Discrimination of mushroom disease‐related mould species based solely on unprocessed chromatograms

Abstract

Agaricus bisporus A15 species (bisporic button mushroom) and its two main mould diseases (Mycogone perniciosa and Trichoderma aggressivum) were analysed using headspace solid-phase microextraction sampling coupled with gas chromatograpy-mass spectrometry analysis. The presence or absence of mushroom disease-related moulds can easily be detected and monitored in the air by headspace solid-phase microextraction gas chromatograpymass spectrometry via their emitted microbial volatile organic compounds. Detrended fluctuation analysis (DFA) was first applied to distinguish different mould samples based on their unprocessed total ion chromatograms, which describe the air polluted by microbial volatile organic compounds. A two-dimensional plot, generated from the results of DFA, visualizes the relationship of the analysed samples. The pattern found by DFA was compared with the pattern found by the traditionally applied principal component analysis. Cluster analysis (using Euclidean distance and Ward's method) of the principal component analysis scores and DFA coefficients showed characteristic groupings. A methodology is introduced, which uses the unprocessed chromatogram, without any time-consuming feature extraction and can indicate the presence of infected samples. The proposed methodology is able to give a support to the mushroom growers to indicate different mushroom disease-related infection via air monitoring. Additionally, DFA is a sample-independent and universal method. Hence, it can be also applied to distinguish unprocessed chromatograms produced by any other analytical equipment.

Application of Detrended Fluctuation Analysis and Yield Stability Index to Evaluate Near Infrared Spectra of Green and Roasted Coffee Samples

“…In order to create overlapping ranges, sliding window DFA approach was developed, which has been successfully used for pattern recognition and grouping. The presented paper uses the algorithm introduced by Radványi and co-workers [28]. Physisonet [42] was used to perform DFA and additional computations were carried out using R-project (R version 4.0.0 (Arbor Day), R Core Team, Vienna, Austria, 2019) [39].…”

“…One promising technique, detrended fluctuation analysis (DFA) has been introduced for the analysis of chromatograms [28]. DFA is a widely used time series data analysis tool and was successfully applied in the past few years for the evolution of high-viscosity gas-liquid flows [29], water contaminant classification [30], for EEG patterns associated with real and imaginary arm movements [31], air traffic flow analysis [32], and even for the analysis of NBA results [33], for instance.…”

Penicillium hermansii, a new species causing smoky mould in white button mushroom production

“…Competitive moulds from spawn-run compost can have devastating effects on production levels. An important and wellknown example is Trichoderma aggressivum and much research is performed on this species (Kosanovic et al 2015;O'Brien et al 2014;O'Brien et al 2017;Radvanyi et al 2016). Another less commonly and poorly documented competing contaminant is known as 'smoky mould', which is capable of wiping out a complete crop (Fletcher and Gaze 2008;Grogan and Harvey 1999;Grogan et al 2000).…”

Evaluation of the safe use and dietary risk of beta-cypermethrin, pyriproxyfen, avermectin, diflubenzuron and chlorothalonil in button mushroom

“…Fungal pathogens, such as Lecanicillium (Verticillium) fungicola, Mycogone perniciosa, Cladobotryum (Dactylium) spp . and Trichoderma spp ., can cause very serious fungal diseases in button mushrooms 18 – 20 , but chlorothalonil is a broad-spectrum fungicide that has the potential to control these diseases.…”