1. Data collection and advanced statistical analysis in phytotoxic activity of aerial parts exudates of Salvia spp
- Author
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Giovanni Romussi, S. Pivetti, Daniele Fraternale, Angela Bisio, S. Bertolini, Emanuela Giacomelli, Donata Ricci, N. De Tommasi, and Mauro Giacomini
- Subjects
Data Analysis ,food.ingredient ,Neural Networks ,Toxicology and Pharmaceutics (all) ,lcsh:RS1-441 ,Self organising maps ,Salvia ,Distance Interactions ,lcsh:Pharmacy and materia medica ,food ,Statistics ,Botany ,Data analysis ,Distance interactions ,Germination indices ,Neural networks ,Phytotoxicity ,Self-organising maps ,Web based database for long ,Pharmacology, Toxicology and Pharmaceutics (all) ,Statistical analysis ,General Pharmacology, Toxicology and Pharmaceutics ,Pharmacology ,Data collection ,biology ,biology.organism_classification ,Web Based Database for Long ,Avena ,Germination ,Germination Indices ,Data Analysis, Phytotoxicity, Germination Indices, Web Based Database for Long, Distance Interactions, Neural Networks, Self-Organising Maps ,Self-Organising Maps - Abstract
In order to define the phytotoxic potential of Salvia species a database was developed for fast and efficient data collection in screening studies of the inhibitory activity of Salvia exudates on the germination of Papaver rhoeas L. and Avena sativa L.. The structure of the database is associated with the use of algorithms for calculating the usual germination indices reported in the literature, plus the newly defined indices (Weighted Average Damage, Differential Weighted Average Damage, Germination Weighted Average Velocity) and other variables usually recorded in experiments of phytotoxicity (LC50, LC90). Furthermore, other algorithms were designed to calculate the one-way ANOVA followed by Duncan's multiple range test to highlight automatically significant differences between the species. The database model was designed in order to be suitable also for the development of further analysis based on the artificial neural network approach, using Self-Organising Maps (SOM).
- Published
- 2011