Machine learning-based prediction of morphophysiological, ionic, and biochemical responses of Lolium multiflorum to salinity stress.
- DOI
- 10.1186/s12870-026-09748-4
- Published
- 2026 Aug 13
- Container
- BMC plant biology
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12870-026-09748-4,
title = {Machine learning-based prediction of morphophysiological, ionic, and biochemical responses of Lolium multiflorum to salinity stress.},
author = {Akparlar E and Okumuş O and Say A and Demirel S and Demirel F and Türkoğlu A and Yaman M and Uzun S},
year = {2026},
journal = {BMC plant biology},
doi = {10.1186/s12870-026-09748-4},
url = {https://doi.org/10.1186/s12870-026-09748-4}
}RIS
TY - JOUR TI - Machine learning-based prediction of morphophysiological, ionic, and biochemical responses of Lolium multiflorum to salinity stress. AU - Akparlar E AU - Okumuş O AU - Say A AU - Demirel S AU - Demirel F AU - Türkoğlu A AU - Yaman M AU - Uzun S PY - 2026 JO - BMC plant biology DO - 10.1186/s12870-026-09748-4 UR - https://doi.org/10.1186/s12870-026-09748-4 ER -
APA
E, A., O, O., A, S., S, D., F, D., A, T., M, Y., & S, U. (2026). Machine learning-based prediction of morphophysiological, ionic, and biochemical responses of Lolium multiflorum to salinity stress.. BMC plant biology. https://doi.org/10.1186/s12870-026-09748-4
Source records
- pubmed · retrieved 2026-11-10T18:53:24.370Z