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Effect of temperature change on refractive index of an egg white and yolk - a preliminary study

MetadataDetails
Publication Date2022-07-01
JournalPhotonics Letters of Poland
AuthorsPatryk SokoƂowski
InstitutionsGdaƄsk University of Technology
AnalysisFull AI Review Included

This preliminary study investigates the thermal dependence of the refractive index (RI) in egg white and yolk using a fiber-optic Fabry-Perot Interferometer (FPI) setup.

  • Core Objective: Determine the refractive index of egg white and yolk across a biologically relevant temperature range (30 °C to 47 °C) at 1550 nm.
  • Sensing Mechanism: A fiber-optic FPI sensor head was employed, utilizing interference between the polished fiber end-face and an aluminum weighing dish containing the liquid sample.
  • Key Finding (Temperature Dependence): The refractive index of both egg white and yolk showed a strong, visible dependence on temperature, confirming RI as a sensitive physical parameter for biological composition.
  • Egg White RI Range: Measured RI values for egg white spanned approximately 1.1 to 1.35 across the tested temperature range.
  • Egg Yolk RI Range: Measured RI values for egg yolk exhibited a wider variation, ranging from approximately 1.2 to 1.7.
  • Metrological Significance: The RI serves as a potential marker for assessing factors influencing egg composition, such as hen age, diet, or environmental conditions.
  • Instrumentation: The setup utilized standard telecom components, including a Superluminescent Diode (1550 nm) and an Optical Spectrum Analyzer (OSA), demonstrating a robust, high-resolution sensing platform.
ParameterValueUnitContext
Measurement Wavelength (Center)1550nmSuperluminescent Diode (SLD)
SLD Spectral Width35nmSLD-1550-13, FiberLabs Inc.
Temperature Range Tested30 - 47°CMeasurements taken in 1 °C steps
Egg White RI Range (Approx.)1.1 - 1.35N/AMeasured median values at 1550 nm
Egg Yolk RI Range (Approx.)1.2 - 1.7N/AMeasured median values at 1550 nm
Air Refractive Index (RI)1.0003N/AUsed for initial cavity length estimation
Geometrical Cavity Length (Egg White)238.8”mDetermined during calibration
Geometrical Cavity Length (Egg Yolk)211.7”mDetermined during calibration
Optical Signal ProcessorAndo AQ6319N/AOptical Spectrum Analyzer (OSA)

The refractive index determination relied on measuring the interference spectrum generated by a customized fiber-optic Fabry-Perot Interferometer (FPI) setup.

  1. Sensor Head Construction: The FPI cavity was formed between the polished end-face of an optical fiber (1) and the reflective surface of an aluminum weighing dish (3).
  2. Optical Configuration: A 1550 nm Superluminescent Diode (SLD) provided the broadband light source. Light was coupled to the sensor via a 2:1 fiber coupler, and the reflected interference signal was analyzed by an Optical Spectrum Analyzer (OSA).
  3. Cavity Length Calibration: The geometrical path length (L) was initially estimated by filling the cavity with air (RI = 1.0003) at room temperature and measuring the wavelengths of two neighboring interference maxima (λ1 and λ2).
  4. Sample Preparation: Free-range eggs were cracked, separated into white and yolk components, and placed in milliliter quantities onto the aluminum dish.
  5. Thermal Control: A custom-built heat plate was used to control the sample temperature precisely, cycling from 30 °C to 47 °C with a 1 °C step size.
  6. Data Collection: At each temperature point, 6 separate measurements were recorded for each sample (white and yolk) to ensure statistical validity.
  7. Refractive Index Calculation: The RI (n) of the sample was calculated using the measured interference spectrum and the calibrated geometrical cavity length (L), based on the relationship derived from the phase shift equation (φ = 4πnL/λ).
  8. Statistical Filtering: Boxplot analysis was applied to the data to determine the median RI and identify outliers (measurements deviating by > 1.5 Interquartile Range, IQR).

The demonstrated high-resolution, temperature-dependent RI sensing technique using fiber-optic FPIs is applicable across several industries requiring non-invasive fluid characterization.

  • Food Quality and Safety:
    • Real-time, non-destructive assessment of egg freshness, thermal history, and compositional changes (e.g., protein denaturation) during storage or pasteurization.
    • Quality control in liquid food processing (e.g., dairy, juices) where RI correlates directly with sugar or solid content (Brix).
  • Biomedical and Pharmaceutical Monitoring:
    • Development of compact, biocompatible fiber sensors for continuous monitoring of RI in biological fluids (e.g., blood, serum) to track hydration, glucose levels, or protein concentration.
    • High-resolution sensing in microfluidic devices for rapid diagnostic testing.
  • Chemical and Process Control:
    • Monitoring the concentration and mixing ratios of binary or multi-component liquid solutions in chemical reactors.
    • In-situ measurement of polymerization or curing processes where RI changes indicate reaction progress.
  • Advanced Optical Metrology:
    • Utilizing the strong thermal dependence of RI in specific liquids to create highly localized, precise fiber-optic temperature sensors for harsh or inaccessible environments.
    • Calibration and validation of other optical sensing systems requiring accurate liquid RI standards.
View Original Abstract

In this article, the refractive index of an egg white and yolk depending on temperature in range 30 - 47 °C over 1550 nm was determined. The measurement head was constructed as fiber optic Fabry-Perot interferometer with interference between polished fiber end-face and aluminum weighing dish. The measurement setup has been made of an optical spectrum analyzer, a superluminescent diode with a central wevelength of 1550 nm, 2:1 fiber coupler and heat plate. Full Text: PDF ReferencesP. Magdelaine, “Egg and egg product production and consumption in Europe and the rest of the world, Improving the Safety and Quality of Eggs and Egg Products”, Egg Chemistry, Production and Consumption, 3 (2011). CrossRef H. Kuang, F. Yang, Y. Zhang, T. Wang, and G. Chen, “The Impact of Egg Nutrient Composition and Its Consumption on Cholesterol Homeostasis”, Cholesterol (2018). CrossRef J. Gienger, K. Smuda, R. MĂŒller, M. BĂ€r, and J. Neukammer, “Refractive index of human red blood cells between 290 nm and 1100 nm determined by optical extinction measurements”, Sci. Rep. 9, 1 (2019). CrossRef P. Listewnik, M. Hirsch, P. Struk, M. Weber, M. Bechelany, and M. Jędrzejewska-Szczerska, “Preparation and Characterization of Microsphere ZnO ALD Coating Dedicated for the Fiber-Optic Refractive Index Sensor”, Nanomaterials 9, 2 (2019) CrossRef Y. Wu, Y. Zhang, J. Wu, and P. Yuan, “Fiber-Optic Hybrid Structured Fabry-Perot Interferometer Based On Large Lateral Offset Splicing for Simultaneous Measurement of Strain and Temperature”, J. Lightwave Technol., 35, 19 (2017). CrossRef M. Islam, M. Mahmood, M Lai, K. Lim, and H. Ahmad, “Chronology of Fabry-Perot Interferometer Fiber-Optic Sensors and Their Applications: A Review”, Sensors 14, 4 (2014). CrossRef K. Karpienko, M. WrĂłbel, and M. Jędrzejewska-Szczerska, “Determination of refractive index dispersion using fiber-optic low coherence Fabry-Perot interferometer: implementation and validation”, Opt. Eng. 53, 7 (2014). CrossRef M. Kosowska, D. Majchrowicz, K. Sankaran, M. Ficek, K. Haenen, and M. Szczerska, “Doped Nanocrystalline Diamond Films as Reflective Layers for Fiber-Optic Sensors of Refractive Index of Liquids”, Materials 12, 13 (2019). CrossRef G. Xiao, A. Adnet, Z. Zhang, F. Sun, and C. Grover, “Monitoring changes in the refractive index of gases by means of a fiber optic Fabry-Perot interferometer sensor”, Sensors and Actuators 118, 2 (2005). CrossRef