Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/48246
Title: Sorting biotic and abiotic stresses on wild rocket by leaf-image hyperspectral data mining with an artificial intelligence model
Authors: Navarro, Alejandra
Nicastro, Nicola
Costa, Corrado
Pentangelo, Alfonso
Cardarelli, Mariateresa 
Ortenzi, Luciano 
Pallottino, Federico
Cardi, Teodoro
Pane, Catello
Journal: PLANT METHODS 
Issue Date: 2022
Abstract: 
Wild rocket (Diplotaxis tenuifolia) is prone to soil-borne stresses under intensive cultivation systems devoted to ready-to-eat salad chain, increasing needs for external inputs. Early detection of the abiotic and biotic stresses by using digital reflectance-based probes may allow optimization and enhance performances of the mitigation strategies.
URI: http://hdl.handle.net/2067/48246
ISSN: 1746-4811
DOI: 10.1186/s13007-022-00880-4
Rights: Attribution 4.0 International
Appears in Collections:A1. Articolo in rivista

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