This study focuses on the classification of six different macrofungi species using advanced deep learning techniques. Fungi species, such as Amanita pantherina, Boletus edulis, Cantharellus cibarius, Lactarius deliciosus, Pleurotus ostreatus and Tricholoma terreum were chosen based on their ecological importance and distinct morphological characteristics. The research employed 5 different machine learning techniques and 12 deep learning models, including DenseNet121, MobileNetV2, ConvNeXt, EfficientNet, and swin transformers, to evaluate their performance in identifying fungi from images. The DenseNet121 model demonstrated the highest accuracy (92%) and AUC score (95%), making it the most effective in distinguishing between species. The study also revealed that transformer-based models, particularly the swin transformer, were less effective, suggesting room for improvement in their application to this task. Further advancements in macrofungi classification could be achieved by expanding datasets, incorporating additional data types such as biochemical, electron microscopy, and RNA/DNA sequences, and using ensemble methods to enhance model performance. The findings contribute valuable insights into both the use of deep learning for biodiversity research and the ecological conservation of macrofungi species.

In the present study, fungal specimens collected from Yeşildere village in Uşak province, Türkiye were evaluated. The specimens underwent detailed examination through both mor-phological and DNA (nrITS rDNA region and TEF1a gene) sequence-based phylogenetic analysis. Based on the evaluation of micro- and macromorphological characteristics, and phylogenetic analyses, the specimen was identified as A. vidua Gasch, G. Moreno & P.-A. Moreau. This identification marks A. vidua as a new record for the Turkish Amanita section Phalloideae. The study described this newly recorded species, including specific details such as its location, habitat observations, geographical coordinates, collection date, and pho-tographs showcasing its macro and micromorphological features. Additionally, it also in-cludes illustrations of some microscopic structures of the species. The study is further en-riched with SEM images, offering a detailed view of the species characteristics, and the findings are briefly discussed.

In 2023, fungal specimens were collected from the Tınaztepe Campus of Dokuz Eylül University (İzmir-Türkiye). These samples underwent a comprehensive and meticulous evaluation involving morphological examination and phylogenetic analysis based on nrITS rDNA sequencing. The DEU AKATA & SAHIN 148 samples exhibited microscopic and macroscopic characteristics that closely matched those of Rhodocybe asyae, initially described by Sesli & Vizzini. The genetic sequence analysis revealed over 99% similarity with R. asyae Sesli & Vizzini. This report represents the second recorded occurrence of R. asyae in Türkiye and the third globally. The study documents the collection site, geographical coordinates, habitat observations, the collection date, etc. Furthermore, the research provides macroscopic photographs, microscopic illustrations of the specimens, and detailed discussion, demonstrating the reliability of the present findings.

Inocybe specimens were collected from Ankara University Beşevler 10. Yıl Campus, (Ankara, Türkiye) on October 19, 2022. As a result, the samples were identified as I. costinitii, a new record for Turkish Inocybe. This study presents a detailed description of this newly recorded species, covering aspects such as its location, observations of its habitat, geographical coordinates, the date of collection, and photographs that highlight its macroscopic and microscopic characteristics. Moreover, the study features the species' drawings and some of its microscopic traits. The study is enhanced by images obtained from a scanning electron microscope (SEM), briefly examining the spore features and discussed briefly.

This study presents a comprehensive taxonomic assessment of fungal specimens collected from Çanakkale Province in northwestern Türkiye. An integrative approach was employed, combining detailed macro and micromorphological analyses with molecular phylogenetic methods based on the internal transcribed spacer (nrITS,rDNA) region of nuclear ribosomal DNA. The results confirmed the identity of the specimens as Rhodocybe fumanellii R.J. Ferrari, Vizzini & Fellin, representing the first record of this species in Türkiye. As a newly documented member of section Rufobrunnea, this finding broadens the known geographical distribution of the species and contributes to understanding the genus Rhodocybe in the region. The study includes thorough morphological descriptions, ecological data, precise locality information with geographic coordinates, collection details, and photographic documentation, thereby enriching the knowledge of fungal biodiversity in Türkiye.

The samples were collected from Ankara, Gaziantep, Konya, Niğde, and Şanlıurfa (Türkiye), between 2020 and 2023. Morphological analyses and nrITS rDNA sequence-based phylogenetic methods were used to examine the samples. Twenty-one specimens displayed morphological features consistent with Terfezia claveryi Chatin at both macro and micro levels. Genetic analysis revealed over 99% sequence similarity with this species. Detailed documentation included habitat descriptions, geographical coordinates, collection dates, and photographic records of macroscopic and microscopic structures. These findings contribute valuable insights into the distribution and taxonomy of T. claveryi in Türkiye.