Methoden vergleichen

	Gas-Chromatographie-Olfaktometrie	Elektronische Nase	Texturprofilanalyse
Fachgebiet	Lebensmittelwissenschaft	Lebensmittelwissenschaft	Lebensmittelwissenschaft
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Entstehungsjahr	1997	1982	1968
Urheber	Terry Acree	Krishna Persaud	Malcolm Bourne
Typ	Sensory-Instrumental Coupling	Chemical Sensing Device	Mechanical Texture Method
Wegweisende Quelle	Acree, T. E. (1997). GC/Olfactometry. Analytical Chemistry, 69(5), 170A-175A.	Persaud, K., & Dodd, G. (1982). Analysis of discrimination mechanisms in the mammalian olfactory system using a model nose. Nature, 299(5881), 352-355.	Bourne, M. C. (1968). Texture profile of foods. Journal of Food Science, 33(3), 280-283.
Aliasnamen	GC-O	e-Nose, artificial olfaction	TPA
Verwandt	3	3	3
Zusammenfassung	Gas Chromatography-Olfactometry (GC-O) combines the separation power of gas chromatography with human olfactory perception to identify which volatile compounds in a food sample contribute to its aroma. Developed by Acree and colleagues in the 1990s, GC-O allows researchers to bypass the human nose's inability to consciously identify which of many simultaneous odors they are perceiving, replacing the 'olfactory bulb' with a trained human panelist.	An electronic nose (e-nose) is an instrumental analytical device that mimics the mammalian olfactory system to detect and identify volatile organic compounds (odors) in food products. Developed by Persaud and Dodd in 1982, e-noses use arrays of non-selective chemical sensors combined with pattern recognition algorithms to create electronic signatures of food aromas, enabling objective, rapid quality assessment and shelf-life prediction.	Texture Profile Analysis (TPA) is an objective, mechanical method that simulates mastication (chewing) to measure the textural properties of food products. Developed by Bourne in 1968, TPA uses a texture analyzer (a machine that applies defined forces and movements to a sample) to generate a force-time curve from which multiple texture attributes (hardness, springiness, chewiness, cohesiveness, adhesiveness) are extracted and quantified.