%0 Generic %A Rychlik, Michael %A Schmitt-Kopplin, Philippe %D 2020 %T Table_1_Reading From the Crystal Ball: The Laws of Moore and Kurzweil Applied to Mass Spectrometry in Food Analysis.pdf %U https://frontiersin.figshare.com/articles/dataset/Table_1_Reading_From_the_Crystal_Ball_The_Laws_of_Moore_and_Kurzweil_Applied_to_Mass_Spectrometry_in_Food_Analysis_pdf/11911482 %R 10.3389/fnut.2020.00009.s001 %2 https://frontiersin.figshare.com/ndownloader/files/21845193 %K metabolome databases %K analytical chemistry %K high resolution %K LC-MS sensitivity %K structure identification %K single molecule detection %K dark matter %X

Predictions about the future knowledge of the “complete” food metabolome may be assayed based on the laws of Moore and Kurzweil, who foresee a technological development on exponential behavior. The application of these laws allows us to extrapolate and predict roughly when each single metabolite in foods could be (1) known, (2) detectable, and (3) identifiable. To avoid huge additional uncertainties, we restrict the range of metabolites to those in unprocessed foods. From current metabolite databases and their coverage over time, the conservative number of all considered food metabolites can be estimated to be 500,000, predicting them being known by around 2025. Assuming these laws and extrapolating the current developments in chromatography and mass spectrometry technology, the year 2032 can be estimated, when single molecule detection will be possible in “routine” mass spectrometry. A possible forecast for the identification of all food metabolites, however, is much more difficult and estimated at the earliest in 2041 as the year when this may be achieved. However, the real prediction uncertainty is extreme and is discussed in the essay presented here.

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