scholarly journals Laser-Induced Breakdown Spectroscopy: An Efficient Tool for Food Science and Technology (from the Analysis of Martian Rocks to the Analysis of Olive Oil, Honey, Milk and Other Natural Earth Products)

Molecules ◽  
2021 ◽  
Vol 26 (16) ◽  
pp. 4981
Author(s):  
Dimitrios Stefas ◽  
Nikolaos Gyftokostas ◽  
Eleni Nanou ◽  
Panagiotis Kourelias ◽  
Stelios Couris
Keyword(s):  
Olive Oil ◽  
Laser Induced Breakdown Spectroscopy ◽  
Food Science ◽  
Efficient Tool ◽  
Breakdown Spectroscopy ◽  
Research Activities ◽  
Current State ◽  
Laser Induced Breakdown ◽  
Art Research ◽  
Chemometric Algorithms

Laser-Induced Breakdown Spectroscopy (LIBS), having reached a level of maturity during the last few years, is generally considered as a very powerful and efficient analytical tool, and it has been proposed for a broad range of applications, extending from space exploration down to terrestrial applications, from cultural heritage to food science and security. Over the last decade, there has been a rapidly growing sub-field concerning the application of LIBS for food analysis, safety, and security, which along with the implementation of machine learning and chemometric algorithms opens new perspectives and possibilities. The present review intends to provide a short overview of the current state-of-the-art research activities concerning the application of LIBS for the analysis of foodstuffs, with the emphasis given to olive oil, honey, and milk.

scholarly journals Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1241
Author(s):  
Nikolaos Gyftokostas ◽  
Eleni Nanou ◽  
Dimitrios Stefas ◽  
Vasileios Kokkinos ◽  
Christos Bouras ◽  
...  
Keyword(s):  
Machine Learning ◽  
Olive Oil ◽  
Absorption Spectra ◽  
Absorption Spectroscopy ◽  
Laser Induced Breakdown Spectroscopy ◽  
Spectroscopic Techniques ◽  
Breakdown Spectroscopy ◽  
Olive Oils ◽  
Laser Induced Breakdown

In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.

scholarly journals Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nikolaos Gyftokostas ◽  
Dimitrios Stefas ◽  
Vasileios Kokkinos ◽  
Christos Bouras ◽  
Stelios Couris
Keyword(s):  
Machine Learning ◽  
Olive Oil ◽  
Virgin Olive Oil ◽  
Geographic Origin ◽  
Classification Performance ◽  
Machine Learning Algorithms ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
The Mediterranean

AbstractOlive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.

Nanosecond laser-induced breakdown assisted by femtosecond laser pre-ionization in air: the effect on spatial resolution and continuous radiation

2020 ◽  
Vol 92 (2) ◽  
pp. 20701
Author(s):  
Bo Li ◽  
Xiaofeng Li ◽  
Zhifeng Zhu ◽  
Qiang Gao
Keyword(s):  
Femtosecond Laser ◽  
Spatial Resolution ◽  
Laser Induced Breakdown Spectroscopy ◽  
Nanosecond Laser ◽  
Breakdown Threshold ◽  
Powerful Technique ◽  
Breakdown Spectroscopy ◽  
Continuous Radiation ◽  
Laser Induced Breakdown

Laser-induced breakdown spectroscopy (LIBS) is a powerful technique for quantitative diagnostics of gases. The spatial resolution of LIBS, however, is limited by the volume of plasma. Here femtosecond-nanosecond dual-pulsed LIBS was demonstrated. Using this method, the breakdown threshold was reduced by 80%, and decay of continuous radiation was shortened. In addition, the volume of the plasma was shrunk by 85% and hence, the spatial resolution of LIBS was significantly improved.

Characterization of Amethysts from Sukamara, Central Kalimantan, Using Laser-Induced Breakdown Spectroscopy (LIBS)

2020 ◽  
Vol 1 (2) ◽  
pp. 5-8
Author(s):  
Komang Gde Suastika, Heri Suyanto, Gunarjo, Sadiana, Darmaji
Keyword(s):  
Emission Intensity ◽  
Laser Energy ◽  
Emission Spectra ◽  
Atomic Emission ◽  
Laser Induced Breakdown Spectroscopy ◽  
Chemical Formula ◽  
Central Kalimantan ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

Abstract - Laser-Induced Breakdown Spectroscopy (LIBS) is one method of atomic emission spectroscopy using laser ablation as an energy source. This method is used to characterize the type of amethysts that originally come from Sukamara, Central Kalimantan. The result of amethyst characterization can be used as a reference for claiming the natural wealth of the amethyst. The amethyst samples are directly taken from the amethyst mining field in the District Gem Amethyst and consist of four color variations: white, black, yellow, and purple. These samples were analyzed by LIBS, using laser energy of 120 mJ, delay time detection of 2 μs and accumulation of 3, with and without cleaning. The purpose of this study is to determine emission spectra characteristics, contained elements, and physical characteristics of each amethyst sample. The spectra show that the amethyst samples contain some elements such as Al, Ca, K, Fe, Gd, Ba, Si, Be, H, O, N, Cl and Pu with various emission intensities. The value of emission intensity corresponds to concentration of element in the sample. Hence, the characteristics of the amethysts are based on their concentration value. The element with the highest concentration in all samples is Si, which is related to the chemical formula of SiO2. The element with the lowest concentration in all samples is Ca that is found in black and yellow amethysts. The emission intensity of Fe element can distinguish between white, purple, and yellow amethyst. If Fe emission intensity is very low, it indicates yellow sample. Thus, we may conclude that LIBS is a method that can be used to characterize the amethyst samples.Key words: amethyst, impurity, laser-induced, breakdown spectroscopy, characteristic, gemstones

Research progress on portable laser-induced breakdown spectroscopy

2020 ◽  
Vol 13 (6) ◽  
pp. 1-18
Author(s):  
ZENG Qing-dong ◽  
◽  
YUAN Meng-tian ◽  
ZHU Zhi-heng ◽  
CHEN Guang-hui ◽  
...  
Keyword(s):  
Research Progress ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown
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