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Coffee Bean Sensory Analysis Data
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About
Detailed quality metrics and sensory evaluation information for coffee beans from around the world are provided in this data. Sourced from the Coffee Quality Institute (CQI) database, it covers a range of factors influencing coffee quality, from production and processing details to genetics and soil types. The data is a valuable resource for coffee professionals, enthusiasts, and researchers interested in understanding the elements that contribute to a high-quality coffee experience.
Columns
- REC_ID: A unique identifier for each record in the database.
- Species: The botanical species of the coffee, primarily Arabica or Robusta.
- Continent.of.Origin: The continent where the coffee lot was grown.
- Country.of.Origin: The specific country where the coffee lot originated.
- Harvest.Year: The year the coffee was harvested.
- Expiration: The assigned expiration date for the coffee lot record.
- Variety: The specific cultivar or type of coffee plant, such as Caturra or Bourbon.
- Color: The observed colour of the raw coffee bean, typically blue, green, or mixed.
- Processing.Method: The method used to process the beans after harvesting, like Washed / Wet or Natural / Dry.
- Aroma: A score representing the scent or fragrance of the coffee.
- Flavor: A score evaluated on the coffee's taste, including notes of sweetness, bitterness, and acidity.
- Aftertaste: A score for the lingering taste that remains after swallowing the coffee.
- Acidity: A score representing the brightness or liveliness of the taste.
- Body: A score for the perceived thickness or viscosity of the coffee.
- Balance: A score for how well the different flavour components work together.
- Uniformity: A score for the consistency of the coffee from cup to cup.
- Clean.Cup: A score indicating a coffee is free of off-flavours or defects.
- Sweetness: A score representing the sweetness perceived in the taste.
- Moisture: The moisture content of the coffee beans, measured as a percentage.
- Quakers: The number of unripe or defective beans that failed to roast properly.
- Category.One.Defects: The total count of primary defects, like black or sour beans.
- Category.Two.Defects: The total count of secondary, more severe defects, such as mouldy or insect-damaged beans.
- Rec_Cnt: The total record count for each location bin (only present in grouped datasets).
Distribution
The data is distributed in three CSV files: a main coffee quality dataset, and two others grouped by continent and country respectively. The main file (
Coffee_Qlty.csv) has a size of 170.59 kB and contains 1339 records across 22 columns.Usage
- Analysing the relationship between processing methods and sensory scores.
- Identifying trends in coffee quality based on geographic origin (country or continent).
- Building predictive models for coffee quality based on bean characteristics and defect counts.
- Exploring the impact of harvest year and variety on flavour profiles.
Coverage
The data covers a global geographic scope, with records originating from 34 unique countries across 5 continents. North America is the most represented continent. The time range for the harvest year spans from 2009 to 2018. Some records have missing values for fields such as
Variety, Color, and Processing.Method.License
CC BY-SA 4.0
Who Can Use It
- Data Scientists and Analysts: Can use this data to build predictive models for coffee quality or uncover insights into regional taste profiles.
- Coffee Industry Professionals: Roasters, buyers, and quality control specialists can analyse trends in coffee attributes and defects.
- Researchers in Agriculture and Food Science: Can study the factors that influence coffee quality, from origin to processing.
- Coffee Enthusiasts: Can explore the characteristics of high-quality coffee from different parts of the world.
Dataset Name Suggestions
- Global Coffee Quality Metrics
- Coffee Bean Sensory Analysis Data
- CQI Coffee Quality and Origin Database
- International Coffee Bean Characteristics
- Specialty Coffee Quality Scores
Attributes
Original Data Source: Coffee Bean Sensory Analysis Data
QUALITY