Saturday, August 29, 2009

Charting the chocolate chip cookie

In a previous post, I described my favorite chocolate chunk cookie, made using a recipe adapted from dessert genius Jacques Torres by David Leite in the New York Times.

One of my early theories about why the cookies were so good was that they simply had a lot more chocolate than the average cookie. That line of thinking reminded me of Meg's brilliant post about her "mean" chocolate chip cookie recipe, where "mean" had two meanings: slangy (excellent) and statistical (the average value of a collection of numbers).

To make her mean cookie, Meg took twelve distinct cookie recipes (but surprisingly not the classic Toll House recipe), entered them into a spreadsheet, calculated the average quantity for each ingredient, and then used her baking judgment to determine an average set of mixing procedures. The result:
These cookies were pretty damn good! I'd expected the worst. I'd expected they'd be inedible, or burnt, or floury and gooey at the same time. I had a hint they might not be too bad when I tasted the dough. But when I pulled them from the oven, I was amazed. The first bite revealed a cookie crispy around the rim, warm and chewy on the inside. A few hours later, they were firmer, but still tasty. The best chocolate chip cookies ever? I'm not sure, but I baked A Mean Chocolate Chip Cookie. And that's enough for me.
I took the spreadsheet (which Meg made available on her website as an Excel file) and did what comes naturally to me: make some charts. The first thing I did, however, was correct a small oversight that Meg made when she did not normalize the recipes to a fixed point, like the quantity of sugar or flour. Not normalizing means that the importance of an individual recipe in the final result depends on the size of the recipe: in other words, the weight of a recipe calling for 4 cups of flour and 3 eggs would have more influence on the final result than one with 1 1/3 cups of flour and 1 egg. Since these were all pure flour recipes (no oatmeal), I scaled the ingredients in each recipe so that they would have two cups of flour.Clearly, this is not an ideal normalization because not all cookies rely on the same amount of flour for their structure, but it seems like a reasonable approximation. Other normalizations, like the quantity of butter or amount of chocolate, could be used too, but as we'll see below, I'm not sure it really matters. 

In some provinces of Geekdonia, people have been know to chart first, ask questions later. As I have been thinking about this post, I've realized that I'm one of those people.  There were many questions that I should have asked and answered before making the charts, like "How much do I like each cookie?", "What style is each cookie (thin and crispy, thick and chewy, in-between)?"  And so, alas, the charts that I carefully prepared are more like pieces of art than explanatory figures.

The first chart shows the volume of chocolate chips in each recipe after the flour normalization.  The names of the recipes on the vertical axis are taken directly from Meg's Excel file (except for Toll House, which I added myself); I provide links to each one (when available) at the bottom of this post. We see quite a significant variation, from 1 cup all the way to almost 2.5 cups (1 cup = 8 fluid ounces = 236 mL). Torres/Leite's recipe is on the high end of the range, with the second most chocolate. Part of the variation, of course, is that different cookies have different styles — crispy, cakey, etc.
The next chart shows how butter and chocolate quantities relate for the collection of recipes.  The x-axis is butter (in sticks — 4 ounces, 1/2 cup, 113 grams), the y-axis is the volume of chocolate chips. The red symbol represents the Torres/Leite recipe, the green symbol represents Meg's mean recipe. If there was some universal ratio of butter to chocolate, the points would fall on a line, but they clearly do not. The 'butter outlier' to the left is "The Cookie Book" recipe; the two high chocolate recipes are Torres/Leite and David Lebovitz.



The final chart shows the relationship between chocolate chips and sugar (brown and white types). These points are even more scattered than the butter points, because 1) sugar probably plays less of a structural role than butter, and 2) recipe developers might be influenced by the 'sticking' of butter, i.e., picking one, 1 1/2 or two sticks for a recipe instead of 3.25 ounces or another unusual number. In this chart, the Torres/Leite recipe has the lowest amount of sugar. Combine that with a high quantity of dark chocolate and you get a seriously good cookie.


Although I'm sure that the food industry has people that make lots of charts exploring the make-up of chocolate chip cookies — attempting to understand how to improve flavor, reduce costs, and so on — for a hobbyist like me the charts turned out to be a somewhat futile exercise, resulting on only a reinforcing of the idea that cookie recipes can vary significantly and confirming my initial impression that the Torres/Leite cookies had more chocolate than average.

When a three-day rainstorm hits the Bay Area on a weekend this winter, perhaps I'll try taking this exercise to the next level: baking each cookie and comparing my preference with their ingredients — a chart comparing my ranking with the butter to sugar ratio, for example. Like this exercise, it might not tell me anything new, but the experimental samples will be a worthwhile result.

The list of recipes:




Random link from the archive:  You Are What You Eat Meme

Technorati tags: Chocolate : Baking : Food : Cookies

3 comments:

Elise said...

Now I know why your blog is named "mental" masala.

Cody said...

I love this! I'm a financial analyst and a food blogger - and this might already be my favorite post of the week!!!

Phoebe and Cara, The Quarter-Life Cooks said...

wow, such fine baking-induced analytics! I wish my mental capacity could handle more than measuring cups!