Application of Three-Dimensional Digital Photogrammetry to Quantify the Surface Roughness of Milk Powder.

Area of Science:

• Food Science and Technology
• Materials Science
• Image Analysis

Background:

• Milk powder surface appearance is critical for functional properties and consumer perception.
• Current methods for assessing milk powder surface roughness rely on subjective and time-consuming expert panels.
• Variability in spray drying conditions leads to inconsistent milk powder surface textures.

Purpose of the Study:

• To develop and validate a rapid, objective, and repeatable method for classifying milk powder surface roughness.
• To establish a quantitative link between surface topography and perceived quality.
• To provide an alternative to traditional subjective assessment methods.

Main Methods:

• Utilized three-dimensional (3D) digital photogrammetry to capture detailed surface topography of milk powder samples.
• Performed contour slice analysis and frequency analysis on the generated 3D models.
• Employed a nonlinear support vector machine (SVM) model for surface roughness classification.

Main Results:

• Smooth-surfaced milk powders exhibited more circular contours and lower standard deviations compared to rough-surfaced powders.
• A lower signal energy value (Q) correlated with smoother milk powder surfaces.
• The SVM model effectively classified milk powder samples based on their surface roughness.

Conclusions:

• 3D digital photogrammetry provides a practicable and objective alternative for quantifying milk powder surface roughness.
• This technique can enhance quality control and consistency in milk powder production.
• Objective surface characterization can lead to improved product quality and consumer satisfaction.