# Contribution of grape-associated fungal species to the FMA defect on grapes and in musts

Adrien Destanque, Flora Pensec, Adeline Picot, Anne Thierry, Marie-Bernadette Maillard, Alexis Commereuc, Elisabeth Poirier, Louis Coroller, Emmanuel Coton, Marion Hervé, et al.

► To cite this version:

Adrien Destanque, Flora Pensec, Adeline Picot, Anne Thierry, Marie-Bernadette Maillard, et al. Contribution of grape-associated fungal species to the FMA defect on grapes and in musts. LWT - Food Science and Technology, 2026, 241, pp.118945. 10.1016/j.lwt.2025.118945. hal-05507613

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# Contribution of grape-associated fungal species to the FMA defect on grapes and in musts

Adrien Destanque<sup>a,b</sup>, Flora Pensec<sup>a</sup>, Adeline Picot<sup>a</sup>, Anne Thierry<sup>c</sup>, Marie-Bernadette Maillard<sup>c</sup>, Alexis Commereuc<sup>a</sup>, Elisabeth Poirier<sup>a</sup>, Louis Coroller<sup>a</sup>, Emmanuel Coton<sup>a</sup>, Marion Hervé<sup>b</sup>, Monika Coton<sup>a, *, D</sup>

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

### Keywords:

Mycobiota

Fungal growth models

Fresh mushroom aroma

Co-inoculations

Volatile organic compounds (VOCs)

## ABSTRACT

Among reported wine defects, the fresh mushroom aroma (FMA) off-odor has been linked to fungal volatile compounds (VOCs). However, the fungi causing this defect and the associated VOCs have not been fully elucidated, except for some reported FMA markers. Also, the biotic and abiotic factors impacting fungal growth and FMA production are poorly understood. Here, using a multidisciplinary approach combining predictive and classical mycology, sensorial and biochemical analyses, we determined growth patterns and VOCs profiles for 18 grape-associated fungal isolates, individually or in co-inoculation, on must media or Meunier grapes. FMA was primarily linked to *Penicillium* species, especially *Penicillium croicicola* with high intensity. On grapes, *Botrytis cinerea* co-inoculations with *Penicillium bialowiezense* or *Penicillium citreonigrum* led to detectable FMA off-odors and an increase in 3-octanol and 3-octanone FMA markers. *Penicillium* species competitively grew with *Botrytis* on grapes in comparison to other fungi, often leading to higher FMA perception. Fungal growth kinetics on must-based media were determined, and fastest growth rates were observed for *Botrytis cinerea* and *Penicillium croicicola* isolates although most fungi were able to grow in a wide range of conditions. Overall, our results pinpointed which individual and co-inoculated grape-associated fungi thrived on berries and in must conditions, and which combinations favored FMA off-odor production. This data can be used for better vineyard management practices and to anticipate potential conditions leading to FMA emergence in the future and in link with climate change and develop predictive tools for better vineyard management.

## 1. Introduction

Fungal contaminations are known to cause significant yield losses in vineyards, and some may induce organoleptic deviations in wines thus compromising their quality and commercialisation (Rousseaux et al., 2014; Steel et al., 2013). Climatic conditions during grape berry ripening and harvest, especially linked to humidity and temperature, may exacerbate undesirable fungal colonization and growth on berries. Fungi are well-known producers of volatile organic compounds (VOCs) inducing off-odors, including earthy moldy taste (EMT) or the fresh mushroom aroma (FMA) off-flavor (Delcros et al., 2023; Destanque et al., 2024; La Guerche et al., 2006). Moreover, some fungal interactions can further intensify such off-odors (La Guerche et al., 2007; Destanque et al., 2024). Among known fungal contaminants, *Plasmopara*

*viticola* can produce undesirable aromas such as cooked fruit and grassy notes, notably characterized by an increase in 3-methyl-2,4-nonanedione (Pons et al., 2018). *Botrytis cinerea* negatively impacts sensory properties of grapes by oxidizing phenolic compounds, modifying quinolones and affecting essential aroma compounds like monoterpenes (Bock et al., 1986; Bojkov et al., 2020). Other molds such as *Penicillium* species (e.g, *P. brevicompactum*, *P. thomii*, *P. expansum*, *P. carneum*) are frequently identified as fruit contaminants as they grow rapidly on harvested grapes and produce numerous volatile compounds including 1-octen-3-ol or geosmin/2-methylisoborneol, contributing to FMA and EMT in wines, respectively (La Guerche et al., 2006). Geosmin, a highly volatile fungal metabolite, creates a persistent earthy taste and this compound is detectable at concentrations as low as 4 ng/L (Liato and Aïder (2017). Filtered grape juice precultures carried out with some

<footnote><sup>a</sup> Univ Brest, INRAE, Laboratoire Universitaire de Biodiversité et Ecologie Microbienne, Plouzané, F-29280, France</footnote>

<footnote><sup>b</sup> Centre de Recherche Robert-Jean de Vogüé, Moët-Hennessy, Oiry, F-51530, France</footnote>

<footnote><sup>c</sup> INRAE, Institut Agro, UMR STLO, Rennes, F-35000, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: monika.coton@univ-brest.fr (M. Coton).</footnote>
B. cinerea strains led to a higher geosmin production by P. expansum (La Guerche et al., 2007), suggesting that undesirable volatile compounds may be the result of direct or indirect fungal interactions.

FMA was described in 2005 as an emerging sensorial defect in wines (Meistermann et al., 2021) and is still a challenge for the winemaking professionals. To date, mainly saturated and unsaturated seven (C7), eight (C8) and nine carbon (C9) VOCs have been linked to FMA off-odors (Darriet et al., 2002; Delcros et al., 2023; La Guerche et al., 2006; Ployon et al., 2025; Pons et al., 2011); however, other VOCs, alone or in combinations, may lead to FMA off-odors or increase FMA perception and should be considered. The main reported compounds include 1-octen-3-ol, 2-octen-3-ol, 1-octen-3-one (Steel et al., 2013), and more recently 1-hydroxyoctan-3-one (Delcros et al., 2023) and its derivative octane-1,3-diol (Ployon et al., 2025). Notably, 1-octen-3-one has a strong odorant potential, with a perception threshold as low as 40 ng/L in neutral white wine (Pons et al., 2011). Several fungi, including B. cinerea, Erysiphe necator, Alternaria spp., Aspergillus niger or other Aspergillus section Nigri species, Crustomyces subabruptus, P. thomii, P. brevicompactum and P. glabrum are known producers of these FMA-associated compounds (Börjesson et al., 1992; Darriet et al., 2002; Kaminski et al., 1974; La Guerche et al., 2006; Lopez Pinar et al., 2016; Meistermann et al., 2021; Rousseaux et al., 2014). Oxidation of linoleic acid by lipoxygenase is described as the starting point for some FMA-associated compound metabolic pathways among Basidiomycota and Ascomycota phyla members (Tasaki et al., 2019). Concerning the newly identified 1-hydroxyoctan-3-one (Delcros et al., 2023), this molecule is potentially a precursor or a product of 1-octen-3-one. It was recently identified in C. subabruptus lab-contaminated musts that led to the FMA defect in the corresponding wines. The identification of its derivative octane-1,3-diol in oenological matrices provides a new means to discriminate against musts with FMA potential as well as FMA wines (Ployon et al., 2025). In general, the FMA defect tends to appear after vinification, making early detection of these VOCs very challenging during the winemaking process (Delcros et al., 2023; La Guerche et al., 2006) and reinforcing the need for early detection of relevant analytical but also fungal markers. A better understanding of the role of fungal species, individually or in combinations, on grapes or in musts, in FMA off-odor production is key and should lead to improved vineyard management practices and overall microbiological grape quality in the future.

Unanswered questions were thus addressed in this study, namely i) which grape-associated fungi are involved in the FMA defect? ii) what volatile compounds are produced by these fungal species and which ones can be linked with FMA, and iii) what must or berry associated conditions favor fungal growth or contribute to the FMA off-odor? To address these questions, we selected 18 fungal isolates based on the off-odors, including FMA, they produced. Then, we determined their VOCs production profiles after growth on must media or Meunier berries using headspace GC-MS. Finally, we evaluated the impact of temperature, pH and fungal interactions favoring growth and/or FMA off-odor production. This data provides new knowledge on both the impact of biotic and abiotic factors favoring fungal growth and FMA defect in the context of viticultural practice transitions and climate change.

# 2. Material and methods

## 2.1. Selection and identification of fungal isolates with strong off-odors

### 2.1.1. Fungal isolate collection

Fungal isolates were previously collected from grapes sampled in Pinot noir and Meunier vineyards located in the Northeast region of France, spanning the Côtes des Blancs to the Massif Saint Thierry, during the 2021 harvest period as well as in the resulting musts (Destanque et al., 2024). This unique fungal culture collection included 685 grape-associated molds (Destanque et al., 2024). This collection was further completed with fungal isolates belonging to the Robert-Jean de

Vogüé research center culture collection. All filamentous fungi were cryopreserved in 10 % (v/v) glycerol at -80 °C.

### 2.1.2. Selection of isolates associated with strong off-odor perception

During fungal isolation and purification, isolates with pronounced and detectable off-odors, such as fresh mushroom (FMA) or earthy (EMT), were selected as follows. Among the 685 grape-associated molds (Destanque et al., 2024), a subset of 80 isolates representative of the observed diversity (i.e. species, vineyard plots, sampling stage, grape variety) were further screened by olfactory analysis for off-odors after 7-days growth on M2Lev medium at 25 °C. Sensory analyses were carried out by 4 panelists. For each isolate, an intensity score was attributed to each off-odor class. The score ranged from 0, meaning no FMA or EMT off-odor was detected, to 5, indicating that a strong off-odor was detected. Then, 18 isolates, among those associated with the strongest off-odors, were further selected to ensure efficient representativeness of grape-associated fungal diversity and prevalence (Table 1). This final selection was therefore first based on their FMA and EMT off-odor intensities, except for Keratinophyton submersum that produced a distinct bell pepper off-odor. We also selected fungi isolated from various geographical locations (i.e. vineyard plots) and grape varieties.

### 2.1.3. Monospore preparations

The 18 selected isolates were purified using a monospore isolation technique. After 5-days growth on M2Lev agar (supplemented with penicillin 10,000 U/L and streptomycin 100 mg/L), 2 mL of sterile water supplemented with 0.2 % (w/v) Tween 80 were added to the culture surface and spores were sterilely scraped off. Spore suspensions were quantified using a Malassez cell, then diluted to reach concentrations of $10^6$ spores/mL. Subsequently, 100 µL of each dilution was plated on Potato Dextrose Agar (PDA, Biomérieux, France). After 15-30 h incubation at 25 °C (depending on the considered fungal species), well-isolated spores were selected using a binocular loupe and explants were extracted before being plated onto M2Lev agar and incubated at 25 °C for 7-10 days. After growth, 2 mL of water supplemented with Tween 80 (Sigma-Aldrich) were added to the surface to collect a spore suspension. Each suspension was quantified using a Malassez cell, then diluted to obtain a stock suspension at $10^6$ spores/mL. Calibrated monospore suspensions were cryopreserved at a final concentration of 10 % glycerol (v/v) and stored at -80 °C until use.

### 2.1.4. Species level identification of fungal isolates

For each selected isolate and after 7 days growth on M2Lev plates at 25 °C, fungal biomass was collected and transferred to a Lysing Matrix A tube (MN Bead Tubes Type A 50p from Machery - Nagel SAS) containing 1 mL of lysis solution (Mag-Bind Universal Pathogen DNA Kit, VWR International SAS). The tube contents were mixed vigorously at 30 Hz for 30 s three times using a mixer mill (Retsch MM400) before centrifugation for 10 min at 14000 g. DNA purification was performed using the KingFisherDuo Prime Purification System (Thermo Scientific), following manufacturer's instructions. DNA aliquots were stored at -20 °C. For species-level identifications, isolates were pre-identified to the genus level based on macroscopic morphology to select the most relevant taxonomic target, namely the β-tubulin gene for Penicillium (targeted by the Bt2a/Bt2b primers, Glass & Donaldson, 1995), the actin gene for Cladosporium (Act512F/Act783R primers, Carbone & Kohn, 1999) and the internal transcribed spacer (ITS) region for other molds (ITS 4/ITS 5 primers, White et al., 1990). In addition to the ITS barcode, Botrytis isolates were further identified by sequencing the HSP60 region (HSP60for+/HSP60rev + primers, Staats, 2004). PCR conditions described in Destanque et al. (2024) were used. Sequencing was performed by the GATC sequencing platform (Eurofins, Germany). The obtained sequences were trimmed and assembled using Geneious before blasting against the nr/nt database (blastn) (Altschul et al., 1990).
<caption>**Table 1**</caption>

Selection of 18 isolates based on the perception of off-odors on M2Lev medium by 4 panelists, list of isolate codes from the LUBEM collection, origins and their use in this study (*MHCS Collection). Scores correspond to the maximum score attributed by at least two panelists, ranging between 0 and 5, 5 being the highest perceived intensity (**: descriptor was perceived by only one panelist and is thus scored 0). Bc: *B. cinerea*; Cr: *C. rosea*; Cls: *C. subtilissimum*; Pbi: *P. bialowiezense*; Pbr: *P. brevicompactum*; Pci: *P. citreonigrum*; Pcr: *P. crocicola*; Tm: *T. minioluteus*; Chs: *K. submersum*; EMT earthy musty taste; FMA: fresh mushroom aroma.

<table><thead><tr><th>Isolate codes</th><th>Descriptor</th><th>Score</th><th>Sampling stage</th><th>Sampling variety</th><th>Species identification</th><th>Used in single inoculations</th><th>Used in co-inoculation experiments</th></tr></thead><tbody><tr><td>Bc1</td><td>EMT</td><td>3</td><td>Must</td><td>Pinot noir</td><td>Botrytis cinerea</td><td>X</td><td>X</td></tr><tr><td>Bc2</td><td>FMA</td><td>3</td><td>Harvest</td><td>Meunier</td><td>Botrytis cinerea</td><td>X</td><td>X</td></tr><tr><td>Clsl</td><td>FMA</td><td>3</td><td>Harvest</td><td>Pinot noir</td><td>Cladosporium subtilissimum</td><td>X</td><td>X</td></tr><tr><td>Cr1</td><td>EMT</td><td>1</td><td>Veraison</td><td>Meunier</td><td>Clonostachys rosea</td><td>X</td><td>X</td></tr><tr><td>Pbi1</td><td>FMA</td><td>0**</td><td>Must</td><td>Meunier</td><td>Penicillium bialowiezense</td><td>X</td><td>X</td></tr><tr><td>Pci1</td><td>FMA</td><td>3</td><td>Must</td><td>Pinot noir</td><td>Penicillium citreonigrum</td><td>X</td><td>X</td></tr><tr><td>Pcr1</td><td>FMA</td><td>4</td><td>*Collection</td><td>*Collection</td><td>Penicillium crocicola</td><td>X</td><td>X</td></tr><tr><td>Pcr2</td><td>FMA</td><td>5</td><td>Must</td><td>Meunier</td><td>Penicillium crocicola</td><td>X</td><td>X</td></tr><tr><td>Bc3</td><td>FMA/EMT</td><td>2</td><td>Must</td><td>Pinot noir</td><td>Botrytis cinerea</td><td>X</td><td>X</td></tr><tr><td>Bc4</td><td>EMT</td><td>0**</td><td>Harvest</td><td>Pinot noir</td><td>Botrytis cinerea</td><td>X</td><td>X</td></tr><tr><td>Chs1</td><td>Other</td><td>2</td><td>NA</td><td>Pinot noir</td><td>Keratinophyton submersum</td><td>X</td><td>X</td></tr><tr><td>Pbi2</td><td>FMA</td><td>3</td><td>Veraison</td><td>Meunier</td><td>Penicillium bialowiezense</td><td>X</td><td>X</td></tr><tr><td>Pbi3</td><td>FMA</td><td>4</td><td>Harvest</td><td>Pinot noir</td><td>Penicillium bialowiezense</td><td>X</td><td>X</td></tr><tr><td>Pbr1</td><td>EMT</td><td>3</td><td>Harvest</td><td>Meunier</td><td>Penicillium brevicompactum</td><td>X</td><td>X</td></tr><tr><td>Pcr3</td><td>FMA</td><td>5</td><td>*Collection</td><td>*Collection</td><td>Penicillium crocicola</td><td>X</td><td>X</td></tr><tr><td>Pcr4</td><td>FMA</td><td>3</td><td>Must</td><td>Pinot noir</td><td>Penicillium crocicola</td><td>X</td><td>X</td></tr><tr><td>Pcr5</td><td>FMA</td><td>5</td><td>Veraison</td><td>Pinot noir</td><td>Penicillium crocicola</td><td>X</td><td>X</td></tr><tr><td>Tm1</td><td>FMA</td><td>5</td><td>*Collection</td><td>*Collection</td><td>Talaromyces minioluteus</td><td>X</td><td>X</td></tr></tbody></table>

## 2.2. Impact of fungal isolates, grown alone or in co-inoculations, on VOC production

### 2.2.1. Fungal cultures on synthetic must solid medium and Meunier grapes

The selected 18 fungal isolates were grown alone or in co-inoculation experiments on two different matrices, synthetic must medium (SM) and Meunier grape berries. The SM grape must medium was prepared as follows: glucose (100 g/L), fructose (100 g/L), yeast extract (1 g/L), (NH₄)₂SO₄ (2 g/L), citric acid (0.3 g/L), l-malic acid (5 g/L), l-tartaric acid (5 g/L), MgSO₄ (0.4 g/L), KH₂PO₄ (5 g/L), NaCl (0.2 g/L), MnSO₄ (0.05 g/L), agar (15 g/L) with pH adjusted to 3.2 (Rossouw et al., 2012). For co-inoculation experiments, 6 isolates associated with either strong FMA off-odors (*Cladosporium subtilissimum* Cls1, *P. citreonigrum* Pci1, *P. crocicola* Pcr1 and Pcr2, Table 1), low FMA off-odors (*P. bialowiezense* Pbi1) or low EMT off-odors (*Clonostachys rosea* Cr1) were selected. These 6 isolates were co-inoculated with either *B. cinerea* Bc1, linked to earthy off-odors, or *Bc2*, linked to FMA off-odors (Table 1 and Table S1). These two *Botrytis* isolates were selected not only based on their odor intensity scores, but also based on their different geographical locations and the fact that we previously showed that *Botrytis* spp. co-occurred with *Penicillium* spp. in samples leading to FMA off-odors (Destanque et al., 2024). All experiments were performed in triplicates and all cultures were incubated at 20 °C in darkness. On SM medium, inoculations were performed using 2 µL of each calibrated monospore suspension (10⁶ spores/mL) at the center of the plate for single inoculations and at a 1 cm distance for co-inoculations. On Meunier grapes, individual berries with peduncles were first sorted according to their density by placing them in different concentrations of food grade sugar solutions ranging from 190 g/L to 300 g/L to select berries with similar degrees of ripeness. We selected the berries that sank in the 280 g/L solution but floated in the 290 g/L solution. The selected Meunier grape berries were then washed with distilled water, followed by 20 s in 70 % ethanol and a final rinse with sterile water before being transferred to a sterile tube (30 mL). Under sterile conditions, berries were subsequently punctured (with one or two punctures according to whether isolates were single or co-inoculated) using a sterile needle. Next, 5 µL of a calibrated spore suspension (10⁶ spores/mL) were inoculated directly onto the wound for individual isolates or onto two wounds spaced at 0.5 cm for co-inoculation experiments (Table S1). For co-inoculations, *B. cinerea* (Bc1) was inoculated using 2 µL and *B. cinerea* (Bc2) using 1.5 µL (10⁶ spores/mL). The inoculated berries were then incubated in the dark at 20 °C for 35 days. A total of six replicates were performed for the berry inoculation experiments with individual or co-inoculations. The three

replicates showing the most homogeneous fungal colonization were then selected for subsequent sensory, VOC, and growth analyses. Fungal colonization of Meunier grapes was assessed macroscopically daily and expressed as the percentage of grape berry surface colonized by fungal growth (0–10%; 10–25%; 25–50%; 50–99%; 100%), as described in Table S1.

### 2.2.2. Untargeted volatile organic compound measurement and sensorial analyses

For SM, only GC-MS chemical analyses were conducted. After 15 days of growth, agar plugs (2.5 g ± 0.1 g) were sampled at the margin of the thallus, for single inoculations, and at the junction of the 2 mycelia, for co-inoculations. The plugs were transferred to 22 mL PerkinElmer vials and then hermetically sealed and stored at –80 °C until analysis. All experiments were done in triplicates.

For inoculated Meunier grape berries, after 20 days of growth, sensory analyses were conducted by four panelists to detect FMA or EMT odors; other odors were annotated as ‘-’. The panelists were asked to determine their perception of FMA and EMT based on the intensity score previously described in section 2.1.2 (Table S1).

After 31 days of growth, the berries were then manually crushed and 1 ± 0.1 g portions of each were placed in 22 mL PerkinElmer vials, hermetically sealed, and stored at –80 °C until analysis. All experiments were done in triplicate.

VOCs were analyzed using an untargeted approach by headspace gas chromatography-mass spectrometry (HS-GC-MS) as described by Savary et al., 2023. Briefly, volatile compounds were extracted using a PerkinElmer Turbomatrix HS-40 trap automatic headspace sampler with trap enrichment and a Clarus 680 gas chromatograph coupled to a Clarus 600 T quadrupole mass spectrometer (PerkinElmer, France). Samples were injected in a random order. VOCs were identified by comparing their retention index (RI) and mass spectra to those of molecules in the NIST 2008 Mass Spectral Library (Scientific Instrument Services, Ringoes, NJ, United States), and with those reported in the literature but also, when available, with standards (Sigma Aldrich, France) analyzed in the same conditions. VOCs were semi-quantified from the abundance of one specific mass fragment (m/z), in arbitrary units. GC-MS data were processed using the PerkinElmer Turbomass software, version 5.4.2.1617 and by converting the raw data to time- and mass-aligned chromatographic peaks areas using the open source XCMS package implemented with the R statistical language (Smith et al., 2006). For quantification, the method described by Pogačić et al., 2015 was used and the linearity range, limit of detection (LOD) and limit of quantification determined
for ten neutral and 8 acidic VOCs in an aqueous solution. LOD ranged between 2 and 8 ng/g for neutral VOCs and 33 and 586 ng/g for acidic VOCs.

## 2.3. Impact of abiotic and biotic parameters on fungal growth

### 2.3.1. Fungal growth monitoring in synthetic must and Meunier grape must solid media

The SM medium previously described and Meunier grape must medium (real must, RM; must obtained from the 2021 harvest, filtered using 0.2 µm filters and stored at -20 °C before use) supplemented with 1.2 % of agarose (agar sterilized at 121 °C for 15 min) were used for growth experiments. Fungal inoculation was performed by spotting 2 µL of each calibrated spore suspension (10⁶ spores/mL) onto the center of the plates. Triplicates of each condition were incubated at 20 °C for 15 days. Radial growth was measured daily by assessing the perpendicular distances, and the average of the two measurements was calculated.

### 2.3.2. Impact of temperature and pH on fungal growth kinetics determined in synthetic liquid must by laser nephelometry

High throughput monitoring of fungal growth in liquid media was performed using laser nephelometry. Two abiotic factors were tested: temperature (4, 8, 14, 20, 25, 27, 30, 34, 40 °C with a pH adjusted to 3.20) and pH (2.45, 3.20, 4.50, 5.65, 6.55, 7.22, 8.50 with the temperature set to 20 °C). Ninety-six well plates (Nunc 96, Thermo Scientific) were filled with 190 µL of SM medium but without agar. Ten µL of calibrated fungal monospore suspensions (10⁶ spores/mL) or of water with Tween 80, for negative controls, were added. All experimental conditions were performed in triplicate. Growth was recorded daily for 22 days using a NEPHELOstar Plus reader (BMG Labtech, France) with a 635 nm laser. Before each reading, plates were shaken at 300 rpm for 1 s using the “double orbital” shaking mode. Laser intensity was set at 70 %, with a focus of 2.5 mm.

At the end of each monitoring period, nephelometric growth kinetics, expressed in Relative Nephelometric Units (RNUs), were acquired. The data was compiled using Microsoft Excel after export from NEPHELOstar Galaxy software for nephelometry. Each kinetic curve was fitted using the modified Gompertz equation (primary sensing, Equation (1)) (Zwietering et al., 1990):

$$y = a \cdot \exp \left[ - \exp \left( \frac{\mu_m \cdot \exp(1)}{a} \right) \cdot (\lambda - t) + 1 \right] \qquad \text{Equation (1)}$$

where y represents the RNUs recorded at the time t, a corresponds to the maximum amplitude of the signal, μm is the maximum growth rate (RNU/d), and λ is the latency time (day), corresponding to the time before fungal growth detection. The threshold a was fixed to a mean value estimated by isolate to ensure convergence on all kinetics. The fixed a values were 1.4 × 10⁶ for the Bc1, Bc2, Cls1, Cr1, Pcr1, Pcr3, Pbi2, Tm1, Pcr4, Pbi3, Pcr5, Bc3 isolates; 1 × 10⁶ for the Pci1, Pcr2, Pbr1, Bc4 isolates; 0.85 × 10⁶ for isolate Chs1 and 0.65 × 10⁶ for isolate 5.

For secondary modeling, maximum growth rates were fitted by the cardinal model (Equations (2) and (3); Dagnas & Membré, 2013; Mason, 2006):

$$\mu_m = \mu_{opt} \cdot CMn(X) \qquad \text{Equation (2)}$$

where, μopt corresponds to the optimum growth rate (RNU/d), X represents the studied factor (either temperature or pH). CMn(X) reflects the impact of the environmental factor on the growth rate. Xopt, Xmin, and Xmax are, respectively, the optimum, minimum, and maximum values of growth for the considered factor X, with n = 2 for temperature and n = 1 for pH.

The primary and secondary models were fitted with these equations by minimizing the sum of squares error (nlinfit function in MATLAB R2018b software, Natick, Massachusetts: The MathWorks Inc.). Five-percent confidence intervals were calculated using the Jacobian matrix (nlparchi function, MATLAB R2018b software, Natick, Massachusetts: The MathWorks Inc.). The root mean square error (RMSE) was computed as fitting criteria.

## 2.4. Statistical data treatment

The JMP software (V15.1, 2020, SAS) was used to compare the means of the FMA score given by each panelist between monocultures and co-inoculations conditions (Kruskal Wallis and Wilcoxon pairwise test). It was also used to perform a hierarchical classification (Ward method) and generate a heat map of the detected VOCs (as variable), for isolates (as individuals) on Meunier grape berries and on must medium, for each condition (isolates alone or in co-inoculation). A principal component analysis (with centered-reduced data) of the VOC profile distribution (as variable) on Meunier grape berries according to each cluster (as individuals) was also performed with JMP, in each condition (isolates alone or in co-inoculation). Complementary to JMP, a principal component analysis (PCA) was also performed by using the PCA function of the FactoMineR R package on the volatile profile in the different monocultures or cocultures. Hierarchical clustering was performed on PCA data. The association of qualitative variables with sample clusters was investigated by using v-tests and was considered significant for v-test values < -2 or >2.

Production of volatile compounds associated with FMA off-odors was evaluated based on the abundance of a selected mass fragment, expressed in arbitrary units semi-quantified by HS-GC-MS). Then, for each compound, mean abundance was compared between mono- and co-cultures using either the Tukey or Wilcoxon pairwise test, depending on normality conditions evaluated by Shapiro-Wilk test and residual distributions.

For radial growth analyses, an analysis of variance (ANOVA) was performed with the R software version 4.2.3 (supported by 2024 R Consortium) under the RStudio environment (2024-02-29) to compare growth rates of the tested isolates and evaluate medium effect. A Tukey post-hoc test was then performed to compare means between isolates for each of the two tested media.

# 3. Results

## 3.1. Selection of isolates producing high intensity off-odors

From a collection of 685 grape berry and must-associated molds isolates (Destanque et al., 2024), 80 isolates, representative of the taxonomic diversity and sampling sources (vineyards, grape variety, berry development stage), were screened for their ability to produce FMA or EMT off-odors after 7 days growth on M2Lev, a malt agar based medium. This pre-selected collection contained isolates belonging to 10

$$\text{If } X \le X_{\min} \text{ or } X \ge X_{\max} \quad \text{then} \quad CMn(X) = 0 \\ \text{If } X_{\min} < X < X_{\max} \quad \text{then} \quad CMn(X) = \frac{(X - X_{\max}) \cdot (X - X_{\min})^n}{(X_{\opt} - X_{\min})^{n-1} \{ (X_{\opt} - X_{\min}) \cdot (X - X_{\opt}) - (X_{\opt} - X_{\max}) \cdot [(n-1) \cdot X_{\opt} + X_{\min} - n \cdot X] \}} \qquad \text{Equation (3)}$$
identified genera, namely Penicillium (52.5 %), Botrytis (18.75 %), Talaromyces (12.5 %), Cladosporium (7.5 %), Acremonium (2.5 %), Clonostachys (2.5 %), Aspergillus (1.25 %), Epicoccum (1.25 %) and Keratinophyton (1.25 %). Based on the sensory analysis, we further selected 18 isolates that produced strong FMA or EMT odors, except for Keratinophyton characterized by a strong bell pepper off-odor (Table 1). They belonged to 6 genera and included 9 species (their macroscopic aspect is shown in Fig. S1), namely Botrytis cinerea (n = 4 isolates), Cladosporium subtilissimum (n = 1), Clonostachys rosea (n = 1), Keratinophyton submersum (n = 1), Penicillium bialowiezense (n = 3), Penicillium citreonigrum (n = 1), Penicillium crocicola (n = 5), Penicillium brevicompactum (n = 1), and Talaromyces minioluteus (n = 1). Among the odors detected during this first sensorial analysis (Table 1), FMA was primarily linked to Penicillium spp., especially P. crocicola with high-intensity FMA scores ranging from 4 to 5 (Table 1) while other fungal species, such as B. cinerea, produced EMT and/or FMA odors. Two isolates of B. cinerea (Bc1 and Bc2) produced distinct and different off-odors, EMT and FMA, respectively, and were further selected for co-inoculation experiments. Off-odors produced by C. subtilissimum, C. rosea and K. submersum were associated with a low to medium perception of FMA, EMT and "Other" (spicy/bell pepper) off-odors, respectively (Table 1).

## 3.2. Identification and semi-quantification of volatile organic compounds

### 3.2.1. Volatile compound production by fungal isolates on synthetic must medium

VOC production profiles of the 18 fungal isolates were first determined using the SM medium. Isolates of interest were grown alone and in co-inoculation experiments with the two selected B. cinerea isolates, Bc1 and Bc2, to determine to what extent their VOC production profiles changed in the presence of the latter isolates. Overall, a total of 92 compounds were identified from single and co-inoculations of fungal isolates on SM medium. Among these compounds, 27 % corresponded to aldehydes, 23 % to ketones, 15 % to alcohols, 12 % to acids, 12 % to esters, 7 % to alkanes, 2 % to alkenes and 2 % to amides. Details of all identified VOCs are given in Fig. S2 and Table S2 (sheet 1). Hierarchical classification clustered the VOC profiles according to isolates and/or species (Fig. S2). Cluster 1 mainly included B. cinerea (both isolates Bc1 & Bc2) grown alone or in co-inoculation experiments with C. subtilissimum. Cluster 2 mainly included P. citreonigrum and P. bialowiezense, alone or in co-inoculations with both B. cinerea isolates, as well as P. brevicompactum alone. Cluster 3 included all controls (uninoculated SM medium) as well as T. minioluteus and C. subtilissimum cultures, while cluster 4 contained most P. crocicola isolates grown alone or in co-inoculation with the two B. cinerea isolates (Fig. S2). As shown, distinct shifts in VOC production intensities and/or profiles were observed for most fungal isolates grown alone in comparison to when they were co-inoculated with B. cinerea isolates. The strongest variations that separated mono- and co-inoculations were observed for P. citreonigrum, C. subtilissimum, P. bialowiezense and P. crocicola (Fig. S2) thus indicating that fungal interactions modified VOC production profiles in the tested conditions.

### 3.2.2. Growth, volatile compound production and sensory analysis on Meunier grape berries

To better mimic grape berry conditions, VOC production profiles were also determined for the 18 isolates inoculated alone or co-inoculated (using the same two B. cinerea isolates) directly on Meunier berries to evaluate how the actual matrix (i.e. grape berries) influenced VOC, including FMA-associated compounds, production. In single inoculations, B. cinerea, T. minioluteus, P. crocicola and P. brevicompactum were all able to colonize the entire surface of wounded berries within 31 days. In co-inoculations with B. cinerea isolates, only two P. crocicola isolates were able to colonize half of the berries with B. cinerea, the growth of each species being well separated from each other, while P. citreonigrum, C. rosea and C. subtilissimum colonized only 10 % of the

grape berry surface and both B. cinerea isolates completely covered the berries with their mycelium over time (Table S1). K. submersum was unable to grow regardless of whether it was inoculated alone or co-inoculated on berries. After 20 days of incubation, sensory analyses of the Meunier grape berries were conducted to determine if off-odors were detected by the panel. In single inoculations, P. crocicola isolates were associated with low FMA off-odors for Pcr1, Pcr2 and Pcr3 and strong FMA off-odors for Pcr4 and Pcr5, while the other species and isolates were associated with EMT or no detected target off-odor (Table S1). While B. cinerea isolate Bc1 was consistently associated with EMT on both substrates, Bc2, which was qualified as a FMA producer on M2Lev malt medium, was associated with EMT on Meunier grapes.

For volatile compounds, 92 compounds were identified from the Meunier grape berry experiments after 31 days growth and included 35 % alcohols, 20 % aldehydes, 14 % ketones, 11 % acids, 9 % esters, 5 % alkenes, 3 % alkanes, 1 % amides and 1 % terpenes (Table S2, sheet 2). In addition, an unidentified compound (Unknown_1) not present in the NIST database was quantified by the abundance of two *m/z* fragments (Unknown_43 and Unknown_99). It was putatively identified as 1-hydroxyoctan-3-one, as i) its mass spectrum was very similar to that of the latter molecule (Fig. S3) as recently described by Delcros et al. (2023), and ii) its retention time (~34.5 min) was close to the one predicted by linear regression done on compounds eluting in the same area of the chromatogram in Delcros et al. (2023) and in the present study (data not shown). A second unidentified compound (Unknown_299) with a retention time of 36.07 min was also retained because it was in high abundance in the same cultures as the first unknown compound; however, this compound could not be identified (Table S2, sheet 2).

Based on hierarchical classification of VOC abundances produced by the different isolates, individually or in combinations, five distinct clusters were determined for Meunier berries (Fig. 1A for monocultures and 1B for co-inoculations). These clusters were then linked to the determined sensorial analysis off-odor descriptors by the panel (Fig. 1A). Cluster C1 included all B. cinerea strains with a detected EMT off-odor (detection of EMT and EMT + for 67 % of isolates by the panel). Clusters C2 and C4 included C. subtilissimum, P. bialowiezense, C. rosea, P. citreonigrum, K. submersum, P. brevicompactum, berry controls and one T. minioluteus replicate. Cluster C3 gathered all P. crocicola isolates, except for one replicate included in cluster 4 and was associated to the FMA descriptor as either FMA and FMA+ (40 % of isolates), FMA / EMT (21 %) or to "no FMA or EMT off-odors" (29 %) detected by the panel. Cluster C5 only included two out of three T. minioluteus (Fig. 1A).

VOC profiles for co-inoculation experiments were separated into four clusters (Fig. 1B). Cluster C'1 included co-inoculations between B. cinerea (both Bc1 & Bc2 isolates) with C. subtilissimum, P. bialowiezense and P. citreonigrum, and were mainly associated with EMT and EMT+ (39 %), FMA / EMT (30 %) or FMA (22 %) sensorial off-odors detected by the panel. Cluster C'2 included B. cinerea (Bc1 & Bc2) and two P. crocicola isolates (Pcr1 & Pcr2) and these combinations were associated with FMA and FMA+ detection (69 % in combinations). Cluster C'3 included B. cinerea (Bc1 & Bc2) and C. rosea co-inoculations and was linked to EMT (33 %) and FMA / EMT (67 %) off-odors while cluster C'4 included all control berries with no detected off-odors (Fig. 1B). Despite the fact that co-inoculation experiments did not significantly amplify the perception of FMA off-odors compared to monoculture experiments (p-value >0.05, Wilcoxon pairwise test), FMA off-odors were systematically perceived by the sensorial panel in co-inoculations between B. cinerea (Bc1, Bc2) and P. crocicola (Pcr1, Pcr2), but also with P. citreonigrum, P. bialowiezense and C. rosea. In contrast, FMA was not detected in P. citreonigrum, P. bialowiezense and C. rosea monocultures, and only detected by one panelist and for one replicate for P. crocicola (Pcr1) monocultures. Based on the generated data, principal component analysis (PCA) and hierarchical classification were also performed to determine which compounds were involved in the data clustering observed on the heatmaps. PCA followed by hierarchical classification
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Heatmap representation of the 92 volatile organic compounds (VOCs) identified after growth of the 18 fungal isolates inoculated either alone on Meunier grape berries (A), or for a subset of fungal isolates, co-inoculated with *B. cinerea* Bc1 and Bc2 (B). VOCs were identified after samples were incubated for 31 days at 25 °C. The ID of each isolate and the corresponding sensorial descriptor described in Table S1 are indicated on the left, while ('-') corresponds to no FMA or EMT detection. The heatmap was generated using hierarchical classification and the Ward method. Highest to lowest values are represented from red to blue.</figcaption></figure>
for both monocultures and co-inoculations significantly discriminated the clusters associated with the FMA off-odor (v-test values > 2). Considering the clusters involving *P. crocicola*, either in single (cluster C3 - strong FMA) or in co-inoculation conditions (cluster C'2 - associated with a strong FMA off-odor, Fig. S4), a total of ten compounds well-associated to these clusters were identified. Eight were identified in monoculture experiments (cluster C3 - strong FMA), namely ethyl 2-methylpropanoate; ethyl 2-methylbutanoate; dimethyl disulfide; 4-methyl-3-hexanone; 4-methyl-3-hexanol; 3,6-dimethylhexahydrobenzofuran; formic acid and 1,3-dimethoxybenzene. Among these compounds, ethyl 2-methylbutanoate; dimethyl disulfide; 4-methyl-3-hexanone; formic acid and 1,3-dimethoxybenzene were significantly more produced by members of cluster C3 than those of clusters C1 and C2 (p-value <0.005, Wilcoxon pairwise test). In co-inoculation experiments, five compounds were associated with cluster C'2, namely ethyl 3-hydroxy-3-methylbutanoate; 2-methoxyphenol as well as ethyl 2-methylbutanoate; formic acid and 1,3-dimethoxybenzene also associated with cluster C3. Among these compounds, 2-methoxyphenol and 1,3-dimethoxybenzene were significantly more produced by members of cluster C'2 than clusters C1 and C3 (p-value <0.005, Wilcoxon pairwise test).

A focus was then placed on specific VOCs associated with FMA reported in the literature. To highlight potential increases in the production of such compounds during co-inoculations, a comparison of abundances of these FMA-associated compounds in single and co-inoculations on Meunier grape berries was then performed. Interestingly, based on a mean comparison test, production of 3-octanol and 3-octanone was increased when *B. cinerea* (Bc2) and *P. bialowiezense* (Pbi1) were co-inoculated, compared to their respective single cultures (Anova test, p-values = 0.0012 and 0.024, respectively) and production of 3-octanol also significantly increased when *B. cinerea* (Bc1) was co-inoculated with *P. citreonigrum* (Pci1), compared to single cultures (Anova test, p-value = 0.0041, Fig. 2). These results thus confirmed that

fungal interactions, mainly between some *Penicillium* isolates and *B. cinerea* isolates, favored the production of various FMA-related VOCs on Meunier berries.

### 3.3. Impact of abiotic factors on fungal growth in synthetic and real musts

#### 3.3.1. Fungal growth monitoring in synthetic liquid must

In order to identify the abiotic conditions favoring fungal development, the growth rate of the 18 isolates in liquid SM at pH ranges from 2.45 to 8.5 and temperatures from 4 to 40 °C was calculated. Different

<caption>**Table 2**</caption>

Cardinal growth values for temperature for each of the 18 isolates and pH ranges for growth. Some values are not reliable (depicted in light grey italics) due to the model's lack of precision in certain instances. For genus name, see Table 1.

<table><thead><tr><th>ID</th><th>Species</th><th>T<sub>min</sub></th><th>T<sub>opt</sub></th><th>T<sub>max</sub></th><th>pH growth range</th></tr></thead><tbody><tr><td>Bc1</td><td><i>B. cinerea</i></td><td>-14</td><td>23.6</td><td>31.6</td><td>2.4-8.5</td></tr><tr><td>Bc2</td><td><i>B. cinerea</i></td><td>-20.6</td><td>24.7</td><td>25</td><td>3.2-8.5</td></tr><tr><td>Bc3</td><td><i>B. cinerea</i></td><td>-19.2</td><td>34</td><td>34</td><td>2.4-8.5</td></tr><tr><td>Bc4</td><td><i>B. cinerea</i></td><td>-42.1</td><td>24.9</td><td>25</td><td>2.4-8.5</td></tr><tr><td>Pcr1</td><td><i>P. crocicola</i></td><td>2.1</td><td>28.9</td><td>40</td><td>2.4-8.5</td></tr><tr><td>Pcr2</td><td><i>P. crocicola</i></td><td>1.3</td><td>31.2</td><td>40</td><td>2.4-8.5</td></tr><tr><td>Pcr3</td><td><i>P. crocicola</i></td><td>0.6</td><td>31.1</td><td>40</td><td>2.4-8.5</td></tr><tr><td>Pcr4</td><td><i>P. crocicola</i></td><td>0.9</td><td>26.7</td><td>34</td><td>2.4-8.5</td></tr><tr><td>Pcr5</td><td><i>P. crocicola</i></td><td>1.7</td><td>27</td><td>34</td><td>2.4-8.5</td></tr><tr><td>Pbi1</td><td><i>P. bialowiezense</i></td><td>-2.6</td><td>20.5</td><td>30</td><td>2.4-8.5</td></tr><tr><td>Pbi2</td><td><i>P. bialowiezense</i></td><td>4</td><td>17.5</td><td>30</td><td>2.4-7.2</td></tr><tr><td>Pbi3</td><td><i>P. bialowiezense</i></td><td>-15.4</td><td>23.3</td><td>30</td><td>2.4-8.5</td></tr><tr><td>Pbr1</td><td><i>P. brevicompactum</i></td><td>4.8</td><td>19.4</td><td>34</td><td>2.4-8.5</td></tr><tr><td>Pci1</td><td><i>P. citreonigrum</i></td><td>5.7</td><td>18.4</td><td>32.7</td><td>2.4-8.5</td></tr><tr><td>Tm1</td><td><i>T. minioluteus</i></td><td>8</td><td>21.8</td><td>34</td><td>2.4-8.5</td></tr><tr><td>Cr1</td><td><i>C. rosea</i></td><td>14</td><td>22.5</td><td>30</td><td>3.2-8.5</td></tr><tr><td>Chs1</td><td><i>K. submersum</i></td><td>9.6</td><td>22.6</td><td>30</td><td>2.4-8.5</td></tr><tr><td>Clsl</td><td><i>C. subtilissimum</i></td><td>4</td><td>19.3</td><td>30</td><td>3.2-7.2</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Mean and standard deviation of the amount of volatile organic compounds known to be associated with the FMA off-odor (e.g. 3-octanone, 1-nonanol, 1-octen-3-ol, 1-octen-3-one, 2-heptanone, 2-nonanone, 2-octen-1-ol and 3-octanol) analyzed by HS-GC-MS and expressed in arbitrary units produced during incubation on Meunier berries during 31 days at 25 °C mono- (red) and co-cultures (blue) of fungal isolates. Letters represent the significant differences between monoculture and co-inoculation experiments (Tukey HSD or Wilcoxon pairwise, according to the normality conditions, p-value <0.05).</figcaption></figure>

<figure><img src="image_5.png" /></figure>
growth patterns were observed among species and some intraspecific variations were also observed between isolates belonging to the same species (Table 2; Fig. S5). Based on secondary growth models, optimal growth for *B. cinerea* was observed at temperatures between 23.6 and 24.9 °C, with a maximum at 31.6 °C for the Bc1 isolate, but the lack of additional temperatures between 30 and 40 °C made it impossible to estimate the maximum growth temperature for some isolates (Bc2, Bc3 and Bc4). Species with the lowest optimal growth temperatures (ranging between 17.5 and 19.5 °C) were *P. citreonigrum* (Pci1), *P. brevicompactum* (Pbr1), *C. subtilissimum* (Cls1) and *P. bialowiezense* (Pbi2). On the contrary, *P. croicicola* grew optimally at higher temperatures ranging from 26.7 to 31.2 °C, with a maximum temperature between 34 and 40 °C, depending on the considered isolate (Table 2; Fig. S5). *P. bialowiezense* (Pbi1 and Pbi3), *T. minioluteus*, *K. submersum* and *C. rosea* presented optimal temperatures between 20.5 and 23.5 °C with a maximum growth temperature ranging from 30 to 34 °C depending on the considered species and isolates (Table 2; Fig. S5).

For pH, most isolates grew in all the tested conditions, from 2.4 up to 8.5, except for one *B. cinerea* isolates (Bc2), *C. subtilissimum* (Cls1) and *C. rosea* (Cr1) which were not able to grow below pH 3.2. *C. subtilissimum* and one *P. bialowiezense* (Pbi 2) isolate were also unable to grow above pH 7.2 (Table 2).

### 3.3.2. Fungal radial growth monitoring on solidified synthetic and real musts

Radial growth of the selected fungal isolates was also assessed on both gelified RM to mimic berry surface growth and SM media. The highest growth was observed for *B. cinerea*, ranging between 19-22.8 and 11.5-14.4 mm/day on RM and SM media, respectively, which was 4-20 times higher than for all other fungal isolates (Fig. 3). *P. croicicola*

showed average growth (5.2–7 and 3.5–5.1 mm/day on RM and SM media, respectively) while *C. subtilissimum* and *C. rosea* were the slowest species, with less than 1.3 mm/day on both media (Fig. 3). In general, growth was faster on RM medium than on SM medium, regardless of the considered fungal isolate (p-value<0.001, Welsh test, Fig. 3).

## 4. Discussion

This study evaluated VOC production profiles, with a focus on FMA off-odors, and the biotic and abiotic factors influencing the growth of 18 grape-associated fungal isolates. Selected fungal isolates were grown individually or in co-inoculations with two *B. cinerea*, each producing a different off-odor, on gelified must medium or Meunier grape berries. In this context, it would also be of interest to study Pinot Noir and Chardonnay cultivars as varietal composition may impact both fungal growth and VOCs production. An untargeted GC-MS approach was used to identify as many VOCs as possible with a focus on FMA-related VOCs. One of the originalities of our study was to determine to what extent fungal co-inoculation modified VOC production profiles and if any increase in FMA off-odors was perceived by sensorial analyses. We then determined how pH and temperature affected the growth of these grape-associated molds using liquid or solid must media.

The first step was to determine the VOC production profiles for the 18 selected isolates on both synthetic must medium and Meunier grape berries using semi-quantitative HS-GC-MS. We also studied how the volatile profiles were impacted for a subset of eight isolates when co-inoculated with two different *B. cinerea* isolates on must medium or directly on Meunier berries. Noteworthy, for *B. cinerea* cultures, some isolates were associated with distinct FMA off-odors on M2Lev malt medium but rather with the EMT defect when cultured on grapes. Only

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Radial growth rate (mm/day) of each isolate according to the growth medium: gelified grape must medium (RM) and synthetic must medium (SM) at 20 °C. Each replicate is represented by a circle. For each medium, isolates with different letters have significantly different growth rates (Tukey, p-value <0.05). Isolate IDs in the x-axis refer to those described in Table 1 on the left side panel. Bc: *B. cinerea*; Cr: *C. rosea*; Cs: *C. subtilissimum*; Pbi: *P. bialowiezense*; Pbr: *P. brevicompactum*; Pci: *P. citreonigrum*; Pcr: *P. croicicola*; Tm: *T. minioluteus*.</figcaption></figure>
P. crocicola isolates produced intense FMA after growth on both matrices. For some of the other studied species, including *C. subtilissimum*, FMA off-odors were detected on malt medium, but not on Meunier berries, possibly due to very weak fungal development on that matrix, although other factors (e.g medium composition, substrate metabolisation) may also be involved. In contrast, *P. bialowiezense* successfully colonized berries but did not produce detectable off-odors on Meunier grape berries despite generating distinct FMA off-odor on malt medium. The nature of the matrix indeed influenced the production or perception of odors produced by the isolates, and these observations highlighted the need to confirm the results obtained using *in vitro* conditions in conditions closely related to the vineyard or wine making. This was particularly demonstrated by the fact that out of a total of the 92 VOCs identified on SM medium and Meunier grape berries, only 37 compounds were shared between the two matrices whereas the remaining 55 other compounds were matrix-specific and were thus probably associated with the matrix itself or fungal metabolism on said matrix.

In a study in which Cabernet Sauvignon berries were infected by *B. cinerea*, an increase in the levels of 2-methylpropanoic acid, ethyl isobutyrate, 3-hydroxy-2-butanone and acetic and propionic acids compared to non-inoculated berries was reported (Li et al., 2022), in agreement with our results. White Riesling, red Riesling and red Tra-miner musts inoculated with *B. cinerea* were also analyzed for VOCs in Lopez Pinar et al. (2016). Several of these VOCs were detected in our study, namely isobutanoic acid (or 2-methylpropanoic) associated to cheesy odor, ethyl isobutyrate (or ethyl isobutanoate) associated to berry odors, 3-hydroxy-2-butanone associated to fatty, butter odors, acetic acid associated to vinegar odor, octanoic acid associated to fresh, plastic, musty odors, hexanoic acid associated to cheesy, rancid, pungent odors, hexanal associated to green, tomato odors, 2,3-butanedione (diacetyl) associated to butter odor, 1-hexanol associated to fruity, cherry odor and also 1-octen-3-one and 1-octen-3-ol associated to FMA. As previously stated, these latter compounds are potentially involved in fungal and/or plant metabolism (Pennerman et al., 2022).

Since FMA detection was particularly associated with isolates of *P. crocicola* inoculated either alone or co-inoculated with *B. cinerea*, VOC profiles associated with FMA were *de facto* associated with the presence of *P. crocicola*. In particular, 10 compounds (8 from the *P. crocicola* monoculture and 5 in association with *B. cinerea*) were produced in significantly higher amounts by isolates associated with these FMA-associated clusters on Meunier grape berries, than with EMT- or ‘no off-odor’-associated clusters, suggesting that these compounds may be involved in FMA odor perception. These compounds are namely ethyl 2-methylpropanoate, ethyl 2-methylbutanoate, dimethyl disulfide, 4-methyl-3-hexanone, 4-methyl-3-hexanol, 3,6-dimethylhexahydrobenzofuran; formic acid, 1,3-dimethoxybenzene, ethyl 3-hydroxy-3-methylbutanoate and 2-methoxyphenol, respectively, and some of them (2-methoxyphenol and 1,3-dimethoxybenzenewere for co-inoculation and ethyl 2-methylbutanoate; dimethyl disulfide; 4-methyl-3-hexanone; formic acid and 1,3-dimethoxybenzene for monoculture). However, no previous studies in literature have linked these compounds specifically to the FMA off-odor. These compounds are instead mainly associated with fruity, herbal sulfurous or smoky odors (based on the good scent company, https://www.thegoodscentscompany.com/search.html). Our hypothesis is that these compounds were probably specific to *P. crocicola* metabolism, considering that these clusters consisted almost exclusively of *P. crocicola* inoculated alone or in co-inoculation experiments with *B. cinerea* on Meunier grape berries. Our results also suggest that many other VOCs or VOC combinations may be linked to the FMA defect or its perception, thus beyond what has already been described in the literature. From an applied point of view, in the future, it would be of interest to design molecular tools to target at-risk FMA species for early detection on grape berries leading to preventative methods to control these fungal populations (e.g. CuSO₄ application or use of biocontrol agents).

Among these 10 compounds particularly produced by the *P. crocicola*

cluster, propanoic acid has already been identified by Li et al. (2022) and was found to be produced at significantly higher levels in infected Cabernet Sauvignon bunches compared to control. In the same study, the authors demonstrated that the production of dimethyl sulfide, also detected in our study, increased in Cabernet Sauvignon bunches during infection, whereas it decreased in Petit Manseng bunches. Dimethyl disulfide was also linked to fungal metabolism and was present in multiple infected matrices, which is why Moulatar, Robine, Ramalho, and Oturan (2008) proposed to select this compound as a potential marker for mold detection.

To better understand the factors favoring the growth of these fungi, growth rates were evaluated depending on temperature and pH. Concerning the influence of temperature, as already described in literature, *B. cinerea* isolates grew with an optimal temperature in the range of 23-25 °C (Ma et al., 2018). These are typical temperature conditions encountered in vineyards during the growing season. *B. cinerea* also displayed the highest growth rate on SM media at 20 °C in comparison to the other tested isolates in the present study. On berries, temperatures between 15 and 25 °C were already described as optimal in laboratory conditions when assessing disease incidence caused by *B. cinerea*, but the authors pointed out that humidity rate and duration also considerably impacted disease incidence (Ciliberti et al., 2015; González-Domínguez et al., 2015). Among *Penicillium* species, some inter- and intraspecific variations in optimal, minimum and maximum growth temperatures were observed, supporting the need for multi-isolate testing when determining cardinal values for growth. For example, *P. crocicola*, *P. citreonigrum*, *P. bialowiezense* and *P. brevicompactum*, which were among the most dominant *Penicillium* species previously identified on grape berries from Champagne region at harvest (Destanque et al., 2024), had optimal growth temperatures of 26.7-31.2 °C, 18.4 °C, 17.5-23.3 °C and 19.4 °C, respectively, depending on the considered isolate. Optimal growth temperature reported in literature for some of these species were 23 °C for *P. brevicompactum* and 25 °C for *Penicillium thomii* (Pitt & Hocking, 2009), recently revised as belonging to a clade including *P. crocicola* (Houbraken et al., 2014). To the best of our knowledge, no other cardinal values for growth were reported for the studied species. *P. crocicola* was also the second fastest species to grow on both substrates, mimicking must or real must, which can be directly linked to its capacity to readily colonize grape berries in vineyards, especially as we observed higher abundances in must samples (Destanque et al., 2024; unpublished data). This facilitated colonization of *P. crocicola* was also confirmed after inoculations on Meunier grape berries, either inoculated alone or with *B. cinerea*. Finally, based on the optimal temperature ranges for the studied isolates, warm temperatures at harvest, between 24 and 30 °C, could favor *B. cinerea* and *P. crocicola* development, both of which were associated with strong EMT and FMA off-odor. This suggests that the latter species might be favored in the context of higher temperatures. Moreover, high hygrometry might also contribute to both fungal growth and FMA defect (unpublished data). Thus, millesimal climate variations could also be an indicator of a need for more intensive fungal community surveillance. In link with current climate change scenarios, it would be of interest to also evaluate the impact of water activity and CO₂ pressure on *P. crocicola* growth and VOCs production as well as the other at-risk fungal species. The combinatory effects of these factors are also of interest. In the case of cooler conditions at harvest, between 20 and 25 °C, other *Penicillium* spp. growth could be favored (*P. brevicompactum*, *P. bialowiezense*, *P. citreonigrum*), as well as *T. minioluteus*, *K. submersum*, *C. rosea* and *C. subtilissimum*. However, our data confirms that temperatures below 5 °C and above 35 °C significantly reduce, or even stop fungal growth for most fungal species, as already described in literature (Pitt & Hocking, 2009).

Concerning the impact of pH on fungal growth, all isolates and species grew in a wide range of pH from 2.4 to 8.5 and some interspecific, and to a lesser extent intraspecific, variations were observed. For *P. crocicola*, while capable of growing at a pH of 2.4, growth declined when pH was inferior to 3.2. In general, *Penicillium* spp. are described as
being able to grow over a wide range of pH values, tolerant to acidic media, with some reduction in growth below pH 5 (Wheeler, Hurdman, & Pitt, 1991; Brancato & Golding, 1953). Here, we clearly demonstrated that the isolated *Penicillium* spp. grew well in the tested must conditions, with acidic pH around 3 (Prat-Bernachot et al., 2022). Similarly to our study, Grangeteau et al. (2017) detected *Penicillium* spp. in Chardonnay musts that usually have pH around 3.

Interestingly, we found that the production of the reported FMA-associated compounds 3-octanol and 3-octanone was significantly increased in co-inoculations involving *B. cinerea* with *P. citreonigrum* and/or *P. bialowiezense*, compared to the respective monocultures. However, this did not result in a significant increase in perception of the FMA defect, potentially because the amount was below the detection limit or due to the limited number of panelists. It would be of interest to perform further sensorial analyses using an expert panel (i.e. consisting of winemakers) with several panelists enabling more robust statistical analyses.

These results align with our initial hypothesis that interactions between fungal species influence the biosynthesis of FMA-associated compounds. One hypothesis explaining this enhanced production of FMA-related compounds could be that these compounds are produced during competitive interactions to inhibit the growth of other competitors, while another hypothesis could be that some fungal isolates produce chemical compounds that are used as substrates by other fungal isolates to produce VOCs with off-odors. As reviewed by Pennerman et al. (2022), these FMA-related compounds are known to inhibit fungal germination, suppress fungal growth and/or are involved in fungal defense mechanisms. Pure 3-octanol was also shown to reduce *B. cinerea* cell viability by inducing the expression of an autophagy-related gene, in addition to inhibition of conidial germination described above in PDA medium, on grape berries and on strawberry fruit (Zhang et al., 2023).

Moreover, we observed that co-inoculations involving *P. crocicola* were the only ones which restricted the growth of *B. cinerea* (Table S1). This latter species usually covered the entire berry surface, whether or not co-inoculated with another fungus. Although *P. crocicola* is known to grow rapidly, it is also possible that it produces a greater quantity of FMA-related compounds (for ex. C8 compounds), possibly among other compounds, thereby inhibiting the growth of *B. cinerea* and resulting in an intensification of the FMA off-odor. Quick growth of *P. crocicola* isolates associated with specific VOC production may confer this species competitive advantages when co-inoculated with other fast-growing fungi such as *B. cinerea* but further studies are needed to determine the exact role of FMA-associated compounds for the producing fungus.

## 5. Conclusion

This study applied a highly multidisciplinary approach, combining not only predictive and classical mycology but also sensorial and biochemical analyses, to better decipher the biotic and abiotic factors conditioning fungal growth and FMA defect. We showed that grape-associated mold isolates produced a very wide range of VOCs in must-based media as well as on Meunier berries, with some culture conditions clearly enhancing off-odor intensities and the FMA defect. In this context, it would also be of interest to study Pinot Noir and Chardonnay cultivars as varietal composition may impact both fungal growth and VOCs production. We also showed how abiotic factors, i.e. pH and temperature, impact the growth of these off-odor producing grape-associated isolates in conditions mimicking grape berries and musts. The obtained data showed to what extent molds are well equipped to thrive in a wide range of conditions, which is of major importance with current climate change scenarios that may favor their development in certain wine regions worldwide. Further experiments could be of interest to continue to identify which species and co-culture conditions specifically lead to higher FMA related compounds production, but also to better characterize other VOCs associated with FMA perception and understand their role for the producing fungal species. Additional

experimental work could also involve interaction studies between *Penicillium* spp. and *Botrytis cinerea* isolates with potential biocontrol agents that we previously described (Destanque et al., 2024) to determine to what extent such interactions impact the sensory and volatile compound profiles, especially for FMA. Such complementary studies could ultimately lead to practical solutions to improve winemaking processes or grape management for at-risk vintages.

## CRediT authorship contribution statement

**Adrien Destanque:** Writing – original draft, Methodology, Formal analysis. **Flora Pensec:** Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Methodology, Funding acquisition, Conceptualization. **Adeline Picot:** Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Methodology, Funding acquisition, Conceptualization. **Anne Thierry:** Writing – review & editing, Validation, Methodology, Formal analysis. **Marie-Bernadette Maillard:** Validation, Formal analysis. **Alexis Commereuc:** Formal analysis. **Elisabeth Poirier:** Formal analysis. **Louis Coroller:** Writing – review & editing, Supervision, Formal analysis. **Emmanuel Coton:** Writing – review & editing, Supervision, Resources, Funding acquisition, Conceptualization. **Marion Hervé:** Writing – review & editing, Supervision, Resources, Methodology. **Monika Coton:** Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Conceptualization.

## Ethical statement

For sensory analyses by the panelists, no human ethics committee or formal documentation process was required. We confirm that the appropriate protocols for protecting the rights and privacy of all participants were utilized during the execution of the research, e.g. no coercion to participate, full disclosure of study requirements and risks, verbal consent of participants, no release of participant data without their knowledge, ability to withdraw from the study at any time.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

We would like to thank the ANRT (Association Nationale Recherche Technologie, Cifre grant, France) and MHCS for funding this project (Project OV 2022_00532). We would also like to thank the Robert-Jean de Vogüé research center (Moët - Hennessy) members who helped with berry sampling in the vineyards: Julien Jeanmougin, Raphaël Paulin, Pierre Gheusi, Marion Sellier, Romane Holtzinger, Manon Combe. We would like to thank Laurence Mercier and Yohan Gruson for the help provided during berry sorting. Finally, we would like to acknowledge Olivier Brack for his guidance with statistical analyses.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.lwt.2025.118945.

## Data availability

Data will be made available on request.
## References

Altschul, P. S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool.

Bock, G., Benda, I., & Schreier, P. (1986). Biotransformation of linalool by *Botrytis cinerea*. *Journal of Food Science*, 51(3), Article 3. https://doi.org/10.1111/j.1365-2621.1986.tb13904.x

Bojkov, G., Mitrev, S., & Arsovi, E. (2020). Determination on microclimatic conditions at vines upon development on gray mold (*Botrytis cinerea*). *Agricultural Sciences*, 11(11), Article 11. https://doi.org/10.4236/as.2020.1111065

Börjesson, T., Stöllman, U., & Schnürer, J. (1992). Volatile metabolites produced by six fungal species compared with other indicators of fungal growth on cereal grains. *Applied and Environmental Microbiology*, 58(8), Article 8. https://doi.org/10.1128/aem.58.8.2599-2605.1992

Brancato, F. P., & Golding, N. S. (1953). The diameter of the mold colony as a reliable measure of growth. *Mycologia*. https://www.tandfonline.com/doi/abs/10.1080/002751953.12024321.

Carbone, I., & Kohn, L. M. (1999). A method for designing primer sets for speciation studies in filamentous ascomycetes. *Mycologia*, 91(3), Article 3. https://doi.org/10.1080/00275514.1999.12061051

Ciliberti, N., Fermaud, M., Roudet, & Rossi, V. (2015). Environmental conditions affect *Botrytis cinerea* infection by mature grape berries more than the strain or transposon genotype. *Phytopathology*, 105(8), 1090-1096. https://doi.org/10.1094/PHYTO-10-14-0264-R

Dagnas, S., & Membré, J.-M. (2013). Predicting and preventing mold spoilage of food products. *Journal of Food Protection*, 76(3), Article 3. https://doi.org/10.4315/0362-028X.JFP-12-349

Delcros, L., Costis, A., Le Guerneve, C., Collas, S., Hervé, M., & Roland, A. (2013). First identification of a new molecule involved in the fresh mushroom off-flavor in wines: 1-hydroxyoctan-3-one. *Food Chemistry*, 413, Article 135678. https://doi.org/10.1016/j.foodchem.2023.135678

Destanque, A., Picot, A., Pensec, F., Pawtowski, P., Rolland, N., Treguer-Fernandez, S., Debaets, S., Guérin, L., Mercier, L., Coton, E., Hervé, M., & Coton, M. (2024). Grape berry mycobiota and its contribution to fresh mushroom aroma off-odour in wine. *EnoOne*, 58(4). https://doi.org/10.20870/eeno-one.2024.58.4.8105

Glass, N. L., & Donaldson, G. C. (1995). Development of primer sets designed for use with the PCR to amplify conserved genes from filamentous ascomycetes. *Applied and Environmental Microbiology*, 61(4), Article 4. https://doi.org/10.1128/aem.61.4.1323-1330.1995

González-Domínguez, E., Caffi, T., Ciliberti, N., & Rossi, V. (2015). A mechanistic model of *Botrytis cinerea* on grapevines that includes weather, Vine growth stage, and the main infection pathways. *PLoS One*, 10(10), Article e0140444. https://doi.org/10.1371/journal.pone.0140444

Grangeteau, C., Roullier-Gall, C., Rousseaux, S., Gougeon, R. D., Schmitt-Kopplin, P., Alexandre, H., & Guilloux-Benatier, M. (2017). Wine microbiology is driven by vineyard and winery anthropogenic factors. *Microbial Biotechnology*, 10(2), 354-370. https://doi.org/10.1111/1751-7915.12428

Houbraken, J., Visagie, C. M., Meijer, M., Frisvad, J. C., Busby, P. E., Pitt, J. I., Seifert, K. A., Louis-Seize, G., Demirel, R., Yilmaz, N., Jacobs, K., Christensen, M., & Samson, R. A. (2014). A taxonomic and phylogenetic revision of *Penicillium* section *Aspergilloides*. *Studies in Mycology*, 78(1), Article 1. https://doi.org/10.1016/j.smyczo.2014.09.002

Kaminski, E., Stawicki, S., & Wasowicz, E. (1974). Volatile flavor compounds produced by molds of *Aspergillus*, *Penicillium*, and *Fungi imperfecti*. *Applied Microbiology*, 27(6), 1001-1004. https://doi.org/10.1128/am.27.6.1001-1004.1974

La Guerche, S., Dauphin, B., Pons, M., Blancard, D., & Darriet, P. (2006). Characterization of some mushroom and earthy off-odors microbially induced by the development of rot on grapes. *Journal of Agricultural and Food Chemistry*, 54(24), Article 24. https://doi.org/10.1021/jf0615294

La Guerche, S., De Senneville, L., Blancard, D., & Darriet, P. (2007). Impact of the *Botrytis cinerea* strain and metabolism on (–)-geosmin production by *Penicillium expansum* in grape juice. *Antonie Van Leeuwenhoek*, 92(3), Article 3. https://doi.org/10.1007/s10482-007-9161-7

Li, X., Li, T., Li, M., Chen, D., Liu, X., Zhao, S., Dai, X., Chen, J., Kong, Z., & Tan, J. (2022). Effect of pathogenic fungal infestation on the berry quality and volatile organic compounds of cabernet sauvignon and petit Manseng grapes. *Frontiers in Plant Science*, 13. https://doi.org/10.3389/fplss.2022.942487

Lio, V., & Aider, M. (2017). Geosmin as a source of the earthy-musty smell in fruits, vegetables and water: Origins, impact on foods and water, and review of the removing techniques. *Chemosphere*, 181, 9-18. https://doi.org/10.1016/j.chemosphere.2017.04.039

Lopez Pinar, A., Rauhut, D., Ruehl, E., & Buettner, A. (2016). Effects of *Botrytis cinerea* and *Erysiphe necator* fungi on the aroma character of grape must: A comparative approach. *Food Chemistry*, 207, 251-260. https://doi.org/10.1016/j.foodchem.2016.10.110

Ma, S., Hu, Y., Liu, S., Sun, J., Irfan, M., Chen, L.-J., & Zhang, L. (2018). Isolation, identification and the biological characterization of *Botrytis cinerea*. *International Journal of Agriculture and Biology*, 20. https://doi.org/10.17957/IJAB.15.0600

Mason, I. G. (2006). Mathematical modelling of the composting process: A review. *Waste Management*, 26(1), Article 1. https://doi.org/10.1016/j.wasman.2005.01.021

Meistermann, E., Villaumé, S., Goffette, D., Trarieux, C., Coarer, M., Roulland, C., & Dupont, J. (2021). A *Basidiomycetea Fungus* responsible for fresh mushroom off-flavour in wines: *Crustomyces subabruptus*, (Bourdot & Galzin) Jülich 1978. *ENO One*, 55(3), Article 3. https://doi.org/10.20870/eeno-one.2021.55.3.3004

Moularat, S., Robine, E., Ramalho, O., & Oturan, M. A. (2008). Detection of fungal development in closed spaces through the determination of specific chemical targets. *Chemosphere*, 72(2), 224-232. https://doi.org/10.1016/j.chemosphere.2008.01.057

Pennerman, K. K., Yin, G., & Bennett, J. W. (2022). Eight-carbon volatiles: Prominent fungal and plant interaction compounds. *Journal of Experimental Botany*, 73(2), 487-497. https://doi.org/10.1093/jxb/erab438

Pitt, J. I., & Hocking, A. D. (2009). *Fungi and food spoilage*. Springer US. https://doi.org/10.1007/978-0-387-92207-2

Ployon, S., Suc, L., Le Guerevé, C., Augès, E., Mahé, H., Hervé, M., Bloem, A., & Roland, A. (2025). High throughput LC-MS/MS discrimination of musts and wines contaminated by fresh mushroom off-flavor on the basis of reliable and easily quantifiable analytical markers: 1-hydroxyoctan-3-one and its derivative octane-1, 3-diol. *Food Chemistry*, 482, Article 143454. https://doi.org/10.1016/j.foodchem.2025.143454

Pogaćić, T., Maillard, M.-B., Leclerc, A., Hervé, C., Chuat, V., Yee, A. L., Valence, F., & Thierry, A. (2015). A methodological approach to screen diverse cheese-related bacteria for their ability to produce aroma compounds. *Food Microbiology*, 46, 145-153. https://doi.org/10.1016/j.fm.2014.07.018

Pons, M., Dauphin, B., La Guerche, S., Pons, A., Lавigne-Cruege, V., Shinkaruk, S., Bunner, D., Richard, T., Monti, J.-P., & Darriet, P. (2011). Identification of impact odorants contributing to fresh mushroom off-flavor in wines: Incidence of their reactivity with nitrogen compounds on the decrease of the olfactory defect. *Journal of Agricultural and Food Chemistry*, 59(7), Article 7. https://doi.org/10.1021/jf104215a

Pons, A., Mouakka, N., Deliere, L., Crachereau, J. C., Davidou, L., Sauris, P., Guilbault, P., & Darriet, P. (2018). Impact of Plasmopara viticola infection of Merlot and Cabernet Sauvignon grapes on wine composition and flavor. *Food Chemistry*, 239, 102-110. https://doi.org/10.1016/j.foodchem.2017.06.087

Prat-Bernachot, B., Collas, S., & Descòtes, A. (2022). Les Moûts de 2021. *Revue technique du CVC*.

Rossouw, D., Du Toit, M., & Bauer, F. F. (2012). The impact of co-inoculation with Oenococcus oeni on the transcriptome of Saccharomyces cerevisiae and on the flavour-active metabolite profiles during fermentation in synthetic must. *Food Microbiology*, 29(1), 121-131. https://doi.org/10.1016/j.fm.2011.09.006

Rousseaux, S., Diguta, C. F., Radoï-Matei, F., Alexandre, H., & Guilloux-Bénatier, M. (2014). Non-*Botrytis* grape-rotting fungi responsible for earthy and moldy off-flavors and mycotoxins. *Food Microbiology*, 38, 104-121. https://doi.org/10.1016/j.fm.2013.08.013

Savary, O., Coton, E., Maillard, M.-B., Gaucheron, F., Le Meur, C., Frisvad, J., Thierry, A., Jany, J.-L., & Coton, M. (2023). Functional diversity of *Bisifusarium domesticum* and the newly described Nectriaceae cheese-associated species. *Food Research International*, 168, Article 112691. https://doi.org/10.1016/j foodres.2023.112691

Smith, C. A., Want, E. J., O'Maille, G., Abagyan, R., & Siuzdak, G. (2006). XCMs: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. *Analytical Chemistry*, 78, 779-787. https://doi.org/10.1021/ac051437y

Staats, M. (2004). Molecular phylogeny of the plant pathogenic genus *botrytis* and the evolution of host specificity. *Molecular Biology and Evolution*, 22(2), 333-346. https://doi.org/10.1093/molbev/msi020

Steel, C., Blackman, W., John, Schmidtke, M., & Leigh. (2013). Grapevine bunch rots: Impacts on wine composition, quality, and potential procedures for the removal of wine faults. *Journal of Agricultural and Food Chemistry*. https://pubs.acs.org/doi/abs/10.1021/jf400641r

Tasaki, Y., Kobayashi, D., Sato, R., Hayashi, S., & Joh, T. (2019). Variations in 1-octen-3-ol and lipoxygenase gene expression in the oyster mushroom *Pleurotus ostreatus* according to fruiting body development, tissue specificity, maturity, and postharvest storage. *Mycoscience*, 60(3). https://doi.org/10.1016/j.myc.2019.02.005. Article 3.

Wheeler, K. A., Hurdman, B. F., & Pitt, J. I. (1991). Influence of pH on the growth of some toxigenic species of *Aspergillus*, *Penicillium* and *Fusarium*. *International Journal of Food Microbiology*, 12(2-3), 141-149. https://doi.org/10.1016/0168-1605(91)90063-U

White, T. J., Bruns, T., Lee, S., & Taylor, J. (1990). Amplification and direct sequencing of fungal ribosomal rna genes for phylogenetics. In *PCR protocols* (pp. 315-322). Elsevier. https://doi.org/10.1016/B978-0-12-372180-8.50042-1

Zhang, X., Li, G., Zhang, Z., & Tian, S. (2023). 3-Octanol controls gray mold on postharvest fruit by inducing autophagy of *Botrytis cinerea*. *Postharvest Biology and Technology*, 205, Article 112525. https://doi.org/10.1016/j.postharvio.2023.112525

Zwietering, M. H., Jongenburger, I., Rombouts, F. M., & Van 'T Riet, K. (1990). Modeling of the bacterial growth curve. *Applied and Environmental Microbiology*, 56(6). https://doi.org/10.1128/aem.56.6.1875-1881.1990. Article 6.