FinnFoodPics: Image database of food items for the study of eating behaviors in residents of Finland (Kanyamibwa et al. 2024).
Description: 72 food images (i.e., snacks) each in ten different portions (40, 80, 120, 160, 200, 240, 280, 320, 360 and 400 kcal), classified into three macronutrient categories with one group containing high amounts of calories predominantly from carbohydrates (Carbohydrate category), one with calories predominantly from fat (Fat category), and the third group with items containing a high percentage of calories from both carbohydrates and fat (Combo category) (Fromm et al., 2021). Aside from the 720 images, the database contains nutritional information of the food item per 100 g as well as the specific portion size of 120 kcal. In addition, visual image properties (Blechert et al., 2014) and subjective food ratings from a representative sample of residents of Finland are provided for the 120 kcal portion.
We also included the source of the items (for example, Lidl supermarket), brand names, commercial prices at the time of purchase, and NOVA classification based on Monteiro and colleagues (Monteiro et al., 2010, 2019).
Details:
- Food characteristics: energy density (kcal/g), protein (g/120 kcal), fat (g/120 kcal), carbohydrates (g/120 kcal), fibre (g/120 kcal), salt (g/120 kcal), sugars (g/120 kcal), saturated fat (g/120 kcal), price (€/120 kcal), NOVA classification.
- Food ratings: liking (% of scale), familiarity (% of scale), healthiness (% of scale), expected satiety (% of scale), frequency of consumption (days/month), estimated energy density (% of scale), estimated energy content (kcal).
- Visual properties: visual area of food (cm2), R/G/B values, brightness, within object contrast, complexity (edge detection), spatial frequency.
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