Ultrafast GC E-Nose Profiles Vegetable Breads

How food looks, tastes, and smells all play a part in how we experience it, and no single instrument can capture all these qualities at once. Using several machines that mimic the human senses, and then combining their results, offers a way to measure these qualities objectively.

In a recent study, researchers tested five breads: a plain bread and four breads made with added vegetables, namely pumpkin, a type of kudzu root called Pueraria thomsonii, red pepper, and celery. They used three instruments: an “electronic eye” to measure color, an “electronic tongue” to measure taste, and an “electronic nose” based on ultrafast gas chromatography (GC), which quickly separates and detects the compounds that give food its smell. The team published their findings in the journal Frontiers in Nutrition.¹

Why Use Electronic Eyes, Tongues, and Noses to Study Food Instead of Relying Only on Human Taste Testers?

How a food looks, smells, and tastes all work together to shape how we experience it and what we think of it. Traditional taste tests with people are still essential for judging food quality, because they directly capture what people experience. However, the results can be affected by the testers’ experience, how they’re feeling physically, and their surroundings. This can make the results less consistent and harder to repeat, especially when many samples are being tested or when the differences between them are small. This is where instruments can help, by providing objective measurements to go alongside human judgment. Thanks to advances in sensor technology and data analysis, “electronic eyes,” “electronic tongues,” and “electronic noses” are now widely used in food research. These devices measure color, taste, and smell, respectively, giving scientists objective tools for studying each of these qualities in food.^2-4

What Did the Electronic Eye, Tongue, and Nose Reveal About How the Vegetable Juices Changed the Bread’s Color, Taste, and Smell?

The researchers found that each vegetable juice gave the bread its own distinct color, taste, and smell. For each instrument, the researchers used a statistical method that boils large amounts of data down to a few main patterns, and in every case a handful of patterns captured most of the differences between the breads.¹

In terms of color, the pumpkin bread was a strong, bright yellow, the red pepper bread had a clear orange-yellow look, and the celery bread kept a green tint. When it came to taste, the kudzu root bread scored relatively high for savory (umami) and bitter tastes, while the celery bread scored relatively high for saltiness.¹

The electronic nose tentatively identified 17 compounds that contribute to smell. The kudzu root bread gave strong readings for several compounds linked to fermentation. A compound that was likely acetone showed up only in the red pepper bread, while two compounds with fresh, herby aromas, myrcene and beta-phellandrene, were especially strong in the celery bread.¹

When the researchers combined the data from all three instruments, a few main patterns still explained most of the differences between the breads. Information from the electronic eye, tongue, and nose all contributed to telling the breads apart, showing that the three together gave a fuller picture than any one alone.¹

“Breads prepared with different vegetable juices exhibited distinct characteristics in terms of color, taste-response profiles, and volatile-compound profiles,” reported the authors of the paper.¹ “Feature-level fusion of multisource intelligent sensory data enables the joint representation of information from these three instrumental dimensions within a unified analytical framework, providing a methodological framework for the multidimensional characterization of vegetable breads.”

References

1. Jiang, Y.; Yang, H.; Jian, C. et al. Multidimensional Characterization of Vegetable Breads Using Multisource Intelligent Sensory Technologies and Feature-level Data Fusion. Front Nutr. 2026, 13, 1970901. DOI: 10.3389/fnut.2026.1970901
2. Ross, C. F. Considerations of the Use of the Electronic Tongue in Sensory Science. Curr Opin Food Sci. 2021, 40, 87–93. DOI: 10.1016/j.cofs.2021.01.011
3. Lu, L.; Hu, Z.; Hu, X. et al. Electronic Tongue and Electronic Nose for Food Quality and Safety. Food Res Int. 2022, 162 (Pt B), 112214. DOI: 10.1016/j.foodres.2022.112214
4. Calvini, R.; Pigani, L. Toward the Development of Combined Artificial Sensing Systems for Food Quality Evaluation: A Review on the Application of Data Fusion of Electronic Noses, Electronic Tongues and Electronic Eyes. Sensors (Basel) 2022, 22 (2), 577. DOI: 10.3390/s22020577