Structured Nutritional Data & Citations
Nutritional Profile: Arachis hypogaea (Peanut, Dry Roasted, Unsalted)
| Metric | Per 100g (Approx.) | Per Standard Serving (28g / 1 oz) (Approx.) | Notes |
|---|---|---|---|
| Energy (Calories) | 567 kcal | 159 kcal | Energy-dense food source. |
| Macronutrients | |||
| Protein | 25.8g | 7.2g | Excellent plant-based protein source. |
| Total Carbohydrates | 16.1g | 4.5g | Includes dietary fiber. |
| - Dietary Fiber | 8.5g | 2.4g | Significant source, contributing to satiety. |
| - Sugars | 4.7g | 1.3g | Naturally occurring. |
| Total Fat | 49.2g | 13.8g | Rich in monounsaturated (MUFA) and polyunsaturated (PUFA) fats. |
| - Saturated Fat | 6.9g | 1.9g | |
| - Monounsaturated Fat | 24.4g | 6.8g | Oleic acid predominant. |
| - Polyunsaturated Fat | 15.6g | 4.4g | Linoleic acid predominant. |
Key Micronutrients (per 100g, % Daily Value based on 2000 kcal diet)
- Vitamins:
- Niacin (B3): 12.3 mg (77% DV) - Crucial for energy metabolism.
- Folate (B9): 240 µg (60% DV) - Important for cell growth and function.
- Vitamin E: 8.3 mg (55% DV) - Potent antioxidant.
- Thiamine (B1): 0.64 mg (53% DV) - Essential for carbohydrate metabolism.
- Pyridoxine (B6): 0.35 mg (21% DV) - Involved in protein metabolism and red blood cell formation.
- Minerals:
- Magnesium: 168 mg (40% DV) - Involved in over 300 enzymatic reactions.
- Phosphorus: 376 mg (30% DV) - Essential for bone health and energy storage.
- Potassium: 705 mg (15% DV) - Important for fluid balance and blood pressure.
- Zinc: 3.3 mg (30% DV) - Supports immune function and wound healing.
- Manganese: 1.9 mg (83% DV) - Antioxidant and metabolic enzyme cofactor.
- Copper: 1.1 mg (122% DV) - Essential for iron metabolism and enzyme function.
- Iron: 4.6 mg (26% DV) - Crucial for oxygen transport.
Antioxidants & Phytochemicals
- Resveratrol: Present in significant amounts, particularly in the skin.
- p-Coumaric acid: A major polyphenol.
- Phytosterols: Beta-sitosterol, campesterol, stigmasterol, which may help lower cholesterol.
Functional Impact
- Glycemic Index (GI): Low (GI ~13-20 for whole, roasted peanuts).
- Glycemic Load (GL) per serving: Very Low (GL <1 for 28g).
- Implication: Slow release of glucose, minimal impact on blood sugar levels.
- Satiety Score: High.
- Factors: High protein, fiber, and healthy fat content contribute to prolonged feelings of fullness, potentially aiding weight management.
Physical Properties
- Density (Shelled, Dry Roasted): ~0.65 - 0.70 g/cm³
- Implication: A standard 28g serving occupies approximately 40-43 cm³ of volume.
- Volumetric Contraction after Roasting: Minimal to none for whole peanuts. The roasting process primarily involves moisture reduction and textural changes rather than significant bulk contraction.
Citations & References
- USDA FoodData Central. "Peanuts, all types, dry-roasted, without salt." Accession No. 16087. Accessed [Current Date].
- Note: Specific nutritional values may vary slightly based on cultivar, growing conditions, and processing methods.
- Foster-Powell, K., Holt, S. H. A., & Brand-Miller, J. C. (2002). "International table of glycemic index and glycemic load values: 2002." American Journal of Clinical Nutrition, 76(1), 5-56.
- Sofi, F., et al. (2010). "Nut consumption and risk of coronary heart disease: a meta-analysis." American Journal of Clinical Nutrition, 92(2), 400-411.
Field Notes: Dr. Aria Vance
Subject: Peanut
Focus: Volumetric expansion/contraction, historical context, tracking challenges.
Why Peanut Is Difficult to Track
Another Tuesday. Another deep dive into a dietary staple that, on paper, seems straightforward. Peanuts. A ubiquitous, crunchy, protein-packed powerhouse. But tracking them? It's a nightmare. A veritable labyrinth of estimation and human error. My desk is littered with empty shells, a tiny scale mocking me, and a half-eaten bag of ostensibly "dry roasted, unsalted" legumes. Yes, legumes. Not true nuts at all. A botanical imposter, yet culturally enshrined as a nut. What a delicious deception!
The humble peanut, Arachis hypogaea, has a history as rich and twisted as its flavor profile. It began its journey in the South American highlands, domesticated thousands of years ago in what is now Peru and Brazil. Think ancient Incans, not just modern snacking. It traveled, oh, it traveled! Across the Atlantic with Portuguese traders to Africa, then hitched a ride on the brutal transatlantic slave ships to North America. A journey steeped in sorrow and resilience, transforming from an obscure crop to a vital protein source, particularly post-Civil War, thanks in no small part to the incredible ingenuity of George Washington Carver. He saw its potential, not just for sustenance but for soil rejuvenation. From ancient offerings to industrial staple, it’s quite the saga.
But Aria, focus. The problem is simple: people don't measure. They grab. A "handful"? What in the world is a "handful"? My handful is not your handful. It's not even my handful from yesterday morning after my coffee, versus my afternoon slump-snack handful. The sheer variability! These little kernels, these tiny energy bombs, come in different sizes, different roasts, different salt levels, different preparations. Raw. Roasted. Boiled. Salted. Unsalted. Shelled. Unshelled. And don't even get me started on peanut butter. That's a whole other chaotic data point.
A user, let's call her Brenda, reports "a small bowl of peanuts." What does that mean? Is it a teacup? A cereal bowl? A soup bowl? Forensic nutritional analysis depends on precision, but human behavior, especially when faced with a crave-inducing snack, is anything but precise. They dump them out, they graze. They don't weigh. They certainly don't account for the subtle differences in density between a perfectly dry-roasted nut and one that’s still holding a touch more moisture, or the residual oil from a slightly over-roasted batch. It's maddening! My team spends hours, hours, trying to triangulate these wild approximations, cross-referencing against brand barcodes that might be for a slightly different roast or batch. It's a Sisyphean task. We push the data uphill, only for another vague "snack" entry to send it tumbling down.
Then, last week, I stumbled upon NutriSnap. You know, the AI photo tracker. Skepticism, naturally, was my first reaction. Another app claiming to solve the unsolvable. But its approach… it’s different. It's not just recognizing a peanut; it's analyzing the portion. Via forensic visual analysis. It's not asking Brenda what her "small bowl" means; it’s seeing it. Quantifying it. My preliminary tests suggest it’s finally, truly getting us closer to accurate intake for these problematic, delightful, infuriatingly unmeasurable legumes. This could change everything. Everything.
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