Fungi and oomycetes release volatiles into their environment which could be used for olfactory detection and identification of these organisms by electronic-nose (e-nose). The aim of this study was to survey volatile compound emission using an e-nose device and to identify released molecules through solid phase microextraction–gas chromatography/mass spectrometry (SPME–GC/MS) analysis to ultimately develop a detection system for fungi and fungi-like organisms. To this end, cultures of eight fungi (Armillaria gallica, Armillaria ostoyae, Fusarium avenaceum, Fusarium culmorum, Fusarium oxysporum, Fusarium poae, Rhizoctonia solani, Trichoderma asperellum) and four oomycetes (Phytophthora cactorum, P. cinnamomi, P. plurivora, P. ramorum) were tested with the e-nose system and investigated by means of SPME-GC/MS. Strains of F. poae, R. solani and T. asperellum appeared to be the most odoriferous. All investigated fungal species (except R. solani) produced sesquiterpenes in variable amounts, in contrast to the tested oomycetes strains. Other molecules such as aliphatic hydrocarbons, alcohols, aldehydes, esters and benzene derivatives were found in all samples. The results suggested that the major differences between respective VOC emission ranges of the tested species lie in sesquiterpene production, with fungi emitting some while oomycetes released none or smaller amounts of such molecules. Our e-nose system could discriminate between the odors emitted by P. ramorum, F. poae, T. asperellum and R. solani, which accounted for over 88% of the PCA variance. These preliminary results of fungal and oomycete detection make the e-nose device suitable for further sensor design as a potential tool for forest managers, other plant managers, as well as regulatory agencies such as quarantine services.

Electronic noses can be applied as a rapid, cost-effective option for several applications. This paper presents the results of measurements of samples of two pathogenic fungi, Fusarium oxysporum and Rhizoctonia solani, performed using two constructions of a low-cost electronic nose. The first electronic nose used six non-specific Figaro Inc. metal oxide gas sensors. The second one used ten sensors from only two models (TGS 2602 and TGS 2603) operating at different heater voltages. Sets of features describing the shapes of the measurement curves of the sensors’ responses when exposed to the odours were extracted. Machine learning classification models using the logistic regression method were created. We demonstrated the possibility of applying the low-cost electronic nose data to differentiate between the two studied species of fungi with acceptable accuracy. Improved classification performance could be obtained, mainly for measurements using TGS 2603 sensors operating at different voltage conditions.

Compared with traditional gas chromatography–mass spectrometry techniques, electronic noses are non-invasive and can be a rapid, cost-effective option for several applications. This paper presents comparative studies of differentiation between odors emitted by two forest pathogens: Pythium and Phytophthora, measured by a low-cost electronic nose. The electronic nose applies six non-specific Figaro Inc. metal oxide sensors. Various features describing shapes of the measurement curves of sensors’ response to the odors’ exposure were extracted and used for building the classification models. As a machine learning algorithm for classification, we use the Support Vector Machine (SVM) method and various measures to assess classification models’ performance. Differentiation between Phytophthora and Pythium species has an important practical aspect allowing forest practitioners to take appropriate plant protection. We demonstrate the possibility to recognize and differentiate between the two mentioned species with acceptable accuracy by our low-cost electronic nose.

Heterobasidion annosum (Fr.) Bref. sensu lato (s.l.) is a dangerous forest pathogen causing root and butt rot disease in most conifers of the northern hemisphere. This pathogen is most widespread in the forests of Europe and North America. The economic impact on forestry related to tree mortality, reduction in timber yield, and wood rot is calculated in millions of dollars and euros. The genus Heterobasidion (Basidiomycota; Russulales) has been relatively recently separated into three genetically distinct groups (H. annosum, H. insulare and H. araucariae) comprising a total of 12 species and one newly described hybrid taxon. These species are the best studied in terms of the ecology, the physiology of control methods, and the tree’s resistance to the pathogen. The article gives an overview of the symptoms and the etiology of the disease and provides information on ways to recognize the disease and limit the economic damage.

The purpose of this study was to better understand the interactive impact of two soil-borne pathogens, Phytophthora cactorum and Armillaria gallica, on seedlings of silver birch (Betula pendula Roth.) subjected to stress caused by mechanical defoliation, simulating primary insect feeding. This is the first experimental confirmation of silver birch seedling root damage (and in consequence shoot mortality) caused by the additive effect of defoliation stress and P. cactorum inoculation via soil. However, the most severe damage to roots occurred after A. gallica inoculation. One year after treatments, chlorophyll fluorescence measurement, and gas chromatography coupled with mass spectrometry (GC-MS) were used to analyze the photosynthetic activity in leaves, the volatile organic compounds (VOCs) emitted by the birch leaves, and chemical compounds from the roots. The cumulative effect of the two pathogens and partial defoliation reduced photosynthetic activity, suggesting dysfunction of photosystem PSII due to the applied stresses. In summary, it seems that the main differences in photosynthetic performance could be attributed to Armillaria infection. The birch leaves in seedlings exposed to 50% defoliation, and inoculation with P.cactorum and A. gallica, emitted more aromatic carbonyls and alcohols, as well as half as much aliphatic esters, compared to controls. In infected birch roots, the production of phenols, triterpenes, and fatty alcohols increased, but fatty acids decreased. Higher levels of aromatic carbonyls and alcohols in leaves, as well as phenolic compounds in the roots of stressed birches (compared to control) suggest an activation of plant systemic acquired resistance (SAR).

The presence of forest tree pathogens may lead to substantial problems and their early detection during seed storage or in nurseries may be critical for the choice of appropriate management strategy. A new construction of a low-cost electronic nose was tested on the samples of pathogenic fungi and oomycetes of Fusarium oxysporum and Phytopthora plurivora . The electronic nose uses Figaro Inc. TGS series sensors with applied heater voltage modulation. Such a mode of electronic nose operation may be more appropriate for application for constant monitoring of seeds storage, when we compare it to the method making use of modulation of the gas concentration. A rectangular shape of the sensors’ heater voltage modulation pattern, with a shallow drop of the heater voltage from the nominal voltage, was proposed. Data visualization using the principal component analysis method and the random forest machine learning technique was used to build classification models. A classification accuracy of 97% was obtained by a fusion of data collected by TGS 2610 and TGS 2602 sensors.