France: Exploring Historical Cookbooks

Introduction

This project is an exploration of historical French cookbooks containing recipes from the 19th century. Through analyzing these cookbooks, we explore the most frequently used ingredients and food categories by region. We also examine the cooccurrence of ingredients and food categories.

Research questions

1. What were the main ingredients used in 1900 in France?

2. Can we observe a difference per region?

Project Plan and Milestones

Date	Tasks	Completion
Week 3	Find multiple cookbooks in French or English from different times. Prepare project proposals. Milestone 1: Project proposals	✓
Week 4	Compare different cookbooks, consider the OCR scan and think of possible research questions. Discuss the goal and implementation of the project.	✓
Week 5	Decide on one French cookbook. Scan the physical book page by page. Sanitize the initial dataset.	✓
Week 6-7	Separate .png files by subregions. Perform the OCR of each page. Start to construct the dataset.	✓
Week 8-9	Construct dataset and think of data structures to store in an optimal way the information. Milestone 2: Midterm presentation	✓
Week 10	Set up the GitHub repository. Finish the creation of the dataset.	✓
Week 11	Go through the dataset and perform some changes to facilitate the data processing. Create categories for ingredients.	✓
Week 12	Perform the data processing of the ingredients. Exploratory analysis of the dataset.	✓
Week 13	Further improve the dataset. Overall analysis & Per region analysis.	✓
Week 14	Prepare the final presentation Finish the Wikipedia page Milestone 3: Final presentation	✓

Methodology

Data digitalization

For a start, we scanned a physical French cookbook. This one is from the 19th century and has ingredients listed on the margin of the page.

• 

  French cookbook

• 

  A page of the scanned book

• 

  Example OCR result

Then we did a basic OCR for the scanned files. Here is a sample output from OCR. It is noticeable that there is a mismatch between recipes and ingredients.

Data processing

In our project, we will extract and construct the following information from the recipes:

• quantity: the amount of the ingredient
• unit: the metric of the ingredient
• ingredient: the entity appeared in the recipes
• category: the major category the ingredient belongs to

Units

Type	Unit
Spoons	cuil. à café, cuil. café, cuil. à soupe, cuil. soupe, petite cuil., grande cuil., cuil.
Glasses	petit verre, verre à liqueur, verres à liqueur, verres, verre, tasses, tasse
Bottles	bout., bouteilles, bouteille
Containers	g rande boîte, boîtes, boîte, tubes, tube
Spices & Aromatic plants	gousses, gousse, branches, branche, bâtons, bâton, pincée
Meat related	membres, membre, tronçons, tronçon, tranches, tranche
Standard measures	litres , litre , cl , dl , kg , g, l

Categories

We map different ingredients to several major categories

Category	Ingredient
Viande	viande, oie, canard, oiseau, lard, bœuf, veau, poule, poulet, poularde, volaille, porc, caille, canard, caneton, mouton, cochon, coq, chevreuil, lièvre, levraut, lapin, faisan, gibier, jambon, chorizo, cervelas, agneau, escargot, grenouille
Poisson	poisson, brochet, carpe, morue, lamproie, lotte, maquereau, omble, rouget, sardine, thon, truite, anchois, anguille, merlan, sole, barbue, turbot, raie, perche, saumon, colin, goujon, loup, congre, rascasse, grondin, merlu, merluza, hareng, alose, brême
Fruit de mer	crevette, langouste, moule, écrevisse, palourde, homard, chiperon, seiche, huître, coquille, poulpe
Alcool	alcool, bière, vin, cidre, fine, liqueur
Plante aromatique	bouquet garni, ail, anis, aromate, angélique, basilic, persil, sarriette, cerfeuil, ciboule, ciboulette, clou de girofle, clous de girofle, girofle, cive, câpre, estragon, feuille de vigne, fines herbes, laurier, menthe, pissenlit, romarin, thym
Epice	cannelle, coriandre, curry, safran, poivre, sel, moutarde, muscade, paprika, piment, sauge, serpolet, épices
Produit laitier	lait, crème, fromage, gruyère, parmesan
Légume	artichaut, asperge, aubergine, bette, betterave, cardon, chou, cornichon, courgette, cresson, céleri, fenouil, légume, navet, panais, poireau, pomme de terre, pommes de terre, potiron, rave, salade, tomate, échalote, épinard
Fruit	abricot, banane, cerise, coing, fraise, framboise, groseille, raisin, olive, orange, pomme
Agrume	citron, cédrat, fleur d'oranger, fleurs d'oranger
Céréale	farine, pain, pâte, riz
Légumineuse	févette, haricot, pois
Fruit sec	amande, noix, noisette
Champignon	champignon, truffe, cèpe, girofle, morille, levure, oronge, duelle

Region

We map subregions to 6 major regions in 19th-century France.

Region	Subregion
Paris, Ile-de-France, Val de Loire	Paris, Ile-de-France, Orléans, Touraine
Pays de l’Ouest	Anjou, Bretagne, Poitou Vendée, Charentes
Sud-Ouest & Pyrénées	Bordelais, Gascogne, Pays Basque, Roussillon, Périgord, Languedoc'
Sud-Est & Méditérannée	Provence, Nice, Corse, Dauphiné, Savoie, Lyon, Auvergne, Limousin
Bourgogne, Champagne, Bresse, Franche-Comté, Alsace, Lorraine	Bourgogne, Champagne, Bresse, Franche-Comté, Alsace, Lorraine
Nord & Normandie	Nord, Normandie

Data analysis

We have a total of 352 different recipes from 30 regions, 6 subregions.

Top 10 most used ingredients.

Rank	Ingredient	Number of occurrences	Picture
1)	Beurre	180
2)	Sel	167
3)	Poivre	146
4)	Œufs	101
5)	Oignons	95
6)	Farine	89
7)	Persil	82
8)	Ail	76
9)	Vin balanc	69
10)	Bouquet garni	46

• Explaining the analysis process • Overall analysis (with a reference to top 10 most used ingredients) • Speaking about per region analysis (refering to the heatmap) • Speaking about per subregion analysis (refering about the heatmap) • Speaking about co-occurences of ingredient (separately)

Data visualization

Heatmap of categories by subregion.

Heatmap of categories by region.

Matrix of co-occurences by subregion.

Map of France.

Discussion and limitations

Like many other research, this project has its limitations. For example, in the data analysis part, it was a roughly count of categories and we did not take quantity into account.

Future work

• Build a search engine that would display the recipes and add filters to search them by name, region or ingredients

• User-friendly interface to visualize the results of the analysis

• Comparison with other cookbooks from different periods or different countries

Links

Github repository

Scanned book

OCR result