Application of Near-Infrared Spectroscopy for the Detection of Metanil Yellow in Turmeric Powder

Kar, Satyajit; Tudu, Bipan; Bag, Anil Kumar; Bandyopadhyay, Rajib

doi:10.1007/s12161-017-1106-9

Cited by 57 publications

(17 citation statements)

References 37 publications

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“…With an increased demand for traditional medicines, many herbal ingredients are traded in bulk as highly-processed dried powders, lacking morphological characteristics of the original root material ( 4 ). In the absence of the unprocessed root material to confirm identity, incidences of adulteration of turmeric medicinal products with commercial dyes to enhance the yellow color is known to occur ( 5 – 7 ). In order to detect adulteration of products and to ensure product quality and safety, fit-for-purpose analytical methods are required to monitor active ingredients in herbal ingredients and finished products.…”

mentioning

confidence: 99%

Determination of Curcuminoids in Turmeric Dietary Supplements by HPLC-DAD: Multi-laboratory Study Through the NIH-ODS/NIST Quality Assurance Program

Mudge

Brown

Rimmer

et al. 2020

Journal of AOAC INTERNATIONAL

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Background Turmeric is a medicinal herb containing curcuminoids, used as quality markers in dietary supplements. In 2016, an AOAC first action official method was adopted for quantitation of curcuminoids and requires multi-laboratory reproducibility data for final action status. Objective Collect reproducibility data for the quantitation of curcuminoids in dietary supplements through the NIH/ODS NIST Quality Assurance Program (QAP). Methods Laboratories that participated in the QAP by following OMA 2016.16 submitted data for ten turmeric products. The data were analyzed for mean, repeatability and reproducibility standard deviations (SDr/R), repeatability (RSDr) and reproducibility (RSDR). Results Initial data collection resulted in an insufficient replicates (five) for each test sample to determine reproducibility, therefore laboratories were provided additional materials resulting in an incremental data approach. For homogenous products, reproducibility for curcumin ranged from 3.4% to 10.3%. Bis-demethoxycurcumin with reproducibility ranging from 6.4% to 14.8% and Demethoxycurcumin ranging from 5.6% to 9.9%. The method was unsuitable for the quantitation of curcuminoids in complex smoothie products, products containing microbeads or tinctures based on interlaboratory variances. Recommendations were provided for future multi-laboratory studies performed through QAPs and incremental approaches. Conclusions OMA 2016.16 is suitable for the quantitation of curcuminoids and should be adopted for final action status for single and multi-ingredient dietary supplements containing dried roots, dried powders/extracts in bulk material, capsules and softgels. Highlights Reproducibility for OMA 2016.16 was collected through a non-traditional incremental data multi-laboratory study. The method is suitable for quantitation of curcuminoids in most common dietary supplements.

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mentioning

confidence: 99%

Determination of Curcuminoids in Turmeric Dietary Supplements by HPLC-DAD: Multi-laboratory Study Through the NIH-ODS/NIST Quality Assurance Program

Mudge

Brown

Rimmer

et al. 2020

Journal of AOAC INTERNATIONAL

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“…However, the authors mention that the LOD is not found in the legislation limits. On the other hand, samples of turmeric were adulterated with metanil yellow (1% to 25%) to try to quantify the level of adulteration using NIR spectroscopy (Kar, Tudu, Bag, & Bandyopadhyay, ). The authors observed that absorption intensities corresponding to metanil yellow are present in the region between 1000 and 1200 nm (second overtone region of N–H bonds) and 1350 to 1550 nm (first overtone region of N–H bonds).…”

Section: Nontargeted Analytical Methodsmentioning

confidence: 99%

“…Then, unknown samples (a test set) can be predicted. PLS regression, PCR, and HLA were the most commonly used supervised calibration methods for spice's authentication (Haughey et al., ; Hu et al., ; Kar et al., ; Lohumi et al., ; Wu et al., ).…”

Section: Chemometrics For Spice Authenticationmentioning

confidence: 99%

“…Works that study the application of portable spectroscopic devices for the authentication of spices are few. An NIR portable spectrometer NIR portable was used for the detection of metanil yellow in turmeric powder (Kar et al., ). A good PLSR model was built using spectral data ( R 2 = 0.96 to 0.99; RMSEP = 0.44 to 0.91) to predict metanil yellow concentration in turmeric powder.…”

Section: Portable/handheld Spectrometers For Spice's Authenticationmentioning

confidence: 99%

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Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

Oliveira

Cruz-Tirado

Barbin

2019

Comp Rev Food Sci Food Safe

108

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Food fraud in herbs and spices is an important topic, which has led to new technologies being studied as potential tools for fraud identification. Nontargeted technologies have proven to be a useful tool for the authentication of herbs and spices. The present review focuses on the use of near‐infrared, hyperspectral imaging, Fourier‐transform infrared, Raman, nuclear magnetic resonance, and electron spin resonance spectroscopy for the authentication of spices, which includes the determination of origin and irradiated spices and the identification of adulterants. The methods developed based on vibrational spectroscopy combined with chemometric techniques seem to be promising tools for determining the presence of adulterants and contaminants in herbs and spices. On the other hand, nuclear magnetic resonance seems to be the most efficient technology to determine the origin of herbs and spices although, for some cases, studies with near‐infrared spectroscopy can be a viable substitute. Electron spin resonance spectroscopy is the technique par excellence used for the authentication of irradiated herbs and spices, so its use should be expanded to many more spices’ varieties. Portable devices are preferred by those involved in the food industry, due to its manageability and low cost. Data fusion and big data are shown as promising tools for spice fraud control. In conclusion, spectroscopic techniques show a great efficiency to authenticate spices, although their evaluation must be expanded to other spice varieties, to new strategies of data analysis (as data fusion and big data), and to the use of portable devices.

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“…where K ¼ 3 for detection and K ¼ 10 for quantification. 36,37 Finally, the linearity of the predicted values from the two NIR spectrometers was tested using a Passing and Bablok regression 38,39 at a ¼ 0.05, with the null hypotheses that the slope of the predicted MY by the handheld to the predicted MY by the benchtop NIR (i.e., d MY h vs. d MY b ) be close to unity and the intercept close to zero.…”

Section: Pls Regression Of Nir Data From Benchtop and Handheld Nir Spmentioning

confidence: 99%

Use of a handheld near infrared spectrometer and partial least squares regression to quantify metanil yellow adulteration in turmeric powder

Rukundo

Danao

Weller

et al. 2020

Journal of Near Infrared Spectroscopy

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The efficacy of using a handheld near infrared spectrometer to predict metanil yellow (MY) adulteration levels (0-30% w/w) in dried turmeric powder was tested against a benchtop near infrared spectrometer using partial least squares regression models. The differences between near infrared instruments were resolution (i.e., 1 nm (handheld) vs. 0.5 nm (benchtop)) and sample container during scanning (plastic pouch (handheld) vs. quartz glass cup (benchtop)). Prediction performance of the calibration models developed was evaluated using number of model factors ([Formula: see text]), coefficients of determination of calibration and validation ([Formula: see text] and[Formula: see text], respectively), root-mean-square errors of calibration, cross-validation, and validation (RMSEC, RMSECV, and RMSEP), ratio of prediction error to standard deviation (RPD), and limits of detection (LOD) and quantification (LOQ). The best benchtop calibration models were based on spectral data preprocessed with Savitzky–Golay first derivative algorithm for the benchtop near infrared and standard normal variate for the handheld near infrared, yielding low[Formula: see text], high [Formula: see text] and[Formula: see text], low RMSEC, RMSECV, RMSEP, and high RPD. The LOD and LOQ for both spectrometers were 0.33 and 1.10%, respectively, and no significant difference was found between the predicted [Formula: see text] values by the benchtop and handheld near infrared spectrometers. The models were, in general, not sensitive to sample source and size of the validation set. When spectra from the benchtop near infrared were standardized using a reverse standardization strategy, calibrated against[Formula: see text], and transferred to the handheld near infrared, prediction performance dropped, from [Formula: see text] of 0.99 to 0.98, RMSEP increased from 0.96% to 1.53%, and [Formula: see text] decreased from 10.1 to 6.3. Despite the reduced prediction performance, the handheld near infrared with a transferred calibration model from the benchtop near infrared was still useful for screening, quality control, and process control applications.

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Application of Near-Infrared Spectroscopy for the Detection of Metanil Yellow in Turmeric Powder

Cited by 57 publications

References 37 publications

Determination of Curcuminoids in Turmeric Dietary Supplements by HPLC-DAD: Multi-laboratory Study Through the NIH-ODS/NIST Quality Assurance Program

Determination of Curcuminoids in Turmeric Dietary Supplements by HPLC-DAD: Multi-laboratory Study Through the NIH-ODS/NIST Quality Assurance Program

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

Use of a handheld near infrared spectrometer and partial least squares regression to quantify metanil yellow adulteration in turmeric powder

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