DataFood Engine.Monexa Data Node
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High Efficiency

Quinoa rossa.

Metabolic profile analysis. Technical breakdown of Quinoa rossa and its impact on skeletal muscle retention and daily energy expenditure.

Total Energy1kcal
Bio-Protein14g
Carbohydrates69g
Total Lipids5g

Nutritional Efficiency Report

Quinoa rossa is a very low-calorie food with moderate-protein content. At 1 kcal per 100g, it delivers 14g of protein — representing 5600% of its total caloric load. Carbohydrates account for 27600% and fats for 4500% of calories.

"Efficiency Score 1.00 — this asset ranks in the top tier of the DataFood database for protein delivery per calorie. Optimal for fat loss, lean bulking, and body recomposition phases."

At 69g carbs per 100g, it is better suited to carb-cycling or maintenance phases.

With only 1 kcal per 100g, Quinoa rossa is a high-volume food — you can consume a large serving while keeping total caloric intake controlled. This makes it particularly effective for hunger management in deficit phases.

Protocol Compatibility

Ketosis Impact

At 69g carbs per 100g, it is better suited to carb-cycling or maintenance phases.

Thermic Effect (TEF)

With 14g protein per 100g, the thermic contribution is moderate. Pairing with higher-protein sources increases the overall TEF of your meal and supports lean mass retention.

Expand Your Protocol.

Based on the metabolic profile of Quinoa rossa, these related data nodes are most relevant to your nutrition architecture:

Fat Loss Foods Database Balanced Nutrition Guide

Integrate Asset.

Use the clinical weekly planner to distribute Quinoa rossa across your metabolic windows.

Generate Weekly Protocol

Input physical metrics to generate a synchronized 7-day protocol.

1. Biological Metrics

2. Dietary Logic

Institutional Disclaimer: The nutritional data provided for Quinoa rossa is derived from clinical databases and algorithmic estimation. This report is for metabolic infrastructure planning only and does not constitute medical advice. Consult a clinical nutritionist before implementing aggressive deficit protocols.