Application of Optical Spectroscopic Techniques and Multivariate Statistical Analysis as a Method of Determining the Percentage and Type of Adulteration of Extra Virgin Olive Oil

2021 ◽  
Author(s):  
Giorgos Stavrakakis ◽  
Aggelos Philippidis ◽  
Michalis Velegrakis
Keyword(s):  
Statistical Analysis ◽  
Olive Oil ◽  
Multivariate Statistical Analysis ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Spectroscopic Techniques ◽  
Multivariate Statistical

EXPRESS: Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils

2020 ◽  
pp. 000370282097470
Author(s):  
Joshua M. Ottaway ◽  
J. Chance Carter ◽  
Kristl L Adams ◽  
Joseph Camancho ◽  
Barry Lavine ◽  
...  
Keyword(s):  
Olive Oil ◽  
Peroxide Value ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Spectroscopic Techniques ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Calibration Models

The peroxide value (PV) of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine PVs using field portable and process instrumentation; those efforts presented ‘best-case’ scenarios with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique, or combination thereof, is best for predicting PVs. Following PV assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression (PLSR) calibration models to predict the PV of unknown oil samples. A global PV model based on near-infrared (8 mm optical path length – OPL) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm OPL near infrared (5.1), Raman (6.9) and 50 μm OPL mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global PV models based on low-level fusion of the NIR (8 and 24 mm OPL) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes.

scholarly journals Near UV-Vis and NMR Spectroscopic Methods for Rapid Screening of Antioxidant Molecules in Extra-Virgin Olive Oil

Antioxidants ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1245
Author(s):  
Giulia Vicario ◽  
Alessandra Francini ◽  
Mario Cifelli ◽  
Valentina Domenici ◽  
Luca Sebastiani
Keyword(s):  
Olive Oil ◽  
Oil Quality ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Rapid Screening ◽  
Chemical Components ◽  
Total Phenolic ◽  
Spectroscopic Techniques ◽  
Olive Oils ◽  
13C Nuclear Magnetic Resonance

Several spectroscopic techniques have been optimized to check extra-virgin olive oil quality and authenticity, as well as to detect eventual adulterations. These methods are usually complementary and can give information about different olive oil chemical components with bioactive and antioxidant properties. In the present work, a well-characterized set of extra-virgin olive oil (cultivar Frantoio) samples from a specific area of Tuscany (Italy) were investigated by combining near UV-Vis absorption spectroscopy, 1H and 13C nuclear magnetic resonance (NMR) to identify and quantify different chemical components, such as pigments, secoiridoids and squalene, related to the nutritional and quality properties of olive oils. Moreover, the pigmentation index of olives, organoleptic and sensory properties, total phenolic compound contents and the lipidic fractions of olive oils were investigated. The results obtained are, finally, compared and discussed in order to correlate several properties of both olives and olive oils with specific features of the cultivation area.

Efficient Detection of Extra Virgin Olive Oil Adulteration via UV and FTIR Spectra in combination with Heat-Mediated Oxidation Method

2021 ◽  
Author(s):  
Sepideh Gholami Khesht ◽  
E Kavusi ◽  
M Mousavi
Keyword(s):  
Olive Oil ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Peak Position ◽  
Uv Spectra ◽  
Ftir Spectra ◽  
Spectroscopic Techniques ◽  
Chemical Waste ◽  
Bending Vibrations ◽  
Efficient Detection

The main aim of this study is simple and fast authentication of extra virgin olive oil by different spectroscopic techniques individually and also in combination with minimal chemical waste. UV spectra of the EVOO and mixed olive oil samples were recorded before the heating test and then along the thermal degradation experiments at the 45- and 90-mins intervals set for the analysis.  The EVOO and mixed oils samples showed high absorption values around 240-300 nm band. The results showed that the characteristics of FTIR spectra including peak number, peak position and peak shape in mixed samples were significantly different from EVOO samples. According to the studies, the frequencies of around 2920 cm−1 and 2856 cm−1 could be related with C–H stretching (e.g. cis-double bonds) and with –C–H asymmetrical and symmetrical stretching in methylene groups. The frequency at 2925 cm−1 is associated with aliphatic CH2 groups. Around 1366 cm−1 and 1451 cm−1, these frequencies could be associated with the bending vibrations of C–H groups. The results reveal that the UV–VIS and FT-IR analytical tools are the most suitable and reliable tools to detect and quantify high levels (over 10%) of adulteration in mixes of EVO with other vegetable oils.

scholarly journals Lymph node pathology using optical spectroscopy in cancer diagnostics

2008 ◽  
Vol 22 (2-3) ◽  
pp. 97-104 ◽  
Author(s):  
M. Isabelle ◽  
N. Stone ◽  
H. Barr ◽  
M. Vipond ◽  
N. Shepherd ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Statistical Analysis ◽  
Lymph Nodes ◽  
Optical Spectroscopy ◽  
Multivariate Statistical Analysis ◽  
Diagnostic Methods ◽  
Spectroscopic Techniques ◽  
Multivariate Statistical ◽  
Analysis Tools ◽  
Raman And Infrared Spectroscopy

Raman and infrared spectroscopy are optical spectroscopic techniques that use light scattering (Raman) and light absorption (infrared) to probe the vibrational energy levels of molecules in tissue samples. Using these techniques, one can gain an insight into the biochemical composition of cells and tissues by looking at the spectra produced and comparing them with spectra obtained from standards such as proteins, nucleic acids, lipids and carbohydrates. As a result of optical spectroscopy being able to measure these biochemical changes, diagnosis of cancer could take place faster than current diagnostic methods, assisting and offering pathologists and cytologists a novel technology in cancer screening and diagnosis.The purpose of this study is to use both spectroscopic techniques, in combination with multivariate statistical analysis tools, to analyze some of the major biochemical and morphological changes taking place during carcinogenesis and metastasis in lymph nodes and to develop a predictive model to correctly differentiate cancerous from benign lymph nodes taken from oesophageal cancer patients.The results of this study showed that Raman and infrared spectroscopy managed to correctly differentiate between cancerous and benign oesophageal lymph nodes with a training performance greater than 94% using principal component analysis (PCA)-fed linear discriminant analysis (LDA). Cancerous nodes had higher nucleic acid but lower lipid and carbohydrate content compared to benign nodes which is indicative of increased cell proliferation and loss of differentiation.With better understanding of the molecular mechanisms of carcinogenesis and metastasis together with use of multivariate statistical analysis tools, these spectroscopic studies will provide a platform for future development of real-time (in surgery) non-invasive diagnostic tools in medical research.

scholarly journals Development of Rapid Extra Virgin Olive Oil Quality Assessment Procedures Based on Spectroscopic Techniques

Agronomy ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 41 ◽  
Author(s):  
Paola Baltazar ◽  
Natalia Hernández-Sánchez ◽  
Belén Diezma ◽  
Lourdes Lleó
Keyword(s):  
Olive Oil ◽  
Oil Quality ◽  
Virgin Olive Oil ◽  
Fluorescence Emission ◽  
Emission Spectra ◽  
Extra Virgin Olive Oil ◽  
Spectroscopic Techniques ◽  
Least Squares Regression ◽  
Fluorescence Emission Spectra ◽  
Physico Chemical

The main objective of this study was to evaluate the feasibility of developing multivariate models to estimate physico-chemical characteristics and antioxidant content of extra virgin olive oil from fluorescence spectra obtained at specific excitation wavelengths. Six replicates of each extra virgin olive oil sample were contained in clear glass bottles. Two replicates were subjected to four weeks of natural indirect light; two bottles for two days; and the third couple were kept it in darkness as a control. For each pair, one bottle was used for spectroscopic measurements and the other was sent to an accredited external laboratory to obtain physico-chemical measurements: acidity, peroxide index, K270, K232, total tocopherols, α-tocopherol, β-tocopherol and γ-tocopherol. Fluorescence emission spectra were acquired at different excitation wavelengths: 326 nm, 350 nm and 365 nm and partial least squares regression (PLSR) models were developed. The highest R2 values were found for excitation at 350 nm, reaching almost 0.9 in most of the parameters.

scholarly journals Use of multivariate statistical methods for classification of olive oil

2021 ◽  
Vol 6 (1) ◽  
pp. 035-043
Author(s):  
Moacyr Cunha Filho ◽  
Renisson Neponuceno Araujo Filho ◽  
Ana Luiza Xavier Cunha ◽  
Victor Casimiro Piscoya ◽  
Guilherme Rocha Moreira ◽  
...  
Keyword(s):  
Olive Oil ◽  
Statistical Methods ◽  
Virgin Olive Oil ◽  
Principal Component ◽  
Extra Virgin Olive Oil ◽  
Fuzzy Cluster ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Fuzzy Clustering Method ◽  
Silhouette Index

Multivariate statistical methods can contribute significantly to classification studies of extra virgin and common olive oil groups. Therefore, nuclear magnetic resonance (NMR) was used to discriminate olive oil samples, multivariate statistical techniques Principal Component Analysis - PCA, Fuzzy Cluster, Silhouette Validation Method to describe and classify. The groups' distinction into organic and common was observed by applying the non-hierarchical Fuzzy grouping with a distinction between the two groups with a 65% confidence interval. The validation was performed by the silhouette index that presented S (i) of 0.73, which showed that the adopted grouping presented adequate strength and distinction criterion. However, PCA only analyzed the behaviors of data from extra virgin olive oil. Thus, the Fuzzy clustering method was the most suitable for classifying extra virgin olive oil.

Quality control of herbal medicines by using spectroscopic techniques and multivariate statistical analysis

2009 ◽  
Vol 48 (2) ◽  
pp. 134-141 ◽  
Author(s):  
Sunil Kumar Singh ◽  
Sunil Kumar Jha ◽  
Anand Chaudhary ◽  
R. D. S. Yadava ◽  
S. B. Rai
Keyword(s):  
Quality Control ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Herbal Medicines ◽  
Spectroscopic Techniques ◽  
Multivariate Statistical
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