Structured Nutritional Data & Citations
EDAMAME: A NUTRITIONAL PROFILE AND BIO-PHYSICAL ANALYSIS
1. Nutritional Composition (per 100g cooked, boiled, drained, without salt)
- Energy: 122 kcal
- Macronutrients:
- Protein: 11.9 g
- Total Carbohydrates: 9.9 g
- Dietary Fiber: 5.2 g
- Sugars: 2.2 g
- Net Carbohydrates: 4.7 g
- Total Fat: 5.2 g
- Saturated Fat: 0.6 g
- Monounsaturated Fat: 1.0 g
- Polyunsaturated Fat: 2.2 g (Omega-3: 0.4 g, Omega-6: 1.8 g)
2. Standard Serving (80g cooked, shelled edamame)
- Energy: 98 kcal
- Macronutrients:
- Protein: 9.5 g
- Total Carbohydrates: 7.9 g
- Dietary Fiber: 4.2 g
- Sugars: 1.8 g
- Net Carbohydrates: 3.8 g
- Total Fat: 4.2 g
3. Key Micronutrients (per 100g cooked, relative to Daily Value - DV)
- Vitamins:
- Vitamin K (Phylloquinone): 26.5 µg (22% DV)
- Folate (B9): 311 µg (78% DV)
- Thiamin (B1): 0.2 mg (17% DV)
- Riboflavin (B2): 0.2 mg (15% DV)
- Vitamin C: 6.1 mg (7% DV)
- Minerals:
- Manganese: 0.6 mg (26% DV)
- Magnesium: 64 mg (15% DV)
- Iron: 2.3 mg (13% DV)
- Phosphorus: 188 mg (15% DV)
- Potassium: 436 mg (9% DV)
- Copper: 0.2 mg (22% DV)
- Antioxidants & Phytochemicals:
- Isoflavones (Genistein, Daidzein): Significant levels (soy-specific)
- Saponins
- Phytic Acid
4. Functional Impact
- Glycemic Index (GI): Low (typically ~20-30 for soybeans, including edamame).
- Glycemic Load (GL): Very Low (estimated <5 per standard serving).
- Satiety Score: High, attributed to robust protein and fiber content, promoting prolonged fullness and reduced subsequent energy intake.
5. Physical Properties
- Density (shelled, cooked): Approximately 0.85 g/cm³
- Volumetric Change (post-cooking): Individual shelled edamame beans exhibit a slight volumetric expansion (approx. 5-10%) due to water absorption during boiling/steaming, rather than contraction. The overall volume of a given mass of shelled edamame increases negligibly.
6. Citations & References
- USDA FoodData Central. (n.d.). Edamame, frozen, cooked, boiled, drained, without salt (FDC ID: 2550119). Retrieved from https://fdc.nal.usda.gov/fdc-app.html#/food-details/2550119/nutrients
- International Tables of Glycemic Index and Glycemic Load Values. (2021). American Journal of Clinical Nutrition, 114(5), 1625-1632. (General reference for soybean GI/GL data).
Field Notes: Dr. Aria Vance
Subject: Edamame
Focus: Volumetric expansion/contraction, historical context, tracking challenges.
The Manual Tracking Problem: The Edamame Enigma
Dr. Aria Vance, Lead Nutrition Data Scientist, NutriSnap Journal Entry, October 27th.
Edamame. Little green jewels. Verdant mysteries. They're everywhere now, a staple in health-conscious homes, a go-to snack from sushi bars to supermarkets. But the journey of these humble soybeans, Glycine max, is far older than our modern infatuation. Dating back millennia, primarily cultivated in East Asia, known as Mao Dou in China or simply "branch bean" in Japanese, they’ve been an integral, fresh component of diets for centuries. A cultural touchstone. A symbol of spring's bounty.
Yet, for all their nutritional prowess and storied past, edamame present a tracking nightmare. A true data scientist's headache. The great edamame conundrum. Seriously.
Consider the variability. You grab a bag. Is it in-pod? Shelled? Massive difference! A standard weight of edamame pods might be, oh, 150 grams. But once you get those plump, often gloriously irregular beans out, you're down to what, 60, maybe 70 grams of edible material? The pod, a veritable botanical ballast, skews any initial weighing. Most people, in their rush, weigh the whole damn thing, pods and all. Or they eyeball it. "A handful," they'll say. What's a handful, Susan? Is your hand the size of a catcher's mitt or a child's? It's chaos!
Then there's the preparation. Boiled, steamed, roasted crisp with a dash of sesame oil and sea salt—each method whispers its own caloric secrets, its own macro narrative. You think someone's meticulously removing the salt post-boil to get the "without salt" data? No chance. A sprinkling of coarse sea salt adds negligible mass but impacts perception. It's a nutritional ghost in the machine. A behavioral blind spot. This isn't just about calories; it’s about macro accuracy, fiber intake, all the critical elements for precise dietary analysis. We are attempting to build precision health profiles with data gathered by prayer and a wing. It's deeply frustrating.
This is precisely why NutriSnap isn't just a convenience; it's a scientific necessity. Our AI, our digital Sherlock Holmes, can look at a photo of edamame – in-pod, shelled, steamed, roasted – and through forensic visual analysis, distinguish not just volume, but estimate edible portions, account for preparation methods, and deliver accurate nutritional breakdowns. No more guessing. No more cumbersome shelling and re-weighing just to log a snack. Finally, precision tracking for these delightful, yet deceptively complex, little green enigmas.
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