Classifying Plant-Based Drinks Using New Methods
Author Information
Author(s): Papp Zsigmond, Nemeth Laura Gabriela, Nzetchouang Siyapndjeu Sandrine, Bufa Anita, Marosvölgyi Tamás, Gyöngyi Zoltán
Primary Institution: University of Pécs, Hungary
Hypothesis
Can gas chromatography with ion mobility spectrometry (GC-IMS) and an electronic nose effectively classify plant-based drinks based on their volatile compounds?
Conclusion
The electronic nose outperformed GC-IMS in classifying plant-based drinks, achieving higher accuracy and faster analysis times.
Supporting Evidence
- The electronic nose was able to completely separate seven samples, while GC-IMS could only separate one.
- Classification accuracies for GC-IMS ranged from 15.4% to 100%, while electronic nose accuracies ranged from 96.2% to 100%.
- Both methods are useful for classification, but the electronic nose performed slightly better than GC-IMS.
Takeaway
This study looked at different ways to tell plant-based drinks apart by smelling them, and found that one method worked better and faster than the other.
Methodology
The study used gas chromatography with ion mobility spectrometry (GC-IMS) and an electronic nose to analyze 111 plant-based drink samples.
Limitations
Further research is needed to improve the methods and establish a rapid, cost-effective food quality control system.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website