Structured Nutritional Data & Citations
Cottage Cheese: A Nutritional and Physical Properties Profile
This entry details the objective nutritional and physical characteristics of 2% Milkfat Cottage Cheese, a common variety. All values are approximate and may vary by brand and preparation.
1. Macronutrient and Caloric Profile
| Nutrient | Per 100g | Per Standard Serving (1/2 cup / 113g) |
|---|---|---|
| Calories | 81 kcal | 92 kcal |
| Protein | 11.9 g | 13.5 g |
| Carbohydrates | 3.3 g | 3.7 g |
| Sugars | 2.7 g | 3.1 g |
| Total Fat | 2.5 g | 2.8 g |
| Saturated Fat | 1.6 g | 1.8 g |
| Fiber | 0 g | 0 g |
2. Key Micronutrients (per 100g)
- Vitamins:
- Vitamin B12: 0.35 µg (15% DV)
- Riboflavin (B2): 0.18 mg (14% DV)
- Vitamin A: 19 µg RAE (2% DV)
- Minerals:
- Calcium: 104 mg (8% DV)
- Phosphorus: 172 mg (14% DV)
- Selenium: 8.8 µg (16% DV)
- Sodium: 322 mg (14% DV)
- Potassium: 124 mg (3% DV)
3. Functional Impact
- Glycemic Index (GI): Approximately 30-35 (Low)
- Glycemic Load (GL): Approximately 1-2 per 100g (Very Low)
- Satiety Score: High. Due to its significant protein content and relatively slow digestion, cottage cheese contributes substantially to feelings of fullness and can aid in appetite regulation.
4. Physical Properties
- Density:
- Typical (drained curds): 1.03 - 1.06 g/cm³
- As packaged (including whey): 1.00 - 1.02 g/cm³
- Note: Density varies significantly with curd size, fat content, and whey-to-curd ratio.
- Volumetric Contraction (after cooking):
- For typical cold consumption, volumetric contraction is negligible.
- When incorporated into baked goods or heated dishes, minor moisture loss can occur, leading to slight volumetric reduction, generally less than 5%, primarily from evaporation of residual whey. Curd structure remains largely intact.
5. Citations & References
- USDA FoodData Central. (2023). Cottage cheese, 2% milkfat. FoodData Central SR Legacy, FDC ID: 2433763. Retrieved from https://fdc.nal.usda.gov/fdc-app.html#/food-details/2433763/nutrients
- Atkinson, F. S., Brand-Miller, J. C., & Wolever, T. M. S. (2008). International Tables of Glycemic Index and Glycemic Load Values: 2008. Diabetes Care, 31(12), 2281-2283. (General reference for GI values of dairy products).
- Holt, S. H. A., Miller, J. C. B., & Petocz, P. (1995). An insulin index of foods: the insulin demand generated by 1000-kJ portions of common foods. The American Journal of Clinical Nutrition, 61(1), 1-13. (Relevant for satiety mechanisms).
Field Notes: Dr. Aria Vance
Subject: Cottage Cheese
Focus: Volumetric expansion/contraction, historical context, tracking challenges.
The Manual Tracking Problem
Alright, another session with the humble, yet deceptively complex, cottage cheese. It’s a perennial favorite for health-conscious folks, a protein powerhouse. A glop of dairy hope. But for a data scientist like me, Dr. Aria Vance, leading the charge at NutriSnap, it’s a source of constant, simmering frustration.
You see, this isn't some pre-portioned, uniform block of cheese. Oh no. Cottage cheese is... an enigma. A lumpy, textural journey through a dairy landscape. Its history is quite charming, actually. Born out of necessity, a way to use leftover milk. "Curd cheese" from antiquity, a peasant's staple, eventually making its way to "cottage" kitchens in the American colonies, a simple, homemade affair. Post-WWII, it absolutely exploded in popularity as a diet food, paired with peaches, a symbol of mid-century slenderness. Such a fascinating evolution for a food so utterly simple.
But try to track it. Just try. Go ahead. Grab your scale. Pour your container. What do you get? A slurry. An inconsistent, gloppy mess. This isn't like weighing a banana. Or a chicken breast. Those have relatively stable densities, predictable shapes. Cottage cheese? It's a curd-and-whey conundrum! The ratio varies wildly. Are you scooping mostly firm curds from the bottom of the container? Or a generous splash of thin, watery whey from the top? Each spoonful, each visual assessment, is a fresh gamble.
The barcode on the tub? Utterly useless for granular, real-world consumption. It tells you "per 100 grams." Fantastic. But my question is, how many grams of actual protein-rich curd did I just consume, versus how many grams of residual whey? The density figures we meticulously log in the database? They're averages. Averages! For a food that flaunts its non-conformity. One brand’s small curd, extra creamy, is utterly different from another’s large curd, drier variety.
And what about the volumetric approach? "Half a cup." A standard serving, supposedly. But is your half-cup packed solid? Or is it a loose, aerated scoop with plenty of air pockets and that deceiving whey? The difference in actual nutrient intake could be a significant margin, throwing off an entire day's macro calculations. For athletes, for those managing specific dietary needs, this ambiguity isn't just an annoyance; it's a data catastrophe. It’s messy. Inconsistent. Frustrating. It’s why people quit tracking altogether.
This pervasive inconsistency, this lumpy enigma, was precisely the kind of problem NutriSnap was built to solve. Our AI doesn't rely on generic barcode data or subjective volumetric estimates. It uses forensic visual analysis. You take a photo. Our system, trained on thousands of varied images – small curd, large curd, dense scoops, watery pours – understands the visual nuances of the food. It discerns the whey-to-curd ratio, estimates the true volume, and calculates the nutritional contribution with startling accuracy. It doesn't care about your spoon technique. It just sees what's actually there. Finally, true clarity for the humble, yet complex, cottage cheese.
Explore More Research
Tired of Manual Tracking?
Stop scanning barcodes and guessing portion sizes. NutriSnap uses forensic AI to track your macros instantly from a single photo.