Genomic prediction in quinoa across contrasting environments using statistical and machine learning models
- DOI
- 10.1002/tpg2.70277
- Published
- 2026-08-19
- Container
- The Plant Genome
- Publisher
- Wiley
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1002/tpg2.70277,
title = {Genomic prediction in quinoa across contrasting environments using statistical and machine learning models},
author = {Clara S. Stanschewski and Mark Warmington and Irfan Afzal and Elodie Rey and Gabriele Fiene and Evan Craine and Kevin Murphy and Mark Tester and Jesse Poland},
year = {2026},
journal = {The Plant Genome},
doi = {10.1002/tpg2.70277},
url = {https://doi.org/10.1002/tpg2.70277}
}RIS
TY - JOUR TI - Genomic prediction in quinoa across contrasting environments using statistical and machine learning models AU - Clara S. Stanschewski AU - Mark Warmington AU - Irfan Afzal AU - Elodie Rey AU - Gabriele Fiene AU - Evan Craine AU - Kevin Murphy AU - Mark Tester AU - Jesse Poland PY - 2026 JO - The Plant Genome DO - 10.1002/tpg2.70277 UR - https://doi.org/10.1002/tpg2.70277 ER -
APA
Stanschewski, C. S., Warmington, M., Afzal, I., Rey, E., Fiene, G., Craine, E., Murphy, K., Tester, M., & Poland, J. (2026). Genomic prediction in quinoa across contrasting environments using statistical and machine learning models. The Plant Genome. https://doi.org/10.1002/tpg2.70277
Source records
- crossref · retrieved 2026-09-24T23:34:50.547Z