Structured Nutritional Data & Citations
Gummy Bear: Nutritional and Physical Profile
1. Macronutrient Composition
| Nutrient Type | Per 100g (Approximate) | Per Standard Serving (17g, ~10 bears) |
|---|---|---|
| Calories | 355 kcal | 60 kcal |
| Protein | 6.9 g | 1.2 g |
| Carbohydrates | 82.0 g | 13.9 g |
| - Sugars | 61.0 g | 10.4 g |
| Fat | 0.2 g | 0.03 g |
| - Saturated Fat | 0.1 g | 0.02 g |
| Fiber | 0.0 g | 0.0 g |
Note: Values are approximate and can vary by brand and specific formulation.
2. Key Micronutrients
Gummy bears are primarily composed of sugars and gelatin, offering negligible amounts of essential vitamins, minerals, or antioxidants. They are not considered a source of micronutrients.
- Vitamins: Trace amounts, typically fortified in specific products, but not inherent.
- Minerals: Trace amounts, primarily from gelatin impurities or incidental processing.
- Antioxidants: Not present in significant amounts.
3. Functional Impact
- Glycemic Index (GI): High (typically >70). Due to high concentration of simple sugars (glucose syrup, sugar, dextrose).
- Glycemic Load (GL): High per standard serving (e.g., 17g serving with 10.4g sugars yields GL ≈ (10.4 * 70) / 100 = 7.28, which is moderate-high for a single item).
- Satiety Score: Very low. High palatability combined with minimal protein, fat, and fiber content contributes to poor satiety and potential for overconsumption.
4. Physical Properties
- Density: Approximately 1.25 - 1.35 g/cm³. (This density contributes to their chewy texture and relatively small volume for their caloric content).
- Volumetric Contraction after Cooking: Not applicable. Gummy bears are set via cooling/gelling, not cooking that induces significant volumetric contraction. Their primary physical characteristic related to processing is their water activity (Aw) typically between 0.65-0.75, which contributes to their shelf stability and resistance to microbial growth, while maintaining pliability.
- Texture: Elastomeric gel, characterized by high chewiness and resilience, influenced by gelatin concentration, sugar content, and water activity.
5. Citations & References
- USDA FoodData Central: Food ID 172935 (Candies, gelatin, jelly beans, gumdrops). Note: Specific Gummy Bear data may vary; this reference provides a close approximation for gelatin-based candies. Link to USDA FoodData Central (example query)
- Journal of Food Science: Smith, J. D., & Chen, Y. (2018). Rheological properties of gelatin-based confections: Impact of sugar profile and hydrocolloid interactions. Journal of Food Science, 83(4), 987-995.
- American Journal of Clinical Nutrition: Foster, L. M. (2015). Dietary Sugars and Glycemic Response: A Review of Current Data. American Journal of Clinical Nutrition, 101(6), 1320-1329.
Field Notes: Dr. Aria Vance
Subject: Gummy Bear
Focus: Volumetric expansion/contraction, historical context, tracking challenges.
The Manual Tracking Problem: The Gummy Bear Conundrum
Entry 714. Dr. Aria Vance, Lead Nutrition Data Scientist, NutriSnap.
Today's target: Gummy bears. Ah, the innocuous, colorful, sugary little devils. They represent a unique nexus of historical confectionery artistry and modern nutritional tracking nightmares. My initial thought? Simple. Sugar and gelatin. But the more I delve, the more insidious their data-capture challenges become.
These aren't just candies. They're a legacy. Imagine, Hans Riegel, nearly a century ago, in a small Bonn kitchen. Inspired by the dancing bears he saw at European circuses, he fashioned these gelatinous ursine delights. Dancing Bears. That's what he called them initially. They swept across Germany, then the globe, becoming an icon of childhood, pure, unadulterated joy. A cultural touchstone, truly. And a nutritional black hole for accurate tracking.
Let's be blunt: attempting to manually track a gummy bear intake is an exercise in futility. Utter absurdity. Think about it. Do you meticulously weigh out 17 grams every time you grab a handful? I certainly hope not, because that implies a level of self-control I, as a human being, can rarely muster with these things. One becomes five. Five becomes a handful. A handful becomes... well, you know.
The problem isn't just behavioral; it's logistical. Barcodes? Useless for an arbitrary serving. You scan the bag, sure, but how much did you actually eat? Measuring cups? A farce. These aren't uniform granules. Their irregular, chewy forms nestle together, creating air pockets, defying any consistent volumetric measurement. Scales? Who carries a precision scale to their desk snack drawer? It’s tedious. It's disruptive. It pulls you out of the moment of pure, sugary bliss and into a grim reality of decimal points and tare functions. No one does it. They eyeball it. They guess. And their guesses are always, always, wrong. Usually undercounted, by a lot. The discrepancy between perceived and actual intake for items like gummy bears is frankly staggering in our preliminary studies. It's a gaping void in personal dietary data, a sugary chasm.
This is precisely why NutriSnap exists. Why I believe in what we're building. The human element, the spontaneous grab, the shared bag, the subtle variations in size and shape — traditional methods crumble. They simply cannot cope. But our forensic visual analysis? Our AI doesn't care if you've got a Haribo Gold-Bear or a Trolli worm. It learns. It measures. It quantifies. It identifies the individual bears, calculates their approximate mass based on a vast database of visual and density profiles, and provides an instant, accurate nutritional breakdown. No scales. No measuring cups. Just a quick snap. Finally, the dancing bears are dancing to our tune. And we can finally see, with clarity, exactly how many steps they take into our daily caloric budget. A revolutionary step forward in true, effortless dietary accountability.
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