Chemical profiling of saffron for authentication of origin

Wakefield, Joshua; McComb, Kiri; Ehtesham, Emad; Hale, Robert Van; Barr, David; Hoogewerff, Jurian; Frew, Russell

doi:10.1016/j.foodcont.2019.06.025

Cited by 32 publications

(29 citation statements)

References 27 publications

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“…From Iran, 41 saffron samples were collected by the authors of Wakefield et al [ 29 ] directly from producers in northeastern (Khorasan Province) between September 2010 and November 2011. Nine samples were collected from the La Mancha region in Spain in November 2011 by the authors directly from producers and a further 2 from a trusted commercial redistributor [ 29 ]. In the case of both datasets, concentrations of 42 elements were determined as described by [ 29 ].…”

Section: Methodsmentioning

confidence: 99%

“…To demonstrate problems that may arise during the analysis of chemical elements in food science, datasets on the chemical compositions of honey and saffron were selected. Chemical profiling of honey [ 26 , 27 ] and saffron [ 28 , 29 ] is an important issue when determining their botanical and geographical origins. Honey is mainly composed of sugars and water with minor amounts of minerals, vitamins, amino acids, organic acids, flavonoids and other phenolic compounds, and aromatic substances [ 27 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Statistical Analysis of Chemical Element Compositions in Food Science: Problems and Possibilities

Templ

2021

Molecules

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In recent years, many analyses have been carried out to investigate the chemical components of food data. However, studies rarely consider the compositional pitfalls of such analyses. This is problematic as it may lead to arbitrary results when non-compositional statistical analysis is applied to compositional datasets. In this study, compositional data analysis (CoDa), which is widely used in other research fields, is compared with classical statistical analysis to demonstrate how the results vary depending on the approach and to show the best possible statistical analysis. For example, honey and saffron are highly susceptible to adulteration and imitation, so the determination of their chemical elements requires the best possible statistical analysis. Our study demonstrated how principle component analysis (PCA) and classification results are influenced by the pre-processing steps conducted on the raw data, and the replacement strategies for missing values and non-detects. Furthermore, it demonstrated the differences in results when compositional and non-compositional methods were applied. Our results suggested that the outcome of the log-ratio analysis provided better separation between the pure and adulterated data and allowed for easier interpretability of the results and a higher accuracy of classification. Similarly, it showed that classification with artificial neural networks (ANNs) works poorly if the CoDa pre-processing steps are left out. From these results, we advise the application of CoDa methods for analyses of the chemical elements of food and for the characterization and authentication of food products.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of Chemical Element Compositions in Food Science: Problems and Possibilities

Templ

2021

Molecules

View full text Add to dashboard Cite

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“…Five stable isotopes (δ 13 C, δ 15 N, δ 34 S, δ 2 H and δ 18 O) and 42 elements were considered. To the best of our knowledge, except for the work of Wakefield et al, 25 this is the first investigation combining multielemental and isotopic ratio patterns for tracing saffron. The isotopic and the elemental composition was used to attempt a geographical discrimination of the saffron samples through univariate statistics and multivariate classification approaches.…”

Section: Introductionmentioning

confidence: 95%

“…10 They provided isotopic values of defatted saffron samples along with chemical composition characteristics of the spice (colour, taste and aroma) to check whether it would be possible to relate saffron properties to its origin using multivariate statistical analysis. 10 25 this is the first investigation combining multielemental and isotopic ratio patterns for tracing saffron. The isotopic and the elemental composition was used to attempt a geographical discrimination of the saffron samples through univariate statistics and multivariate classification approaches.…”

Section: Introductionmentioning

confidence: 99%

“…They provided isotopic values of defatted saffron samples along with chemical composition characteristics of the spice (colour, taste and aroma) to check whether it would be possible to relate saffron properties to its origin using multivariate statistical analysis 10 . Wakefield et al managed to discriminate between samples of saffron coming from the Chilohorasan province of Iran and the La Mancha province of Spain by using carbon, nitrogen and hydrogen isotopic ratios of the bulk samples in addition to 42 elements 25 …”

Section: Introductionmentioning

confidence: 99%

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Stable isotope ratio analysis combined with inductively coupled plasma‐mass spectrometry for geographical discrimination between Italian and foreign saffron

et al. 2020

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Seventy-six samples of saffron were analysed through inductively coupled plasmamass spectrometry (ICP-MS) and stable isotope ratio analysis. The dataset was formed by 67 samples harvested in different areas of Italy, Morocco and Iran, and nine samples purchased in the Italian market. For the first time, 42 elements and five stable isotopes (δ 13 C, δ 15 N, δ 34 S, δ 2 H and δ 18 O) were considered to carry out the discrimination of the samples on the basis of their geographical origin. Combined ICP-MS and isotopic composition data turned out to be a useful tool for the geographical discrimination of saffron among predefined cultivation sites.

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Rapid detection and quantification of adulteration in saffron by excitation–emission matrix fluorescence combined with multi‐way chemometrics

Chen,

Wu,

Wang

et al. 2023

J Sci Food Agric

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BackgroundSaffron has gained people's attention and love for its unique flavor and valuable edible value, but the problem of saffron adulteration in the market is also serious. It is urgent for us to find a simple and rapid identification and quantitative estimation of adulteration in saffron. Therefore, the excitation‐emission matrix fluorescence combined with multi‐way chemometrics was proposed for the detection and quantification of adulteration in saffron.ResultsThe fluorescence composition analysis of saffron and saffron adulterants (safflower, marigold and madder) were accomplished by alternating trilinear decomposition algorithm (ATLD). The ATLD and two‐dimensional principal component analysis combined with k nearest neighbor (ATLD‐kNN and 2DPCA‐kNN) and ATLD combined with data driven soft independent modeling of class analogies (ATLD‐DD‐SIMCA) were applied for rapid detection of adulteration in saffron. 2DPCA‐kNN and ATLD‐DD‐SIMCA methods were adopted for the classification of chemical EEM data firstly with 100% correct classification rate. The content of adulteration of adulterated saffron was predicted by the N‐way partial least squares regression (N‐PLS) algorithm. In addition, new samples were correctly classified and the adulteration level in adulterated saffron was estimated semi‐quantitatively, which verifies the reliability of these models.ConclusionATLD‐DD‐SIMCA and 2DPCA‐kNN are recommended methods for the classification of pure saffron and adulterated saffron. N‐PLS algorithm shows potential in prediction of adulteration levels. These methods are expected to solve more complex problems in food authenticity.This article is protected by copyright. All rights reserved.

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Chemical profiling of saffron for authentication of origin

Cited by 32 publications

References 27 publications

Statistical Analysis of Chemical Element Compositions in Food Science: Problems and Possibilities

Statistical Analysis of Chemical Element Compositions in Food Science: Problems and Possibilities

Stable isotope ratio analysis combined with inductively coupled plasma‐mass spectrometry for geographical discrimination between Italian and foreign saffron

Rapid detection and quantification of adulteration in saffron by excitation–emission matrix fluorescence combined with multi‐way chemometrics

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