scholarly journals Non-Invasive Monitoring of Ethanol and Methanol Levels in Grape-Derived Pisco Distillate by Vibrational Spectroscopy

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6278
Author(s):  
Ahmed Menevseoglu ◽  
Didem P. Aykas ◽  
Beatriz Hatta-Sakoda ◽  
Victor Hugo Toledo-Herrera ◽  
Luis E. Rodriguez-Saona
Keyword(s):  
Prediction Models ◽  
Least Squares Regression ◽  
Non Invasive ◽  
Calibration Models ◽  
Excitation Laser ◽  
Ft Ir ◽  
Online Stores ◽  
Non Destructive ◽  
Ft Ir Spectroscopy

Handheld Raman and portable FT-IR spectroscopy devices were evaluated for fast and non-invasive determination of methanol and ethanol levels in Peruvian Pisco. Commercial Peruvian Pisco (n = 171) samples were kindly provided by the UNALM Alliance for Research in Alcohol and its Derivatives (Lima, Peru) and supplemented by purchases at grocery and online stores. Pisco spectra were collected on handheld Raman spectrometers equipped with either a 1064 nm or a 785 nm excitation laser and a portable infrared unit operating in transmission mode. The alcohol levels were determined by GC–MS. Calibration models used partial least-squares regression (PLSR) to develop prediction algorithms. GC–MS data revealed that 10% of Pisco samples had ethanol levels lower than 38%, indicating possible water dilution. Methanol levels ranged from 10 to 130 mg/100 mL, well below the maximum levels allowed for fruit brandies. Handheld Raman equipped with a 1064 nm excitation laser gave the best results for determining ethanol (SEP = 1.2%; RPre = 0.95) and methanol (SEP = 1.8 mg/100 mL; RPre = 0.93). Randomly selected Pisco samples were spiked with methanol (75 to 2800 mg/100 mL), and their Raman spectra were collected through their genuine commercial bottles. The prediction models gave an excellent performance (SEP = 98 mg/100 mL; RPre = 0.97), allowing for the non-destructive and non-contact determination of methanol and ethanol concentrations without opening the bottles.

scholarly journals High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3723 ◽  
Author(s):  
Hacer Akpolat ◽  
Mark Barineau ◽  
Keith A. Jackson ◽  
Mehmet Z. Akpolat ◽  
David M. Francis ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
High Performance ◽  
Prediction Models ◽  
Least Squares Regression ◽  
Family Farms ◽  
Non Invasive ◽  
Uv Visible ◽  
The Ohio State University ◽  
Non Destructive ◽  
Β Carotene

Our objective was to develop a rapid technique for the non-invasive profiling and quantification of major tomato carotenoids using handheld Raman spectroscopy combined with pattern recognition techniques. A total of 106 samples with varying carotenoid profiles were provided by the Ohio State University Tomato Breeding and Genetics program and Lipman Family Farms (Naples, FL, USA). Non-destructive measurement from the surface of tomatoes was performed by a handheld Raman spectrometer equipped with a 1064 nm excitation laser, and data analysis was performed using soft independent modelling of class analogy (SIMCA)), artificial neural network (ANN), and partial least squares regression (PLSR) for classification and quantification purposes. High-performance liquid chromatography (HPLC) and UV/visible spectrophotometry were used for profiling and quantification of major carotenoids. Seven groups were identified based on their carotenoid profile, and supervised classification by SIMCA and ANN clustered samples with 93% and 100% accuracy based on a validation test data, respectively. All-trans-lycopene and β-carotene levels were measured with a UV-visible spectrophotometer, and prediction models were developed using PLSR and ANN. Regression models developed with Raman spectra provided excellent prediction performance by ANN (rpre = 0.9, SEP = 1.1 mg/100 g) and PLSR (rpre = 0.87, SEP = 2.4 mg/100 g) for non-invasive determination of all-trans-lycopene in fruits. Although the number of samples were limited for β-carotene quantification, PLSR modeling showed promising results (rcv = 0.99, SECV = 0.28 mg/100 g). Non-destructive evaluation of tomato carotenoids can be useful for tomato breeders as a simple and rapid tool for developing new varieties with novel profiles and for separating orange varieties with distinct carotenoids (high in β-carotene and high in cis-lycopene).

Non-Invasive Analysis of Green Stone Pieces from Tomb 1 of Chiapa de Corzo, Chiapas

2014 ◽  
Vol 1618 ◽  
pp. 17-29 ◽  
Author(s):  
M. D. Manrique-Ortega ◽  
P. Claes ◽  
E. Casanova-González ◽  
J. L. Ruvalcaba-Sil ◽  
Ma. A. García-Bucio ◽  
...  
Keyword(s):  
Analytical Techniques ◽  
Classic Period ◽  
X Ray ◽  
Non Invasive ◽  
Integrated Methodology ◽  
Ft Ir ◽  
Trading Networks ◽  
Different Cultures ◽  
Non Destructive ◽  
Ft Ir Spectroscopy

ABSTRACTRecently, a team of archaeologists discovered the existence of the oldest burial in a pyramid known to date in Mesoamerica. The tomb, referred to as Tomb 1, was discovered in Chiapa de Corzo, Chiapas, Mexico. In here, two skeletons were excavated along with a rich offering of green stone pieces, indicating their elite origin. The burial dresses consist of various necklaces, bracelets, belts, and anklets from which some beads were carved in the shape of gourds, monkeys, and alligators. Here we present a full, integrated methodology based on a variety of non-invasive and non-destructive analytical techniques, such as X-ray fluorescence (XRF), Raman, and Fourier Transform infrared (FT-IR) spectroscopy. These techniques are used to characterize and identify the minerals which were found in these burials. This information contributes not only to conservation and restoration purposes, but also gives more insights on the green stone (jadeite and other minerals) trading networks between different cultures in south Mesoamerica in the Pre-Classic period (c.a. 750 – 700 B. C.).

scholarly journals Application of Fourier Transform Infrared Spectroscopy and Multivariate Analysis Methods for the Non-Destructive Evaluation of Phenolics Compounds in Moringa Powder

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 10
Author(s):  
Rahul Joshi ◽  
Ramaraj Sathasivam ◽  
Sang Un Park ◽  
Hongseok Lee ◽  
Moon S. Kim ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Phenolic Compounds ◽  
Ir Spectroscopy ◽  
High Performance ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Least Squares Regression ◽  
Ft Ir ◽  
Non Destructive ◽  
Ft Ir Spectroscopy

This study performed non-destructive measurements of phenolic compounds in moringa powder using Fourier Transform Infrared (FT-IR) spectroscopy within a spectral range of 3500–700 cm−1. Three major phenolic compounds, namely, kaempferol, benzoic acid, and rutin, were measured in five different varieties of moringa powder, which was approved with respect to the high-performance liquid chromatography (HPLC) method. The prediction performance of three different regression methods, i.e., partial least squares regression (PLSR), principal component regression (PCR), and net analyte signal (NAS)-based methodology, called hybrid linear analysis (HLA/GO), were compared to achieve the best prediction model. The obtained results for the PLS regression method resulted in better performance for the prediction analysis of phenolic compounds in moringa powder. The PLSR model attained a correlation coefficient () value of 0.997 and root mean square error of prediction (RMSEP) of 0.035 mg/g, respectively, which is comparatively higher than the other two regression models. Based on the results, it can be concluded that FT-IR spectroscopy in conjugation with a suitable regression analysis method could be an effective analytical tool for the non-destructive prediction of phenolic compounds in moringa powder.

Non-Invasive Blood Glucose Monitoring by Means of near Infrared Spectroscopy: Methods for Improving the Reliability of the Calibration Models

1997 ◽  
Vol 20 (5) ◽  
pp. 285-290 ◽  
Author(s):  
U.A. Müller ◽  
B. Mertes ◽  
C. Fischbacher ◽  
K.U. Jageman ◽  
K. Danzer
Keyword(s):  
Blood Glucose ◽  
Near Infrared ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Least Squares Regression ◽  
Non Invasive ◽  
Infrared Reflection ◽  
Calibration Models ◽  
Infrared Reflection Spectroscopy

The feasibility of using near infrared reflection spectroscopy for non-invasive blood glucose monitoring is discussed. Spectra were obtained using a diode-array spectrometer with a fiberoptic measuring head with a wavelength ranging from 800 nm to 1350 nm. Calibration was performed using partial least-squares regression and radial basis function networks. The results of different methods used to evaluate the quality of the recorded spectra in order to improve the reliability of the calibration models, are presented.

Applications of Diffuse Reflectance FT-IR to Pigment Photodecomposition in Paint

1982 ◽  
Vol 36 (2) ◽  
pp. 155-157 ◽  
Author(s):  
D. B. Chase ◽  
R. L. Amey ◽  
W. G. Holtje
Keyword(s):  
Ir Spectroscopy ◽  
Infrared Spectra ◽  
Diffuse Reflectance ◽  
Spectral Subtraction ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Diffuse reflectance FT-IR spectroscopy is used to obtain infrared spectra of paints directly on paper panels. The binder contribution to the spectrum can be effectively eliminated by spectral subtraction and the spectra of photodecomposition products are obtained. Comparison with reference spectra allows the determination of the photodecomposition mechanism.

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