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dc.citation.number 4 -
dc.citation.startPage e42407 -
dc.citation.title Heliyon -
dc.citation.volume 11 -
dc.contributor.author Lim, Seunghyun -
dc.contributor.author Baek, Insuck -
dc.contributor.author Hong, Seok Min -
dc.contributor.author Lee, Yoonjung -
dc.contributor.author Kirubakaran, Silvas -
dc.contributor.author Kim, Moon S. -
dc.contributor.author Meinhardt, Lyndel W. -
dc.contributor.author Park, Sunchung -
dc.contributor.author Ahn, Ezekiel -
dc.date.accessioned 2026-04-22T15:01:49Z -
dc.date.available 2026-04-22T15:01:49Z -
dc.date.created 2026-04-22 -
dc.date.issued 2025-02 -
dc.description.abstract Understanding the factors influencing cacao flower morphology and abundance is essential for optimizing productivity. This study investigated the influence of vertical flower position and associated environmental and physiological gradients on these traits across two cacao genotypes, CCN51 and SCA6, under controlled greenhouse conditions. We measured flower size (lateral area, length, width, and perimeter), shape, and abundance at different developmental stages and vertical tree heights. Significant variations were observed between genotypes and across vertical positions, highlighting the roles of genetic and environmental factors in cacao reproductive biology. For example, CCN51 exhibited significantly larger flowers, with an average area of 18.63 mm2 compared to 14.88 mm2 for SCA6. Leveraging machine learning techniques, particularly Support Vector Machine, we successfully predicted genotypes based on flower measurements with high accuracy, achieving an area under the receiver operating characteristic curve of 0.87. These findings emphasize the phenotypic diversity of cacao flowers and demonstrate the potential of machine learning in genotype identification, offering valuable insights for breeding and cultivation strategies to enhance cacao productivity. © 2025 -
dc.identifier.bibliographicCitation Heliyon, v.11, no.4, pp.e42407 -
dc.identifier.doi 10.1016/j.heliyon.2025.e42407 -
dc.identifier.issn 2405-8440 -
dc.identifier.scopusid 2-s2.0-85217217877 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/91435 -
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S240584402500787X?pes=vor&utm_source=scopus&getft_integrator=scopus -
dc.language 영어 -
dc.publisher Elsevier Ltd -
dc.title Cacao floral traits are shaped by the interaction of flower position with genotype -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Flower -
dc.subject.keywordAuthor Morphology -
dc.subject.keywordAuthor Shape -
dc.subject.keywordAuthor Size -
dc.subject.keywordAuthor Vertical height -
dc.subject.keywordAuthor Cacao -
dc.subject.keywordAuthor Environmental and physiological gradients -

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