Rapid evaluation technique to differentiate mushroom disease-related moulds by detecting microbial volatile organic compounds using HS-SPME-GC-MS

Early detection of dry bubble disease in Agaricus bisporus using volatile compounds

Lecanicillium fungicola is a pathogen of the commercial white button mushroom (Agaricus bisporus) and is the causal agent of dry bubble disease, which can cause severe economic losses to mushroom growers. Volatile compounds were measured by GC/MS techniques over pure cultures of mycelia on agars, over microcosms of growing mushrooms, and over harvested mushrooms to identify compounds that might give an early warning of the disease. The mushroom strain tested was Agaricus bisporus, strain Sylvan A15; either deliberately infected with L. fungicola or water as a control. Over microcosms, the appearance of β-copaene, β-cubebene, and α-cedrene coincided with, but did not precede, the earliest visual signs of the disease. Mushrooms with dry bubble symptoms also had high levels of β-barbatene and an unknown diterpene (UK 1821). Over some harvested mushroom sets, high levels of cis-α-bisabolene developed as a defence reaction to infection.

Challenges and applications of volatile organic compounds monitoring technology in plant disease diagnosis

Biotic and abiotic stresses are well known to increase the emission of volatile organic compounds (VOCs) from plants. The analysis of VOCs emissions from plants enables timely diagnostic of plant diseases, which is critical for prompting sustainable agriculture. Previous studies have predominantly focused on the utilization of commercially available devices, such as electronic noses, for diagnosing plant diseases. However, recent advancements in nanomaterials research have significantly contributed to the development of novel VOCs sensors featuring exceptional sensitivity and selectivity. This comprehensive review presents a systematic analysis of VOCs monitoring technologies for plant diseases diagnosis, providing insights into their distinct advantages and limitations. Special emphasis is placed on custom-made VOCs sensors, with detailed discussions on their design, working principles, and detection performance. It is noteworthy that the application of VOCs monitoring technologies in the diagnostic process of plant diseases is still in its emerging stage, and several critical challenges demand attention and improvement. Specifically, the identification of specific stress factors using a single VOC sensor remains a formidable task, while environmental factors like humidity can potentially interfere with sensor readings, leading to inaccuracies. Future advancements should primarily focus on addressing these challenges to enhance the overall efficacy and reliability of VOCs monitoring technologies in the field of plant disease diagnosis.

Advances in microbial analysis: based on volatile organic compounds of microorganisms in food

In recent years, microbial volatile organic compounds (mVOCs) produced by microbial metabolism have attracted more and more attention because they can be used to detect food early contamination and flaws. So far, many analytical methods have been reported for the determination of mVOCs in food, but few integrated review articles discussing these methods are published. Consequently, mVOCs as indicators of food microbiological contamination and their generation mechanism including carbohydrate, amino acid, and fatty acid metabolism are introduced. Meanwhile, a detailed summary of the mVOCs sampling methods such as headspace, purge trap, solid phase microextraction, and needle trap is presented, and a systematic and critical review of the analytical methods (ion mobility spectrometry, electronic nose, biosensor, and so on) of mVOCs and their application in the detection of food microbial contamination is highlighted. Finally, the future concepts that can help improve the detection of food mVOCs are prospected.

Smelling the difference: separation of healthy and infected button mushrooms via microbial volatile organic compounds

In the literature there is a lack of consensus regarding mushroom volatiles; most of the studies identify only a few volatiles. This study deals with button mushrooms, their emitted volatiles, and the main changes during infections (green mould and cobweb disease) in a time series experiment. Emitted volatile profiles were determined using HS-SPME-GC-MS coupled analytical technique. The separation of healthy and infected mushroom samples was done using different multivariate statistical methods (PCA, PLS-DA, HeatMap). The main volatile compounds were also determined. As a result, several compounds were found to successfully distinguish healthy (bisabolene, cymene, myrtenol, d-limonene, etc.) and infected (thujopsene, cedr-8-ene, chamigrene, patchulane, longifolene, etc.), mushroom samples, and an early disease detection was achieved. Results can be used for further investigation of infected mushroom identification in an early stage in packaged mushroom products. Furthermore, these results could help to identify infections in commercially available mushrooms, thus increasing shelf-life in super/hypermarkets.

Volatile Metabolic Markers for Monitoring Pectobacterium carotovorum subsp. carotovorum Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry

Identifying the extracellular metabolites of microorganisms in fresh vegetables is industrially useful for assessing the quality of processed foods. Pectobacterium carotovorum subsp. carotovorum (PCC) is a plant pathogenic bacterium that causes soft rot disease in cabbages. This microbial species in plant tissues can emit specific volatile molecules with odors that are characteristic of the host cell tissues and PCC species. In this study, we used headspace solid-phase microextraction followed by gas chromatography coupled with mass spectrometry (HS-SPME-GC-MS) to identify volatile compounds (VCs) in PCC-inoculated cabbage at different storage temperatures. HS-SPME-GC-MS allowed for recognition of extracellular metabolites in PCC-infected cabbages by identifying specific volatile metabolic markers. We identified 4-ethyl-5-methylthiazole and 3-butenyl isothiocyanate as markers of fresh cabbages, whereas 2,3-butanediol and ethyl acetate were identified as markers of soft rot in PCC-infected cabbages. These analytical results demonstrate a suitable approach for establishing non-destructive plant pathogen-diagnosis techniques as alternatives to standard methods, within the framework of developing rapid and efficient analytical techniques for monitoring plant-borne bacterial pathogens. Moreover, our techniques could have promising applications in managing the freshness and quality control of cabbages.

Multicriteria decision making for evergreen problems in food science by sum of ranking differences

Finding optimal solutions usually requires multicriteria optimization. The sum of ranking differences (SRD) algorithm can efficiently solve such problems. Its principles and earlier applications will be discussed here, along with meta-analyses of papers published in various subfields of food science, such as analytics in food chemistry, food engineering, food technology, food microbiology, quality control, and sensory analysis. Carefully selected real case studies give an overview of the wide range of applications for multicriteria optimizations, using a free, easy-to-use and validated method. Results are presented and discussed in a way that helps scientists and practitioners, who are less familiar with multicriteria optimization, to integrate the method into their research projects. The utility of SRD, optionally coupled with other statistical methods such as ANOVA, is demonstrated on altogether twelve case studies, covering diverse method comparison and data evaluation scenarios from various subfields of food science.

Volatile Organic Compounds of Endophytic Burkholderia pyrrocinia Strain JK-SH007 Promote Disease Resistance in Poplar

Volatile organic compounds (VOCs) play important roles in the regulation of plant growth and pathogen resistance. However, little is known about the influence of VOCs released from endophytic strains (Burkholderia pyrrocinia strain JK-SH007) on controlling pathogens or inducing systemic resistance in poplar. In this study, we found that VOCs produced by strain JK-SH007 inhibit three poplar canker pathogens (Cytospora chrysosperma, Phomopsis macrospora, and Fusicoccum aesculi) and promote defense enzyme activity and malondialdehyde (MDA) and total phenol (TP) accumulation. Thirteen kinds of VOC components were identified using the solid-phase microextraction combined with gas chromatography-mass spectrometry method. Dimethyl disulfide (DMDS) accounted for the largest proportion of these VOCs. Treatments of poplar seedlings with different volumes of VOC standards (DMDS, benzothiazole, dimethylthiomethane, and phenylacetone) showed that DMDS had the greatest effects on various defense enzyme activities and MDA and TP accumulation. We also found that the inhibitory effect of the VOCs on the three pathogens was gradually enhanced with increasing standard volume. Moreover, the treatment of samples with DMDS significantly reduced the severity and development of the disease caused by three poplar canker pathogens. Comparative transcriptomics analysis of poplar seedlings treated with DMDS showed that there were 1,586 differentially expressed genes in the leaves and stems, and quantitative PCR showed that the gene expression trends were highly consistent with the transcriptome sequencing results. The most significant transcriptomic changes induced by VOCs were related to hormone signal transduction, transcriptional regulation of plant-pathogen interactions, and energy metabolism. Moreover, 137 transcription factors, including members of the ethylene response factor, NAC, WRKY, G2-like, and basic helix-loop-helix protein families, were identified to be involved in the VOC-induced process. This study elucidates the resistance induced by Burkholderia pyrrocinia strain JK-SH007 to poplar canker at the molecular level and can make possible a new method for the comprehensive prevention and control of poplar disease.

A comparison of electronic nose and gas chromatography-mass spectrometry on discrimination and prediction of ochratoxin A content in Aspergillus carbonarius cultured grape-based medium

This study investigated discrimination and prediction of ochratoxin A (OTA) in three Aspergillus carbonarius strains cultured grape-based medium using E-nose technology and GC-MS analysis. Results showed that these strains cultured medium samples were divided into four groups regarding their log 10 OTA value using an equispaced normal distribution analysis. Partial least squares-discriminant analysis (PLS-DA) revealed that GC-MS PLS-DA model only separated the low OTA level medium samples from the rest OTA level samples, whereas all the OTA level samples were segregated from each other using E-nose PLS-DA model. Partial least squares regression (PLSR) analysis indicated that an excellent prediction performance was established on the accumulation of OTA in these medium samples using E-nose PLSR, whereas GC-MS PLSR model showed a screening performance on the OTA formation. These indicated that E-nose analysis could be a reliable method on discriminating and predicting OTA in A. carbonarius strains under grape-based medium.

Fungal volatiles - a survey from edible mushrooms to moulds

Covering: up to January 2017This review gives a comprehensive overview of the production of fungal volatiles, including the history of the discovery of the first compounds and their distribution in the various investigated strains, species and genera, as unravelled by modern analytical methods. Biosynthetic aspects and the accumulated knowledge about the bioactivity and biological functions of fungal volatiles are also covered. A total number of 325 compounds is presented in this review, with 247 cited references.