-792","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/pages\/792","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/users\/567"}],"replies":[{"embeddable":true,"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/comments?post=792"}],"version-history":[{"count":2,"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/pages\/792\/revisions"}],"predecessor-version":[{"id":803,"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/pages\/792\/revisions\/803"}],"wp:attachment":[{"href":"https:\/\/units.cals.ncsu.edu\/grad-aid-for-ag-nrt\/wp-json\/wp\/v2\/media?parent=792"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}