Egg Freshness Evaluation Using Transmission and Reflection of NIR Spectroscopy Coupled Multivariate Analysis

Area of Science:

• Agricultural Science
• Analytical Chemistry
• Food Science

Background:

• Egg freshness is crucial for food safety and quality.
• Traditional methods for assessing egg freshness can be time-consuming and destructive.
• Non-destructive techniques are needed for efficient egg quality assessment.

Purpose of the Study:

• To develop and evaluate near-infrared (NIR) spectroscopy combined with multivariate models for detecting egg freshness.
• To compare the effectiveness of diffuse transmission and reflection modes in NIR spectroscopy for egg freshness assessment.
• To predict key physical indices of egg quality.

Main Methods:

• Utilized near-infrared (NIR) spectroscopy in diffuse transmission and reflection modes.
• Employed linear discriminant analysis (LDA) for pattern recognition and classification of egg freshness.
• Applied synergy interval partial least squares (Si-PLS) for predicting physical indices like Haugh unit, yolk index, and weight loss.

Main Results:

• Diffuse transmission mode was found to be more suitable for judging egg freshness.
• The LDA model achieved 91.4% discrimination accuracy for eggs stored at room temperature.
• The LDA model showed lower accuracy (25.6%) for refrigerated eggs.
• Si-PLS models accurately predicted Haugh unit (RMSEP=4.25), yolk index (RMSEP=0.031), and weight loss (RMSEP=0.005432) for eggs under normal conditions.

Conclusions:

• NIR diffuse transmission spectroscopy is a promising non-destructive method for assessing egg freshness, especially for room-temperature storage.
• The LDA model demonstrates significant potential for discriminating egg storage time.
• Further refinement is needed for accurate freshness detection in refrigerated eggs.
• NIR spectroscopy combined with Si-PLS offers a reliable approach for predicting egg physical quality indices.