Fungal Species: Lepiota

Mushroom data creation, curation, and simulation to support classification tasks

This study creates a new dataset of over 61,000 mushroom records from 173 species to help computers learn to identify whether mushrooms are safe to eat or poisonous. The researchers extracted mushroom information from an identification textbook and used computer programs to generate realistic hypothetical mushroom entries. They tested different AI methods and found that random forests (a type of machine learning algorithm) worked best, achieving perfect accuracy in identifying poisonous versus edible mushrooms.

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Nomenclatural review of names published in the fungal genus Dermoloma (Basidiomycota, Agaricales, Tricholomataceae) based on morphological analyses of type specimens

Scientists have carefully re-examined nine fungal specimens from the genus Dermoloma that serve as the reference standards for naming these mushroom species. Using detailed microscopic analysis, they found that some specimens previously classified as Dermoloma actually belong to different genera, while others represent distinct species. This work helps clarify the true identity of Dermoloma mushrooms and provides a stable foundation for accurately naming new species discovered in the future.

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