Allergen Status Of Food Products

The Allergen Status of Food Products dataset is a collection of information detailing the allergen status of various food products. It serves as a comprehensive resource for researchers, food manufacturers, healthcare professionals, and individuals with food allergies.

Size: This dataset comprises 400 records, each representing a specific food product and its associated allergen information.

Allergens: The dataset covers a wide range of allergens commonly found in food items, including dairy, wheat, nuts (almonds, peanuts, pine nuts), seafood (anchovies, fish, shellfish), grains (oats, rice), animal-based ingredients (chicken, pork), plant-based ingredients (celery, mustard, soybeans), and common ingredients (cocoa, eggs). Some entries in the dataset also indicate the absence of specific allergens.

Data Structure: The dataset is structured with nine informative columns:

• Food Product: The name of the food product.
• Main Ingredient: The primary ingredient used in the food product.
• Sweetener: Any sweetening agent present in the product.
• Fat/Oil: The type of fat or oil used in the food product.
• Seasoning: Seasonings or spices used to flavor the dish.
• Allergens: A list of allergens associated with the food item, specifying allergenic ingredients present.
• Price ($): The price of the food product.
• Customer Rating (Out of 5): Customer ratings on a scale of 5, reflecting their satisfaction.
• Prediction: A classification indicating whether the food product contains allergens or not.

Potential Applications:

Allergen Detection Model: This dataset can be utilized to develop a model that predicts whether a food product contains allergens, aiding individuals with allergies.

Ingredient Similarity Analysis: Analyzing ingredient profiles can reveal similarities and differences among different types of dishes, aiding in menu planning and recipe development.

Allergen Prevalence Analysis: Researchers can gain insights into the prevalence of different allergens in food products, which can inform labeling and safety measures.

Recommender Systems: The dataset can be harnessed to create recommender systems for individuals with dietary restrictions or allergies, suggesting safe food choices.

This dataset empowers various stakeholders in making informed decisions about food consumption, allergen avoidance, and dietary preferences.