Early Detection of Fungal Growth in Bakery Products by Use of an Electronic Nose Based on Mass Spectrometry

2004 ◽  
Vol 52 (20) ◽  
pp. 6068-6074 ◽  
Author(s):  
Maria Vinaixa ◽  
Sonia Marín ◽  
Jesús Brezmes ◽  
Eduard Llobet ◽  
Xavier Vilanova ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Early Detection ◽  
Electronic Nose ◽  
Fungal Growth ◽  
Bakery Products

scholarly journals Coupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma

2020 ◽  
Vol 20 (1) ◽  
pp. 841-857
Author(s):  
Malena Manzi ◽  
Martín Palazzo ◽  
María Elena Knott ◽  
Pierre Beauseroy ◽  
Patricio Yankilevich ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Renal Cell Carcinoma ◽  
Early Detection ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Learning Approach ◽  
Cell Renal Cell Carcinoma ◽  
Machine Learning Approach

The influence of foxtail millet flour on the formation of bakery products flavor

2021 ◽  
Vol 30 (3) ◽  
pp. 58-62
Author(s):  
L.I. Kuznetsova ◽  
◽  
M.K. Sadygova ◽  
T.A. Kuchmenko ◽  
R. U. Umarkhanov ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Foxtail Millet ◽  
Bakery Products ◽  
Amaranth Flour ◽  
Destructive Processes

The article presents the results of a study of the formation of flavor‑forming substances in flour products with the addition of foxtail millet and amaranth flour to the recipe. It is proved instrumentally on the smell analyzer «MAG‑8» with the methodology «electronic nose» that for the samples submitted for testing, the smell is correct and not pronounced, the absence of aromatic additives, odor enhancers, the presence of destructive processes and mold formation.

Sign in / Sign up

Export Citation Format

Share Document