Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning.
- DOI
- 10.3389/fpls.2025.1686506
- Published
- 2025
- Container
- Frontiers in plant science
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fpls.2025.1686506,
title = {Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning.},
author = {Tietze H and Abdelhakim L and Pleskačová B and Kurtz-Sohn A and Fridman E and Nikoloski Z and Panzarová K},
year = {2025},
journal = {Frontiers in plant science},
doi = {10.3389/fpls.2025.1686506},
url = {https://doi.org/10.3389/fpls.2025.1686506}
}RIS
TY - JOUR TI - Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning. AU - Tietze H AU - Abdelhakim L AU - Pleskačová B AU - Kurtz-Sohn A AU - Fridman E AU - Nikoloski Z AU - Panzarová K PY - 2025 JO - Frontiers in plant science DO - 10.3389/fpls.2025.1686506 UR - https://doi.org/10.3389/fpls.2025.1686506 ER -
APA
H, T., L, A., B, P., A, K., E, F., Z, N., & K, P. (2025). Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning.. Frontiers in plant science. https://doi.org/10.3389/fpls.2025.1686506
Source records
- pubmed · retrieved 2026-09-25T21:59:26.476Z