Comment by refurb | Hacker News Reader

Comment by refurb | Hacker News Reader

Some thoughts from an organic chemist who has a decent amount of experience using IR spectroscopy.

- IR spectroscopy is one of several methods used together to determine the structure of a molecule. It's certainly not definitive by itself.

- Some functional groups in molecules will give very specific signals (1700 cm^-1 for carbonyl functional groups, C=O), but for a lot of other functional groups, you get very weak signals that can sometimes be hard to distinguish

- IR works pretty good for pure compounds, but when you start to measure mixtures, the overlapping signals can get very difficult to isolate and identify

- As rjdagost mentioned, taking a sensor out of the lab will lead to all sorts of issues. Any stray light will likely cause any readings to look like garbage

I could see this technology being useful to identify different types of plastic. You have a limited universe of possible materials along with some pretty specific functional groups that are either there or not.

To use it as a "molecule sensor for all", seems a big problem to try and tackle.

And how the hell does it determine the ripeness of a avocado through the skin?

If your only exposure is analytical lab work (where by definition the work is difficult), you may not be familiar with the breadth of field utility of near-IR.

Some application examples: https://news.ycombinator.com/item?id=7699186

> And how the hell does it determine the ripeness of a avocado through the skin?

eg: http://ucanr.edu/datastoreFiles/234-347.pdf and http://www.aseanfood.info/Articles/13004404.pdf

[edit: removed LMGTFY link - sorry, that was rude. But please don't pull the expert card outside your area of expertise: NIR has been used to assess fruit ripeness for decades]

The optical and internal quality data were then merged and a PLS regression analysis was conducted using the NSAS software package (NSAS, 1990).

My comment wasn't that you couldn't test the ripeness of fruit using near-IR, it was that you could reliably doing it using a handheld consumer product.

There is a BIG difference between running a lab analysis using near-IR and making a consumer friendly product that can accurately produce the same data.

There are multiple manufacturers making NIR-based fruit quality sensors used quite far from laboratory conditions, as well as portable NIR sensors.

(See my other comments in this thread)

By "lab setting" I mean someone who can run controls, and do the statistical analysis to arrive a decent data, not just portable equipment.

I guess if they are willing to measure ripeness with a margin of error of +/-50%, that'll work.

+/- 50% wouldn't work in a consumer setting, but +/- 5% would work great. If you're in a lab, +/- 5% might be a disaster.

One of the proposed use cases of the SCiO is pharmaceutical identification. Consumer Physics needs to be EXTREMELY careful with marketing this use. I would actually discourage this type of application if I were them.

I was interested to see them use a Bayer Aspirin in their demo. Aspirin is -- or was (my pharmaceutical formulation training is nearly three decades out of date) almost unique in being one of the few drugs that has the perfect powder flow, binding, and dispersal characteristics to pressure-form into tablets using a tablet punch machine without any other binders, lubricants, bursting agents, or other ingredients. Back when I was studying the topic, an aspirin tablet was generally just that -- powdered acetyl salicylate compressed into a tablet shape.

If this thing can correctly identify an enteric-coated or other sustained-release pharmaceutical formulation other than by checking a muddy absorption curve against a database of known samples I'll eat my hat.

Also: the app they used purported to identify tablets by their manufacturer brand? Ahem: WTF? This does indeed look like it's just throwing a spectrum at a database of samples and looking for the closest match. Which is hardly going to weed out some of the better counterfeits on the [black] market ...

Not to mention that it supposedly can tell you how many grams of sugar are in something, or what "percentage of water" is in an apple? No, there's no way you could do that with spectroscopy. Say you have an apricot, you measure it with the device, and it indeed says it's an apricot. Apricots are not all the same, the "CandyCot" apricot has about 2x to 3x the sugar content of other apricots. There's no way they could check the DNA of the plant and determine specifically what kind of apricot it was, unless perhaps you were to isolate the dna and change the setting on the device to 'DNA' and you had a database of the characteristics of different Apricot DNA.

This is inaccurate; water content is one of the easiest things to measure with near-infrared spectroscopy, and NIR has enough penetrance to be useful even for fruits with fairly tough skins (eg avocados, see last link below)

There are multiple commercial manufacturers selling NIR sensors for fruit quality control:

http://www.moisttech.com/

http://www.ndc.com/en/Products/On-Line-NIR-Gauges.aspx

Research articles: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673116/ http://www.cropj.com/miraee_4_3_2010_175_179.pdf http://www.brimrose.com/pdfandwordfiles/I_GRASA-CSIC.pdf http://cdn.intechopen.com/pdfs-wm/36050.pdf (avocados)

Sure, but for sugar you need to measure refraction not absorption.

SCiO is based-on near-IR spectroscopy, instead of typical IR spectroscopy. Even though they both share the same "IR" in the name. The way how these technique work can be significantly different.

SCiO do not use typical IR spectroscopy. For near-IR typically, chemometrics (or let's say PCA) has to be used to get any type useful information from the result.

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