scholarly journals Measurement Strategies for the Classification of Edible Oils Using Low-Cost Miniaturised Portable NIR Instruments

Foods ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2856
Author(s):  
Barbara Giussani ◽  
Alix Tatiana Escalante-Quiceno ◽  
Ricard Boqué ◽  
Jordi Riu
Keyword(s):  
Cost Analysis ◽  
Near Infrared ◽  
Edible Oils ◽  
Low Cost ◽  
Olive Oils ◽  
Different Types ◽  
Measurement Strategies

Miniaturised near-infrared (NIR) instruments have been increasingly used in the last few years, and they have become useful tools for many applications on different types of samples. The market already offers a wide variety of these instruments, each one having specific requirements for the correct acquisition of the instrumental signal. This paper presents the development and optimisation of different measuring strategies for two miniaturised NIR instruments in order to find the best measuring conditions for the rapid and low-cost analysis of olive oils. The developed strategies have been applied to the classification of different samples of olive oils, obtaining good results in all cases.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

scholarly journals Fast, Low-Cost and Non-Destructive Physico-Chemical Analysis of Virgin Olive Oils Using Near-Infrared Reflectance Spectroscopy

Sensors ◽  
2017 ◽  
Vol 17 (11) ◽  
pp. 2642 ◽  
Author(s):  
Ana Garrido-Varo ◽  
María-Teresa Sánchez ◽  
María-José De la Haba ◽  
Irina Torres ◽  
Dolores Pérez-Marín
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Virgin Olive Oils ◽  
Olive Oils ◽  
Physico Chemical ◽  
Non Destructive

scholarly journals Detecting Food Fraud in Extra Virgin Olive Oil Using a Prototype Portable Hyphenated Photonics Sensor

2020 ◽  
Author(s):  
Yannick Weesepoel ◽  
Martin Alewijn ◽  
Michiel Wijtten ◽  
Judith Müller-Maatsch
Keyword(s):  
Data Fusion ◽  
Olive Oil ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Food Fraud ◽  
Olive Oils ◽  
Level Data ◽  
High Level

Abstract Background Current developments in portable photonic devices for fast authentication of extra virgin olive oil (EVOO) or EVOO with non-EVOO additions steer towards hyphenation of different optic technologies. The multiple spectra or so-called “fingerprints” of samples are then analyzed with multivariate statistics. For EVOO authentication, one-class classification (OCC) to identify “out-of-class” EVOO samples in combination with data-fusion is applicable. Objective Prospecting the application of a prototype photonic device (“PhasmaFood”) which hyphenates visible, fluorescence, and near-infrared spectroscopy in combination with OCC modelling to classify EVOOs and discriminate them from other edible oils and adulterated EVOOs. Method EVOOs were adulterated by mixing in 10–50% (v/v) of refined and virgin olive oils, olive-pomace olive oils, and other common edible oils. Samples were analyzed by the hyphenated sensor. OCC, data-fusion, and decision thresholds were applied and optimized for two different scenarios. Results: By high-level data-fusion of the classification results from the three spectral databases and several multivariate model vectors, a 100% correct classification of all pure edible oils using OCC in the first scenario was found. Reducing samples being falsely classified as EVOOs in a second scenario, 97% of EVOOs adulterated with non-EVOO olive oils were correctly identified and ones with other edible oils correctly classified at score of 91%. Conclusions Photonic sensor hyphenation in combination with high-level data fusion, OCC, and tuned decision thresholds delivers significantly better screening results for EVOO compared to individual sensor results. Highlights Hyphenated photonics and its data handling solutions applied to extra virgin olive oil authenticity testing was found to be promising.

FT-NIR the method of choice to verify the authenticity of extra virgin olive oils

NIR news ◽  
2017 ◽  
Vol 28 (4) ◽  
pp. 6-9 ◽  
Author(s):  
John KG Kramer ◽  
Hormoz Azizian
Keyword(s):  
Fourier Transform ◽  
Olive Oil ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Volatile Fraction ◽  
Olive Oils ◽  
Calibration Models ◽  
A Minor

Fourier transform near infrared spectroscopy was recently demonstrated to be an excellent method to evaluate the authenticity and adulteration of extra virgin olive oil. Since this method is matrix dependent, it takes a chemical fingerprint of all the components which sets it apart from the targeted methods. Careful examinations of the Fourier transform near infrared spectra lead to the identification of a minor carbonyl overtone absorption at 5269 cm−1 associated with the volatile fraction in extra virgin olive oil that appears to be a reliable indicator of authenticity. The same spectra were used to identify the fatty acids present in the oil using models based on comparison to accurate GC data. Gravimetric mixtures of extra virgin olive oil with refined edible oils were then prepared to develop PLS1 calibration models to identify possible adulterants and by how much. The great varietal difference in olive oils made it necessary to develop four unique sets of PLS1 calibration models for each extra virgin olive oil variety. As a result, an extra virgin olive oil acceptance specification was established.

scholarly journals Verifying the Geographical Origin and Authenticity of Greek Olive Oils by Means of Optical Spectroscopy and Multivariate Analysis

Molecules ◽  
2020 ◽  
Vol 25 (18) ◽  
pp. 4180
Author(s):  
Renate Kontzedaki ◽  
Emmanouil Orfanakis ◽  
Georgia Sofra-Karanti ◽  
Katerina Stamataki ◽  
Aggelos Philippidis ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Optical Spectroscopy ◽  
Near Infrared ◽  
Geographical Origin ◽  
Multivariate Statistical ◽  
Olive Oils ◽  
Machine Learning Methods ◽  
Geographical Regions

Olive oil samples from three different Greek regions (Crete, Peloponnese and Lesvos) were examined by optical spectroscopy in a wide spectral region from ultraviolet to near infrared using absorption, fluorescence and Raman spectroscopies. With the aid of machine learning methods, such as multivariate partial least squares discriminant analysis, a clear classification of samples originating from the different Greek geographical regions was revealed. Moreover, samples produced in different subareas of Crete and Peloponnese were also well discriminated. Furthermore, mixtures of olive oils from different geographical origins were studied employing partial least squares as a tool to establish a model between the actual and predicted compositions of the mixtures. The results demonstrated that optical spectroscopy combined with multivariate statistical analysis can be used as an emerging innovative alternative to the classical analytical methods for the identification of the origin and authenticity of olive oils.

Rapid screening of commercial extra virgin olive oil products for authenticity: Performance of a handheld NIR device

NIR news ◽  
2017 ◽  
Vol 28 (1) ◽  
pp. 9-14 ◽  
Author(s):  
Sanjeewa R Karunathilaka ◽  
Ali R Fardin-Kia ◽  
Cynthia Srigley ◽  
Jin K Chung ◽  
Magdi M Mossoba
Keyword(s):  
Olive Oil ◽  
Near Infrared ◽  
Edible Oils ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Oil Products ◽  
Rapid Screening ◽  
Conformity Index ◽  
Virgin Olive Oils ◽  
Olive Oils

The performance of a handheld near infrared spectroscopic device was evaluated for the rapid screening of extra virgin olive oil for authenticity. Without any sample preparation, the spectra of authentic reference extra virgin olive oils, refined olive oils, potential adulterants consisting of edible oils, extra virgin olive oil spiked with adulterants, and a total of 93 commercial olive oil products were each rapidly (10 s) measured in the transflection mode. The univariate conformity index and the multivariate supervised soft independent modeling of class analogy classification tools were used to differentiate among the various oils investigated. Out of 88 commercial products labeled extra virgin olive oil, 39 (44%) were classified as belonging to the class of authentic extra virgin olive oils. The results were compared to those recently reported for analyses carried out with a benchtop Fourier transform-near infrared spectrometer.

Use of near infrared spectroscopy for the rapid low-cost analysis of waste papers and cardboards

2017 ◽  
Vol 202 ◽  
pp. 465-482 ◽  
Author(s):  
D. J. M. Hayes ◽  
M. H. B. Hayes ◽  
J. J. Leahy
Keyword(s):  
Particle Size ◽  
Cost Analysis ◽  
Near Infrared ◽  
Low Cost ◽  
Analytical Data ◽  
Nir Spectroscopy ◽  
Klason Lignin ◽  
Total Sugars ◽  
Size Fractions ◽  
Particle Size Fractions

Analytical data and quantitative near infrared (NIR) spectroscopy models for various lignocellulosic components (including Klason lignin and the constituent sugars glucose, xylose, mannose, arabinose, galactose, and rhamnose), ash, and ethanol-soluble extractives were obtained for 53 samples of paper and cardboard. These samples were mostly the type of materials typically found in domestic wastes (e.g. newspapers, printing paper, glossy papers, food packaging). A number of the samples (48) were obtained by separating a sample, after milling, into two particle size fractions. It was found that the fractions containing the smaller particles typically had higher ash and Klason lignin contents and lower glucose and xylose contents than the larger particle size fractions. Nevertheless, all of the sample types had attractive total sugars contents (>50%), indicating that these could be suitable feedstocks for the production of biofuels and chemicals in hydrolysis-based biorefining technologies. NIR models of a high predictive accuracy (R2 of >0.9 for the independent validation set) were obtained for total sugars, glucose, xylose, Klason lignin, and ash, with values for the Root Mean Square Error of Prediction (RMSEP) of 2.36%, 2.64%, 0.56%, 1.98%, and 4.87%, respectively. Good NIR models (R2 of >0.8) were also obtained for mannose, arabinose, and galactose. These results suggest that NIR spectroscopy is a suitable method for the rapid, low-cost, analysis of the major lignocellulosic components of waste paper/cardboard samples.

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