Detection of soybean in soy-based meat substitutes

Area of Science:

• Food Science
• Analytical Chemistry
• Nutritional Science

Background:

• Soybean is a versatile ingredient in food products, including meat substitutes.
• Accurate quantification of soybean content is crucial for product consistency and nutritional labeling.
• Predictive models for ingredient composition can optimize recipe development.

Purpose of the Study:

• To establish statistical models for forecasting soy percentage in recipes based on nutritional analysis.
• To evaluate the utility of electropherogram band areas for quantifying whole soybean in soy-based meat products.

Main Methods:

• Statistical analysis of nutritional data (protein, fat, fiber, calcium, methionine, lysine).
• Development of linear regression equations to correlate nutritional components with added soy percentage.
• Electropherogram analysis to identify and measure band areas in soy-based samples.

Main Results:

• Straight-line equations for protein, fat, fiber, calcium, methionine, and lysine successfully predicted added soy percentage.
• Areas of identified bands in electropherograms served as a reliable method for quantifying whole soybean content.

Conclusions:

• Nutritional profiling offers a viable method for predicting soy inclusion in food formulations.
• Electropherogram analysis provides an effective tool for the quantitative determination of soybean in processed foods.