Pepper Pungency on the Scoville Scale

Plot the ranking of peppers by their Scoville heat rating and create a peppers image collage

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). Wolfram Language includes "ScovilleRating" data for dozens of pepper varieties, from the mild pimento pepper to the scorching scorpion and ghost peppers.

First, get all of the spicy pepper entities, and display the last 10 peppers in the list:

In[1]:=

peppers=EntityList[EntityClass["Food",{"FoodTypeGroup""Peppers","Variety""Spicy"}]];peppers〚-10;;〛

Out[1]=



Tabiche Pepper

(Wolfram Knowledgebase)

Thai Pepper

(Wolfram Knowledgebase)

Tien Tsin Pepper

(Wolfram Knowledgebase)

Trinidad 7 Pot CARDI Strain

(Wolfram Knowledgebase)

Trinidad 7 Pot Jonah

(Wolfram Knowledgebase)

Trinidad 7 Pot Primo

(Wolfram Knowledgebase)

Trinidad Moruga Scorpion

(Wolfram Knowledgebase)

Trinidad Scorpion (Butch T strain)

(Wolfram Knowledgebase)

Trinidad Yellow 7 Pot

(Wolfram Knowledgebase)

Trinidad Yellow Scorpion

(Wolfram Knowledgebase)



Retrieve the associated SHUs for each pepper entity, and display the first 20 peppers in the list:

In[2]:=

peppersScovilleRatingAssoc=DeleteMissing[AssociationMap[EntityValue[#,"ScovilleRating"]&,peppers]];peppersScovilleRatingAssoc〚;;20〛

Out[2]=



7-Pot Douglah

(Wolfram Knowledgebase)

Interval[{923589.,1.85394×

}],

Aji Pepper

(Wolfram Knowledgebase)

Interval[{30000.,50000.}],

Aleppo Pepper

(Wolfram Knowledgebase)

Interval[{10000.,10000.}],

Anaheim Pepper

(Wolfram Knowledgebase)

Interval[{500.,2500.}],

Ancho Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2000.}],

Bahamian Pepper

(Wolfram Knowledgebase)

Interval[{95000.,110000.}],

Bhut Jolokia Pepper / Ghost Chile Pepper

(Wolfram Knowledgebase)

Interval[{855000.,1.04143×

}],

Birds Eye Pepper

(Wolfram Knowledgebase)

Interval[{100000.,225000.}],

Carolina Cayenne Pepper

Interval[{100000.,125000.}],

Cascabel Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2500.}],

Cayenne Pepper

Interval[{30000.,50000.}],

Charleston Hot Pepper

(Wolfram Knowledgebase)

Interval[{70000.,100000.}],

Cherry Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2500.}],

Chiltepin pepper

(Wolfram Knowledgebase)

Interval[{50000.,100000.}],

China Express Pepper

(Wolfram Knowledgebase)

Interval[{60000.,100000.}],

Chipotle Pepper

Interval[{5000.,10000.}],

Chungyang Red Pepper

(Wolfram Knowledgebase)

Interval[{10000.,23000.}],

Congo Pepper - Black

(Wolfram Knowledgebase)

Interval[{300000.,500000.}],

Congo Pepper - Red

(Wolfram Knowledgebase)

Interval[{300000.,400000.}],

Congo Pepper - Yellow

(Wolfram Knowledgebase)

Interval[{300000.,300000.}]

ListPlot is a good way to visualize the full range of SHUs. Use the Sort function to arrange the peppers from mild to hot in a scatter plot:

In[3]:=

ListPlot[Sort[peppersScovilleRatingAssoc],ImageSize600,AxesLabel"SHUs",PlotRangeAll]

Out[3]=

Just as peppers vary in pungency, they are delightfully different in shapes and shades. Use WebImageSearch and ImageCollage to create a colorful snapshot.

Mild to moderately hot peppers are popular in cooking. Create a subset of these popular peppers by taking the 10th to 25th peppers from the sorted list of all peppers:

In[4]:=

pepperSubset=Take[Sort[peppersScovilleRatingAssoc],{10,25}]

Out[4]=



Espanola Pepper

(Wolfram Knowledgebase)

Interval[{1000.,1500.}],

Poblano Pepper

(Wolfram Knowledgebase)

Interval[{1000.,1500.}],

Ancho Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2000.}],

Pasilla Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2000.}],

Cascabel Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2500.}],

Cherry Pepper

(Wolfram Knowledgebase)

Interval[{1000.,2500.}],

Peppadew Pepper

(Wolfram Knowledgebase)

Interval[{1177.,1177.}],

Mirasol Pepper

(Wolfram Knowledgebase)

Interval[{1500.,2500.}],

Rocotillo Pepper

(Wolfram Knowledgebase)

Interval[{1500.,2500.}],

Sandia Pepper

(Wolfram Knowledgebase)

Interval[{1500.,2500.}],

Guajillo Pepper

(Wolfram Knowledgebase)

Interval[{2500.,5000.}],

Jalapeño Pepper

Interval[{2500.,8000.}],

Fresno Pepper

(Wolfram Knowledgebase)

Interval[{2500.,10000.}],

Chipotle Pepper

Interval[{5000.,10000.}],

Hungarian Wax Pepper

(Wolfram Knowledgebase)

Interval[{5000.,10000.}],

Aleppo Pepper

(Wolfram Knowledgebase)

Interval[{10000.,10000.}]

Map the names to the pepper entities:

In[5]:=

pepperSubsetNames=KeyMap[EntityValue[#,"Name"]&,pepperSubset]

Out[5]=

Espanola PepperInterval[{1000.,1500.}],Poblano PepperInterval[{1000.,1500.}],Ancho PepperInterval[{1000.,2000.}],Pasilla PepperInterval[{1000.,2000.}],Cascabel PepperInterval[{1000.,2500.}],Cherry PepperInterval[{1000.,2500.}],Peppadew PepperInterval[{1177.,1177.}],Mirasol PepperInterval[{1500.,2500.}],Rocotillo PepperInterval[{1500.,2500.}],Sandia PepperInterval[{1500.,2500.}],Guajillo PepperInterval[{2500.,5000.}],Jalapeño PepperInterval[{2500.,8000.}],Fresno PepperInterval[{2500.,10000.}],Chipotle PepperInterval[{5000.,10000.}],Hungarian Wax PepperInterval[{5000.,10000.}],Aleppo PepperInterval[{10000.,10000.}]

Search the web for one image of each of the pepper names in the subset, and compute the mean Scoville rating for each pepper in the list:

In[6]:=