The principle behind thermal analysis is elegantly simple. Every food has a chemical signature, and that signature dictates how it behaves under heat. DSC measures heat flow into or out of a sample relative to a reference as temperature changes, capturing melting points, crystallization temperatures, glass transitions, and protein denaturation events. TGA, by contrast, continuously records changes in sample mass under a controlled atmosphere, revealing moisture content, decomposition temperatures, and degradation pathways. Because adulteration, substitution, or raw material variation alters these thermal events—shifting melting temperatures, changing enthalpy values, or reshaping mass-loss curves—each food generates a characteristic thermal fingerprint that fraud cannot easily disguise.

What makes these techniques so attractive compared with conventional methods is practicality. Chromatographic techniques such as gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry remain the gold standard for definitive molecular identification, but they demand extensive sample preparation, expensive instrumentation, solvents, and long analysis times. DSC and TGA require minimal or no sample preparation, tiny sample quantities, no solvents, and only minutes of analysis time. This aligns squarely with the principles of green analytical chemistry, and it makes the techniques well suited to high-throughput routine screening where hundreds of samples must be triaged quickly.

Edible oils illustrate the power of the approach most vividly. Premium oils such as extra virgin olive oil are among the most frequently adulterated commodities in the world, and their market value depends on botanical origin, geography, and production method. Because each oil’s triacylglycerol composition is unique, each produces a distinctive crystallization profile that adulteration measurably distorts. Recent studies reviewed by the authors show DSC combined with chemometrics detecting sunflower, corn, and soybean adulteration in extra virgin olive oil with quantitative prediction errors as low as a few percent. In flaxseed oil work, linear discriminant analysis achieved 99.5 percent classification accuracy for rapeseed adulteration, while artificial neural networks delivered quantitative predictions with a correlation coefficient of 0.996. Data fusion of DSC with GC-MS in walnut oil studies pushed support vector machine classification to 100 percent accuracy.

Honey, another fraud magnet, has proven equally amenable to thermal fingerprinting. The glass transition temperature of honey is highly sensitive to sugar composition and water content, so adding cheap syrups such as high-fructose corn syrup, rice syrup, or inverted sugar systematically lowers the glass transition and alters heat capacity changes. One research team used DSC with partial least squares regression to successfully predict adulterant concentrations in sunflower honey contaminated with five different syrups at levels of 5 to 20 percent. More strikingly, recent work has coupled DSC with artificial intelligence: convolutional neural networks boosted by synthetic minority over-sampling improved classification accuracy of adulterated stingless bee and Tualang honeys from a baseline of 24 to 67 percent up to 60 to 91 percent, while a separate study using graph-based semi-supervised learning achieved accurate classification of corn syrup adulteration with only a limited number of labeled samples.

Beyond oils and honey, the review documents thermal analysis succeeding across a remarkable range of matrices. In dairy, DSC coupled with machine learning models including gradient boosting machines and multilayer perceptrons achieved 100 percent classification accuracy in detecting formaldehyde, whey, urea, and starch adulteration in raw bovine milk. Thermogravimetry combined with chemometrics detected starch in commercial yogurt above the legal 1 percent threshold with over 83 percent accuracy. DSC has resolved species-specific thermal fingerprints in beef, pork, rabbit, and chicken for solvent-free halal authentication, and TGA with derivative thermogravimetry quantified corn, husk, and straw adulteration in ground roasted Arabica coffee with a detection limit of just 0.36 percent by mass.

The techniques also serve quality control well beyond fraud detection. DSC-derived oxidation induction times and onset temperatures correlate strongly with conventional peroxide and anisidine values, providing rapid indicators of oil deterioration during storage. Glass transition measurements have been shown to predict chemical stability: in condensed biopolymer matrices, storing lipids below the glass transition slowed oxidation by restricting molecular diffusion, suggesting DSC can forecast shelf life without months of storage trials. DSC further characterizes cocoa butter polymorphism—critical to the gloss and snap of chocolate—starch gelatinization, and protein denaturation, with recent nano-DSC work resolving the thermal transitions of six individual whey proteins by manipulating pH and ion chelation conditions.

The authors are candid about the limitations. Thermal profiles are influenced by cultivar, geography, climate, processing history, oxidation, and experimental conditions such as heating rate, sample mass, and thermal history, all of which can complicate comparisons between laboratories. Overlapping thermal events in complex matrices can obscure individual transitions, and sensitivity to low-level adulteration is limited when adulterants behave thermally like the authentic product. The review also raises a pointed methodological question the field has largely ignored: what is the minimum detectable thermal shift below which DSC- and TGA-based claims become unreliable? Without systematic detection thresholds for each food matrix, cross-study comparisons remain largely qualitative. High classification accuracies reported after machine learning integration, the authors caution, should not be mistaken for universal detection capability, particularly when models rest on small datasets without independent external validation.

The future, however, looks increasingly intelligent. The review outlines a roadmap in which deep learning extracts discriminative features directly from raw thermal curves, explainable AI techniques such as SHAP reveal which temperature ranges drive classification decisions, and transfer learning compensates for small thermal databases. Federated learning could allow laboratories and regulators to train shared models without sensitive data ever leaving its site of origin, while digital-twin frameworks could couple thermal sensors to real-time, in-line quality monitoring under Industry 4.0 infrastructure. Portable miniaturized DSC devices may eventually bring authentication to the point of collection, and hyphenated systems combining thermal analysis with FTIR, Raman, or mass spectrometry promise multimodal fingerprints capturing variations no single technique can detect.

The review’s bottom line is measured but optimistic: DSC and TGA will not replace chromatography or spectroscopy as confirmatory reference methods, but positioned as rapid, solvent-free screening tools within a complementary analytical strategy, they offer a practical route to catching fraud before it reaches consumers. Realizing that vision will require standardized protocols, large and diverse reference databases built on FAIR data principles, interlaboratory validation, and eventual regulatory acceptance. If those pieces fall into place, the humble thermogram—once confined to polymer labs—may become one of the food industry’s most powerful anti-fraud weapons.

Subject of Research: Applications of differential scanning calorimetry and thermogravimetric analysis in food quality control and authenticity verification

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

Article References: Pourmoradian, A., Mohammadi, A., & Barzegar, M. (2026). Recent applications of DSC and TGA in food quality control and authenticity verification: Current progress and future directions. Food Chemistry: X, Article 104587. https://doi.org/10.1016/j.fochx.2026.104587

Image Credits: AI Generated

DOI: Not provided

Keywords: food fraud, food authentication, differential scanning calorimetry, thermogravimetric analysis, thermal analysis, adulteration detection, olive oil, honey, chemometrics, machine learning, oxidative stability, glass transition

The starting materials were far from glamorous. Grape seed oil is a secondary product of winemaking, extracted from the pomace left behind after pressing. A large share of olive oils, meanwhile, never make the grade for extra virgin classification; roughly 41 percent of collected oils in some seasons are downgraded because of defects or excessive acidity, then refined and blended into cheaper commercial products. Refining stabilizes these oils, but it strips out most of the aromatic and bioactive compounds that give premium oils their complexity, leaving behind a neutral-tasting lipid with little antioxidant punch. Aromatization offers a route to upgrade these bland carriers, and pairing the process with food by-products multiplies the sustainability payoff.

The Italian team turned to ultrasound-assisted extraction, a green technology that accelerates the transfer of lipophilic compounds from plant material into oil. A 38 kHz probe-type system operating at 70 percent of a 1000 W generator delivered cavitation bubbles that collapse violently in the oil, rupturing plant cell walls and driving phenolics, capsaicinoids, and pigments into the surrounding fat in minutes rather than days. Dried chili peppers and basil leaves, both rejected from normal sale channels for failing size or shape standards, were ground and processed at carefully controlled low temperatures of 30 to 35 degrees Celsius for just 10 minutes each. Conventional infusion methods can take days at room temperature, exposing the oil to oxidation throughout; the ultrasound route compresses that window dramatically.

Chemically, the transformation was striking. Basil flavoring pushed total phenolic content more than 30 percent higher than chili flavoring, with basil-infused olive oil reaching levels comparable to unflavored extra virgin olive oil. Chili pepper, by contrast, was the star of carotenoid enrichment: both chili-flavored oils showed significant carotenoid uptake, while the controls and basil versions showed little or none. These pigments are largely lost during refining, which can strip as much as 98.6 percent of carotenoids from an oil, so their recovery via ultrasound represents a meaningful restoration of both color and nutritional value. Radical-scavenging activity measured by the DPPH assay rose significantly in all flavored oils except chili-flavored olive oil, suggesting that non-polyphenolic antioxidants such as tocopherols and capsaicinoids also migrated into the oils.

Quality parameters told a more nuanced story. Peroxide values and free fatty acid levels remained essentially unchanged after chili flavoring, but basil flavoring raised peroxide values considerably, from around 3 to over 13 meq O2/kg in olive oil and above the Codex reference threshold of 10 for refined seed oils in grape seed oil. The researchers attribute this difference to the flavoring matrix rather than the oil itself, pointing to the varying endogenous enzymes and pro-oxidant compounds that different herbs carry. Still, the dramatically shortened processing time offers an advantage over traditional infusion, which in one published comparison caused a sevenfold rise in free fatty acids and a doubling of peroxide values over six days. The takeaway is that processing conditions and storage need to be tailored to each specific herb and oil combination.

Chemistry, however, is only half the battle. A functional oil nobody wants to buy is a commercial failure, so the team recruited 70 untrained consumers for a rigorous sensory trial at the University of Camerino under controlled ISO-standard conditions. In a first blind phase, participants rated appearance, odor, flavor, and pungency on hedonic scales without knowing anything about the samples. Chili-flavored oils came out on top, earning overall liking scores of 6.23 and 6.14 for olive and grape seed versions respectively, while basil versions scored 5.49 and 4.86. Interestingly, the unfamiliarity of grape seed oil did not drag its scores down relative to olive oil, suggesting that intrinsic sensory performance can compensate for limited consumer knowledge when no other cues are available.

Just-About-Right scales and penalty analysis pinpointed exactly where each formulation fell short. For both chili-flavored oils, pungency and flavor were frequently rated as too intense, with more than 60 percent of consumers finding the spiciness of chili-flavored grape seed oil excessive, making it the main driver of lost liking. Basil oils suffered the opposite problem: over half of participants rated their aroma and flavor as too weak, indicating a need for higher herb loading or longer extraction. These findings give product developers a concrete reformulation roadmap: tame the capsaicin burn, amplify the basil bouquet, and the oils themselves matter less than the flavoring matrix.

The most psychologically intriguing results came in the second phase, an informed expectation test in which participants learned the oil type, the flavoring matrix, and the polyphenol and antioxidant content of each basil oil before re-rating them. Flavor liking jumped by 15.37 percent for basil olive oil and 20.37 percent for basil grape seed oil compared to blind scores, a statistically significant assimilation effect consistent with expectation-disconfirmation theory. Overall liking rose 11.66 and 13.79 percent respectively, though those gains did not reach statistical significance. The effect was strongest for grape seed oil, the less familiar product, supporting the idea that positive sustainability and health information fills the knowledge gap that unfamiliar products typically suffer from.

Purchase intention shifted even more dramatically. Willingness to repurchase climbed from 46 to 64 percent for basil-flavored olive oil and from 29 to 46 percent for basil-flavored grape seed oil once the enrichment story was disclosed. Under expectation-disconfirmation theory, the positive cues about bioactive content and by-product valorization generated expectations that consumers then integrated into their hedonic judgments, even though the oils themselves were identical between the blind and informed rounds. The researchers note this pattern aligns with earlier work showing that nutritional and health-related claims can reshape sensory perception, and they caution that their same-session design, though mitigated by randomization and palate cleansing, may have introduced memory effects.

The study has limitations that the authors openly acknowledge: spectrophotometric assays captured overall antioxidant enrichment but not individual compounds, storage stability and batch variability remain untested, and the panel was overwhelmingly Italian, which matters given the cultural variability of spice tolerance. Future work should add chromatographic profiling, complementary antioxidant assays, shelf-life studies, and broader consumer panels. Still, the core message stands: a 10-minute burst of ultrasound can convert two discounted oils and two categories of agricultural waste into antioxidant-rich flavored products that consumers actively want, provided the label tells them why it matters. For an industry under pressure to cut waste and add value, the sound of sustainability may well be a 38 kHz hum.

Subject of Research: Ultrasound-assisted enrichment of refined olive and grape seed oils with basil and chili pepper by-products and its effect on consumer perception

Article Title: From By‐Products to Flavored Oils: Ultrasound‐Assisted Enrichment of Refined Olive and Grape Seed Oils and Consumer Perception Under Blind and Informed Conditions

Article References: Corsetti, S., Bailetti, L. I., Calzolari, S., Floridi, M., Sagratini, G., & Alessandroni, L. (2026). From By‐Products to Flavored Oils: Ultrasound‐Assisted Enrichment of Refined Olive and Grape Seed Oils and Consumer Perception Under Blind and Informed Conditions. Food Science & Nutrition, 14(9), Article e72374. https://doi.org/10.1002/fsn3.72374

Image Credits: AI Generated

DOI: 10.1002/fsn3.72374

Keywords: ultrasound-assisted extraction, grape seed oil, olive oil, food by-products, basil, chili pepper, antioxidants, polyphenols, carotenoids, consumer perception, circular economy, sensory evaluation