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.

scholarly journals Sensitivity and Calibration of the FT-IR Spectroscopy on Concentration of Heavy Metal Ions in River and Borehole Water Sources

2020 ◽  
Vol 10 (21) ◽  
pp. 7785
Author(s):  
Matthew Mamera ◽  
Johan J. van Tol ◽  
Makhosazana P. Aghoghovwia ◽  
Elmarie Kotze
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Ir Spectroscopy ◽  
Water Sources ◽  
Partial Least Square ◽  
Least Square ◽  
Borehole Water ◽  
Ft Ir ◽  
Ir Calibration ◽  
Ft Ir Spectroscopy

Heavy metals in water sources can threaten human life and the environment. The analysis time, need for chemical reagents, and sample amount per analysis assist in monitoring contaminants. Application of the Fourier Transform Infrared (FT-IR) Spectroscopy for the investigation of heavy metal elements has significantly developed due to its cost effectiveness and accuracy. Use of chemometric models such as Partial Least Square (PLS) and Principle Component Regression Analysis (PCA) relate the multiple spectral intensities from numerous calibration samples to the recognized analytes. This study focused on the FT-IR calibration and quantification of heavy metals (Ag, Cd, Cu, Pb and Zn) in surveyed water sources. FT-IR measurements were compared with the atomic absorption spectrometer (AAS) measurements. Quantitative analysis methods, PCA and PLS, were used in the FT-IR calibration. The spectral analyses were done using the Attenuated Total Reflectance (ATR-FTIR) technique on three river and four borehole water sources sampled within two seasons in QwaQwa, South Africa (SA). The PLS models had good R2 values ranging from 0.95 to 1 and the PCA models ranged from 0.98 to 0.99. Significant differences were seen at 0.001 and 0.05 levels between the PLS and PCA models for detecting Cd and Pb in the water samples. The PCA models detected Ag concentrations more (˂0 mg L−1 on selected sites). Both the PLS and PCA models had lower detection only for Zn ions mostly above 45 mg L−1 deviating from the AAS measurements (<0.020 mg L−1). The FT-IR spectroscopy demonstrated good potential for heavy metal determination purposes.

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

scholarly journals Authentication of Patin Fish Oil (Pangasius micronemus) using FTIR Spectroscopy Combined with Chemometrics

2020 ◽  
pp. 23
Author(s):  
Anggita Rosiana Putri ◽  
Abdul Rohman ◽  
Sugeng Riyanto ◽  
Widiastuti Setyaningsih
Keyword(s):  
Root Mean Square Error ◽  
Fish Oil ◽  
Ftir Spectroscopy ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square

Authentication of Patin fish oil (MIP) is essential to prevent adulteration practice, to ensure quality, nutritional value, and product safety. The purpose of this study is to apply the FTIR spectroscopy combined with chemometrics for MIP authentication. The chemometrics method consists of principal component regression (PCR) and partial least square regression (PLSR). PCR and PLSR were used for multivariate calibration, while for grouping the samples using discriminant analysis (DA) method. In this study, corn oil (MJ) was used as an adulterate. Twenty-one mixed samples of MIP and MJ were prepared with the adulterate concentration range of 0-50%. The best authentication model was obtained using the PLSR technique using the first derivative of FTIR spectra at a wavelength of 650-3432 cm-1. The coefficient of determination (R2) for calibration and validation was obtained 0.9995 and 1.0000, respectively. The value of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.397 and 0.189. This study found that the DA method can group the samples with an accuracy of 99.92%.

scholarly journals Prediction of Soil Organic Carbon for Ethiopian Highlands Using Soil Spectroscopy

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Tadele Amare ◽  
Christian Hergarten ◽  
Hans Hurni ◽  
Bettina Wolfgramm ◽  
Birru Yitaferu ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Diffuse Reflectance ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Calibration Models ◽  
The Stability

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used. The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9), Maybar (84. 0.57, 2.5), Megech (85, 0.15, 2.6), and Wondo Genet (86, 0.52, 2.7) indicating that the models were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

scholarly journals CRYSTAL ENGINEERING OF QUERCETIN BY LIQUID ASSISTED GRINDING METHOD

2018 ◽  
Vol 81 (1) ◽  
Author(s):  
Umi Athiyah ◽  
Putu Andika Kusuma ◽  
Tutik Tutik ◽  
Maria L. A. D. Lestari ◽  
Dewi Isadiartuti ◽  
...  
Keyword(s):  
Ir Spectroscopy ◽  
Succinic Acid ◽  
Crystal Engineering ◽  
Crystal Habit ◽  
Dissolution Profile ◽  
X Ray ◽  
Pure Compounds ◽  
Ft Ir ◽  
The Impact ◽  
Ft Ir Spectroscopy

Quercetin has been proposed to exhibit numerous pharmacological benefits yet suffer low bioavailability due to the extremely low solubility. A research to study the impact of cocrystallization of quercetin with succinic acid on the solubility and dissolution profile has been performed. Cocrystallization in molar stoichiometry of 1:1 was carried out via liquid assisted grinding with methanol in ball milling apparatus. Cocrystal formation was identified by hot stage microscopy (HSM) at first, then cocrystal phase was characterized using differential thermal analysis (DTA), powder X-ray diffractometry (PXRD), scanning electron microscopy (SEM), and fourier-transform infrared (FT-IR) spectroscopy. Solubility and dissolution test were conducted as well. DSC thermogram exhibits new endothermic peak at 280.32°C representing the melting point of cocrystal phase alongside with endothermic point of pure compounds. Powder X-ray diffractograms show new diffraction peaks on behalf of cocrystal formation at 2θ=8.92, 9.88, 13.04, 29.78, 35.35°. FT-IR spectroscopy reveals band shifting in –OH group region. On SEM photographs, one can observe crystal habit of succinic acid being covered by crystal with different habit. This indicates that quercetin interacts with succinic acid only on the surfaces and causes imperfect formation of cocrystal phase. Cocrystallization quercetin improves solubility by 1.62 times higher and dissolution rate by 1.25 higher than pure quercetin (one-way ANOVA, p < 0.05).

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 The Use of Fourier Transform Infrared Spectroscopy for Quantification of Adulteration in Virgin Walnut Oil

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Pengjuan Liang ◽  
Hao Wang ◽  
Chaoyin Chen ◽  
Feng Ge ◽  
Diqiu Liu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Seed Oil ◽  
Fourier Transform Infrared ◽  
Partial Least Square ◽  
Least Square ◽  
Attenuated Total Reflectance ◽  
Walnut Oil ◽  
Tea Seed Oil ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Currently, the authentication of virgin walnut oil (VWO) has become very important due to the possible adulteration of VWO with cheaper plant oils such as soybean oil (SO), puer tea seed oil (PO), and sunflower oil (SFO). Methods involving Fourier transform infrared (FT-IR) spectroscopy combined with chemometric techniques (partial least square) were developed for quantification of SO, PO, and SFO in VWO. IR spectra of oil samples were recorded at frequency regions of 4000–650 cm−1on horizontal attenuated total reflectance (HATR) attachment of FT-IR. PLS model correlates the actual and FT-IR estimated values of oil adulterants (SO, PO, and SFO) with coefficients of determination (R2) of 0.9958, 0.9925, and 0.9952, respectively. The obtained RMSEC values of SO, PO, and SFO in VWO are 1.35%, 1.85%, and 1.43% (v/v), respectively. The method, therefore, has potential as a rapid method for quantification of product adulteration.

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