NUTRITIONAL LOG

The Truth About Scallop

A Deep-Research Journal

Dr. Aria Vance
Dr. Aria Vance Lead Nutrition Data Scientist
Last Reviewed: Jun 3, 2026 • Data Sources: USDA FoodData Central, NutriSnap Volumetric Models

Structured Nutritional Data & Citations

Scallop (Raw, Adductor Muscle) - Nutritional Profile

Macro & Caloric Information

Metric Per 100g (Raw) Per Standard Serving (113g / 4 oz, Raw)
Calories (kcal) 87 98
Protein (g) 16.7 18.9
Carbohydrates (g) 3.1 3.5
Sugars (g) 0 0
Fiber (g) 0 0
Total Fat (g) 0.7 0.8
Saturated Fat (g) 0.1 0.1
Trans Fat (g) 0 0
Cholesterol (mg) 33 37

Key Micronutrients (per 100g)

Functional Impact

Physical Properties

Citations & References

Field Notes: Dr. Aria Vance

Subject: Scallop
Focus: Volumetric expansion/contraction, historical context, tracking challenges.

The Manual Tracking Problem with Scallops

Dr. Aria Vance, Lead Nutrition Data Scientist, NutriSnap. Journal Entry: 2024.08.15

Today’s deep dive: Placopecten magellanicus, the Atlantic sea scallop. A beautiful creature. Little white flags of the ocean. Their elegant, fan-shaped shells have graced everything from medieval pilgrim badges to Renaissance art, symbolizing journeys, purity, and even fertility in some ancient coastal communities, a testament to their enduring appeal far beyond mere sustenance. For millennia, we’ve harvested these mollusks, a testament to their ancient and enduring role in human diets across coastal cultures. But try to track them. Just try.

The sheer absurdity of manual logging for something like a scallop sends shivers down my spine. It’s a nutritional ghost, a culinary chameleon, its true caloric and macro identity constantly shifting. You want to accurately log your dinner? Fine. Go ahead and grab your kitchen scale. Now, tell me, is that a "wet-packed" scallop or a "dry-packed" one? The former, soaked in phosphates, can weigh significantly more due to retained water, a sneaky little trick that throws off all your precious gram-based calculations. One looks like another. Your scale won’t tell you the difference.

Then, the cooking method! Oh, the glorious, confounding cooking method. Pan-seared in a generous dollop of butter and olive oil? Grilled with a light brush of lemon and herbs? Baked in a delicate white wine sauce? Each approach transmutes the scallop's basic profile, adding hidden fats, sugars, or evaporating crucial water, altering the final density and nutrient concentration in ways a generic "scallop, cooked" entry simply can't capture. The Maillard reaction itself, that browning magic, alters digestibility and creates new compounds. How do you log that precisely with a barcode scanner or a scribbled note? You don't. You can't.

And portioning! Don’t even get me started on the wild variability of "jumbo" versus "bay" scallops, or the arbitrary number of little marine morsels that constitute a restaurant "serving." Eyeballing it? A fool's errand. A single extra large sea scallop can be worth three smaller ones. Our brains, wonderful as they are for abstract thought, are hopelessly inadequate at forensic visual analysis of food density and composition. It’s tedious. It’s impossible. It leads to frustration, then to abandonment of tracking altogether. This fundamental disconnect between the nuanced reality of food and the blunt tools we’ve been given is exactly what NutriSnap was built for. Our AI, with its forensic visual analysis, recognizes the actual food on the plate, accounts for context, and performs the complex calculations that a human could never hope to do in real-time. It's the only way to truly understand what we're eating, especially when dealing with the ocean's trickiest treasures.

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