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Quality assessment of the saffron samples using second-order spectrophotometric data assisted by three-way chemometric methods via quantitative analysis of synthetic colorants in adulterated saffron
Abstract
Saffron is a valuable culinary spice that can be used not only for dyes and cooking, but also for many medical purposes. Due to its high price and restriction of its production, various fraud manners in its production have been growing. Addition of synthetic colorants to saffron is the most common way for adulteration. In this work, chemometric methods are proposed to resolve the three-dimensional absorbance spectra–pH data for simultaneous determination of the two colorants Tartrazin and Sunset yellow, in adulterated saffron. The rank deficiency in the concentration mode impaired the system. Therefore, to extirpate the ambiguity, which results from rank deficiency, three-way variation array V was generated by subtracting the first pH spectrum from each spectrum at each pH. This allows the extraction of extent reaction profile and mixture reaction spectral profiles, as well as the relative concentrations of the analytes.
... Due to its high market price, saffron is the most adulterated spice in history, which is most frequently carried out by adding adulterants such as pulverized stigmas [114,115] since diverse plants with similar color and morphology to saffron function as adulterants when mixed [86]. Saffron adulteration can be classified into five common practices, as follows: (1) Adulteration using material from other plants such as calendula, arnica, gardenia, beet, pomegranate, turmeric, achiote, and safflower [93,106,115,116] or with other plant parts of C. sativus besides the stigmas; (2) Increasing saffron mass by moistening with honey, corn silk, sugar, fat, inorganic compounds, vegetable oils, or glycerin [18,116]; (3) Using natural or artificial food-grade colorants such as tartrazine, ponceau-4R, quinoline, methyl orange, sunset yellow, Sudan II, and Allura red [117,118]; and other less-used adulteration methods including (4) The addition of exogenous components mixed with food flavorings (erythrosine) and extracted spent saffron (recolored or old), and (5) Geographic origin tagging fraud [31,93,119,120]. ...
This review aims to evaluate the state of saffron’s main bioactive compounds and their relationship with its commercial quality. Saffron is the commercial name for the dried red stigmas of the Crocus sativus L. flower. It owes its sensory and functional properties mainly to the presence of its carotenoid derivatives, synthesized throughout flowering and also during the whole production process. These compounds include crocin, crocetin, picrocrocin, and safranal, which are bioactive metabolites. Saffron’s commercial value is determined according to the ISO/TS3632 standard that determines their main apocatotenoids. Other techniques such as chromatography (gas and liquid) are used to detect the apocarotenoids. This, together with the determination of spectral fingerprinting or chemo typing are essential for saffron identification. The determination of the specific chemical markers coupled with chemometric methods favors the discrimination of adulterated samples, possible plants, or adulterating compounds and even the concentrations at which these are obtained. Chemical characterization and concentration of various compounds could be affected by saffron’s geographical origin and harvest/postharvest characteristics. The large number of chemical compounds found in the by-products (flower parts) of saffron (catechin, quercetin, delphinidin, etc.) make it an interesting aromatic spice as a colorant, antioxidant, and source of phytochemicals, which can also bring additional economic value to the most expensive aromatic species in the world.
... Masoum et. al. [10] performed a data-quality assessment of different saffron samples, employing data by second-order spectrophotometric-type, applying methods based on three-way chemometry. Fernández et al. [11] presented an estimation performed online of the electric arc furnace tap temperature. ...
Sometimes it is difficult, or even impossible, to acquire real data from sensors and machines that must be used in research. Such examples are the modern industrial platforms that frequently are reticent to share data. In such situations, the only option is to work with synthetic data obtained by simulation. Regarding simulated data, a limitation could consist in the fact that the data are not appropriate for research, based on poor quality or limited quantity. In such cases, the design of algorithms that are tested on that data does not give credible results. For avoiding such situations, we consider that mathematically grounded data-quality assessments should be designed according to the specific type of problem that must be solved. In this paper, we approach a multivariate type of prediction whose results finally can be used for binary classification. We propose the use of a mathematically grounded data-quality assessment, which includes, among other things, the analysis of predictive power of independent variables used for prediction. We present the assumptions that should be passed by the synthetic data. Different threshold values are established by a human assessor. In the case of research data, if all the assumptions pass, then we can consider that the data are appropriate for research and can be applied by even using other methods for solving the same type of problem. The applied method finally delivers a classification table on which can be applied any indicators of performed classification quality, such as sensitivity, specificity, accuracy, F1 score, area under curve (AUC), receiver operating characteristics (ROC), true skill statistics (TSS) and Kappa coefficient. These indicators’ values offer the possibility of comparison of the results obtained by applying the considered method with results of any other method applied for solving the same type of problem. For evaluation and validation purposes, we performed an experimental case study on a novel synthetic dataset provided by the well-known UCI data repository.
Aromatic amino acids play an extremely important role in life activities and participate in many biological processes. Their concentration levels are associated with a variety of diseases, such as phenylketonuria and colorectal cancer. Therefore, the quantification of aromatic amino acids is an important task. In the present work, a novel and rapid three-way analytical method was proposed to detect the levels of aromatic amino acids in prostate cancer cells (PC3 cells) and Dulbecco's modified minimal essential medium (DMEM cell culture), by using the affordable ultraviolet-visible spectrophotometer. First, spectrum-pH second-order data were designed per sample; Second, properties of the resulted spectrum-pH-sample three-way data were investigated by utilizing the parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), and constrained alternating trilinear decomposition (CATLD) algorithms, and a flexible scanning approach for determining the constraint parameters of CATLD was proposed; Third, a three-way calibration method based on the CATLD algorithm with the proposed scanning approach was developed for interference-free quantification of aromatic amino acids in these systems. The average relative predictive errors of validation (ARPEV) for phenylalanine, tyrosine, and tryptophan were 1.4%, 3.0%, and 0.7% in prostate cancer cells, and ARPEV for phenylalanine, tyrosine, and tryptophan were 4.1%, 1.2%, and 0.7% in DMEM cell culture. The predicted contents of tyrosine and tryptophan in DMEM cell culture were 64.2 ± 2.9 μg mL-1, 5.6 ± 0.3 μg mL-1, there are no significant differences in the concentrations between the developed analytical method and high performance liquid chromatography method. The proposed spectrum-pH-sample three-way calibration method based on CATLD algorithm can provide an interesting analytical strategy with high selectivity and accuracy for ultraviolet-visible spectrophotometer.
Saffron (Crocus Sativus L.) is a valuable spice with a distinct aroma, flavour, taste and color that is constantly subjected to various adulterations due to its high economic worth, limited worldwide production and increasing global demand. Adulterants in saffron not only degrade the product's quality, but also have a destructive effect on both health and consumer trust. Physical methods, chemical and biochemical techniques (including chromatographic, spectroscopic, immunology, and electrophoresis-based methods), molecular techniques or DNA-based methods, and sensor-based techniques are some examples of saffron adulteration detection techniques discussed briefly in this study. Because none of these techniques are effective on their own in detecting adulteration, a mix of techniques for rapid detection is recommended. Nanosensor-based techniques outperform other approaches owing to their quick detection, low cost, and lack of sample preparation processes. As a result, it is proposed that researchers focus more on the development of nano-based approaches in future studies.
Background
Saffron (Crocus Sativus L.) is an ancient spice, having a long history of therapeutic and medicinal uses, in different countries around the world. Saffron has high market value with ever increasing demand but, its producing areas are limited due to requirement of specific agro-climatic conditions for growth of Saffron. Therefore, fraudulent practices are frequently employed by the traders, to meet up the market demands, as well as fetching higher economic benefits. In contemporary scenario of global trading, it is imperative to authenticate the quality of Saffron that can be done by modern instruments and techniques, available for determination of adulterants.
Scope and approach
In this review, a brief overview of different adulterants including plant based and chemical based origin is provided, along with detailed discussion on varied number of techniques including chromatographic techniques, spectroscopic techniques, sensor based techniques and molecular techniques, employed for determination of adulteration in Saffron in various countries.
Key findings and conclusions
Adulteration by extraneous materials, not only lowers down the quality of Saffron but it may also lead to severe health complications in public. Different techniques have certain advantages with some limitations regarding detection limit and their suitability for detection of specific type of adulterants (natural or synthetic). In this review, various techniques already in use or having futuristic potential for detection of different types of adulterants in Saffron are discussed, that can pave the way of future research efforts.
This review discusses the recent advances in both theories and analytical applications of multi-way calibrations based on various high-order analytical data. In the theory part, we focus on some aspects of multi-way calibration, such as multilinear models and their extensions, multi-way calibration algorithms with second-order or higher-order advantages, and other fundamental issues. According to different types of high-order instrument signals, recent applications of second-, third-, and fourth-order calibrations are then discussed, and their contributions to green analytical chemistry are highlighted.
Saffron, the most expensive spice in the world and so-called red gold, is composed of various bioactive compounds. The primary compounds are crocins, picrocrocin, and safranal, which contribute to its color, flavor, and aroma, respectively. Saffron is traded under various categories defined in national or international standards. Preharvest, and more importantly, postharvest processing and storage conditions have a significant influence on the bioactive content of saffron. Extraction methods proposed for the separation of these compounds are described briefly, along with common and more advanced analytical techniques for the determination of the different classes of the secondary metabolites. Trends and applications of saffron extracts or of individual metabolites in the food, pharmaceutical, and cosmetic industries are also discussed in this chapter with focus on the 21st century achievements.
This paper is conducted to identify the authenticity, quality, and origin of saffron using hyperspectral imaging and multivariate spectral analysis. Reflectance spectra were extracted from hyperspectral images of saffron. Successive projections algorithm, genetic algorithm, uninformative variable elimination, and competitive adaptive reweighted sampling were used to select characteristic wavelengths. Back propagation neural network model was established based on the selected wavelengths. Results showed that the model combining competitive adaptive reweighted sampling with back propagation neural network achieved the best performance. Its prediction accuracy of the one-adulterated, three-domestic and two-imported saffron was 100, 95, 94, 100, 83, and 96%, respectively.
This work reports the validation of an analytical UV spectrophotometric method to assay dexamethasone in tablets (assay and dissolution studies). The method was linear in the range between 1 and 30 µg mL-1 presenting a good correlation coefficient (r = 0.9998, n = 7). Precision and accuracy analysis showed low relative standard deviation (< 2.00%) and good percentual recoveries (95-105%). The procedure was linear, accurate, precise, and robust. The method is simple, and it has low cost. It does not use polluting reagents and can be applied in dissolution studies, being an adequate alternative to assay dexamethasone in tablets.
This paper reviews the literature on recent research on the chemical composition and pharmacological activities of saffron (Crocus sativus) and its active constituents, mainly as antitumoral, hypolipidemic and tissue oxygenation enhancement agents.
A liquid chromatographic tandem mass spectrometric validated method was developed for the detection of chemicals attributing
color, flavor, taste and medicinal properties to saffron (Crocus sativus L. stigma). Ultrasonic extractions of saffron stigmas were followed by LC procedure with Pinnacle II Cyano (5μm 150×2.1mm)
column and acetonitrile: water (70:30, v/v) as mobile phase. Deprotonated ions formed by a turbo ion spray in negative MS mode were used to detect the analytes. MS–MS
detection was by monitoring precursors (m/z) fragmentations; of 149→113 (safranal), 327→283 (crocetin), 329→167 (picrocrocin), 355→327 (dimethyl crocetin), 489→327
(crocin E), 535→489 (carotenes), 651→327 (crocin C), 813→652 (crocin B), 975→651 (crocin A) and 1,137→813 (crocin
F). The method was validated for linearity, precision, repeatability and specificity.
This paper explains the multi-way decomposition method PARAFAC and its use in chemometrics. PARAFAC is a generalization of PCA to higher order arrays, but some of the characteristics of the method are quite different from the ordinary two-way case. There is no rotation problem in PARAFAC, and e.g., pure spectra can be recovered from multi-way spectral data. One cannot as in PCA estimate components successively as this will give a model with poorer fit, than if the simultaneous solution is estimated. Finally scaling and centering is not as straightforward in the multi-way case as in the two-way case. An important advantage of using multi-way methods instead of unfolding methods is that the estimated models are very simple in a mathematical sense, and therefore more robust and easier to interpret. All these aspects plus more are explained in this tutorial and an implementation in Matlab code is available, that contains most of the features explained in the text. Three examples show how PARAFAC can be used for specific problems. The applications include subjects as: Analysis of variance by PARAFAC, a five-way application of PARAFAC, PARAFAC with half the elements missing, PARAFAC constrained to positive solutions and PARAFAC for regression as in principal component regression.
This communication describes a free toolbox for MATLAB® for analysis of multiway data. The toolbox is called “The N-way Toolbox for MATLAB” and is available on the internet at http://www.models.kvl.dk/source/. This communication is by no means an attempt to summarize or review the extensive work done in multiway data analysis but is intended solely for informing the reader of the existence, functionality, and applicability of the N-way Toolbox for MATLAB.
WHAT IS KNOWN: Herbal medicines have been used in the treatment of behavioural and psychological symptoms of dementia but with variable response. Crocus sativus (saffron) may inhibit the aggregation and deposition of amyloid β in the human brain and may therefore be useful in Alzheimer's disease (AD).
The goal of this study was to assess the efficacy of saffron in the treatment of mild to moderate AD.
Forty-six patients with probable AD were screened for a 16-week, double-blind study of parallel groups of patients with mild to moderate AD. The psychometric measures, which included AD assessment scale-cognitive subscale (ADAS-cog), and clinical dementia rating scale-sums of boxes, were performed to monitor the global cognitive and clinical profiles of the patients. Patients were randomly assigned to receive capsule saffron 30 mg/day (15 mg twice per day) (Group A) or capsule placebo (two capsules per day) for a 16-week study.
After 16 weeks, saffron produced a significantly better outcome on cognitive function than placebo (ADAS-cog: F=4·12, d.f.=1, P=0·04; CDR: F=4·12, d.f.=1, P=0·04). There were no significant differences in the two groups in terms of observed adverse events.
This double-blind, placebo-controlled study suggests that at least in the short-term, saffron is both safe and effective in mild to moderate AD. Larger confirmatory randomized controlled trials are called for.
A spectrofluorimetric method has been developed for the quantitative determination of mefenamic, flufenamic, and meclofenamic acids in urine samples. The method is based on second-order data multivariate calibration (unfolded partial least squares (unfolded-PLS), multi-way PLS (N-PLS), parallel factor analysis (PARAFAC), self-weighted alternating trilinear decomposition (SWATLD), and bilinear least squares (BLLS)). The analytes were extracted from the urine samples in chloroform prior to the determination. The chloroform extraction was optimized for each analyte, studying the agitation time and the extraction pH, and the optimum values were 10 minutes and pH 3.5, respectively. The concentration ranges in chloroform solution of each of the analytes, used to construct the calibration matrix, were selected in the ranges from 0.15 to 0.8 microg mL-1 for flufenamic and meclofenamic acids and from 0.25 to 3.0 microg mL-1 for mefenamic acid. The combination of chloroform extraction and second-order calibration methods, using the excitation-emission matrices (EEMs) of the three analytes as analytical signals, allowed their simultaneous determination in human urine samples, in the range of approximately 80 mg L-1 to 250 mg L-1, with satisfactory results for all the assayed methods. Improved results over unfolded-PLS and N-PLS were found with PARAFAC, SWATLD, and BLLS, methods that exploit the second-order advantage.
In regression, cross-validation is an effective and popular approach that is used to decide, for example, the number of underlying features, and to estimate the average prediction error. The basic principle of cross-validation is to leave out part of the data, build a model, and then predict the left-out samples. While such an approach can also be envisioned for component models such as principal component analysis (PCA), most current implementations do not comply with the essential requirement that the predictions should be independent of the entity being predicted. Further, these methods have not been properly reviewed in the literature. In this paper, we review the most commonly used generic PCA cross-validation schemes and assess how well they work in various scenarios.
This paper reviews the literature on recent research on the chemical composition and pharmacological activities of saffron (Crocus sativus) and its active constituents, mainly as antitumoral, hypolipidemic and tissue oxygenation enhancement agents.
Crocin, picrocrocin, and safranal as the major secondary metabolites are important for the high quality of spice saffron. Crocin and picrocrocin were detected in stigma-like structures proliferated in vitro. Safranal appeared after heat treatment. The contents and relative ratio of these substances in the stigma-like structures were similar to those in intact young stigmas, indicating that these stigma-like structures showed not only morphological but also biochemical similarity to the intact stigmas. © 1987, Japan Society for Bioscience, Biotechnology, and Agrochemistry. All rights reserved.
Crocin, picrocrocin, and safranal as the major secondary metabolites are important for the high quality of spice saffron. Crocin and picrocrocin were detected in stigma-like structures proliferated in vitro. Safranal appeared after heat treatment. The contents and relative ratio of these substances in the stigma-like structures were similar to those in intact young stigmas, indicating that these stigma-like structures showed not only morphological but also biochemical similarity to the intact stigmas.
Three common food colorants (tartrazine TT, allura red AR, and sunset yellow SY) were simultaneously quantified in powdered soft drinks by employing a combination of absorbance spectra-pH data matrices and multivariate processing of the generated second-order data. Parallel factor analysis PARAFAC and bilinear least squares/residual bilinearization BLLS/RBL were applied for deconvolution of trilinear data to get spectral and concentration profiles of the dyes as a function of pH. BLLS/RBL outperformed PARAFAC for handling rank deficiency and linear dependency problems that often involved in pH-equilibrating systems. BLLS/RBL was able to mange the earlier problems that came from the high spectral overlap between acid and basic forms of dyes and linear dependency in pH dimension. Using BLLS/RBL, the second order advantage was fully accomplished in which TT, SY, and AR were quantified in four soft drinks even in the presence of many uncalibrated interferents. The concentration levels of dyes in commercial samples were within the safe recommended ones, TT 323–480, SY 84–1016 mg kg−1, and AR was not detected in any product. The comparison of chemometric results with those obtained by standard chromatographic technique proved that the former protocol has a reasonable accuracy with average recoveries of 104% for TT and 104.9% for SY.
This work reports the release of Multivariate Calibration 2 (MVC2), a MATLAB graphical interface toolbox for implementing several second-order multivariate calibration methodologies. The toolbox accepts a variety of input data formats, arranged in either matrices or vectors (i.e., unfolded matrices), and contained in ASCII files. It allows one to manually select working sensor regions and plot landscapes for selected samples. The development of each model and its subsequent application to unknown samples is straightforward. Prediction results are produced along with analytical figures of merit and standard concentration errors, as calculated by modern concepts of uncertainty propagation.
A fast, simple screening method for discriminating between natural and adulterated saffron was developed that reduces the need for time-consuming techniques. The method uses a flow manifold where saffron samples containing adulterants in a phosphate buffer are passed through a column packed with cotton that retains the adulterants for subsequent elution with dilute ammonia. Samples testing positive for adulterants are subjected to a multivariate calibration technique such as partial least-squares regression (PLS) in order to quantify the adulterant analytes. This allows Methyl Orange, tartrazine and Ponceau-4R to be accurately quantified. The proposed method provides a yes/no overall response and allows the presence of adulterant species in positive samples to be confirmed. The calibration model was optimized by using an appropriate number of factors and the most suitable wavelength ranges to construct the Box–Behnken data matrix. The method was validated by application to saffron samples spiked with both individual adulterants and binary and ternary mixtures thereof.
A novel trilinear decomposition algorithm for second-order linear calibration called self-weighted alternating trilinear decomposition (SWATLD) has been designed in this paper. Experiments show SWATLD has the features of fast convergence and being insensitive to the excess factors used in calculation. Due to the unique optimizing scheme employed, SWATLD is much more efficient than the ordinary PARAFAC algorithm. In terms of the variance, the performance of SWATLD is very stable when the number of factors used in calculation varies (as long as it is no less than the actual number of factors). Such a feature will facilitate the analysis of three-way data arrays, since it is now unnecessary to spend a lot of time and effort to accurately determine the number of underlying factors in the system studied as does in PARAFAC. Furthermore, as far as the deviations of the results are concerned, experiments show SWATLD can supply acceptable results in most cases.
SPME–GC–MS analysis on four samples of saffron from different areas of Italy and from Iran were performed. Sample 1 was derived from cultivations of Crocus sativus in the zone of Salerno (Southern Italy). Sample 2 was derived from cultivations in Sardinia, Italy. Sample 3 was derived from cultivations in Abruzzo (Central Italy). Sample 4 was derived from Iran. The main components were those found in ethereal extract of saffron in a work published in 1971. Several compounds found by using other extraction—distillation techniques were not found. We found 18 compounds never discovered in saffron. In all the samples, 3,5,5-trimethyl-2-cyclohexen-1-one, 3,5,5-trimethyl-2-cyclohexen-1,4-dione, safranal and 2,4,4-trimethyl-6-hydroxy-3-carboxaldehyde-2,5-cyclohexadien-1-one were found. 3,5,5-Trimethyl-1,4-cyclohexandione was found in three samples. 5,5-Dimethyl-2-methylene-1-carboxaldehyde-3-cyclohexene, β-ionone were found in six samples, and nonanal, and 2,6-di-t-butylphenol were found in two samples. These compounds represent the compounds found with the highest frequency. Considering the relative amount of the components, safranal is the main component in all the samples. The analyses show that saffrons from different cultivation sites have some peculiarities due to the presence of some unusual components. The sample from Iran showed the presence of 3,5,5-trimethyl-2-hydroxy-2-cyclohexen-1-one, 2,7,7-trimethyl2,4-cycloheptadien-1-one, 1,3,3-trimethyl-2-(E-2-butenylidene)-3-cyclo-hexene, 5,5-dimethyl-1,3-cyclohexadien-1-carbaldehyde, 1,1,3-trimethyl-2-(Z-2-butenylidene)-3-cyclohexene, 1-acetyl-5,5-dimethyl-bycyclo[3.1.0]hexane, and β-ionol. Copyright © 2003 John Wiley & Sons, Ltd.
PARAFAC is well known as an iterative trilinear decomposition method. In practice, an accurate estimation of the number of underlying factors is required; otherwise it is difficult to guarantee the chemical meaning of the results obtained. The absence of a versatile chemometric method for factor estimation has often caused problems for analysts. With the advent of ATLD followed by SWATLD, the above relatively strict constraint can be relaxed. Experiments have shown that the profiles of the underlying factors can be extracted by ATLD (Wu et al., J. Chemometrics 1998; 12: 1) and SWATLD (Chen et al., Chemometrics Intell. Lab. Syst. 2000; 52: 75) as long as the number of factors used in calculation is no less than the number of actual factors. In other words, an overestimation of the number of factors will not affect the obtainment of chemically meaningful results by SWATLD and ATLD. In this paper the authors provide some simple mathematical explanations of this valuable property of SWATLD. Along with these explanations, some other properties of SWATLD as well as some guidelines for designing new trilinear decomposition methods are also discussed. Copyright © 2001 John Wiley & Sons, Ltd.
Tensorial calibration provides a useful approach to calibration in general. For calibration of instruments that produce two-dimensional (second-order) arrays of data per sample, tensoial concepts are as natural a way of solving the calibration problem as vectorial concepts are for the multivariate problem. Similarly, for third- and higher-order data, the tensorial description of calibration is also useful. This paper introduces second-order calibration from a tensorial point of view. Univariate, multivariate and bilinear approaches to calibration are presented. The generalized rank annihilation method (GRAM) is described from the tensorial perspective, and it is shown that GRAM is equivalent to finding a second-order tensorial base that spans both tensors (calibration and unknown) with respective diagonal component matrices. GRAM uses a single calibration sample for multicomponent analysis even in the presence of interference. Second-order bilinear calibration is extended to multiple calibration samples where the effect of collinearities is reduced.
Orthogonal projection approach (OPA) has been used for monitoring batch processes. However, because of the mass balance constraints between the reactants and products in a chemical reaction, standard OPA will fail if rank-deficiency occurs. The effect of the rank-deficiency on using OPA for process reaction data sets is discussed, and a new automatic approach for resolution of rank-deficiency data sets by OPA is proposed for batch control. The method is demonstrated for an industrial batch data set.
Difference spectroscopy is used to monitor small changes or variations in a complex environment. Processes monitored by difference spectroscopy always have the spectrum of the initial stage subtracted and, as a consequence, a rank-deficient data set is obtained. This inherent rank-deficiency of the measurement can add to typical rank-deficiency problems in process spectroscopic monitoring, such as the presence of co-evolving reactions. In this work, we first demonstrate that a rank decrease occurs when working with difference spectra irrespective of the fact that we have full-rank or rank-deficient processes and we provide an interpretation of the chemical meaning of the process profiles and difference spectra that can be actually resolved. In a second point, the hybrid Hard–Soft-Modeling version of Multivariate Curve Resolution-Alternating Least Squares is used to resolve this kind of data sets. Special attention is paid to the strategy of application of specific hard-modeling constraints to circumvent rank-deficiency in difference spectroscopy. It is illustrated on simulated data and on two case studies chosen in the field of time-resolved FTIR spectroscopy and UV–Vis transient absorption spectroscopy. Differences in interpretation of the resolved profiles and in the application of constraints between direct and difference spectroscopy are exposed in detail.
PARAFAC is one of the most widely used algorithms for trilinear decomposition. The uniqueness properties of the PARAFAC model are very attractive regardless of whether one is interested curve resolution or not. The fact that PARAFAC provides one unique solution simplifies interpretation of the model. But in three-way data arrays the uniqueness condition can only be expected when kA + kB + kC ≥ 2F + 2, where F is the number of components and k's are the Kruskal ranks of loadings A to C. As much as second order instruments produce data of varying complexity depending upon the nature of the analytical techniques being combined, with some three-way data it is possible for patterns generated by the underlying sources of variation to have sufficient independent effects in two modes, yet nonetheless be proportional in a third mode. For example, in three-way data for spectrophotometric titrations of weak acids or bases (pH-wavelength-sample), a rank deficiency may occur in two modes, that is closure rank deficiency in the pH mode and proportionality rank deficiency in the sample direction because each analyte will have acidic and basic forms that are linear combinations in the sample mode. The goal of the present paper is to overcome the non-uniqueness problem in the second order calibration of monoprotic acids mixtures. The solution contains two steps: first each pH-absorbance matrix is pretreated by subtraction of the first spectrum from each spectrum in the data matrix. This pretreated data matrix is called the variation matrix. Second, by stacking the variation matrices, a three-way trilinear variation data array will be obtained without the proportional linear dependency problem that can be resolved uniquely by PARAFAC. It is shown, although unique results are not guaranteed by the Kruscal's condition for the original three-way data, this condition is fulfilled for pretreated three-way data. Hence, the variation array may be uniquely decomposed by the PARAFAC algorithm. Studies on simulated as well as real data array reveal the applicability of the proposed method to this kind of problem in the second order calibration of monoprotic acids. Copyright © 2008 John Wiley & Sons, Ltd.
The effect of mass balance on the analysis of two-way data of reaction or process systems is investigated. It is shown that the rank-deficient species-related bilinear model can be converted to a full-rank reaction-related bilinear model, and in general situations the chemical rank for a system is the number of reactions plus one. Two slightly modified procedures are thus suggested to extract the spectral subspaces essential for resolution and to ascertain the number of reactions in different time domains. Based on the reaction-related bilinear model, a procedure of window factor analysis (WFA) is implemented for resolving the extent curves of reactions. A new two-way resolution approach, parallel vector analysis (PVA), is also developed. The idea of PVA is to construct a set of subspaces comprising only one common (spectral) component and then find a vector that is in parallel with a series of vectors coming from different subspaces. With suitably constructed subspaces the PVA procedure offers a versatile avenue to approach the unique resolution of spectral profiles. A four-component system which comprises four different processes or reactions is simulated. Results obtained reveal that favorable resolution is achieved for the spectral and concentration profiles by the suggested procedures of WFA and PVA. Copyright © 2003 John Wiley & Sons, Ltd.
A new method, alternating penalty trilinear decomposition (APTLD), is developed for the decomposition of three-way data arrays. By utilizing the alternating least squares principle and alternating penalty constraints to minimize three different alternating penalty errors simultaneously, the intrinsic profiles are found. The APTLD algorithm can avoid the two-factor degeneracy problem and relieve the slow convergence problem, which is difficult to handle for the traditional parallel factor analysis (PARAFAC) algorithm. It retains the second-order advantage of quantification for analytes of interest even in the presence of potentially unknown interferents. In additions, it is insensitive to the estimated component number, thus avoiding the difficulty of determining a correct component number for the model, which is intrinsic in the PARAFAC algorithm. The results of treating one simulated and one real excitation–emission spectral data set showed that the proposed algorithm performs well as long as the model dimensionality chosen is not less than the actual number of components. Furthermore, the performance of the APTLD algorithm sometimes surpasses that of the PARAFAC algorithm in the prediction of concentration profiles even if the component number chosen is the same as the actual number of underlying factors in real samples. Copyright © 2005 John Wiley & Sons, Ltd.
Saffron spice is the dry stigmata of Crocus sativus L. Methods have been developed for the determination of the quality of the spice using thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC) and gas chromatography (GC). TLC and HPLC gave comparable results for crocin and crocetins (colour principles), picrocrocin (bitter substance) and safranal (flavour). Similarly, the determination of safranal by GC was in agreement with analysis by TLC and HPLC. Separation of the constituents was achieved by silica gel G TLC using an n-butanol-acetic acid-water (4:1:1) system. The resolution of crocin, crocetins and picrocrocin by HPLC was obtained using a Shimadzu 15-cm CLC-ODS column with 20–80% acetonitrile in water as the eluent; for safranal an isocratic run with 76% acetonitrile in water was suitable. GC was adopted only for the determination of safranal using a Shimadzu 5% SE-30 column. HPLC was most suitable for the detection of adulterants and was simpler and more efficient for quality analysis. The TLC method was time-consuming and also gave an overestimation of the colour principles.
An HPLC method to check components and purity in commercial saffron by photodiode array detection has been developed. The method was suitable for the standard analysis of commercial saffron. Therefore, 10 saffron metabolites responsible for the taste, flavour and colour were identified and quantified with high selectivity, precision and accuracy. Also, some artificial colorants, which can be used as adulterants, were also detected and identified. Three different saffron types were studied and their metabolite concentrations determined at different wavelengths.
The analysis of spectral measurements using standard factor-analytical (FA) techniques requires the rank of the absorbance matrix to be equal to the number of absorbing species, S. However, in many practical reaction networks, such an assumption does not hold. This paper examines various scenarios where ‘rank deficiency’ can occur. The most important case is when the number of independent reactions, R, is less than S. In such a case, rank analysis can only reveal R and, hence, standard FA techniques will fail. Hence, one possibility is to perform rotation in the reaction-spectra space of dimension R. Another possibility is to augment the rank of the data matrix to S for which two experimental methods are developed. Rank augmentation is performed by (i) multiple process runs and (ii) addition of reactants or products during the reaction. The composite data matrices are of rank S and, hence, suited to factor analysis. The number of necessary runs or additions can be detected by determining the rank of both the original and column-mean-centered data matrices. With rank augmentation, it is possible to determine both the number of independent reactions and the number of absorbing species. Furthermore, the influence on the rank of data pretreatment such as mean centering, normalization, auto-scaling, and differentiation with respect to time or wavelength is examined.
Three fluoroquinolone antibiotics (ciprofloxacin, norfloxacin and danofloxacin) have been determined in human serum in the presence of the potential interferent salicylate, by processing lanthanide-sensitized excitation-time decay matrix data for their terbium (III) complexes. The algorithm employed, multivariate curve resolution-alternating least-squares, is one of the few methodologies which permit the achievement of the second-order advantage in the presence of a high degree of overlapping between the time decay profiles for the analyte and the interferent complexes. Furthermore, the presence of analyte-background interactions makes it necessary to employ the standard addition method for successful quantitation. Both simulations and experiments showed that the modified standard addition method was suitable for this purpose, in which the test data matrix was subtracted from the standard addition matrices, and quantitation proceeded using classical external calibration procedure. The analyte concentration ranges were all within the therapeutic range, i.e., 0-6 mgL(-1) in serum, with final concentrations in the measuring cell in the order of 0.2 mgL(-1).
The determination of tetracycline by fluorescence spectrophotometry in complex matrices has some difficulties, because the presence of other compounds in the matrix affects the analytical signal. In this work, the effect of some inorganic species that are present in whey milk on the fluorescence signal of tetracycline is studied using a D-optimal experimental design. Next, an experimental strategy is proposed in conjunction with Parallel Factor Analysis, PARAFAC, modeling that leads to suitably modeling the severe matrix effect in the determination of tetracycline in whey milk. A specific design is performed in such a way that the lack of trilinearity due to the effect of the presence of interferents on the signal is obviated. Then, ten test samples from three brands of milk, spiked with different quantities of tetracycline and measured in 2 days were analysed using this methodology (mean of the absolute value of the relative errors: 5.1%). The developed analytical method fulfils the property of trueness, the relative errors being, both in calibration and prediction, inside the interval set by Commission Decision 2002/657/EC at these concentration levels. Decision limits (CCalpha) at x(0)=0 microg L(-1) and at x(0)=100 microg L(-1) were 13.2 and 112.4 microg L(-1) respectively, for alpha=0.05; whereas detection capabilities (CCbeta) were 25.9 microg L(-1) and 124.4 microg L(-1) respectively for alpha=beta=0.05.
The paper reports a direct method for the determination of pyridine in water and wastewater samples based on ultraviolet spectrophotometric measurements using multi-way modeling techniques. Parallel factor analysis (PARAFAC) and multi-way partial least squares (N-PLS) regression methods were employed for the decomposition of spectra and quantification of pyridine. The study was carried out in the pH range of 1.0-12.0 and concentration range of 0.67-51.7 microgmL(-1) of pyridine. Both the three-way PARAFAC and tri-PLS1 models successfully predicted the concentration of pyridine in synthetic (spiked) river water and field wastewater samples. The mean recovery obtained from PARAFAC regression model were 97.39% for the spiked and 99.84% for the field wastewater samples, respectively. The sensitivity and precision of the method for pyridine determination were 0.58% and 5.95%, respectively. The N-PLS regression model yielded mean recoveries of 99.29% and 100.18% for the spiked and field wastewater samples, respectively. The prediction accuracy of the methods was evaluated through the root mean square error of prediction (RMSEP). For PARAFAC, it was 0.65 and 0.82 microgmL(-1) for spiked river water and field wastewater samples, respectively, while for N-PLS, it was 0.25 and 0.37 microgmL(-1), respectively. Both the PARAFAC and N-PLS methods, thus, yielded satisfactory results for the prediction of pyridine concentration in water and wastewater samples.
Second-order calibration methods are gaining widespread acceptance among the analytical community mainly because: (1) a wide range of analytical instrumentation is available that enables high dimensionality data to be obtained; (2) the chemometric techniques for treating these data are highly developed; and (3) they have the so-called "second-order advantage", i.e. they can predict the concentration of the analyte of interest even in the presence of unknown interferents. This also enables several analytes to be determined simultaneously. In this paper we describe the most common instrumental and chemometric techniques used in second-order calibration and discuss their applications since 2000. First, we introduce briefly the techniques and then we comment the applications. Given the practical nature of this paper, we have classified the techniques according to five fields of application: pharmaceuticals, biological matrices, foods, environmental matrices and synthetic matrices.
Topical application of Nigella sativa and Crocus sativus extracts (common food spices) inhibited two-stage initiation/promotion [dimethylbenz[a]anthracene (DMBA)/croton oil] skin carcinogenesis in mice. A dose of 100 mg/kg body wt of these extracts delayed the onset of papilloma formation and reduced the mean number of papillomas per mouse, respectively. The possibility that these extracts could inhibit the action of 20-methylcholanthrene (MCA)-induced soft tissue sarcomas was evaluated by studying the effect of these extracts on MCA-induced soft tissue sarcomas in albino mice. Intraperitoneal administration of Nigella sativa (100 mg/kg body wt) and oral administration of Crocus sativus (100 mg/kg body wt) 30 days after subcutaneous administration of MCA (745 nmol x 2 days) restricted tumor incidence to 33.3% and 10%, respectively, compared with 100% in MCA-treated controls.
Out of various spices and leafy vegetables screened for their influence on the carcinogen-detoxifying enzyme, glutathione-S-transferase (GST) in Swiss mice, cumin seeds, poppy seeds, asafoetida, turmeric, kandathipili, neem flowers, manathakkali leaves, drumstick leaves, basil leaves and ponnakanni leaves increased GST activity by more than 78% in the stomach, liver and oesophagus, - high enough to be considered as protective agents against carcinogenesis. Glutathione levels were also significantly elevated in the three tissues by these plant products. All of them except neem flowers, significantly suppressed (in vivo) the chromosome aberrations (CA) caused by benzo(a)pyrene in mouse bone marrow cells. Multiple CA and exchanges reflecting the severity of damage within a cell were significantly suppressed by these nine plant products. The results suggest that these nine plant products are likely to suppress carcinogenesis and can act as protective agents against cancer.
High-performance liquid chromatography with photodiode-array detection was used to separate picrocrocin (bitter-tasting component, glucoside of safranal), cis/trans-crocins (carotenoids, glucosyl esters of crocetin) and safranal (flavour, monoterpene aldehyde) of saffron. All components of pure red Greek saffron were extracted from dried stigma with 50% methanol. These compounds were detected, separated collected and identified simultaneously using a Merck LiChroCART 125-4 Superspher 100 RP-18 (4 microns) column and as mobile phase a linear gradient from 20% to 100% acetonitrile in water in 20 min with a detection wavelength at 308 nm.
The analytical performances of two algorithms, the recently introduced bilinear least-squares (BLLS) and the popular parallel factor analysis (PARAFAC), are compared as regards second-order fluorescence data recorded for the determination of the fluoroquinolone antibiotic ciprofloxacin in human urine samples. The applied chemometric methodologies employ different strategies for exploiting the so-called second-order advantage, which allows one to obtain individual concentrations of calibrated analytes in the presence of any number of uncalibrated (urine) components. Analysis of a spiked urine test set (in the analyte concentration range 0-200 mg L(-1)) showed that BLLS provides results of slightly better quality than PARAFAC. Satisfactory results have been obtained on comparing the concentrations predicted for a series of real urine samples with those furnished by liquid chromatography. The limit of detection of the fluorescence-based methods is approximately 5 mg L(-1).
A screening method for the detection of artificial colours (naphthol yellow, tartrazine, quinoline yellow, Sunset yellow, Allura red, amaranth, azorubine, Ponceau 4R and Red 2G) in saffron is described. The method involves removal of crocins by precipitation of crocetin (pH 0.1, 90 degrees C) before adsorption of the artificial colours on polyamide SPE cartridges (pH 2). After washing with methanol, acetone and methanol, elution was done with a methanol:ammonia solution (95:5 v/v), and detection was performed by derivative spectrometry. Sample pretreatment changes the UV-Vis saffron extract profile in such a way that second derivative spectra can be used to identify the presence of added colours. Erythrosine, which was found to be pH dependent, could not be detected under the above conditions. The lowest detectable amount for each colour was strongly dependent on chemical structure. The recovery of carminic acid was very low possibly due to irreversible retention on the polyamide. This procedure can replace the current ISO TLC method (2003) and be used alternatively or in combination with HPLC procedures adopted in the same standard.
The combination of unfolded partial least-squares (U-PLS) with residual bilinearization (RBL) has not been properly exploited to process experimental second-order spectroscopic information, although it is able to achieve the important second-order advantage. Among other desirable properties, the technique can handle incomplete calibration information, i.e., when only certain analyte concentrations are known in the training set. It can also cope with analyte spectral changes from sample to sample, due to its latent variable structure. In this work, U-PLS/RBL has been successfully applied to experimental fluorescence excitation-emission matrix data aimed at the quantitation of analytes in complex samples: these were the antibiotic tetracycline and the anti-inflammatory salicylate, in both cases in the presence of human serum, where significant analyte-background interactions occur. The interactions of the analyte with the serum proteins modify their spectral fluorescence properties, making it necessary to employ training sets of samples where the biological background is present, possibly causing analyte spectral changes from sample to sample. The predictive ability of the studied model has been compared with that of parallel factor analysis (PARAFAC), as regards test samples containing different sera, and also other pharmaceuticals which could act as potential interferents.
The aim of this double-blind and placebo-controlled trial was to investigate whether saffron (stigma of Crocus sativus L.) could relieve symptoms of premenstrual syndrome (PMS).
Double-blind, randomised and placebo-controlled trial.
Departments of Gynaecology/Obstetrics and Psychiatry, Tehran and Zanjan University of Medical Sciences.
Women aged 20-45 years with regular menstrual cycles and experience of PMS symptoms for at least 6 months were eligible for the study.
Women were randomly assigned to receive capsule saffron 30 mg/day (15 mg twice a day; morning and evening) (group A) or capsule placebo (twice a day) for a two menstrual cycles (cycles 3 and 4).
The primary outcome measure was the Daily Symptom Report, and secondary outcome measure was the Hamilton Depression Rating Scale.
In this trial, saffron was found to be effective in relieving symptoms of PMS. A significant difference was observed in efficacy of saffron in cycles 3 and 4 in the Total Premenstrual Daily Symptoms and Hamilton Depression Rating Scale.
The results of this study indicate the efficacy of C. sativus L. in the treatment of PMS. However, a tolerable adverse effects profile of saffron may well confirm the application of saffron as an alternative treatment for PMS. These results deserved further investigations.
The paper discusses the applications of voltage source inverter
(VSI) based power electronic systems for interfacing variable-voltage DC
sources to the grid. A variable-speed wind power conversion system is
used for illustration, where the VSI-based interface needs to convert a
variable DC voltage to a nearly constant AC voltage with high-quality
power. The power control principles of VSI are described. Various system
configurations and switching strategies are examined by analysis,
simulation and experimental methods. It is shown that better utilisation
of semiconductors and more flexible control may be achieved by using a
separately controlled DC link, rather than a directly connected VSI that
has to operate at a lower modulation ratio at higher power. In some
cases, multipulse inverter structures may be preferred, despite higher
component count, because of reduced switching losses, fault tolerance
and the absence of filters. The solutions developed in the study could
be applied at a different scale to other renewable energy sources, such
as wave or solar photovoltaic devices
- S Masoum
S. Masoum et al. / Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 148 (2015) 389–395
- R Bro
- Parafac Tutorial
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Quantification of crocetin esters in saffron (Crocus sativus L.) using Raman spectroscopy and chemometrics
- E G Anstasaki
- C D Kanakis
- C Pappas
- L Maggi
- A Zalacain
- M Carmona
- G L Alonso
- M G Polission
E.G. Anstasaki, C.D. Kanakis, C. Pappas, L. Maggi, A. Zalacain, M. Carmona, G.L.
Alonso, M.G. Polission, Quantification of crocetin esters in saffron (Crocus
sativus L.) using Raman spectroscopy and chemometrics, J. Agric. Food Chem.
58 (2010) 6011-6017.
Alternating penalty trilinear decomposition algorithm for second-order calibration with application to interference-free analysis of excitation-emission matrix fluorescence data
- A L Xia
- H L Wu
- S F Li
- S H Zhu
- L Q Hu
- R Q Yu
A.L. Xia, H.L. Wu, S.F. Li, S.H. Zhu, L.Q. Hu, R.Q. Yu, Alternating penalty trilinear
decomposition algorithm for second-order calibration with application to
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