scholarly journals RAPID AUTHENTICATION OF TURMERIC POWDER ADULTERATED WITH CURCUMA ZEDOARIA AND CURCUMA XANTHORRHIZA USING FTIR-ATR SPECTROSCOPY AND CHEMOMETRICS

2019 ◽  
pp. 216-221
Author(s):  
ELLSYA ANGELINE ◽  
RATNA ASMAH SUSIDARTI ◽  
ABDUL ROHMAN
Keyword(s):  
Curcuma Longa ◽  
External Validation ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Calibration Model ◽  
Curcuma Zedoaria ◽  
Curcuma Xanthorrhiza ◽  
Atr Spectroscopy

Objective: The objective of this study is to develop a rapid, simple, non-destructive and inexpensive analytical method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) as a sampling technique, combined with chemometrics for authentication of turmeric powder adulterated with Curcuma zedoaria and Curcuma xanthorrhiza. Methods: Turmeric powder is placed above the diamond crystal in ATR compartment. Spectra are scanned in the absorbance mode from 4000 to 600 cm-1. The obtained spectra is further analyzed by Principal Component Analysis (PCA), Partial Least Square Discriminant Analysis (PLS-DA), and Partial Least Square Regression (PLS-R). Results: PCA score plot shows that Curcuma longa, Curcuma zedoaria, and Curcuma xanthorrhiza can be discriminated well. PLS-DA can be used to build the model for classification between pure turmeric powder and adulterated powder with the values of Q2, R2X, and R2Y of 0.9558, 0.9813, and 0.9746, respectively. The good calibration model for quantification of each adulterant is obtained by PLS-R with R2 value more than 0.99 and lower RMSEC value. Both models have been validated by internal and external validation which result in the high R2 value and low RMSEP value which indicates that both models are accurate and precise. Conclusion: The combination of FTIR-ATR spectroscopy and chemometrics can be used to authenticate turmeric powder adulterated with Curcuma zedoaria and Curcuma xanthorrhiza.

Model Optimization and Stability of Hemoglobin Analysis in Human Soluble Blood Samples by FTIR/ATR Spectroscopy

2011 ◽  
Vol 55-57 ◽  
pp. 1168-1171
Author(s):  
Tao Pan ◽  
Ai Hong Peng ◽  
Wen Jie Huang
Keyword(s):  
Signal To Noise Ratio ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Model Optimization ◽  
Optimal Model ◽  
Blood Samples ◽  
Quantification Method ◽  
Atr Spectroscopy ◽  
Pls Method

Using Fourier transform infrared spectroscopy (FTIR), attenuated total reflection (ATR) technology and partial least square (PLS) method, the rapid quantification method of hemoglobin (HGB) in human soluble blood samples was established. Based on the distribution of samples’ HGB chemical value and absorbance on 1543 cm-1 which had the highest signal to noise ratio for HGB, all samples were divided into calibration set and prediction set for 50 times. PLS models were established for all divisions, based on the average data RMSEPAve, the stable optimal model was selected, the corresponding PLS factor, RMSEPAve and RP,Ave were 2, 6.81 g/L and 0.943 respectively.

Field Nitrogen Dioxide and Ozone Monitoring Using Electrochemical Sensors with Partial Least Squares Regression

2021 ◽  
Vol 5 (1) ◽  
pp. 61
Author(s):  
Rachid Laref ◽  
Etienne Losson ◽  
Alexandre Sava ◽  
Maryam Siadat
Keyword(s):  
Nitrogen Dioxide ◽  
Electrochemical Sensors ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Calibration Model ◽  
Least Squares Regression ◽  
Monitoring Networks ◽  
Concentration Estimation ◽  
The Impact

Low-cost gas sensors detect pollutants gas at the parts-per-billion level and may be installed in small devices to densify air quality monitoring networks for the spread analysis of pollutants around an emissive source. However, these sensors suffer from several issues such as the impact of environmental factors and cross-interfering gases. For instance, the ozone (O3) electrochemical sensor senses nitrogen dioxide (NO2) and O3 simultaneously without discrimination. Alphasense proposes the use of a pair of sensors; the first one, NO2-B43F, is equipped with a filter dedicated to measure NO2. The second one, OX-B431, is sensitive to both NO2 and O3. Thus, O3 concentration can be obtained by subtracting the concentration of NO2 from the sum of the two concentrations. This technique is not practical and requires calibrating each sensor individually, leading to biased concentration estimation. In this paper, we propose Partial Least Square regression (PLS) to build a calibration model including both sensors’ responses and also temperature and humidity variations. The results obtained from data collected in the field for two months show that PLS regression provides better gas concentration estimation in terms of accuracy than calibrating each sensor individually.

Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics

2021 ◽  
pp. 4413-4419
Author(s):  
Dharmastuti Cahya Fatmarahmi ◽  
Ratna Asmah Susidarti ◽  
Respati Tri Swasono ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Herbal Medicine ◽  
Ftir Spectroscopy ◽  
Herbal Medicines ◽  
Principal Component ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Precision Data

The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.

scholarly journals Spectrophotometric determination of phenol in the presence of congeners by multivariated calibration

2001 ◽  
Vol 73 (4) ◽  
pp. 519-524 ◽  
Author(s):  
KELY VIVIANE DE SOUZA ◽  
PATRICIO PERALTA-ZAMORA
Keyword(s):  
Spectrophotometric Determination ◽  
Multivariate Calibration ◽  
Close Correlation ◽  
Degradation Process ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Calibration Model ◽  
Transient Species

The generation of poly-hydroxilated transient species during the photochemical treatment of phenol usually impedes the spectrophotmetric monitoring of its degradation process. Frequently, the appearance of compounds such as pyrocatechol, hydroquinone and benzoquinone produces serious spectral interference, which hinder the use of the classical univariate calibration process. In this work, the use of multivariate calibration is proposed to permit the spectrophotometric determination of phenol in the presence of these intermediates. Using 20 synthetic mixtures containing phenol and the interferents, a calibration model was developed by using a partial least square regression process (PLSR) and processing the absorbance signal between 180 and 300 nm. The model was validated by using 3 synthetic mixtures. In this operation, typical errors lower than 3% were observed. Close correlation between the results obtained by liquid chromatography and the proposed method was also observed.

scholarly journals Detection of Additives and Chemical Contaminants in Turmeric Powder Using FT-IR Spectroscopy

Foods ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 143 ◽  
Author(s):  
Sagar Dhakal ◽  
Walter F. Schmidt ◽  
Moon Kim ◽  
Xiuying Tang ◽  
Yankun Peng ◽  
...  
Keyword(s):  
Ir Spectroscopy ◽  
Curcuma Longa ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Pure Compounds ◽  
Ft Ir ◽  
Mixed Samples ◽  
Ft Ir Spectroscopy

Yellow turmeric (Curcuma longa) is widely used for culinary and medicinal purposes, and as a dietary supplement. Due to the commercial popularity of C. longa, economic adulteration and contamination with botanical additives and chemical substances has increased. This study used FT-IR spectroscopy for identifying and estimating white turmeric (Curcuma zedoaria), and Sudan Red G dye mixed with yellow turmeric powder. Fifty replicates of yellow turmeric—Sudan Red mixed samples (1%, 5%, 10%, 15%, 20%, 25% Sudan Red, w/w) and fifty replicates of yellow turmeric—white turmeric mixed samples (10%, 20%, 30%, 40%, 50% white turmeric, w/w) were prepared. The IR spectra of the pure compounds and mixtures were analyzed. The 748 cm−1 Sudan Red peak and the 1078 cm−1 white turmeric peak were used as spectral fingerprints. A partial least square regression (PLSR) model was developed for each mixture type to estimate adulteration concentrations. The coefficient of determination (R2v) for the Sudan Red mixture model was 0.97 with a root mean square error of prediction (RMSEP) equal to 1.3%. R2v and RMSEP for the white turmeric model were 0.95 and 3.0%, respectively. Our results indicate that the method developed in this study can be used to identify and quantify yellow turmeric powder adulteration.

Time-dependent ammonia emissions from fumed oak wood determined by micro-chamber/thermal extractor (μCTE) and FTIR-ATR spectroscopy

Holzforschung ◽  
2019 ◽  
Vol 73 (2) ◽  
pp. 165-170
Author(s):  
Elfriede Hogger ◽  
Klaus Bauer ◽  
Eva Höllbacher ◽  
Notburga Gierlinger ◽  
Johannes Konnerth ◽  
...  
Keyword(s):  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Gaseous Ammonia ◽  
Ammonia Content ◽  
Oak Wood ◽  
Customer Complaints ◽  
Reflectance Ftir ◽  
Atr Spectroscopy

AbstractThe ongoing preference for dark colours in parquet and furniture is a driving force for colour modification of bright wood species. The treatment of oak wood with gaseous ammonia (fuming) leads to dark colours, but residual ammonia in the wood may lead to bonding failures with resins, odour nuisance and thus customer complaints. The focus of the present paper is the determination and emission of remaining ammonia in fumed oak. A fast and convenient approach based on Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectroscopy was developed to replace the currently applied time-consuming and complex determination procedures. The integrated area of the infrared (IR) region between 1575 and 1535 cm−1shows a relationship with the coefficient of determination (R2=0.76) to the residual ammonia content determined by the micro-chamber/thermal extractor (μCTE) method. The prediction accuracy was further improved by partial least square regression calculations. Promising models with high R2(0.85), low root mean square error of cross-validation (RMSE-CV=1.08%) with five principal components were established and already integrated successfully into the production as input control. FTIR-ATR spectroscopy proved to be a simple and fast predictive method to estimate residual ammonia in fumed oak.

scholarly journals Predicting ambient aerosol thermal–optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites

2016 ◽  
Vol 9 (2) ◽  
pp. 441-454 ◽  
Author(s):  
Matteo Reggente ◽  
Ann M. Dillner ◽  
Satoshi Takahama
Keyword(s):  
Mahalanobis Distance ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Optical Methods ◽  
Calibration Model ◽  
Optical Reflectance ◽  
Wide Range ◽  
Ft Ir ◽  
Absorbance Spectra

Abstract. Organic carbon (OC) and elemental carbon (EC) are major components of atmospheric particulate matter (PM), which has been associated with increased morbidity and mortality, climate change, and reduced visibility. Typically OC and EC concentrations are measured using thermal–optical methods such as thermal–optical reflectance (TOR) from samples collected on quartz filters. In this work, we estimate TOR OC and EC using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE Teflon) filters using partial least square regression (PLSR) calibrated to TOR OC and EC measurements for a wide range of samples. The proposed method can be integrated with analysis of routinely collected PTFE filter samples that, in addition to OC and EC concentrations, can concurrently provide information regarding the functional group composition of the organic aerosol. We have used the FT-IR absorbance spectra and TOR OC and EC concentrations collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA). We used 526 samples collected in 2011 at seven sites to calibrate the models, and more than 2000 samples collected in 2013 at 17 sites to test the models. Samples from six sites are present both in the calibration and test sets. The calibrations produce accurate predictions both for samples collected at the same six sites present in the calibration set (R2 = 0.97 and R2 = 0.95 for OC and EC respectively), and for samples from 9 of the 11 sites not included in the calibration set (R2 = 0.96 and R2 = 0.91 for OC and EC respectively). Samples collected at the other two sites require a different calibration model to achieve accurate predictions. We also propose a method to anticipate the prediction error; we calculate the squared Mahalanobis distance in the feature space (scores determined by PLSR) between new spectra and spectra in the calibration set. The squared Mahalanobis distance provides a crude method for assessing the magnitude of mean error when applying a calibration model to a new set of samples.

scholarly journals Non-Destructive Quality Assessment of Tomato Paste by Using Portable Mid-Infrared Spectroscopy and Multivariate Analysis

Foods ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1300
Author(s):  
Didem Peren Aykas ◽  
Karla Rodrigues Borba ◽  
Luis E. Rodriguez-Saona
Keyword(s):  
External Validation ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Soluble Solids ◽  
Quality Traits ◽  
Sampling System ◽  
Mid Infrared ◽  
Tomato Paste ◽  
Ft Ir

This research aims to provide simultaneous predictions of tomato paste’s multiple quality traits without any sample preparation by using a field-deployable portable infrared spectrometer. A total of 1843 tomato paste samples were supplied by four different leading tomato processors in California, USA, over the tomato seasons of 2015, 2016, 2017, and 2019. The reference levels of quality traits including, natural tomato soluble solids (NTSS), pH, Bostwick consistency, titratable acidity (TA), serum viscosity, lycopene, glucose, fructose, ascorbic acid, and citric acid were determined by official methods. A portable FT-IR spectrometer with a triple-reflection diamond ATR sampling system was used to directly collect mid-infrared spectra. The calibration and external validation models were developed by using partial least square regression (PLSR). The evaluation of models was conducted on a randomly selected external validation set. A high correlation (RCV = 0.85–0.99) between the reference values and FT-IR predicted values was observed from PLSR models. The standard errors of prediction were low (SEP = 0.04–35.11), and good predictive performances (RPD = 1.8–7.3) were achieved. Proposed FT-IR technology can be ideal for routine in-plant assessment of the tomato paste quality that would provide the tomato processors with accurate results in shorter time and lower cost.

scholarly journals Multivariate method for prediction of fumonisins B1 and B2 and zearalenone in Brazilian maize using Near Infrared Spectroscopy (NIR)

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244957
Author(s):  
Denize Tyska ◽  
Adriano Olnei Mallmann ◽  
Juliano Kobs Vidal ◽  
Carlos Alberto Araújo de Almeida ◽  
Luciane Tourem Gressler ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
External Validation ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Contamination Level ◽  
Internal Validation ◽  
Significant Difference

Fumonisins (FBs) and zearalenone (ZEN) are mycotoxins which occur naturally in grains and cereals, especially maize, causing negative effects on animals and humans. Along with the need for constant monitoring, there is a growing demand for rapid, non-destructive methods. Among these, Near Infrared Spectroscopy (NIR) has made great headway for being an easy-to-use technology. NIR was applied in the present research to quantify the contamination level of total FBs, i.e., fumonisin B1+fumonisin B2 (FB1+FB2), and ZEN in Brazilian maize. From a total of six hundred and seventy-six samples, 236 were analyzed for FBs and 440 for ZEN. Three regression models were defined: one with 18 principal components (PCs) for FB1, one with 10 PCs for FB2, and one with 7 PCs for ZEN. Partial least square regression algorithm with full cross-validation was applied as internal validation. External validation was performed with 200 unknown samples (100 for FBs and 100 for ZEN). Correlation coefficient (R), determination coefficient (R2), root mean square error of prediction (RMSEP), standard error of prediction (SEP) and residual prediction deviation (RPD) for FBs and ZEN were, respectively: 0.809 and 0.991; 0.899 and 0.984; 659 and 69.4; 682 and 69.8; and 3.33 and 2.71. No significant difference was observed between predicted values using NIR and reference values obtained by Liquid Chromatography Coupled to Tandem Mass Spectrometry (LC-MS/MS), thus indicating the suitability of NIR to rapidly analyze a large numbers of maize samples for FBs and ZEN contamination. The external validation confirmed a fair potential of the model in predicting FB1+FB2 and ZEN concentration. This is the first study providing scientific knowledge on the determination of FBs and ZEN in Brazilian maize samples using NIR, which is confirmed as a reliable alternative methodology for the analysis of such toxins.

scholarly journals A Rapid Method to Measure Serum Retinol Concentrations in Japanese Black Cattle Using Multidimensional Fluorescence

2020 ◽  
Author(s):  
Yoshio Tamura ◽  
Hiroki Inoue ◽  
Satoshi Takemoto ◽  
Kazuo Hirano ◽  
Kazutoshi Miyaura
Keyword(s):  
Mean Squared Error ◽  
Fluorescence Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Retinol Binding Protein ◽  
Calibration Model ◽  
Serum Retinol ◽  
Japanese Black Cattle ◽  
Multidimensional Fluorescence

Abstract Vitamin A levels in fattening Japanese Black cattle affect meat quality; therefore, it is important to monitor serum retinol concentrations. To simplify and accelerate the evaluation of serum retinol concentrations in cattle, we developed a new predictive method using excitation-emission matrix (EEM) fluorescence spectrophotometry. For analytical comparison, the concentration of serum retinol was also measured using the conventional HPLC method. We examined excitation (Ex) and emission (Em) wavelengths of cattle serum, which were 250–450 and 250–600 nm, respectively. Parallel factor analysis separated four components from EEM data, one of which was related to retinol. Next, a partial least square regression model was created using the obtained EEMs as explanatory variables and accrual measurement values as objective variables. The determination coefficient value (R2), root mean squared error of prediction (RMSEP), and the ratio of performance to deviation (RPD) of the model were determined. A comparison with reference values found that R2, RMSEP, and RPD of the calibration model were 0.95, 6.4 IU/dl, and 4.2, respectively. This implies that EEM can estimate the serum retinol concentration with high accuracy. Additionally, the fluorescent peaks that contributed to the calibration, which were extracted from the regression coefficient and variable importance in projection plots, were Ex/Em = 320/390 and 330/520 nm. Thus, we assume that this method observes not only free retinol, but also retinol-binding protein. In conclusion, multidimensional fluorescence analysis can accurately and quickly determine serum retinol concentrations in fattening cattle.

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