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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #360416

Research Project: Nondestructive Quality Assessment and Grading of Fruits and Vegetables

Location: Sugarbeet and Bean Research

Title: Measurement of optical properties of fruits and vegetables: A review

item Lu, Renfu
item VAN BEERS, ROBBE - Catholic University Of Leuven
item SAEYS, WOUTER - Catholic University Of Leuven
item LI, CHANGYING - University Of Georgia
item CEN, HAIYAN - Zhejiang University

Submitted to: Postharvest Biology and Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/2/2019
Publication Date: 9/18/2019
Citation: Lu, R., Van Beers, R., Saeys, W., Li, C., Cen, H. 2019. Measurement of optical properties of fruits and vegetables: A review. Postharvest Biology and Technology. 159:111003.

Interpretive Summary:

Technical Abstract: This paper provides an overview of the principles and theory of measuring optical properties of biological materials. It then presents the instrumentation and data analysis procedures for implementing several emerging optical techniques, including spatially resolved, time-resolved, and spatial-frequency domain, along with the standard integrating sphere method. Applications of these techniques for optical property measurement, maturity and quality assessment, and defect detection of fruits and vegetables are then reviewed, followed with discussions on issues and challenges that still need to be addressed for these emerging optical techniques. While these optical techniques are overall more sophisticated in instrumentation and computation, they are based on solid radiative transfer theory or diffusion approximation theory. Hence, measurement of optical absorption and scattering properties has the potential of providing more complete, objective information for quality evaluation of horticultural products. At present, these techniques are still slow in measurement, and prone to errors due to modeling and instrumentation deficiencies. Further research is therefore needed in using a better mathematical modeling approach, improving data acquisition accuracy and speed, and developing more robust inverse algorithms for optical property estimations.