Literature DB >> 34168175

Can wood-decaying urban macrofungi be identified by using fuzzy interference system? An example in Central European Ganoderma species.

Alžbeta Michalíková1, Terézia Beck2, Ján Gáper3,4, Peter Pristaš5, Svetlana Gáperová2.   

Abstract

Ganoderma is a cosmopolitan genus of wood-decaying basidiomycetous macrofungi that can rot the roots and/or lower trunk. Among the standing trees, their presence often indicates that a hazard assessment may be necessary. These bracket fungi are commonly known for the crust-like upper surfaces of their basidiocarps and formation of white rot. Six species occur in central European urban habitats. Several of them, such as Ganoderma adspersum, G. applanatum, G. resinaceum and G. pfeifferi, are most hazardous fungi causing extensive horizontal stem decay in urban trees. Therefore, their early identification is crucial for correct management of trees. In this paper, a fast technique is tested for the determination of phytopathologically important urban macrofungi using fuzzy interference system of Sugeno type based on 13 selected traits of 72 basidiocarps of six Ganoderma species and compared to the ITS sequence based determination. Basidiocarps features were processed for the following situations: At first, the FIS of Sugeno 2 type (without basidiospore sizes) was used and 57 Ganoderma basidiocarps (79.17%) were correctly determined. Determination success increased to 96.61% after selecting basidiocarps with critical values (15 basidiocarps). These undeterminable basidiocarps must be analyzed by molecular methods. In a case, that basidiospore sizes of some basidiocarps were known, a combination of Sugeno 1 (31 basidiocarps with known basidiospore size) and Sugeno 2 (41 basidiocarps with unknown basidiospore size) was used. 84.72% of Ganoderma basidiocarps were correctly identified. Determination success increased to 96.83% after selecting basidiocarps with critical values (11 basidiocarps).

Entities:  

Year:  2021        PMID: 34168175     DOI: 10.1038/s41598-021-92237-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  6 in total

1.  Optimization of sampling procedures for DNA-based diagnosis of wood decay fungi in standing trees.

Authors:  F Guglielmo; P Gonthier; M Garbelotto; G Nicolotti
Journal:  Lett Appl Microbiol       Date:  2010-04-29       Impact factor: 2.858

2.  Data processing can mask biology: towards better reporting of fungal barcoding data?

Authors:  Marc-André Selosse; Lucie Vincenot; Maarja Öpik
Journal:  New Phytol       Date:  2016-01-28       Impact factor: 10.151

3.  A multiplex PCR-based method for the detection and early identification of wood rotting fungi in standing trees.

Authors:  F Guglielmo; S E Bergemann; P Gonthier; G Nicolotti; M Garbelotto
Journal:  J Appl Microbiol       Date:  2007-11       Impact factor: 3.772

4.  Classification of diabetes maculopathy images using data-adaptive neuro-fuzzy inference classifier.

Authors:  Sulaimon Ibrahim; Pradeep Chowriappa; Sumeet Dua; U Rajendra Acharya; Kevin Noronha; Sulatha Bhandary; Hatwib Mugasa
Journal:  Med Biol Eng Comput       Date:  2015-06-25       Impact factor: 2.602

Review 5.  Fungal diagnostics.

Authors:  Thomas R Kozel; Brian Wickes
Journal:  Cold Spring Harb Perspect Med       Date:  2014-04-01       Impact factor: 6.915

6.  Alignment-free method for DNA sequence clustering using Fuzzy integral similarity.

Authors:  Ajay Kumar Saw; Garima Raj; Manashi Das; Narayan Chandra Talukdar; Binod Chandra Tripathy; Soumyadeep Nandi
Journal:  Sci Rep       Date:  2019-03-06       Impact factor: 4.379

  6 in total

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