News, Views & Insights
Getting Hot and Spicy on the Scoville Scale with Wolfram Language
National Chili Day is February 23 and we’re celebrating the spicy heat that peppers bring to a great bowl of chili by exploring the "ScovilleRating" property in Wolfram Language.
The Scoville scale ranks the spiciness (or pungency) of peppers by measuring the amount of the molecule capsaicin in a pepper and assigning it a number rating in Scoville heat units (SHUs). Pharmacist and chemist Wilbur Scoville introduced the “Scoville organoleptic test,” which eventually became the Scoville scale, in 1912. At the time, Mr. Scoville relied on human taste testers willing to do this challenging job. Today, scientists use high-performance liquid chromatography (HPLC) to determine the precise amount of capsaicin in a pepper.
From Placid Pimento to Stinging Scorpion
Wolfram Language includes "ScovilleRating" data for dozens of pepper varieties, from the mild pimento pepper to the scorching scorpion and ghost peppers:
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Pepper Plots
ListPlot and FeatureSpacePlot are two great ways to visualize the full range of SHUs and which peppers are most closely aligned:
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Capsaicin: The Spicy Molecule
You know that burning sensation when you eat spicy foods? It’s due to capsaicin, an active component of chili peppers that irritates the mucous membranes in your mouth. On the Scoville scale, pure capsaicin is 16 million SHUs. That makes it 3000 times hotter than a jalapeño pepper:
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You can learn more about the chemical properties of capsaicin with Wolfram|Alpha.
Pepper Pictures
Just as peppers vary in pungency, they are delightfully different in shapes and shades. Use WebImageSearch and ImageCollage to create a colorful snapshot:
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Use TesselateGraphics to get creative with your own pepper pictures. We used AI to generate both our red chili pepper and the black-and-white mask image. Be sure to remove the background of your primary image and set your mask’s Image Mode to Binary to achieve the following effect:
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Engage with the code in this post by downloading the Wolfram Notebook
It is possible that in the near future, advancements may take us a step further. For instance, rather than just assessing sharpness from a photo, AI itself may innovatively combine ingredients to achieve specific and measurable results. For example, when we venture into cold areas, the food we consume could provide significantly more warmth. Or during physical exertion, it could provide a greater oxygen boost, such as a well-nitrated beetroot juice. Essentially, it gradually revolutionizes everything we know into new possibilities, although there may be social and structural challenges during the transition.