Location: Plant Genetic Resources Unit (PGRU)
Title: Evaluation of directly seeded hemp accessions from the USDA collectionAuthor
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Gordon, Tyler |
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Bello, Nora |
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Stansell, Zachary |
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Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 12/18/2025 Publication Date: 3/11/2026 Citation: Gordon, T.C., Bello, N.M., Stansell, Z.J. 2026. Evaluation of directly seeded hemp accessions from the USDA collection. Meeting Abstract. Volume: 9, Issue: 1. https://doi.org/10.1002/ppj2.70069. DOI: https://doi.org/10.1002/ppj2.70069 Interpretive Summary: Hemp is an important source of oil, fiber and food. The USDA is acquiring hundreds of hemp accessions for evaluation of important agronomic traits. In 2023 and 2024 diverse hemp accessions were grown in the field and sown with a grain drill to obtain agronomic information including: stand emergence, flowering date, sex ratio, height, stem diameter, secondary metabolite profile, seed size, and fiber quality using protocols established in the USDA Hemp Descriptor and Phenotyping Handbook. Accession data generated in this study will help hemp breeders develop improved cultivars and provide a statistically powerful framework for advanced selection with preferential trait combinations and can facilitate hemp breeding efforts. Technical Abstract: Hemp (Cannabis sativa L.) is a source of oilseed, fiber, and medical oil. In 2021 the USDA ARS National Plant Germplasm System began acquiring hemp germplasm for conservation, evaluation, and distribution. In this study, 23 hemp accessions from the USDA Collection were evaluated in directly seeded plots planted at 2.47 million seeds ha -1 and sown in early June in Geneva, NY in 2023 and 2024. Accessions were assessed and compared for priority agronomic traits including stand emergence, flowering date, sex ratio, height, stem diameter, secondary metabolite profile, seed size, and fiber quality using protocols established in the USDA Hemp Descriptor and Phenotyping Handbook. Protocols developed in this study provide a statistically powerful framework for advanced selection with preferential trait combinations and can facilitate hemp breeding efforts. |
