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Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelling in Tulipa saxatilis Cover

Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelling in Tulipa saxatilis

Folia Horticulturae
Volume 36 (2024): Issue 3 (December 2024)
By: Ömer Sari  
Open Access
|Oct 2024
DOI: https://doi.org/10.2478/fhort-2024-0024 | Journal eISSN: 2083-5965 | Journal ISSN: 0867-1761
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Language: English
Page range: 381 - 398
Submitted on: May 7, 2024
Accepted on: Aug 26, 2024
Published on: Oct 9, 2024
Published by: Polish Society for Horticultural Sciences (PSHS)
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
flower stem length,
GA,
growing,
machine learning,
nutrient content,
root analysing,
tulips
Related subjects:
Life sciences,
Plant science,
Zoology,
Ecology,
Life sciences, other

© 2024 Ömer Sari, published by Polish Society for Horticultural Sciences (PSHS)
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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