Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 67,
  • Issue 9,
  • pp. 1064-1072
  • (2013)

Application of Laser-Induced Breakdown Spectroscopy (LIBS) and Neural Networks to Olive Oils Analysis

Not Accessible

Your library or personal account may give you access

Abstract

The adulteration and traceability of olive oils are serious problems in the olive oil industry. In this work, a method based on laser-induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification, quality control, traceability, and adulteration detection of extra virgin olive oils. Instant identification of the samples is achieved using a spectral library, which was obtained by analysis of representative samples using a single laser pulse and treatment by NNs. The samples used in this study belong to four countries. The study also included different regions of each country. The results obtained allow the identification of the oils tested with a certainty of more than 95%. Single-shot measurements were enough for clear identification of the samples. The method can be developed for automatic real-time, fast, reliable, and robust measurements, and the system can be packed into portable form for non-specialist users.

PDF Article
More Like This
Identification and quantification of vegetable oil adulteration with waste frying oil by laser-induced fluorescence spectroscopy

Shiguo Hao, Lian Zhu, Ronglong Sui, Mengling Zuo, Ningning Luo, Jiulin Shi, Weiwei Zhang, Xingdao He, and Zhongping Chen
OSA Continuum 2(4) 1148-1154 (2019)

Simple method for liquid analysis by laser-induced breakdown spectroscopy (LIBS)

D. C. Zhang, Z. Q. Hu, Y. B. Su, B. Hai, X. L. Zhu, J. F. Zhu, and X. Ma
Opt. Express 26(14) 18794-18802 (2018)

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.