Molecular Approaches for Detection of Trichoderma Green Mold Disease in Edible Mushroom Production

Author:

Šašić Zorić Ljiljana1ORCID,Janjušević Ljiljana1ORCID,Djisalov Mila1,Knežić Teodora1ORCID,Vunduk Jovana2,Milenković Ivanka3,Gadjanski Ivana1ORCID

Affiliation:

1. BioSense Institute, University of Novi Sad, Dr Zorana Đinđića 1, 21000 Novi Sad, Serbia

2. Institute of General and Physical Chemistry, University of Belgrade, Studentski trg 12/V, 11080 Belgrade, Serbia

3. EKOFUNGI DOO, Zrenjaninski put bb, Industrijska zona, Padinska Skela, 11213 Belgrade, Serbia

Abstract

Due to the evident aggressive nature of green mold and the consequently huge economic damage it causes for producers of edible mushrooms, there is an urgent need for prevention and infection control measures, which should be based on the early detection of various Trichoderma spp. as green mold causative agents. The most promising current diagnostic tools are based on molecular methods, although additional optimization for real-time, in-field detection is still required. In the first part of this review, we briefly discuss cultivation-based methods and continue with the secondary metabolite-based methods. Furthermore, we present an overview of the commonly used molecular methods for Trichoderma species/strain detection. Additionally, we also comment on the potential of genomic approaches for green mold detection. In the last part, we discuss fast screening molecular methods for the early detection of Trichoderma infestation with the potential for in-field, point-of-need (PON) application, focusing on isothermal amplification methods. Finally, current challenges and future perspectives in Trichoderma diagnostics are summarized in the conclusions.

Funder

European Union’s Horizon 2020 research and innovation programme

Ministry of Education, Science and Technological Development of the Republic of Serbia

Publisher

MDPI AG

Subject

General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology

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