Explainable Deep Learning to Predict Kelp Geographical Origin from Volatile Organic Compound Analysis
In addition to its flavor and nutritional value, the origin of kelp has become a crucial factor influencing consumer choices. Nevertheless, research on kelp’s origin traceability by volatile organic compound (VOC) analysis is lacking, and the application of deep learning in this field remains scarce...
Saved in:
| Main Authors: | Xuming Kang, Zhijun Tan, Yanfang Zhao, Lin Yao, Xiaofeng Sheng, Yingying Guo |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/14/7/1269 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
HS-SPME-GC-MS Analysis of the Volatile Composition of Italian Honey for Its Characterization and Authentication Using the Genetic Algorithm
by: Carlotta Breschi, et al.
Published: (2024-09-01) -
Comparative study of volatile and non-volatile flavor substances in squid from multiple origins
by: Mengli Han, et al.
Published: (2025-04-01) -
Research on the Separation Technology of Kelp and Shellfish Box Based on Shellfish–Kelp Mixed Culture Mode
by: Yanan Wang, et al.
Published: (2024-11-01) -
Influence of different geographical origins and bottle storage times on the chemical composition, antioxidant activity and sensory properties of Cabernet Sauvignon wine
by: Yun Xie, et al.
Published: (2024-12-01) -
Comparison and chemometrics analysis of phenolic compounds and mineral elements in Artemisia Argyi Folium from different geographical origins
by: Lifei Hu, et al.
Published: (2024-12-01)