"Density is ink film thickness"

I've heard it said thousands of times. Solid ink density tells you how thick the ink is, and CIELAB tells you the color. Along with this goes the converse: solid ink density does not tell you color, and CIELAB doesn't tell you the amount of ink. I'm writing this post to set the record straight. There is nothing fundamentally different between density and CIELAB, except that there is less information in density.

The start of the scandal

I admit to my own little contribution to this scandal. I have talked about Beer's law. Incessantly. I even wrote a blog about Beer's law. In hindsight, I realize that I should have just stuck with Wien's Law [1]. But there it is, I ordered the Beer.

Beer's law, or Wien's law?

I didn't mention ink in that particular blog, but it wasn't long before I started having a little ink with my Beer. In one post, I used Beer's law to explain why ink sometimes changes in hue when you slather it on. As if that wasn't enough, I pulled out another six-pack to describe how to reach a CIELAB target when all you have control of is ink film thickness or pigment concentration.

Image from the world famous perifarbe blog post

Let's have a look at each of the four myths and see how they stand up.

Myth #1 - Solid ink density is ink film thickness

Now, if there were laws about truth in blogging, I woulda probably shoulda mentioned that Beer's law is a decent approximation, but there are some other things going on that limits it a bit when we are talking about ink.

Beer's law (when applied to ink) assumes that light enters the ink, reflects from the paper underneath the ink, and then goes back through the ink. The more distance it travels in the ink, the more likely it is to be absorbed. Those are the two fates of a photon: it gets caught, or it makes it out of the ink. The thicker the ink, the higher the probability of getting caught. Beer's law puts no limit on this. Given a thick enough ink, the density could be a zillion. (This would correspond, of course, to a reflectance of one in ten to the zillionth. My densitometer doesn't quite go that high.)

There are, however, two other potential fates for a hapless photon. A photon without much hap could bounce off the top of the ink, never having a chance to see the ink at all. This is called specular reflection. Another fate has to do with transparency. Photons could bounce around inside the ink and eventually find their way back out before even seeing the paper.

These two effects guarantee that there will be at least a few wayward photons that wind their way back to the detector. Thus, this puts a limit to the density, so all good proportionality must eventually come to an end. Buy me a beer some day, and I'll tell you everything you want to know about the Tollenaar-Ernst equation [2].

One of my favorite equations, the Tollenaar-Ernst equation

The T-E equation in action

Conclusion? Myth partly busted. 

Myth #2 - CIELAB does not measure ink film thickness

I presented a paper at the 2008 TAGA conference entitled "Building a bridge from Dense City to Colorimetropolis". The paper was dreck, but I am quite proud of the clever title [3].

Photo-realistic drawing of the San Francisco bridge 

In this paper I showed that the color difference between paper and the solid (in deltaE values) correlates reasonably well with (paper relative) density when measuring cyan, magenta, and yellow inks. My conclusion is that CIELAB values contain all the information that density values do.

It is incorrect to say that CIELAB does anything really any different from density. The only issue is that of the software catching up. If spectrophotometers and offline software packages reported the right numbers in a way that could be readily understood by press crews, then the myth would just plain go away.

Myth busted! Here is the correct statement to replace the first two myths: "Both density and CIELAB are indicative of ink film thickness, but neither is completely true, especially when you get to high density." [4]

Myth #3 - CIELAB tells you the color of the ink

Well, duh. CIELAB is color, right?

Some pedantics might argue that CIELAB is not color, but that CIELAB is a good enough approximation to work for many industries. CIELAB tells you a lot about the appearance of an object, but it doesn't take a lot of things into account, like

1. The effect of adjacent colors on our perception of an object
2. The effect of out perception of a white point in our field of view.
3. Goniophotometric effects such as glossiness, opalescence, and metallic luster
4. Eye fatigue
5. Differences  in color vision between people, even among people who are not color-blind

Setting all this sophisticated stuff aside, I'm gonna say that CIELAB is a good measure of what we perceive as color. Myth Confirmed!

Myth #4 - Solid ink density does not tell you the color

All I gotta say is "orange". An orange ink may have exactly the same density as a yellow ink. The blue filter in a densitometer may see exactly the same density on an orange and a yellow ink. But, the orange ink is a different color.

The issue is, solid ink density is only one number, so it can't possibly tell you what the color is. Color is three-dimensional. Well... what if I look at all three density filters, red, green, and blue? A densitometer can report all three of these, right? That gives me three dimensions, so there you go. We have defined the color, right?

I'm gonna say "no". The three filters in a densitometer are different than the three filters in my eye.

Once again, myth confirmed!

My (perhaps unpopular) conclusion

There is nothing magical about density that allows it to put a micrometer on an ink film. Inherently, density and CIELAB are sewn from the same cloth. They are both measures of the reflectance, as measured through specific spectral filters. In one case the filters were selected so as to capture the richest part of the spectrum for specific inks. In the other case, the filters were selected so as to mimic the human eye. Other than that, the only difference is in the math.

If there were just a bit more math applied to CIELAB values to serve as a proxy for ink film thickness, then density would no longer be necessary.

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[1] I'm not kidding. Not only is there a law of physics called Beer's law, but there is a law of physics called Wien's law. It says that if you know one black body radiation curve, you know them all. In some sense, they all look alike no matter what the temperature. This is also known as the Wine-goggles effect. After enough wine, all bodies look the same, no matter how hot they really are.

[2] Tollenaar, D. and Ernst, P.A.H., “Optical density and ink layer thickness,” Adv. Print. Sci. Techn., 1962, Bol. 2, pp. 214-233.

[3] I was also proud of the really ornate and detailed drawing, which was my depiction of the San Francisco bridge. The TAGA conference that year was held in San Francisco.

[4] I have an article in the upcoming IDEAlliance bulletin that looks at the traditional Murray-Davies formula for computing dot gain, which is based on the science that went into density measurement. In the article, I show rather conclusively that this paradigm does not work for determining dot gain of spot colors. The density of a 70% for example, is nearly identical to the density of the solid, when it is clear that the 70% and the solid have different CIELAB values.

I don't yet have the data to come to any conclusion about the relationship between density and ink film thickness for spot colors, but I suspect that the same sort of thing applies. If one looks at the density/ink film relationship at the wavelengths with highest density, I suspect that these too will reach a saturation point long before the color stops changing.

Blue animals

George Carlin had this to say about blue food:

"I often wonder why there's no blue food. Every other color in well represented in the food kingdom. And don't bother me with blueberries; they're purple. The same is true with blue corn and blue potatoes. They're purple. Blue cheese? Nice try. It's actually white cheese with blue mold. Occasionally, you might run across some blue Jell-o in a cafeteria. Don't eat it. It wasn't supposed to be blue. Something went wrong."

I'm not going to argue with George Carlin about blue food, but I will state my opinion. I think blueberries are blue. I mean, are they called purple-berries? And blue potatoes? Gosh darn it... I made mashed potatoes with them, and put them in the fridge over night. I'll be darned if those puppies aren't thermochroic! They change color with temperature.

Comparison of hot and cold mashed blue potatoes

But, this blog post is not about mashed potatoes, thermochromism, or even about food. It is about animals, and in particular, blue animals.

These animals are not blue

Just to set the record straight, the following animals are not blue: blue whale, blue heeler, Latvian blue cow, Babe the Blue Ox, Russian blue cat, Blue Bunny ice cream. Some day, I'm going to write a blog post about the myriad of animals and other things that have been assigned the wrong color name, starting with the Wisconsin state bird, the robin red breast. This tirade will be read by the person in charge of assigning color names to animals and stuff, and some changes are gonna be made. Then we'll see just what a powerful force that my blog can be for the eradication of evil in the universe.

What Rayleigh does to light

My daughters asked me why the sky is blue. I gave them the obvious answer: "It's Rayleigh scattering." They looked at me with their cute little blue eyes and said "oh". Neither one of them have gotten a PhD in physics. At least not yet. Go figger. Maybe if I explained the difference between Rayleigh scattering, Mie scattering, and the Tyndall effect, things would have turned out differently?

Rayleigh scattering is a "pick on someone your own size" kinda thing. When photons are in the right range of wavelength compared to the size of the tiny particles (in this case) in the air, the particles and photons interact much like two dancers coming together in a spin and then suddenly letting go. The cute little photons could head off in any direction. In a cloudless sky, photons near the blue end (shorter wavelength) are more likely to get caught up in this dance, so they are more likely to change direction. Rather than come down on you straight from the sun, they appear to come from somewhere else first.

Light coming from the sun is white. The blue end gets scattered so as to make the sky appear blue. The green light gets scattered a bit too, but the red light does not scatter much. The scattered light shows up as "blue" (or more properly, as cyan, since there is green mixed in as well) and the sun takes on a yellow cast for lack of the blues.

This effect is not limited to the sky. Animals can take advantage of this. By adding tiny particles in some part of their anatomy, they can adorn themselves with brilliant blue shades. As we can see below, a light blue accent can be used to render the male of the species irresistible to the female.

Old Blue Eyes and Old Blue Face

Note: I have avoided showing a picture of the lesula, a primate that was recently discovered in the Congo. The male of this species has that mandrill thing going on, but he adorns his butt. That's just gross. 

The feathers of blue birds, by and large, are also colored by the scattering of light. In the case of blue jays and blue tits, the feathers are constructed with tiny air pockets that scatter light.

Cute little tit from a blue movie

Iridescence

Rayleigh scattering is one mechanism by which color can be imparted to an object. Another spectacular way that color arises is through the action of interference. Since light can be viewed as a wave, reflecting rays of light can combine constructively and destructively so that some wavelengths of light head in other directions than others.

Insects are masters of this coloration technique, as can be seen from the images below. [1]

Clockwise from top-left, bluebottle fly, blue swallowtail butterfly, blue darner, and jewel bugs [2]

If you brush your finger along the wing of a butterfly, you will collect what looks like a fine dust. Each little piece of dust is actually a tiny scale. Each of these scales is shaped much like a Ruffles potato chip [3]. Below is a scanning electron microscope image of a few scales from the wing of a butterfly. The ridges on the scales are the source of the iridescence that we see in many insects.

Convergent evolution?

Years ago, when I was writing software for digital scanning electron microscope, I stuffed a moth in the microscope and started looking at the beautiful scales. I found that this dull colored moth had ridges just like those on a butterfly scale, only the ridges were closer together. If we could see ultraviolet light, we would see a gorgeous luster when we look at the drab moth.

Before I move on to the next source of blue coloring in animals, I have a plethora of words for the logophiles who frequent my blog: The words pearlescent and nacreous are synonyms of iridescent. The former comes from the color of a pearl, and the latter comes from the color of nacre, which is the stuff that the inside of sea shells are made of. To be perfectly correct then, one would refer to a pearl as being pearlescent, and mother-of-pearl as being nacreous. One should always ask before complimenting a woman on her necklace.

Opalescent is another synonym which comes, of course, from the gemstone opal. Margaric is yet another word for the same effect. Margarine got its name from this word. The original margarine had an oily, pearlescent appearance. 

These words all fit under the umbrella of "goniochromic", which refers to an object where the color depends on the angle that you look at it. My advice - memorize a few of these words, and drop them randomly in sentences, like "I have been so nacreous since my margaric told me to eat less goniochromic foods." People will think you are brilliant.

The difference between boobies and tits

Rayleigh scattering and iridescence are two ways that physics has made our world more colorful. Neither of these get rid of light, they just direct it somewhere else. Pigments are a third way to make color. Pigments are chemicals that actually absorb light, and (generally speaking) do so preferentially. When they eat photons, they are selective about the wavelength. Thus, light reflected from a pigmented surface will usually be a different color than the incident light.

Blue-footed boobies get their blue color from pigments and not from scattering or iridescence. The pigment in booby feet is a carotenoid that they derive from their diet [4]. Rather than using these as anti-oxidants (to prevent accidents), boobies divert these carotenoids to their feet to enhance their sex life. 

Blue-footed booby doing the "let's make little boobies" dance

To summarize the important point here, tits are blue because of scattering. Boobies are blue because of the pigments that they eat.

But, what about the yellow underbelly of the tit? This part of their body gets its color from the yellow-green caterpillars that it eats. But, this article is about blue, and not yellow, so I won't talk anymore about the fascinating biochemistry that makes this species of caterpiggle yellow-green.

Blue pigments in vertebrates

Hazel Rossotti, in her entertaining book "Colour - Why the World Isn't Grey", said that "... no blue pigment has been found in any vertebrate..." That's a strong statement, since I had a dog that liked to eat crayons. I frequently found blue pigments in his poo. In Kurt Nassau's also entertaining book "The Physics and Chemistry of Color - The Fifteen causes of Color", the statement is softened just a bit. "Almost all animal blues ... are derived from scattering." [5]

There are certainly blue pigments in invertebrates. Mollusks and arthropods, for example, are true blue bloods. The color of their blood comes from hemocyanin, which is similar to our own hemoglobin, only it is based on copper rather than iron. What about vertebrates?

One vertebrate that proudly displays a variety of colors is the chameleon. One would think there are pigments involved in it's chromatic transmogrification, and one would be correct. There are three layers of skin that allow the chameleon to change color. The uppermost layer contains yellow and red pigments. The bottom-most layer also has a pigment, the ubiquitous melanin. It is the middle layer that is responsible for a chameleon getting the blues, through the action of guanine. But guanine is not a pigment. It is a compound with a relatively high index of refraction, which causes preferential scattering of blue light.

The master of chromatic transmogrification

There are some rare vertebrates that disprove Rossotti's claim, however. I have dug up information on two vertebrates with cyanophores: the poison dart frog and the mandarin fish.

Examples of blue pigmented vertebrates

Future research

All successful research papers must end with a statement of the form "further research is clearly warranted". This, of course, is a euphemism for "I want to keep my job." Since I want to keep my high-paying job as the world's most entertaining applied mathematician / color scientist blogger, I will end with two examples of vertebrates where the jury is still out on whether the blue coloration is mediated by the action of pigments.

The first example is an animal that has received precious little research dollars. It is unfortunate that, in today's fiscal climate, this trend is likely to continue. The Avatar, however, might stand a chance at garnering some resources.

Why is this Smurf so happy when he is so blue?

And then there's Batman. No one really knows why he is blue. Pigment? Rayleigh scattering? Interference? Or is it just the blues of being a lonely superhero? But the video below shows that he definitely has a dark side.

I hope this blog post has helped chase away the winter blues.

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[1] I have often had arguments with otherwise intelligent people who claim that insects are not animals. It would appear that their definition of animal includes only mammals, but does not include fish and birds and frogs and earthworms and butterflies and nematodes and squid and clams with a light cream sauce served on a bed of spinach linguine. I quote from Wikipedia's entry "Animal": "Animals are divided into various sub-groups, including birds, mammals, reptiles, fish and insects."

[2] This attractive set of green and blue jewel bugs is available from the Home Shopping Network. Disclaimers: These jewel bugs, attractive as they are, are not actual jewels. They are also not bugs, meaning, members of the order hemiptera. Instead, these are one of the 640,000 species of beetles (order coleoptera). Coleopterates encompass 80% of all living species of the class insecta.

[3] Despite the obvious similarity, I find the scales on a butterfly's wing to be significantly less tasty than potato chips. That, of course, is just my own preference.

[4] Flamingos, salmon, and shrimp similarly get their coloring from their diet. A flamingo in captivity will lose its orange color if not fed its normal diet of shrimp, or the appropriate carotenoids like canthaxanthin. This applies to farm raised salmon as well.

[5] These two books are both delightful. Rossotti's book is an easy read with lots of factoids that are accessible to anyone who paid attention in high school science class. Nassau's book is more technical (and expensive), but it is still written with an entertaining style.

Recommendation engines

Last night I was not having a good Pandora experience. I was sitting at my home computer, trying to come up with an idea for this week's blog post. Now, I am sure that the fact that my blog post was due in 36 hours and I didn't have a topic might have flavored my experience, but...

Darn! What should I blog about?!?!?

I was hungry for some mambo music. For whatever reason, one neuron in my head talked with one of the seventeen others, and Mama Loves Mambo started playing. Naturally, I fired up Pandora. I like Pandora [1], and I have this notion that maybe it likes my taste in music. Well, usually.

I typed in "Mama Loves Mambo" as a seed song. It gave me a song by a French guy. Heavy guitar, sixties kinda genre. The melody and treatment were (in my mind) vaguely reminiscent of Manfred Mann's version of Quinn the Eskimo. That song I never did understand - hey, Bob Dylan wrote it! But I really was not getting a mambo vibe. So, I clicked thumbs down. Pandora gave me an obsequious apology for ruining my life and gave me a firm promise to never to play this song ever again, for anyone. [2] 

Next up was Johnny Horton. Pandora says that Horton "Horton managed to infuse honky tonk with an urgent rockabilly underpinning."  Now, when I get a case of the urgent underpinnings, I would like to get my tonk honked just as much as the next guy, but I wasn't interested in rocking my billy just then. Another thumbs down, but not before I added Harry Belafonte as another seed.

It took me a while, but I eventually got a few actual mambo songs out. But even today, after Pandora has had a night to sleep on it, and had a chance to head to the library to look up "mambo", it just played "The Lion Sleeps Tonight". This is not like Pandora!

How Pandora works

Pandora has hired scads of musicologists, who do nothing all day but review new songs. Each song has 400 or so characteristics associated with it, including no doubt the beat, tonality, dominant instruments, rhythm, as well as cultural cues.

The staff musicologists at Paindora, a poor competitor of Pandora

The job is simple from there. When Pandora gets a request for a station, it merely has to find other songs that are somewhere near the 400 dimensional block that the seed is in. As more songs are added as seeds, or additional songs are thumbs upped or thumbs downed, the size, shape, and centroid of the neighborhood is adjusted. That would be my first take anyway. I would probably throw in my ellipsoidification algorithm just because it's cool.

Pandora is not the only game in town, of course. There is also iTunes Genius, which will assemble a playlist for you from a single song seed. To do this, it needs to upload information from your own library. Presumably, Genius is crowdsourcing. They combine your playlists with those of every other Genius user to assemble reasonable playlists.

My own little contribution

Several years back, I had a completely different hobby job. I was a karaoke host, under the very original name "John the Revelator". I even had my own blog - go figger. For many gigs, I wound up having to spin some standard music as well as the karaoke. I was just a bit out of my element there... I don't feel I know all the music, especially newer stuff.

The first time I needed to do this, I asked the client for a few seed songs and I went into Pandora to see what it thought went with those songs. This worked out ok, but I had to listen to Pandora for two hours to come up with a two hour set.

I could have used Genius, but the problem was that it is limited to recommending songs that are in my own library, which was perhaps limited. I needed an application that would recommend songs for me to go out and buy. Also, Genius is limited to a single seed. If a client had two or three seed songs, I could only generate two playlists and then combine them.

So I decided to write my own version of Genius.

But first a bit about Netflix

As a math dude, I have read up a bit on how Netflix computes their recommendations. Between 1999 and 2005, Netflix assembled a database of ratings from 480,000 users of nearly 18,000 movies. Netflix decided to turn this data into knowledge by announcing in 2006 a $1M contest for an algorithm that can accurately guess which movies you might like. There were a total of 44,000 submissions for this prize, which was awarded in 2009. Wikipedia discusses the Netflix Prize.

Typical family, addicted to Netflix because of it's awesome recommendation engine

As a gross simplification, Netflix starts with the simple idea. If Joe likes Airplane and Spaceballs, and Bill likes Airplane and Blazing Saddles, then Joe might like Blazing Saddles. And if John only watches movies that feature Pandora Peaks, then he might not want to go out drinking with either Joe or Bill. With a few people in the database, the recommendations might not be all that effective, but with 3.7 zillion ratings ...

It gets a lot more complicated, but that is the gist of it. The algorithm that finally won was a combination of a number of algorithms. To my delight, my favorite technique, singular value decomposition, was part of the winning algorithm.

Back to my work

I found a few websites online that were repositories of playlists. These were streaming music players that allowed people to assemble playlists, and then share them with the full community of users. With some help from my buddy Adam, I downloaded about 30,000 playlists with a total of 15,000 songs and started data mining.

My first approach was fairly simple. Each song in the database was given a list of friends, which were songs that appeared in a playlist with that song. Each friend in the friends list had a count associated with it for every playlist that the two songs shared.

When it came time to turn song seeds into a fully grown playlist, the friends lists of all the seed songs were combined. The playlist was generated by picking random songs from this combined list. The probability of a song being picked was arranged to be proportional to the friend count for the song. 

This worked well enough to create some awesome playlists for a few parties. A few hundred hours work to create playlists of maybe ten hours total? Well worth the effort! 

Problems

I was thinking along the lines of creating an AutoDJ app that would allow someone with no knowledge or interest in music and no social skills to pretend that they were a totally cool DJ, and thus be eligible to all the social advantages implied with that position in life.

Those of you who know me are probably aware that I lack the entourage of groupies that a totally cool DJ has. Since I am no longer in the karaoke host business, I even lack the more sophisticated entourage of karaoke groupies that KJs always have. But, I am never, of course, without my entourage of incredibly sophisticated groupies that follows me around because I am an applied mathematician.

You think you got the groupies?

You guessed it, I never got that killer AutoDJ app going. There were three problems that I ran into. 

The first is that it was labor intensive to clean the playlist data. “Piano Man” might be listed with the artist name “Joel, Billy” or “Billy Joel”, or “Billie Joel”, or even “Bruce Springsteen”. The title might be listed as “Piano Man”, or “Sing Us A Song”, or “Billy Joel – Piano Man”. It was quite common for the title and the artist fields to be reversed. Ya-da, ya-da. All this could be corrected in software, but it would take a bunch of time to develop that code, and I was not all that motivated to do that.

The second problem I found was that, however attractive this idea of crowd-sourcing is, the central limit theorem does not always apply. The average of the group is not always the goal that you want. In this case, the people who upload playlists are generally in their mid-teens to mid-twenties (my guess). As such, the songs that they mix with Johnny Cash are not at all songs that would go over big at a 50th birthday party for a guy who likes real country music.

The third problem was much simpler. I didn't see that it would generate much money. And why else would an applied mathematician apply math?

I could have made a website where a person enters a few songs as seeds and the website generates a fabulous playlist. I could get money from ads. I could link up with Amazon to sell mp3s. Maybe when a playlist is built, it would provide links to buy the songs on Amazon? This might make some money, but I think the whole idea is limited by the existence of Pandora and iTunes Genius. I should add, this was many, many years ago, like maybe four? Back before everyone and their neighbor's pet hamster had a smart phone and a desire to spend trifling sums of money on hundreds of apps that they will never use.

But it's still a cool idea.

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[1] Just to be clear, I am talking about Pandora, the music listening website, and not Pandora Peaks, the ummm, model. I can neither confirm or deny any feelings I may have or may have had for the model whose bra size is higher than my IQ.

[2] I always feel a little sad when I am obliged to tell Pandora that it is not doing a perfect job. I mean, who am I to question when it tells me what kind of music I like?!?!?

John the Math Guy breaks out of the blog, Feb 2013

John the Math Guy continues to make appearances outside of this tiny little blog. He also continues to refer to himself in the third person. Here are the JMG sightings for the month of February.

Annual TAGA conference

TAGA (Technical Association of the Graphic Arts) has always been one of my favorite conferences. This year's conference in Portland (Feb. 3 through the 6) was no exception. Disclaimer: I am on the board of TAGA, so I am required to say good things about the organization. Anti-disclaimer: I wouldn't be on the board if I didn't think the organization was peachy-keen.

The conference got a bit of post-press. Here is a sampling -

Brian Lawler of Cal Poly shared a GigaPan image of Portand, taken at the conference.

TAGA is unique in its high level of student participants. There are roughly 15 active student chapters of TAGA scattered all across the globe. They are regular attendees, of course, but they also participate in a competition for the best student journals. The Grenoble (France) chapter took away the highest honors this year. Here is a blog post from the Ryerson (Toronto) chapter about why they go to TAGA.

Sandy Hubbard, who has the enviable title "Print Futurist", blogged about the TAGA conference.

Since none of these folks explicitly mentioned my favorite topic (me), I have to make up for this oversight. A recent blog post ("A spectrophotometric romance") was adapted from my presentation. I also have the paper itself ("Evaluation of Reference Materials for Calibration of Spectrophotometers") available on my website. 

FlexoGlobal magazine

Laura Hatch, of FlexoGlobal magazine incorporated an adapted version of one of my blogs in her magazine last month. Do you think a dear friend like Laura would be content with just one article? I think not. Sure enough, I got a call one morning at 2:00 AM. Thinking the call was the Nobel prize committee informing me that I had won, I answered the phone. Well, it was Laura, telling me about another blog post of mine ("Why does my cyan have the blues?") that was incorporated into her magazine.

I like it when I get published without having to do any extra work! 

Coco Nuts

I'm going to take a little break from my normal sarcastic treatment of math and color science to share an infrequent hobby of mine - making sarcastic comments about people and companies that prey on the gullibility of consumers to sell "health" products.

Twinkies and other health food

Desperate Twink-ophiles bring vicious dogs with them to guard the treasure [1]

I hate to admit this, but I was in a health food store last week. As you probably know, Twinkies are no longer being manufactured, since the parent company, Hostess, went out of business. I heard a rumor that a local health food store had found a few cases of the delectable snacks. Like the lemming that I am, I went running to the store. Well, not actually running. I drove my car. It was three blocks. 

"Low Glycemic" sugar

I came across this bag of sugar that caught my attention, despite my panic stricken, crazed state of anxiety. "What? It's sugar? Like, real sugar? And it has a low glycemic index???"  I had to learn more about this. 

This is not Peter Bergman, who made the famous TV commercial about not being a doctor 

But before I pontificate, I need to recite a disclaimer. I am not a doctor, but I saw a TV show once that featured someone else who was not a doctor. And I was met someone who read a book that said something about glycemic index.

Glycemic index

The glycemic index (abbreviated GI) is much like the Dow Jones index, in that it goes up and down chaotically in response to any minor stimulation. In the Dow Jones Index, the stimulus is usually something like Obama passing gas or Fox News reporting about Obama passing gas. The GI is actually more about blood sugar levels than passing gas. When you eat something with a high GI (something with lots of sugar or simple carbs), your blood sugar spikes upward, giving you a sugar rush that we normally associate with people who write blogs. Then your body overreacts to this overreaction by pumping in the insulin, and you get a sudden drop in blood sugar level that we normally associate with people bringing their dogs with them to guard the shopping cart full of Twinkies.

The GI is the relative degree that a food will initiate this sort of reaction. Ordinary table sugar has a GI of 65, and honey is 55. [2]

Bubblegum music has a glycemic index of 817

So, that said, I started reading the label of this miracle sugar that has a low GI. I read the whole label of this package. Nowhere on the package did it state the value of the GI for this sugar. Well, that's odd. A qualitative product claim that is not precisely quantified? That never happens! Especially not in a health food store!

It became pretty clear to me that I needed to research this important matter more than I needed to satisfy my Twinkie fix. I needed to dig deep into medical journals, making sure all the experiments were blinded properly, and all the t tests were done using normal tea. In short, I read the entry in Wikipedia on "palm sugar". This article said nothing about the GI.

You may not now this, but there is a little place to click on any Wikipedia entry that will give you the revision history of the article. Just to the left of the search box in the upper right hand corner, there is a tab that says "View History". By reading through thrilling revision history, I can see that the very original version of the article (Dec of 2005) contained nothing at all related to GI. The first version that added this was on Christmas Eve, 2009. There was a lot of new material added, including the statement that palm sugar is "One of the lowest glycemic index sweeteners on the market".

This language was modified over numerous revisions. It soon received the "needs citation" award. Finally on Feb 27, 2011, someone got ticked off, and chucked out a lot of material, saying that they were "Remov[ing] commercial marketing links & dubious, uncited claims." Wow. That's what happens when you try to fool Wikipedia!

Hmmmmm..... It would appear that there might not be agreement on the GI for this sugar.

Cool pic from the Big Tree Farms website

What does the sugar company say?

For my next stop, I had a look at the website for the company that sells the sugar. On their website they actually affix a number to the GI.

"Coconut palm Sugar is naturally low on the Glycemic Index (GI), which has benefits for weight control and improving glucose and lipid levels in people with diabetes (type 1 and type 2).  Coconut palm sugars are rated as a GI 35.   By comparison, most commercial Agaves are GI 42, Honeys are GI 55 and Cane Sugars are GI 68."

Ok... interesting. Is there an attribution for this? Do they cite research or a source for this information? Actually, they do cite an organization. They describe the method used by the Philippine Food and Nutrition Research Institute. Ahh good. Now we are getting somewhere. I clicked on the link they provided, expecting to get the low down. Unfortunately, the link is to the main page of the website.

So I did some searching on this website. Every search I could think of came up empty handed.

Search results for "palm sugar glycemic"

This is starting to look not so good. I started searching the internet in general. I came across a very scientifical looking graph that clearly is the output of some very scientifical work. As proof of the scientificalness, I draw your attention to the legend of the graph (on the right), which is in Brush Script font. This font, originally designed for use on album covers with seascape sunsets, has become very popular of late in technical journals. The school bus yellow font color has also proven very effective in black and white journals. 

Lest I be misunderstood in my very subtle sarcasm, let be a but more precise. I have no doubt that the graph came from a reputable paper investigating glycemic index. Two things raise my skeptical flag: 1) The image is highly photoshopped. 2) There is no reference on this webpage to the authors of the paper, the journal where this was published, nor even the year it was published. There is no way for me to find the paper.

Alternate opinions

I stumbled on this webpage that is rather critical of the coconut palm sugar industry. The bellicose author of this article went so far as to say that "many of the nutrient claims [of coconut palm sugar] may be unfounded." These are truly fighting words. I should point out that the bellicose author offered nothing to support this statement. There was no statement even of which claims may be unfounded. Pardon me for being didactic, but Dear Bellicose Author, Your statement about the unfounded claims is unfounded. I think it is likely true, but I gosh darn would like to see a bit more meat on that drumstick. 

I have often said that a good bellicose web post is worth an egregious rebuttal. Sure enough, I found one.

Fact: Findings were made by a national scientific agency (i.e. Department of Science and Technology/Food Nutrition and Research Institute) using internationally recognized protocols instituted by the University of Sydney (for GI testing). 

What are the author's qualifications to dispute the findings of a national scientific agency such as the Philippine Food and Nutrition Research Institute (PNFRI)? Is the author an academic or a scientist who is in a position to scientifically contest the validity of Glycemic Index (GI) effect studies by the University of Sydney that is accepted worldwide as a reliable, physiological-based food classification system? How much weight does writer's opinion carry against the expert opinion of Food and Agricultral Organization (FAO) of the United Nations (UN) committee endorsement of the GI method made as early as 1997? 

I don't know about you, dear reader, but I find this amusing. This argument is of the form of "Einstein said that your hair is purple. What qualifications to you have to refute him?" This egregious rebuttalist would have a much easier time convincing me if he or she would actually point me to a research paper or some otherwise non-financially involved source of information. Maybe just a link to a web page on the PNFRI website that says "Coconut palm sugar has a low glycemic index"?

The bellicose versus the egregious

Without that, both of these statements are worthless in ascertaining the science.

Pay dirt

I did a lot of digging and finally found a copy of an article from PNFRI: "Glycemic index of coco sugar", by Trinidad P. Trinidad, PhD. This technical paper is one page long. It describes an experiment with ten individuals to determine the GI of "coco sugar". I am guessing that this is the same thing as coconut palm sugar, since the Big Tree Farms website copied from this paper almost verbatim. 

One page. It all sounds reasonable, but it is one page long. The details of the results are not given. No fancy graphs with Brush Script font. Nor is there any indication as to when the study was performed, or where the study was published. I went back to the PNFRI website and searched for the author's name. There were a number of listings but nothing on this particular paper. I searched further to find a reference to this paper. Here is a resume of publications by Dr. Trinidad. The paper in question is not listed. It looks like she has done some good work, but there is no indication that the "GI of Coco Sugar" paper has ever been officially published.

By the way, Google found the paper from Dr. Trinidad for me. The paper is on the Philippine Coconut Authority website. This is a Philippine government agency "that is tasked to develop the [coconut] industry to its full potential". They may well have contracted some good scientific research, but they are clearly not financially disinterested in the results. Oh... I searched the PCA website and could not find a link to the paper by Dr. Trinidad.  

I honestly don't know what to make of this, but I have found absolutely no evidence of peer-reviewed science that backs up the claim that the GI of coconut palm sugar is 35, or even that it is low. What evidence there has not been made readily available.

I did find one interesting fact though. Fructose (which is a major ingredient in high fructose corn syrup) has an average glycemic index of 19. As everyone knows, the rampant use of high fructose corn syrup is the reason why otherwise intelligent people voted for Mitt Romney in the last election [3].  So, maybe finding a sweetener with a low glycemic index is not such a panacea?

Afternote

I would be remiss if I were to skip another piece of evidence that I turned up. Dr. Oz endorses coconut palm sugar. Clearly his endorsement trumps the complete lack of any peer reviewed research on coconut palm sugar. After all, Dr. Oz has informed the public of the miraculous weight loss potential of raspberry ketones, proved the age reversing effects of acai berries by putting lemon juice on apples, and has put all medical doctors out of business by explaining that you can heal yourself with a "medical intuitive".

-----------------------------------------

[1] This dog is a dead ringer for my dog, Scrabble. Honest.

[2] If we get lactose from milk, and fructose from fruit, what type of sugar do we get from french fries? Why, potatose, of course!

[3] I need to clarify a few things here...

First, high fructose corn syrup is not the same as fructose. HFCS is a combination of water, fructose (with a GI of 19) and glucose (with a GI of 100). The GI of the two sugars balance out, so that Coca-Cola, which uses high fructose corn syrup as a sweetener, has a GI of around 58.

Second, HFCS got a bad rap not too long ago with allegations that the body metabolized fructose much differently than other sugars. This has come into question lately. It seems that the jury may still be out as to whether HFCS is worse than other sweeteners, but one thing is clear. Sugar is not a health food.

Third, I understand that papers investigating HFCIRVD (high fructose corn syrup induced Romney voting disorder) are still in peer review, pending publication in either the New England Journal of Medicine, or Mad Magazine, I forget which. 

Followup to the spectrophotometric romance

This is a followup to my blog "A spectrophotometric romance". Be forewarned, this post is rated PG, for Print Geek. And it will be only just a little bit silly.

This post is necessary in order to consolidate comments, questions, and answers that have appeared in many different places. To date (Monday, Feb 18) the post has been viewed 753 times. Since there are only 587 certifiable print geeks in the world, this blog post is the Justin Beiber YouTube video of the print geek crowd.

There have been 76 comments in four LinkedIn discussion groups and on the blog. I have had email and phone conversations about the post with nine people, none of whom are in my immediate family. The interested folks include manufacturers of spectrophotometers and reference materials, printers, physicists, color scientists, people in standards groups, and designers.

Netflix called me the other day to complain that my email traffic was starting to bog down streaming video speed in Los Angeles, the greater New York metropolitan area, and one neighborhood in Scranton, PA. So please forgive me if I left out one of your astute comments. 

Can I read a full copy of the TAGA paper?

Sure. Here is a link to the full paper: Evaluation of Reference Materials for Calibration ofSpectrophotometers. The paper was presented at the 2013 TAGA conference in Portland, OR.

Now for the obligatory plug. TAGA is great. I try not to miss the TAGA conference. It is one of the only conferences where you can learn about new technologies in all parts of the printing industry. You will hear from academics and professionals alike, without the sales hype of most conferences. The next TAGA conference will be held in Fort Worth in March 2014. I hope to see you there. If you do, then buy me a beer.

Do you want a second opinion about TAGA?  Here is what Sandy Hubbard had to say about this year’s TAGA conference: TAGA, You’re It!

What is going on in the industry to try to fix the problem of inter-instrument agreement?

Idealliance (in the US) and Fogra (in Europe) have assembled groups of experts from all the graphic arts spectrophotometer manufacturers to work on the issue. I was cautiously optimistic at the start, and am cautiously a bit more optimistic after attending the first meeting. I attended the US meeting. I was impressed that everyone in the room was sincere in their desire to find agreement on how to find agreement. I didn’t hear any finger-pointing or blustering about why one company provided the one true measurement system and everyone else is wrong.

Of course, we spent the first six hours complaining about how spectrophotometer owners use their delicate instruments to hammer in nails and drop ketchup and fired onions into the optics. But we got past that soon enough, and started complaining about cops who give out speeding tickets and about politicians.

The ISO standards group that covers color measurement for the graphics arts (TC130) has also made some recent changes that will eventually improve inter-instrument agreement. See the heading “What is being courageously changed?” below.

Why do the instruments disagree?

Speaking of finger-pointing, why can’t the various spectrophotometer designers just build their instruments the correct way? Then they all would agree, right?

That all makes sense, but the difficulty is that there are many different ways to build a spectrophotometer “correctly”. The different correct ways may not give the same results. You may think that I am just copping out, since I represent an instrument manufacturer, but listen up. I have a parable for you.

Tevye (from Fiddler on the Roof) is in the marketplace talking politics. One person speaks of the great new world that the tsar is bringing. Tevye looks at this man and says, “You’re right”. The second man disagrees, and says that the tsar is bringing ruin to the country. Tevye looks at this man and says, “You’re right”. The third man is beside himself. “Tevye, how can they both be right!?” Tevye ponders a moment, and then says, “You’re also right!” If two instruments disagree, it is totally possible for both of them to be right.

Here is the short list of things that can go cause disagreement.

Fluorescence – Recently, optical brighteners have become ubiquitous. They are added to paper to make the paper appear brighter. The trouble is, the amount of whitening that happens depends on the amount of UV content in the light in the spectro. If two spectros emit different amounts of UV, they will excite the optical brighteners by different amounts, and the spectros will disagree.

I think we should point the finger at the darn paper companies who put the optical brighteners in the paper. Or maybe at the designers who like the paper that is whiter.

White level – Believe it or not, the various standards labs can’t quite agree on what “white” is. If you send a white tile to be measured by several of them, you may see a 1 ΔE of difference in L*. This is a clear case of “you’re right”. I think we should point the finger at the standards labs.

Lateral diffusion – A spectro illuminates a small area of the sample, and collects the light reflected by another small area. One would think that these should be the same size, this would cause a problem. If the sample has some translucence (it’s cloudy), then light will scatter outside the aperture. The smaller the aperture, the bigger the relative effect. Now get this… a few of the BCRA II tiles have bunches of lateral diffusion.

I think we should point the finger at the print buyers who force us to measure colorbar patches that are 1.5 mm tall. Or the paper companies. You would think they could make each sheet on a paper roll just a millimeter or two longer to make room for decent sized color patches.

By the way, someone wrote a paper about lateral diffusion a long time ago. The guy’s probably in a nursing home in Milwaukee singing Those Were the Days.

Linearity – One would expect that a decent engineer would be able to design a spectro that is linear. Of course, there is a little problem that detectors are nonlinear when they come close to saturation. By the way, that’s where the detector has its best noise immunity.

And there is the little problem that transistors and all that stuff like to be nonlinear down where the signal levels are smallest. Oh, and the issue that it is hard to devise a set of samples to calibrate nonlinearity with. One is left with assembling a series of gray samples with different reflectance values, and having a national standards lab measure them.

Did I mention that the national standards labs are ghastly expensive when you ask them to measure something?  I think I’ll open my own national standards lab. Or just blame the stupid laws of physics.

Black level – Theoretically two spectrophotometers could disagree on the reflectance of a perfectly black object. I think they probably do disagree just a tiny bit, but I don’t have enough data to verify this.

Wavelength shift – Just like two spectros might not agree on what 50% reflectance is, they might disagree on where 500 nm is. Thankfully, we have physical standards, such as mercury-argon lamps, that we can use that will emit at certain precise wavelengths. But… it would be nice if there were a few more emissions lines. Stupid laws of physics, anyway.

Spectral bandpass – Don’t even get me started on this one!

Goniophotometry – This one is a favorite of mine, simply because of all the cool words. Besides “goniophotometry”, there is “indicatrix”, and the acronym “BDRF”.

The basic idea is that the amount of light reflected from a surface depends on the angle that the light hits and upon the angle that it is viewed. In practical terms, a 0/45 spectrophotometer that collects all the light emitted between 40 and 50 degrees might not agree with one that collects all the light emitted between 43 and 47 degrees.

When you see me at TAGA 2014, buy me a beer and we can talk about the birds and the goniophotometers.

By the way, someone once wrote a TAGA paper about the goniophotometry of printing ink. The writing in the paper shows many of the early warning signs for dementia.

So many possible issues! In the words of Rabbi Seymour Goldstein, “Oy vey, mein kapella! This is so meshuga, it gives me such tsuris!”

Also in the words of Rabbi Seymour,

“Grant me the courage to change those things that I can change,

The serenity to accept those that cannot be changed,

The wisdom to know the difference,

And a little duct tape and shoe polish to fill in the gaps.”

What is being courageously changed?

There are a number of things that have changed or are changing to try to improve inter-instrument agreement.

One concrete decision that came out of the Idealliance meeting (in the US) was that we all agreed to trace our “white” back to the same national standards lab. We decided to go with the US-based standards lab NIST. I don’t know if this was discussed at the European meeting, but hopefully we can all decide on a single national lab.

The ISO standards group that works in the graphic arts color measurement arena (TC 130) has recently made some important changes that have already, or will, improve inter-instrument agreement.

Most notable is the “M0 / M1 change”, which addresses the optical brightener issue. Spectrophotometers with the M1 designation will agree in UV content so that optically brightened papers will be measured the same. For more information, have a look at some other wonderfully written articles: “The problem with optical brighteners”, and “New lighting conditions”.

Another change (one that is interesting only to the print uber-geeks) was made to ISO 13655, having to do with wavelength bandwidth. Interested in more information? Buy me a couple of beers and we’ll talk. Buy me a few more beers after that, and we can go sing Don’t Stop Believin’ at a karaoke bar.

These changes to the standards are essential, but they take a while to filter down. The really odd thing is that a change to the standards rarely changes existing equipment, you know? For some reason, I need to send my old spectro in to get it updated, or maybe buy a new one, for gosh sakes.

What serenity is required?

Now it is the print buyer’s turn to get the pointy finger.

There is a rule of thumb in the statistical processing world. The accuracy of an instrument is only allowed to take up 30% of a tolerance window. Thus, if the tolerance window for a certain printed color is 2.0 ΔE, then my instrument must be accurate to within 0.6 ΔE. If you go beyond that, it just makes things worse.

The reality is unfortunately that two instruments of different make and model will likely not agree to within 0.6 ΔE. Setting tolerances closer than that will inevitably just make people want to drink more beer.

Anyone have a spare cup of wisdom?

Wisdom… I wish I was smart enough to know what to say about this.

Hopefully my TAGA paper has contributed to the collective wisdom. My message was to know when a courageous attempt to make two instruments agree should have been tempered with a bit of serenity.

Duct tape and shoe polish

Another discussion item in the US inter-instrument agreement consortium was the development of a test strip with a selection of colored patches that could be measured by different instruments. After measurement, something could be done with the readings.

We discussed several options about what could be done:

1) The measurements taken with a single instrument could be compared over time to verify that the instrument has not changed,

2) One instrument could be compared with another to see if they measure substantially the same,

3) An instrument could be compared with measurements from a national standards lab (or perhaps a secondary lab) to assess the accuracy of the spectrophotometer, or

4) The set of samples could be used to standardize one instrument to another -- that is to provide a way of converting one instrument so as to match another.

The four potential goals are successively more complicated and expensive. In particular, obtaining measurements from a national standards lab would cost thousands of dollars, so it is not cost effective for most users. The fourth option may require a color scientist/math guy, so might only be an option for the spectrophotometer companies that can afford to hire color scientist/math guys.

Colligation

I am not done playing with duct tape. I am in the process of cogitating on colligation. The ancient Greek, Ptolemy developed a set of equations that could be used to predict the positions of the planets at any time. The equations were based on a lot of wrong assumptions like the Earth is in the center, and all the rest of the celestial bodies move in circles that revolved around circles. The model worked, at least to an extent.

A millennium or so later, Copernicus decided that the Sun belonged at the center. (I hope everyone celebrated his birthday yesterday?) Then Kepler came along and decided that ellipses made the whole thing simpler, and then Newton provided the big colligation. The inverse square law of gravity was the grand unifying theory that explained the whole enchilada.

My goal is to colligate. I have gone through the Ptolemaic thing in my TAGA paper, and shown that things go subtly awry when you have the wrong starting assumptions. I have done the Keplerian thing and did regression with (what might be) the right assumptions. It’s time to roll up the sleeves and do the Newtonian thing.

I plan to collect a bunch of spectros, enough to represent the range of physical differences that we see out in the field. I plan to collect a bunch of sample sets. I have the ones that I used for the TAGA paper, but I will gather more. Some new samples are already on a plane, headed to my office.

Then I plan to systematically go through specifically designed sample sets to try to ascertain what differences exist between the real world instruments. For example, I will measure a set of white and gray samples with varying levels of gloss to see if there is a goniophotometric difference – a difference in gloss rejection. I will measure a series of white to gray samples to ascertain whether the typical instruments in the field differ in their view of linearity.

And so on.

I am not sure where the colligation will lead. It could be that it will show that courage will be required, and there will be another round of “gosh darn it, we need to tighten up specs on something or other”. Or it could be that more duct tape is in order, and a simple standardization, carefully applied, can make an appreciable improvement.

I am still cogitating on this inter-instrument colligation. I welcome any suggestions or offers of help. At least, up to the point where I spend 23 hours and 56 minutes a day responding to emails.