Cargando…
In vivo spectroscopy and machine learning for the early detection and classification of different stresses in apple trees
The use of in vivo spectroscopy to detect plant stress in its early stages has the potential to enhance food safety and reduce the need for plant protection products. However, differentiating between various stress types before symptoms appear remains poorly studied. In this study, we investigated t...
Autores principales: | Prechsl, Ulrich E., Mejia-Aguilar, Abraham, Cullinan, Cameron B. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517117/ https://www.ncbi.nlm.nih.gov/pubmed/37739998 http://dx.doi.org/10.1038/s41598-023-42428-z |
Ejemplares similares
-
Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning
por: Nturambirwe, Jean Frederic Isingizwe, et al.
Publicado: (2023) -
Fungicide-free management of Alternaria leaf blotch and fruit spot on apple indicates Alternaria spp. as secondary colonizer
por: Prechsl, Ulrich E., et al.
Publicado: (2023) -
Publisher Correction: Fungicide-free management of Alternaria leaf blotch and fruit spot on apple indicates Alternaria spp. as secondary colonizer
por: Prechsl, Ulrich E., et al.
Publicado: (2023) -
Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification
por: Dahlstrand, Ulf, et al.
Publicado: (2019) -
Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data
por: Vallée, Rodolphe, et al.
Publicado: (2023)