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A Rapid and Cost-Effective Flow Cytometry Method for Detecting Air Inoculum of Botrytis cinerea and Aspergillus carbonarius in Vineyards

This study presents a rapid, cost-effective, and environmentally friendly flow cytometry method that successfully discriminates airborne conidia of *Botrytis cinerea* and *Aspergillus carbonarius* from other fungal species in vineyard air samples, offering a promising tool for early detection and timely intervention to mitigate bunch rot and mycotoxin risks.

Original authors: Emanuele Chiaromonte, Angelo Agnusdei, Fabio Mavelli, Franco Nigro, Francesco Faretra, Emiliano Altamura, Stefania Pollastro

Published 2026-09-30

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Emanuele Chiaromonte, Angelo Agnusdei, Fabio Mavelli, Franco Nigro, Francesco Faretra, Emiliano Altamura, Stefania Pollastro

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

In the quiet rows of a vineyard, invisible to the naked eye, a constant battle for the future of the harvest is already underway. The air is filled with microscopic spores, the reproductive units of fungi that can turn a healthy grape cluster into a rotting mass within days. Two of the most dangerous invaders are Botrytis cinerea, which causes the grey mold that ruins table grapes, and Aspergillus carbonarius, a fungus that not only rots the fruit but also produces a toxic substance called ochratoxin A, a contaminant that poses serious health risks to humans. For farmers and scientists, knowing when these spores are present in the air is crucial. It allows them to predict an outbreak and treat the vines before the damage is done. Traditionally, identifying these invisible travelers has been a slow, labor-intensive process. Scientists would catch the spores on sticky tape or filters, then spend hours peering through a microscope, trying to distinguish one tiny, often translucent shape from another. This method relies heavily on the skill of the observer and can take days to yield results, often missing the critical window for early intervention.

A team of researchers at the University of Bari Aldo Moro in Italy has developed a new way to see these spores that is faster, cheaper, and less dependent on human eyes. They turned to a technology called flow cytometry, a method usually used in medical labs to count blood cells or sort different types of cells. In this study, the researchers adapted the machine to analyze air samples from vineyards. Instead of looking at the spores one by one under a lens, the machine suspends the air sample in a stream of water and shoots it past a laser. As each spore passes through the beam, it scatters the light in a unique pattern based on its size and internal complexity. The machine also uses a harmless fluorescent dye that sticks to the chitin in the fungal cell walls, causing the spores to glow. By measuring how the light scatters and how brightly the spores glow, the machine creates a digital fingerprint for each type of fungus.

The researchers tested this approach with pure cultures of the target fungi, as well as with other common fungi found in vineyards, such as Penicillium and Cladosporium. They found that the machine could clearly separate the spores of Botrytis cinerea and Aspergillus carbonarius from the rest of the crowd. The two dangerous species had distinct signatures that did not overlap with the harmless background noise or the other common fungi. The system was so precise that when the researchers mixed all the different spores together in a single sample, the machine could still identify the specific targets with very few errors. For Botrytis cinerea, the chance of the machine mistaking another spore for this fungus was less than two percent. For Aspergillus carbonarius, the error rate remained low, generally under five percent. This level of accuracy held true even when the researchers tested air samples collected from real vineyards, where the spores were mixed with dust and other environmental debris.

However, the method is not a magic bullet for every single fungus. The researchers discovered that some species, like Cladosporium and Penicillium, look too similar to the machine to be told apart reliably. In these cases, the spores overlapped so much in the data that the machine could not distinguish between them. Similarly, the spores of Alternaria alternata were too variable in their appearance to be identified with certainty, as they blended in with non-living particles in the air. Despite these limitations, the study proved that the technique works exceptionally well for the two most economically damaging pathogens. When the researchers compared the machine's counts to traditional methods, the results matched closely. The flow cytometry counts correlated strongly with the number of fungal colonies that grew on petri dishes in a lab, and also aligned well with genetic tests that count the DNA of the fungi.

The implications of this work are significant for the future of vineyard management. The new method can process up to sixty samples in a single hour, a speed that is impossible with manual microscopy. It requires no toxic chemicals and no complex DNA extraction, making it a practical tool for frequent monitoring. By providing a rapid, reliable count of dangerous spores in the air, this technology could allow farmers to act immediately when a risk is detected, rather than waiting days for a lab report. This shift toward real-time data could help reduce the use of fungicides by targeting treatments only when necessary and could play a vital role in preventing the accumulation of toxins in grapes and wine. The study suggests that while flow cytometry may not replace every existing method, it offers a powerful, efficient bridge between high-tech analysis and the daily needs of protecting the harvest.

Technical Summary: A Rapid and Cost-Effective Flow Cytometry Method for Detecting Air Inoculum of Botrytis cinerea and Aspergillus carbonarius in Vineyards

Problem Statement
Bunch rots, primarily caused by the phytopathogenic fungi Botrytis cinerea (grey mold) and Aspergillus carbonarius, pose significant threats to grape production, leading to economic losses and food safety risks due to mycotoxin contamination, specifically Ochratoxin A (OTA). While monitoring airborne conidia is crucial for disease forecasting and integrated pest management, current diagnostic methods—microscopy, culture-dependent techniques, and molecular assays (PCR/qPCR)—suffer from limitations. Microscopy is operator-dependent and low-throughput; culture methods are slow and biased by selective growth conditions; and molecular techniques require complex nucleic acid extraction and specialized infrastructure, limiting their utility for high-frequency, near-real-time monitoring in vineyard environments.

Methodology
The study developed a morphology-based flow cytometry protocol to discriminate airborne conidia of A. carbonarius and B. cinerea from environmental contaminants and non-target fungal species.

Sample Preparation: Conidial suspensions were prepared from pure cultures of target species (A. carbonarius, B. cinerea) and common vineyard contaminants (A. alternata, A. niger, Cladosporium sp., Penicillium expansum). Spores were stained with Calcofluor White to bind to chitin in the fungal cell wall, enhancing fluorescence detection.
Instrumentation: Analysis was performed using a BD LSRFortessa X-20 Cell Analyzer. Parameters included Forward Scatter (FSC-A) and Side Scatter (SSC-A) for size and internal complexity, alongside fluorescence signals (405 nm excitation, 450 ± 25 nm emission) from the Calcofluor White stain.
Gating Strategy: Species-specific gates were established based on pure culture profiles to capture at least 60% of target events. These gates were validated against mixed suspensions and field-collected air samples (collected via 0.2 µm nylon membrane filters).
Validation: Flow cytometry results were cross-validated using:
1. Biological methods: Culture-based quantification (CFU/mL) on Malt Extract Agar.
2. Molecular methods: Species-specific qPCR targeting A. carbonarius.
3. Statistical analysis: Correlation coefficients ( $R^2$ ) were calculated between the different methods.

Key Results

Discrimination Capability: The method successfully and reliably discriminated B. cinerea and A. carbonarius from other species based on scatter and fluorescence profiles.
- B. cinerea showed near-complete separation from other species, with a misclassification rate approaching zero (max 2% overlap with A. carbonarius).
- A. carbonarius was distinguishable with low misclassification rates (<5% for most species).
Limitations in Specificity:
- Cladosporium sp. and P. expansum exhibited substantial morphological overlap, resulting in high reciprocal misclassification rates (41.5% and 43%, respectively), preventing reliable discrimination between these two taxa.
- A. alternata could not be accurately discriminated due to significant overlap with non-specific background events and debris.
- A. niger showed discrepancies between pure culture gating and environmental sample detection, likely due to the high heterogeneity of the Aspergillus section Nigri complex in natural settings.
Validation Correlations:
- Strong positive correlations were observed between flow cytometry event counts and culture-based CFU counts for B. cinerea ( $R^2 = 0.96$ ) and A. carbonarius ( $R^2 = 0.89$ ).
- A substantial correlation was found between qPCR results and flow cytometry counts for A. carbonarius ( $R^2 = 0.75$ ).
- In naturally contaminated air samples, the method detected target species consistent with biological and molecular validation, though Penicillium and Cladosporium remained the most prevalent culturable populations.

Significance and Claims
The authors posit that this flow cytometry approach offers a rapid, cost-effective, and environmentally friendly alternative for analyzing air samples, processing up to sixty samples per hour. The study claims the method bridges the gap between high-throughput analytical technologies and practical aerobiological monitoring by:

Reducing Operational Time: Eliminating the need for lengthy incubation periods required by culture methods and the nucleic acid extraction steps of molecular assays.
Minimizing Reagents: Operating without harmful or polluting reagents.
Enabling Timely Intervention: Providing a tool for the early detection of airborne inoculum, which can support data-driven disease forecasting and targeted fungicide applications.

The paper modestly concludes that while the method is highly effective for specific, taxonomically distinct pathogens like B. cinerea and A. carbonarius, it is best utilized as a targeted detection tool rather than a comprehensive fungal community profiling method. It suggests that for morphologically similar species, additional markers or molecular confirmation may be necessary. The authors view this technique as a promising strategy for integration into routine vineyard surveillance systems to mitigate bunch rot and OTA contamination risks.

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