Pulse Brain · Growing Health Evidence Index
Tier 4 — Narrative / commentaryPeer-reviewed

Electronic Sensing Technologies in Food Quality Assessment: A Comprehensive Literature Review

Marian Gil; M. Rudy; Paulina Duma‐Kocan; Renata Stanisławczyk

Applied Sciences · 2025

Read source ↗ All evidence

Summary

This comprehensive literature review examines the state of electronic sensing technologies — including e-nose, e-tongue, and machine vision systems — as applied to food quality assessment. The authors, affiliated with a Polish research institution, synthesise published evidence on the capacity of these technologies to replicate or supplement conventional sensory and analytical methods. The review is likely to highlight the growing integration of these tools in quality control and authentication contexts across multiple food sectors.

UK applicability

Although the review is international in scope and not UK-specific, its findings are broadly applicable to UK food quality assurance frameworks, including those governed by Food Standards Agency guidelines and industry authentication requirements. UK food manufacturers and regulators could draw on this evidence base when considering investment in rapid, non-destructive quality monitoring technologies.

Key measures

Sensor response data; classification accuracy; correlation with conventional quality parameters (e.g. flavour, texture, freshness, adulteration detection); technology type and food matrix coverage

Outcomes reported

The review surveys the application of electronic nose, electronic tongue, electronic eye, and related sensor-based technologies in assessing physicochemical, sensory, and compositional quality attributes of food products. It likely evaluates the accuracy, limitations, and practical deployment of these systems across various food categories.

Theme
Measurement & metrics
Subject
Food quality measurement & sensing
Study type
Narrative Review
Study design
Narrative review
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Food supply chain
DOI
10.3390/app15031530
Catalogue ID
NRmo3f02hq-095

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.