Hi Bootlegjones,
Not sure what trends or data home brewers are after, but I am working on something for professional brewers (it might also help home brewers). Can I ask is your project a PhD project? And what Uni are you working out of?
I am currently part of a small Biotech startup in Newcastle CBD, using spectroscopy with machine learning to analyse beer, wine, honey and oils.
For wine we are detecting ABV, specific gravity, pH, titratable acidity (pH 8.2), titratable acidity (pH 7.0), residual glucose and fructose, acetic acid and malic acid, as well as off products.
Tea tree oil, we measure a range of compounds similar to what are found in hops eg. limonene, pinene, terpinolene, viridiflorol.
For beer we are aiming to look at off flavours, ABV, SG, residual sugars, hop flavours etc.
Initially it is just the basic wet chem data, but as we get more samples and data, the long-term ability of the AI learning models could predict malt + mashing profiles, adjuncts added, hop additions (g/L @ specific timepoints). The really long-term aspect of this would be that the machine learning could help suggest improvements to make a better beer.
Regards,
Mark.