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Related Experiment Video

Updated: Sep 5, 2025

Analysis of Arabidopsis thaliana Growth Behavior in Different Light Qualities

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Published on: February 2, 2018

Simulation of light interaction with seedless grapes.

Sophie Jenne¹, Hans Zappe¹

¹Department of Microsystems Engineering - IMTEK, Gisela and Erwin Sick Chair of Micro-Optics University of Freiburg, Freiburg, Germany.

Journal of the Science of Food and Agriculture

|July 5, 2022

Summary

This study determined the optical properties of seedless grapes to create realistic 3D models for food quality monitoring sensors. These models aid in predicting light interaction for improved fruit assessment.

Keywords:

grapevine inverse adding-doubling light propagation optical simulation spectroscopy

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Area of Science:

Agricultural Science
Optical Physics
Food Science

Background:

Spectroscopic techniques are vital for non-destructive fruit quality monitoring.
Understanding optical properties is crucial for developing new sensor devices.
Predicting light-fruit interaction requires accurate optical data.

Purpose of the Study:

To determine the optical properties of three seedless grape varieties.
To create realistic 3D optical models of grape berries for simulations.
To aid in the development of optical applications for food quality monitoring.

Main Methods:

UV-visible/near-infrared spectroscopy with an integrating sphere was used.
Optical properties (absorption, scattering coefficients, anisotropy factor) were calculated using the inverse adding doubling method.
A 3D grape berry model was generated in OpticStudio using determined optical properties and the Henyey-Greenstein distribution for bulk scattering.

Main Results:

Significant differences in optical properties were observed between grape varieties, particularly in the visible spectrum.
Grape berry skin exhibits a higher scattering coefficient with predominantly forward scattering.
Generated 3D models accurately simulated total transmission and specular reflection, validating their realism.

Conclusions:

The developed procedure for creating optical grape models is beneficial for pre- and post-harvest food quality monitoring.
These models facilitate the design and simulation of optical sensor applications.
This research supports advancements in non-destructive food quality assessment technologies.