Evidence map›Paper›PMID 42894680›Full record

ReviewFood chemistry: X2026

Recent applications of DSC and TGA in food quality control and authenticity verification: Current progress and future directions.

Amir Pourmoradian, Alireza Mohammadi, Mohsen Barzegar

Abstract readReview
In one paragraph

Review in Food chemistry: X, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Amir PourmoradianDepartment of Food Science and Technology, Tarbiat Modares University, P.O. Box 14115336, Tehran, Iran.
Alireza MohammadiDepartment of Food Science and Technology, Tarbiat Modares University, P.O. Box 14115336, Tehran, Iran.
Mohsen BarzegarDepartment of Food Science and Technology, Tarbiat Modares University, P.O. Box 14115336, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing complexity of food supply chains and rising consumer demand for transparency underscore the need for rapid, reliable, and cost-effective approaches to food quality control and authenticity assessment. Conventional analytical techniques, including chromatography and spectroscopy, offer high accuracy but involve time, labor, and cost. Thermal analysis (TA), particularly Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA), has emerged as an environmentally sustainable alternative. This review investigates recent advances in TA for food authentication, focusing on its principles and applications across food matrices, including edible oils, dairy products, honey, and meat. Thermal fingerprints generated by DSC and TGA provide indicators of compositional and structural changes, enabling evaluation of authenticity, thermal stability, oxidation, crystallization behavior, and shelf life. Integration with chemometric and machine learning approaches enhances adulteration detection, even at low levels. However, standardized protocols, thermal databases, and regulatory acceptance remain essential for widespread adoption.

Indexed as

ChemometricDifferential scanning calorimetry (DSC)Food authenticationThermal analysisThermogravimetric analysis (TGA)

Identifiers

PMID42894680
PMCPMC13676909

What OpenQuestion holds

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Registered trials

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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.