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Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.

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Pea protein and glycerol coatings offer a sustainable alternative to egg washes for baked goods, enhancing gloss and maintaining color. The 80%/20% pea protein/glycerol ratio provided the highest glossiness in this study.

Keywords:
color analysiscomputer visionegg replacementmachine learningpie crust

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Area of Science:

  • Food Science
  • Sustainable Materials

Background:

  • Egg washes are traditionally used in baked goods for desirable visual properties like color and gloss.
  • There is a growing need for sustainable, plant-based alternatives in food production.

Purpose of the Study:

  • To investigate pea protein and glycerol as a sustainable alternative to egg washes for baked goods.
  • To evaluate the color and gloss properties of pea protein coatings under various conditions.

Main Methods:

  • A simplified pie crust model was used with pea protein coatings at different pea protein/glycerol ratios, pH levels, and application weights.
  • Color (L*, a*, b*) and gloss were assessed using image analysis with random forest and artificial neural network models.
  • Image data was corrected for lighting variations using principal component analysis (PCA).

Main Results:

  • Pea protein glycerol coatings demonstrated superior glossiness compared to traditional egg washes.
  • The 80%/20% pea protein/glycerol ratio yielded the highest gloss.
  • Colorimeter values showed no significant differences across concentrations when 1g of protein was applied.
  • The artificial neural network model effectively estimated color under varying lighting conditions.

Conclusions:

  • Pea protein and glycerol present a viable, sustainable alternative to egg washes in baked goods.
  • The 80%/20% ratio is optimal for achieving enhanced gloss.
  • Image analysis techniques, including PCA and machine learning, can accurately assess coating properties.