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Disclaimer: All the information (including hardware, software, experimental setup, procedure, and results) in this research note is provided "as is" without warranty of any kind. Author makes no warranties, express or implied, that they are free of error, or are consistent with any particular standard of merchantability, or that they will meet your requirements for any particular application and/or problem. They should not be relied on for solving a problem whose incorrect solution could result in incorrect claims which may or may not lead to any kind of monetary loss related to trade and/or legal liability. If you do use them in such a manner, it is at your own risk. The author disclaims all liability for direct, indirect, or consequential damages resulting from your experiments and claims based on their results.
Naturally occurring sugar is the sugar found in whole, unprocessed foods, such as milk, fruit, vegetables and some grains. The most common natural sugars are fructose, which is found in fruit, and lactose, which is found in milk products.
Added sugar is the sugar added to processed food and drinks while they are being made, as well as sugar you may add to your food at home. Food manufacturers may add both natural sugars (such as fructose) and processed sugars (such as high-fructose corn syrup) to processed food and drinks.
Why is sugar added to food and drinks? Well, while added sugar provides no nutritional value, it does serve many uses in food processing. Added sugar can: (1) Serve as a preservative for jellies and jams; (2) Assist in fermentation of breads and alcohol; (3) Maintain the freshness of baked goods. Sugar is also added to processed food and drinks because it makes them taste more appealing.
There are serious health consequences to consuming added sugar. Too much added sugar in your diet can contribute to tooth decay, obesity, difficulty controlling type 2 diabetes, higher triglyceride levels, lower high-density lipoprotein (HDL, also called “good” cholesterol) levels, and heart disease. Also, if you fill up on foods or beverages that contain added sugar, you are less likely to consume healthy foods and beverages that protect your health.
So the question is: Can we come up with a cheap but effective method for household use to detect added sugar in our daily drinks?
In this preliminary study, detection of added sugar in red wine is investigated using visual light spectroscopy.
(So, why did not I use grape juice? Well, wine can be considered as grape juice and I do not like non-alcoholic grape juice at all :) )
In the study, red wine (Gallo Family, Cabarnet Sauvignon) and granulated white sugar are considered. In addition, Public Lab’s webcam-based spectrometer (http://publiclab.org/wiki/spectrometer), and its data collection software “Spectral Workbench” (https://spectralworkbench.org/) along with few extra tools are used (See Figure 1).
Figure 1 - Setup (left) and products used (right)
Total 8 samples are created. Starting from no sugar added red wine, 1 tea spoon (~ 4 grams) of granulated white sugar is added to a cup (~ 235 ml) of red wine for each sample, up to 7 tea spoons.
Once the spectrometer is calibrated with CFL, physical setup (shown in Figure 1) is set. First, a spectral data is recorded with the empty petri dish (90 mm diameter, glass) and a Verilux 18 Watt Natural Spectrum CFL Bulb (http://www.verilux.com/compact-fluorescent-bulbs/compact-fluorescent/ ). We call this spectrum as “baseline”. Later, from each sample, 15 ml is taken and poured in the petri dish and the spectral data are collected. (Those spectral data are on the Public Lab’s website and nomenclature of the data is provided in Appendix.)
Collected spectral data are then smoothed with 5th order Savitzky–Golay filter. Baseline, red wine (no added sugar) and red wine with added sugar (7 tea spoons/cup) are shown in Figure 2.
Figure 2 – Spectral data of the baseline, red wine (no added sugar) and red wine with added sugar (7 tea spoons/cup) - zoomed region on the right
Later, the difference between each sample spectra and the baseline spectrum is calculated. Resulting spectral data (from few samples) are shown in Figure 3.
Figure 3 – Spectral data of the difference between the samples and the baseline (zoomed region on the right)
As a simple metric for measuring the level of added sugar, area under the curve between the wavelengths 425-440 and 590-620 nm are selected. This is more robust measure compared to “peak height” which fluctuate more causing noisy measurements.
Values of the area under the curve (AUC) with respect to different added sugar levels are shown in Figure 4. It is clear that the amount of added sugar and AUC exhibit almost perfect linear relation.
Figure 4 – Adulteration level and AUC exhibit almost perfect linear relation
NOTE-1: The first data point which is calculated from red wine sample (without added sugar) seems to be problematic! That was the first data sample poured into the petri dish and petri dish might not be completely clean at that time. Another potential explanation is: the lamp used in this experiment takes some time to reach its stable maximum intensity as any other CFL and may be that sample spectra collected little early. However, remaining data suggest that the technique works well.
Results of this preliminary study show that, using visual light spectroscopy (using the spectrometer developed by Public Lab), it’s possible to detect/model/measure added sugar amount in red wine in an efficient and simple way. Furthermore, these results indicate that it might be possible to detect and measure added sugar amount in other drinks such as fruit juices, coffee etc. as well.
These results also suggest that, similar approach may be used to identify the level of salt or some other added sweeteners in drinks.
NOTE-2: Looks like the LED lamp I used in my olive oil adulteration study is much better than Verilux CFL that I used in this study.
test2: CFL spectra used for calibration
d3-L: Spectra of the Verilux CFL
d3-b: Spectra of empty petri dish - baseline
d3-rw-s0: Spectra of sample – red wine (no sugar added)
d3-rw-sx: Spectra of sample – x tea spoons of sugar added to a cup (x=1 to 7)
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Wow, very cool! Can you link to your spectra on SW?
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Sorry but what is SW?
Sorry! Spectral Workbench.
Info about the spectra is in the appendix already but I guess you mean something different by linking? Am I missing something?
Oh I was just hoping for links to the raw data you collected.
I just saw an article about detecting if a drink has been drugged:
How much sugar is in wine? How much rohypnol is in beer?
A rather nice exercise, well done. Quite surprising results I think, I would have predicted the extra sugar to have had minimal effect on the transmission of light through the wine. Your results suggest it is both detectable and predictable.
So why are you testing for extra sugar ? I know the Europeans sometimes add sugar to their grapes, but the sugar is then fermented into alcohol by the yeast, so there is usually no remaining sugar in a dry wine. Slightly different for some sweet white wines and fortified, which have residual sugar levels, but you wouldn't expect to have to test for sugar in bottled red wine. Even if the grapes had been "boosted" the sugar is now long gone.
It would be interesting to see if the addition of extra acid to wine could be detected the same way. If you have time on your hands and want another experiment, maybe add tartaric acid in small amounts and see if you can detect the levels. Red wine might have around 8g/litre of tartaric acid (and other acids), so adding an extra 0.5g/L in steps up to 12g/L would be useful. While you are doing the spectroscopic analysis, taste the wine as well and see if you can put the glasses into increasing order of acidity :) We found the palate was quite discriminating. IIRC Euro wines aren't allowed to add extra acid, so that would be a useful test to have available.
well done again, I enjoyed reading about your work (and the Olive Oil analysis), I'd also suggest using a broad spectrum source rather than the CFL, but you already know that !.
Thanks Stu... I just wanted to see if added sugar is detectable first. If yes, you can may be measure the sugar levels during wine making process as well, right? Or chose the appropriate grapes to start with... Also, "no added sugar" labels on juices may not be true :) You can catch them too...Also, may be differentiate different sugars or sweeteners, or may be even detect some other additives in juices...May be it is possible to detect honey adulteration with sugar and/or syrup as well... It was just a humble start :)
ah yes, good thinking. well done again on your work, a very well written research note as well.
I think i found the data on Yagiz's Spectral Workbench profile, and I made a set: https://spectralworkbench.org/sets/show/1369
Embeds don't seem to work, maybe iframes in comments are disallowed?
Thanks a lot Jeff!
Good observations -- but why use a CFL which has poor SNR for wide-band averaging because the spikes prevent using higher light intensities for broad-band measurements? Switch to a halogen and then search for a wider bandwidth (which shows indications of sugar sensitivity) to average which should have a higher SNR.
Hi, how does one download the data in the appendix? Thanks!
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