Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 69,
  • Issue 7,
  • pp. 802-809
  • (2015)

Linear Polarized Transmission Resonance Raman Studies in Fruits: Experimental Versus Model Calculations

Not Accessible

Your library or personal account may give you access

Abstract

A linear polarized transmission resonance Raman spectroscopic technique was developed to measure the depolarization ratio of different β-carotene Raman bands in carrot roots and mangos. Basically, this optical property was measured as a function of the vegetal tissue thickness and fruit postharvest lifetime. In general, the depolarization ratio increases as the sample optical thickness does and decreases as the fruit postharvest lifetime increases. In addition, a previous theoretical model was extended by considering the light state of polarization to obtain the depolarization ratio as a function of the sample absorption and scattering coefficient. It was shown how the reported theoretical model is able to satisfactorily describe the fruit optical parameter dependence on both the sample thickness and its postharvest time. Finally, the advantages and limitations of the present technique and theoretical mode are discussed.

PDF Article
More Like This
Stokes mode Raman random lasing in a fully biocompatible medium

Venkata Siva Gummaluri, S. R. Krishnan, and C. Vijayan
Opt. Lett. 43(23) 5865-5868 (2018)

Monitoring of fruit freshness using phase information in polarization reflectance spectroscopy

M. Sarkar, N. Gupta, and M. Assaad
Appl. Opt. 58(23) 6396-6405 (2019)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.