TL;DR
A paper titled "Electronic Nose for Indoor Mold Detection and Identification" was posted on Wiley Online Library on Jan. 7, 2026. The article's abstract and full text were not accessible from the provided link, so methods, results and authorship are not confirmed in the source.
What happened
Wiley Online Library lists a new item titled "Electronic Nose for Indoor Mold Detection and Identification," published on 2026-01-07 (DOI: 10.1002/adsr.202500124). The entry indicates a scholarly contribution on applying an "electronic nose" approach to detecting and identifying indoor mold. Attempts to retrieve the article from the supplied URL encountered a site security check and did not yield the article content or supplemental materials. Because the full text and abstract were not available through the provided link, details such as the study's experimental design, sensor types, datasets, performance metrics and author affiliations could not be confirmed from the source. The listing itself suggests ongoing research interest in non‑invasive sensing approaches for indoor environmental monitoring, but direct findings and conclusions are not accessible from the provided source material.
Why it matters
- Indoor mold can affect building integrity and occupant health; tools that detect mold earlier or more accurately could improve remediation timing and outcomes.
- Electronic nose systems promise non‑destructive, potentially continuous monitoring compared with manual sampling, which could reduce inspection time if validated.
- If validated and reliable, sensor-based identification could help prioritize inspections and target remediation resources more efficiently.
- Wider adoption would require reproducible performance across environments and integration with building maintenance workflows; those aspects are not confirmed in the source.
Key facts
- Source title: "Electronic Nose for Indoor Mold Detection and Identification" as listed on Wiley Online Library.
- Publication timestamp on the listing: 2026-01-07T00:31:01+00:00.
- DOI provided in the URL: 10.1002/adsr.202500124.
- Access to the article content was blocked by a site security check at the provided link; the full text and abstract were not retrieved.
- Authorship, institutional affiliations and funding information are not confirmed in the source.
- Experimental methods, sensor types, training datasets, analytical approaches and quantitative results are not confirmed in the source.
- The listing signals research activity on using sensor arrays or similar technologies for indoor mold detection, but specific performance claims are not available from the provided link.
What to watch next
- Availability of the full article text and abstract on Wiley Online Library (not confirmed in the source).
- Subsequent peer‑reviewed validations or follow‑up studies testing the system in real indoor environments (not confirmed in the source).
- Any reported sensor types, detection limits, false‑positive/negative rates, and comparison with standard mold assessment methods (not confirmed in the source).
Quick glossary
- Electronic nose: A sensor system that uses an array of chemical sensors and pattern‑recognition algorithms to detect and differentiate complex odors or volatile chemical profiles.
- Indoor mold: Fungi that grow inside buildings on surfaces or within structures, often producing spores and volatile compounds that can affect air quality.
- Volatile organic compounds (VOCs): Organic chemicals that evaporate at room temperature; some VOCs are emitted by microbes, materials, or building occupants and can be detected by gas sensors.
- Pattern recognition: Computational techniques, including machine learning, used to classify sensor responses into distinct categories or diagnoses.
Reader FAQ
What did the article conclude about electronic noses for mold detection?
Not confirmed in the source; the article's conclusions are not accessible from the provided link.
Is the device or system described available commercially?
Not confirmed in the source; commercial availability is not stated in the listing.
How does an electronic nose identify mold in general?
Typically, sensor arrays detect volatile compounds emitted from mold or associated materials; algorithms then match response patterns to known signatures to suggest presence or type.
Were performance metrics like accuracy or detection limits reported?
Not confirmed in the source; specific performance data are not available from the provided listing.
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Sources
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