Near-infrared and Mid-infrared Spectroscopic Techniques for a Fast and Nondestructive Quality Control of Thymi herba

Planta Medica ◽  
2017 ◽  
Vol 84 (06/07) ◽  
pp. 420-427 ◽  
Author(s):  
Cornelia Pezzei ◽  
Stefan Schönbichler ◽  
Shah Hussain ◽  
Christian Kirchler ◽  
Verena Huck-Pezzei ◽  
...  
Keyword(s):  
Antioxidant Capacity ◽  
Rosmarinic Acid ◽  
Near Infrared ◽  
Coefficient Of Determination ◽  
Attenuated Total Reflectance ◽  
Spectroscopic Techniques ◽  
Test Set ◽  
Mid Infrared ◽  
Capacity Coefficient ◽  
Infrared Spectroscopic

AbstractIn this study, novel near-infrared and attenuated total reflectance mid-infrared spectroscopic methods coupled with multivariate data analysis were established enabling the determination of thymol, rosmarinic acid, and the antioxidant capacity of Thymi herba. A new high-performance liquid chromatography method and UV-Vis spectroscopy were applied as reference methods. Partial least squares regressions were carried out as cross and test set validations. To reduce systematic errors, different data pretreatments, such as multiplicative scatter correction, 1st derivative, or 2nd derivative, were applied on the spectra. The performances of the two infrared spectroscopic techniques were evaluated and compared. In general, attenuated total reflectance mid-infrared spectroscopy demonstrated a slightly better predictive power (thymol: coefficient of determination = 0.93, factors = 3, ratio of performance to deviation = 3.94; rosmarinic acid: coefficient of determination = 0.91, factors = 3, ratio of performance to deviation = 3.35, antioxidant capacity: coefficient of determination = 0.87, factors = 2, ratio of performance to deviation = 2.80; test set validation) than near-infrared spectroscopy (thymol: coefficient of determination = 0.90, factors = 6, ratio of performance to deviation = 3.10; rosmarinic acid: coefficient of determination = 0.92, factors = 6, ratio of performance to deviation = 3.61, antioxidant capacity: coefficient of determination = 0.91, factors = 6, ratio of performance to deviation = 3.42; test set validation). The capability of infrared vibrational spectroscopy as a quick and simple analytical tool to replace conventional time and chemical consuming analyses for the quality control of T. herba could be demonstrated.

scholarly journals Comparison of the Potential Abilities of Three Spectroscopy Methods: Near-Infrared, Mid-Infrared, and Molecular Fluorescence, to Predict Carotenoid, Vitamin and Fatty Acid Contents in Cow Milk

Foods ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 592 ◽  
Author(s):  
Julien Soulat ◽  
Donato Andueza ◽  
Benoît Graulet ◽  
Christiane L. Girard ◽  
Cyril Labonne ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Nir Spectroscopy ◽  
Cow Milk ◽  
Coefficient Of Determination ◽  
Attenuated Total Reflectance ◽  
Mid Infrared ◽  
Molecular Fluorescence ◽  
Atr Spectroscopy ◽  
Β Carotene

The objective of this work is to compare the ability of three spectroscopy techniques: molecular fluorescence, near-infrared (NIR), and mid-infrared with attenuated total reflectance (MIR-ATR) spectroscopy to predict the concentrations of 8 carotenoids, 6 vitamins and 22 fatty acids (FA) in cow’s milk. A dataset was built through the analysis of 242 frozen milk samples from different experiments. The milk compounds were analysed using reference methods and by NIR, MIR-ATR, and fluorescence to establish different predictive models. NIR spectroscopy allowed for better prediction of cis9-β-carotene, β-cryptoxanthin and the sum of carotenoids than the other techniques, with a coefficient of cross-validation in calibration (R2CV) > 0.60 and a coefficient of determination in validation (R2V) > 0.50. Their standard errors of prediction (SEP) were equal to 0.01, except for the sum of carotenoids (SEP = 0.15). However, MIR-ATR and fluorescence seem usable for the prediction of lutein and all-trans-β-carotene, respectively. These three spectroscopy methods did not allow us to predict (R2CV < 0.30) vitamin contents except, for vitamin A (the best R²CV = 0.65 with NIR and SEP = 0.15) and α-tocopherol (the best R²CV = 0.56 with MIR-ATR and SEP = 0.41), but all R²V were <0.30. NIR spectroscopy yielded the best prediction of the selected milk FA.

Critical Evaluation of NIR and ATR-IR Spectroscopic Quantifications of Rosmarinic Acid in Rosmarini folium Supported by Quantum Chemical Calculations

Planta Medica ◽  
2017 ◽  
Vol 83 (12/13) ◽  
pp. 1076-1084 ◽  
Author(s):  
Christian Kirchler ◽  
Cornelia Pezzei ◽  
Krzysztof Beć ◽  
Raphael Henn ◽  
Mika Ishigaki ◽  
...  
Keyword(s):  
Standard Error ◽  
Rosmarinic Acid ◽  
Near Infrared ◽  
Cross Validation ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Test Set ◽  
Wavenumber Region

AbstractThe present study evaluates the analytical performance of near infrared as well as attenuated total reflection infrared spectroscopy for the determination of the rosmarinic acid content in Rosmarini folium. Therefore, the recorded near infrared and attenuated total reflection infrared spectra of 42 milled Rosmarini folium samples were correlated with reference data (range: 1.138–2.199 rosmarinic acid %) obtained by HPLC analysis. Partial least squares regression models were established as a quantitative multivariate data analysis tool. Evaluation via full cross-validation and test set validation resulted in comparable performances for both techniques: near infrared [coefficient of determination: 0.90 (test set validation); standard error of cross-validation: 0.060 rosmarinic acid %; standard error of prediction: 0.058 rosmarinic acid %] and attenuated total reflection infrared [coefficient of determination: 0.91 (test set validation); standard error of cross-validation: 0.063 rosmarinic acid %; standard error of prediction: 0.060 rosmarinic acid %]. Furthermore, quantum chemical calculations were applied to obtain a theoretical infrared spectrum of rosmarinic acid. Good agreement to the spectrum of pure rosmarinic acid was achieved in the lower wavenumber region, whereas the higher wavenumber region showed less compliance. The knowledge of the vibrational modes of rosmarinic acid was used for the association with the high values of the regression coefficient plots of the established partial least squares regression models.

scholarly journals Development of Attenuated Total Reflectance Mid-Infrared (ATR-MIR) and Near-Infrared (NIR) Spectroscopy for the Determination of Resistant Starch Content in Wheat Grains

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Rong Wang ◽  
Xia Wei ◽  
Hongpan Wang ◽  
Linshu Zhao ◽  
Cengli Zeng ◽  
...  
Keyword(s):  
Resistant Starch ◽  
Near Infrared ◽  
Coefficient Of Determination ◽  
Attenuated Total Reflectance ◽  
Calibration Model ◽  
Mid Infrared ◽  
Total Reflectance ◽  
Mir Spectroscopy ◽  
Calibration Models

The chemical method for the determination of the resistant starch (RS) content in grains is time-consuming and labor intensive. Near-infrared (NIR) and attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy are rapid and nondestructive analytical techniques for determining grain quality. This study was the first report to establish and compare these two spectroscopic techniques for determining the RS content in wheat grains. Calibration models with four preprocessing techniques based on the partial least squares (PLS) algorithm were built. In the NIR technique, the mean normalization + Savitzky–Golay smoothing (MN + SGS) preprocessing technique had a higher coefficient of determination ( R c 2  = 0.672; R p 2  = 0.552) and a relative lower root mean square error value (RMSEC = 0.385; RMSEP = 0.459). In the ATR-MIR technique, the baseline preprocessing method exhibited a better performance regarding to the values of coefficient of determination ( R c 2  = 0.927; R p 2  = 0.828) and mean square error value (RMSEC = 0.153; RMSEP = 0.284). The validation of the developed best NIR and ATR-MIR calibration models showed that the ATR-MIR best calibration model has a better RS prediction ability than the NIR best calibration model. Two high grain RS content wheat mutants were screened out by the ATR-MIR best calibration model from the wheat mutant library. There was no significant difference between the predicted values and chemical measured values in the two high RS content mutants. It proved that the ATR-MIR model can be a perfect substitute in RS measuring. All the results indicated that the ATR-MIR spectroscopy with improved screening efficiency can be used as a fast, rapid, and nondestructive method in high grain RS content wheat breeding.

Investigating the total antioxidant capacity of gluten-free grains with miniaturized near-infrared spectrometer

NIR news ◽  
2019 ◽  
Vol 30 (5-6) ◽  
pp. 35-38
Author(s):  
Verena Wiedemair ◽  
Christian Wolfgang Huck
Keyword(s):  
Antioxidant Capacity ◽  
Total Antioxidant Capacity ◽  
High Performance ◽  
Near Infrared ◽  
Least Squares Regression ◽  
Test Set ◽  
Total Antioxidant ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
Infrared Instruments

The use of ever smaller near-infrared instruments is becoming more and more prevalent, since they are cheaper, more versatile and often advertised as high-performance spectrometer. The last claim is rarely verified by independent researchers, which is why the presented work evaluates the performance of three hand-held spectrometers in comparison to a benchtop instrument. Seventy-seven samples comprising buckwheat, millet and oat were investigated for their total antioxidant capacity using Folin–Ciocalteu and near-infrared spectroscopy. Partial least squares regression models were established using cross- and test set validation. Results showed that all instruments were able to predict total antioxidant capacity to some extent. The coefficients of determinations ranged from 0.823 to 0.951 for cross-validated and from 0.849 to 0.952 for test set validated models. Errors for cross-validated models ranged from 1.11 to 2.08 mgGAE/g and for test set validated models from 1.02 to 1.86 mgGAE/g.

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 Comparison of Attenuated Total Reflectance Mid-Infrared, Near Infrared, and 1H-Nuclear Magnetic Resonance Spectroscopies for the Determination of Coffee’s Geographical Origin

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jessica Medina ◽  
Diana Caro Rodríguez ◽  
Victoria A. Arana ◽  
Andrés Bernal ◽  
Pierre Esseiva ◽  
...  
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Near Infrared ◽  
Geographical Origin ◽  
Fraud Detection ◽  
Attenuated Total Reflectance ◽  
Mid Infrared ◽  
Total Reflectance ◽  
H Nmr

The sensorial properties of Colombian coffee are renowned worldwide, which is reflected in its market value. This raises the threat of fraud by adulteration using coffee grains from other countries, thus creating a demand for robust and cost-effective methods for the determination of geographical origin of coffee samples. Spectroscopic techniques such as Nuclear Magnetic Resonance (NMR), near infrared (NIR), and mid-infrared (mIR) have arisen as strong candidates for the task. Although a body of work exists that reports on their individual performances, a faithful comparison has not been established yet. We evaluated the performance of 1H-NMR, Attenuated Total Reflectance mIR (ATR-mIR), and NIR applied to fraud detection in Colombian coffee. For each technique, we built classification models for discrimination by species (C. arabica versus C. canephora (or robusta)) and by origin (Colombia versus other C. arabica) using a common set of coffee samples. All techniques successfully discriminated samples by species, as expected. Regarding origin determination, ATR-mIR and 1H-NMR showed comparable capacity to discriminate Colombian coffee samples, while NIR fell short by comparison. In conclusion, ATR-mIR, a less common technique in the field of coffee adulteration and fraud detection, emerges as a strong candidate, faster and with lower cost compared to 1H-NMR and more discriminating compared to NIR.

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