Machine learning applied to canopy hyperspectral image data to support biological control of soil-borne fungal diseases in baby leaf vegetables

Author:

Pane Catello,Manganiello Gelsomina,Nicastro Nicola,Ortenzi Luciano,Pallottino Federico,Cardi Teodoro,Costa Corrado

Funder

Ministero delle Politiche Agricole Alimentari e Forestali

Publisher

Elsevier BV

Subject

Insect Science,Agronomy and Crop Science

Reference60 articles.

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3. Deciphering Trichoderma–Plant–Pathogen Interactions for Better Development of Biocontrol Applications;Alfiky;J. Fungi.,2021

4. Hyperspectral imaging of symptoms induced by Rhizoctonia solani in sugar beet: comparison of input data and different machine learning algorithms;Barreto;JPDP,2020

5. Specim IQ: evaluation of a new, miniaturized handheld hyperspectral camera and its application for plant phenotyping and disease detection;Behmann;Sensors,2018

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