Tea quality prediction using a tin oxide-based electronic nose: an artificial intelligence approach

By R. Dutta, Evor L. Hines, J. Gardner, K. R. Kashwan, Manabendra Bhuyan. 2003

181 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/3e63d872885709492e7a3fddd2c2a09e5d1492a1

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In Analytical Chemistry

1. Amalia Berna

In Biomedical Engineering

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In Spectroscopy

1. Amalia Berna

Citations in the corpus

• Metal Oxide Sensors for Electronic Noses and Their Application to Food Analysis (2010, methodology): “Alcoholic beverages Classification of drinks 12 SnO2, CTO, WO3 C [78] 6 SnO2, CTO, WO3 C [90] 6 SnO2 E [73] 6* SnO2 C [71] 18 SnO2, CTO, WO3 C [91] Off-flavors and aromatic compounds 12 SnO2, CTO, WO3 C [79] 18 SnO2, CTO, WO3 C [91] 16 SnO2 E [93] 16 SnO2 thin film E [95] 16 SnO2 E [94] Non alcoholi”