Independent component analysis-processed electronic nose data for predicting Salmonella typhimurium populations in contaminated beef
By S. Balasubramanian, Suranjan Panigrahi, C. Logue, C. Doetkott, M. Marchello, J. Sherwood. 2008
75 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Biomedical Engineering, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/61e91cb5937e1aed321cbf3a6640a8d51902892e
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In Analytical Chemistry
In Biomedical Engineering
In Molecular Biology
Citations in the corpus
- Metal Oxide Sensors for Electronic Noses and Their Application to Food Analysis (2010, methodology): “Meat Freshness and type of meat 4* SnO2 C [19] Microbiological contamination 7 SnO2 thick film E [20] Origin of meats 6 SnO2 C [22] Taints 5 SnO2 E [25] Fish Freshness 6 SnO2, CTO, WO3 C [27] 6 SnO2, CTO, WO3 C [28] 6 SnO2 E [29] Milk and dairy products Adulteration/ Contamination 10 SnO2 C [32] 12*”
- Application of electronic nose in Chinese spirits quality control and flavour assessment (2012, unknown): “Our group and others have reported the application of electronic nose in food and beverage quality control and assessment, including liquid or solid samples being analysed by detecting the headspace volatiles (Balasubramanian et al., 2008; Concina et al., 2009; Gobbi et al., 2010; Liu & Tu, 2011; Ra”
- Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries (2011, methodology): “The principal components and independent components were plotted against Salmonella population counts and a stepwise linear regression model built [57].”