ReviewACS sensors2024
Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry.
Review in ACS sensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 31 citations in OpenAlex.
- A Biomimetic Solvatochromic Chip With Optimized Chemical Diversity for On-Site Liquid Identification.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Balancing Selectivity and Cross-Sensitivity in Smart Tongue Sensing-Multimode, Multiplexed Optical Sensor Arrays for Dietary Supplement Classification.Sensors (Basel, Switzerland) · 2026Article
- Article
- Advances in Machine Learning-Assisted Optical Sensing Arrays for Disease Diagnosis.Biomimetics (Basel, Switzerland) · 2026Review
- Anthracene-Modified Nanoporous Silica Nanoparticles for ATP Detection and Salivary Diagnostics in Parkinson's Disease.ACS applied nano materials · 2026Article
- An Integrated Plasmonic Sensing Array for Chemical Fingerprinting and Flavor Profiling in Beverages and Other Liquids.ACS sensors · 2025Article
- An Analytical Model of Sorption-Induced Static Mode Nanomechanical Sensing for Multicomponent Analytes.Analytical chemistry · 2025Article
- Design and fabrication of self-calibration colorimetric/fluorescence/SERS tri-modal optical sensor for highly rapid and accurate detection of mercury ions in foods.Food chemistry: X · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons are frequently made to the mammalian nose or tongue and this perspective examines the role of sensing arrays in analyzing food and beverages for quality, veracity, and safety. I focus on optical sensor arrays as low-cost, easy-to-measure tools for use in the field, on the factory floor, or even by the consumer. Novel materials and approaches are highlighted and challenges in the research field are discussed, including sample processing/handling and access to significant sample sets to train and test arrays to tackle real issues in the industry. Finally, I examine whether the comparison of sensing arrays to noses and tongues is helpful in an industry defined by human taste.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.