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This has already been done, and is contained in the USDA nutrient database (http://ndb.nal.usda.gov/), among others.


I know...but this is not the same as being able to procedurally generate this for arbitrary samples


I'm an absolute layman when it comes to this subject, so forgive my verbosity and lack of proper terminology:

When I clicked on that link and searched for "banana" and then clicked on "banana, raw", I was hoping to see a list of the scary-looking names I saw on the blog post that started this thread. I only see things I recognize.

I think what would be cool/interesting (and I'm guessing what cing meant to say) would be if there were a way to get that list (the scary-looking one, not the vitamins and minerals one) from some procedure done to a vegetable.

In that sense, the link you provided does not have the same information that the author of the blog post is (apparently) compiling by hand.


"I think what would be cool/interesting (and I'm guessing what cing meant to say) would be if there were a way to get that list (the scary-looking one, not the vitamins and minerals one) from some procedure done to a vegetable.'

It is currently not possible:

https://en.wikipedia.org/wiki/Metabolomics#Metabolome

Found some papers on Google that try to find fractions of the metabolome -- in this one, the tomato:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1533921/

   The identification of compounds, in particular secondary
   metabolites, through a metabolomic profiling approach
   encounters some major difficulties. First, the number of
   commercially available standards of secondary metabolites
   reported to be present in a specific plant species or
   tissue is low. Second, in an automated online separation,
   PDA detection, MS measurement, and/or MS/MS fragmentation
   of mass signals, it is difficult to meet optimized levels
   for all eluting compounds. Due to overlapping compounds,
   low intensity mass signals, or difficulties in the
   isolation of the mass signal for MS/MS fragmentation,
   the extraction of usable information for identification
   purposes can be complicated. Third, the lack of dedicated
   software and databases that integrate spectroscopic and
   MS data limits the identification procedure to a manual
   level. Nevertheless, by these means 43 metabolites could be
   readily assigned in the tomato fruit extract (Tables III
   and IV), leaving more to be identified. The total number
   of compounds detectable by our LC-MS system is difficult
   to calculate due to the presence of mass signals from
   isotopes, adducts, and unintended in-source fragmentation.




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