Comparison of Machine Learning Algorithms for Predictive Modeling of Beef Attributes Using Rapid Evaporative Ionization Mass Spectrometry (REIMS) Data

Ambient mass spectrometry is an analytical approach that enables ionization of molecules under open-air conditions with no sample preparation and very fast sampling times. Rapid evaporative ionization mass spectrometry (REIMS) is a relatively new type of ambient mass spectrometry that has demonstrat...

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Veröffentlicht in:	Scientific reports 2019-04, Vol.9 (1), p.5721-5721, Article 5721
Hauptverfasser:	Gredell, Devin A., Schroeder, Amelia R., Belk, Keith E., Broeckling, Corey D., Heuberger, Adam L., Kim, Soo-Young, King, D. Andy, Shackelford, Steven D., Sharp, Julia L., Wheeler, Tommy L., Woerner, Dale R., Prenni, Jessica E.
Format:	Artikel
Sprache:	eng
Schlagworte:	631/61/320 639/638/11/296 639/705/531 Algorithms Artificial intelligence Beef Classification Food Analysis - methods Humanities and Social Sciences Ionization Ions Learning algorithms Machine Learning Mass Spectrometry Mass spectroscopy multidisciplinary Prediction models Red Meat Sample preparation Science Science (multidisciplinary) Scientific imaging United States
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