Structured Nutritional Data & Citations
SECTION 1: SEO Data - Chamomile (Matricaria chamomilla L. / Chamaemelum nobile)
Nutritional Profile
| Nutrient Category | Per 100g Dried Flowers (approximate) | Per 240ml (1 cup) Infusion | Reference Basis |
|---|---|---|---|
| Energy | 320 kcal (1339 kJ) | 2-4 kcal (8-17 kJ) | General Dried Herbs; Trace soluble compounds |
| Macronutrients | |||
| Protein | 10.5 g | <0.1 g | |
| Carbohydrates | 67.0 g | 0.5 - 1.0 g | |
| - Fiber | 25.0 g | <0.1 g | |
| - Sugars | 5.0 g | <0.5 g | |
| Fat | 4.0 g | <0.1 g | |
| - Saturated | 0.5 g | 0 g | |
| - Unsaturated | 3.5 g | 0 g |
Note: The nutritional value of chamomile is primarily derived from its bioactive compounds in the infusion, not from macronutrient or vitamin content. Data for dried flowers is estimated based on general dried herb compositions, as precise USDA entries for Matricaria chamomilla dried flowers with full macro breakdown are limited. The infusion data reflects negligible transfer of macros from dried material to water.
Key Micronutrients & Bioactive Compounds (Predominantly in Infusion)
- Flavonoids: Apigenin (most prominent), Luteolin, Quercetin, Rutin. (Antioxidant, anti-inflammatory, anxiolytic properties).
- Sesquiterpenes: Chamazulene (formed from matricin during heating), Bisabolol (alpha-bisabolol). (Anti-inflammatory, antimicrobial).
- Coumarins: Herniarin, Umbelliferone.
- Phenolic Acids: Caffeic acid, Ferulic acid.
- Trace Minerals: Potassium (<10 mg), Calcium (<5 mg), Magnesium (<3 mg) per serving of infusion. (Concentrations are very low and highly dependent on water source and steeping time).
- Vitamins: Negligible amounts.
Functional Impact
- Glycemic Index (GI): Effectively 0 (for infusion).
- Glycemic Load (GL): Effectively 0 (for infusion).
- Satiety Score: Very low. Primarily consumed for functional benefits (relaxation, digestion aid) rather than caloric or macronutrient satiety.
- Therapeutic Effects (via bioactive compounds): Anxiolytic, sedative, anti-inflammatory, antispasmodic, mild antimicrobial.
Physical Properties
- Density (Dried Chamomile Flowers): 0.15 - 0.25 g/cm³ (Light, fluffy, highly variable based on compaction).
- Volumetric Change After Infusion (Solids): Dried chamomile flowers absorb water and swell significantly, increasing their individual volume by approximately 200-300% during infusion before removal. This is an expansion, not a contraction, of the solid material. The liquid product itself (the tea) maintains its volume.
Citations & References
- USDA FoodData Central. "Tea, herbal, brewed, chamomile." (Entry for brewed tea consistently shows negligible macros and calories). Note: Specific entry for dried chamomile flowers with comprehensive macro data not readily available; general herbal data used for estimation.
- Singh, O., Khanam, Z., & Misra, N. (2011). Chamomile (Matricaria chamomilla L.): An overview. Pharmacognosy Reviews, 5(9), 82. (For bioactive compounds and therapeutic effects).
- Srivastava, J. K., Shankar, E., & Gupta, S. (2010). Chamomile: A herbal medicine of the past with a bright future (Review article). Molecular Medicine Reports, 3(6), 895-901. (For phytochemical composition and functional impact).
- National Center for Complementary and Integrative Health (NCCIH). "Chamomile." (General consensus on uses and safety).
- General Nutritional Databases for Dried Herbs. (Used as a proxy for estimating macro profile of dried flowers).
Field Notes: Dr. Aria Vance
Subject: Chamomile
Focus: Volumetric expansion/contraction, historical context, tracking challenges.
SECTION 2: Why Chamomile Is Difficult to Track
Dr. Aria Vance, Lead Nutrition Data Scientist, NutriSnap.
The little flower, chamomile. Deceptively simple, yet a true headache for accurate dietary tracking. I mean, people don't exactly eat handfuls of dried petals, do they? But try explaining that nuance to a standard food logging app. It’s a riot, truly.
Chamomile's history? Oh, it's ancient. Think Egypt, Rome, Greece. Our ancestors knew this plant was special. "Earth apple," the Greeks called it, because of its subtle apple-like aroma. It's been the go-to for millennia: calm nerves, soothe tummies, help you drift off. A mild sedative, an anti-inflammatory whisper. People have used it for everything from sleepless nights to menstrual cramps, a versatile botanical friend. It’s more than just a cuppa; it’s a cultural touchstone, passed down through generations.
But from a data perspective? Ugh. A nightmare. The standard serving is an infusion. You steep the dried flowers. How many? A teaspoon? A tablespoon? A full sachet? Every brand, every loose-leaf batch, every home-grown harvest is different. A teaspoon of fluffy, whole German chamomile is a vastly different beast, volumetrically and mass-wise, from a teaspoon of finely cut Roman chamomile. And don't even get me started on the potency variations: soil quality, harvest time, drying method – all these things affect the concentration of those precious flavonoids like apigenin. The actual caloric and macro contribution of the infusion is practically nil, we know this. It's all about the phytochemicals. But how do you quantify them accurately?
You can't just slap a barcode on a cup of tea. Scales? Fine for the dried stuff, but who's weighing their tea leaves before steeping every time? And then trying to account for the minute solubles transferred? Forget it. Manual logging demands an unrealistic level of precision for something whose primary impact isn't calorie-based, but biochemical. It's like asking someone to manually log the exact humidity in their bathroom after a shower; interesting data point, perhaps, but impractical and utterly irrelevant to most nutritional goals.
This is precisely where the old methods crumble. The sheer variability in physical form, the negligible traditional nutrient profile, the focus on bioactive compounds—it screams for a better way. This botanical wonder deserves accurate tracking, but the old tools just don't cut it. That's why NutriSnap is such a revelation. Our forensic visual analysis doesn't just see "tea." It learns to differentiate, to estimate based on visual cues. It’s a quantum leap for tracking these functional foods. Finally, we can gather meaningful data, not just vague guesses, on these subtle, yet profound, dietary elements.
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