Analytical techniques combined with chemometrics for authentication and determination of contaminants in condiments: A review

Reinholds, Ingars; Bartkevičs, Vadims; Silvis, Isabelle C.J.; Ruth, Saskia M. van; Esslinger, Susanne

doi:10.1016/j.jfca.2015.05.004

Cited by 117 publications

(53 citation statements)

References 136 publications

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“…Moreover, an analytical fingerprint is much harder to intentionally manipulate by a fraudster than just a limited number of specific markers. Examples of such analytical fingerprinting approaches include the discrimination of organic from conventional produce (eggs, , meat (Ballin, 2010;Sentandreu and Sentandreu, 2014)), various geographical origin issues (Cubero-Leon et al, 2014), processing conditions (virgin status of olive oil (Dais and Hatzakis, 2013)), product origin (wild/farmed fish (Arechavala-Lopez et al, 2013)), speciality production (GTS, Leidse kaas: (Galle et al, 2011)) or biological origin or adulteration (Reinholds et al, 2015). All these applications have in common that they use some form of 'conventional' methodology (for food/feed predominantly analytical chemistry) to produce an analytical fingerprint, or chemical or physical profile.…”

Section: Introductionmentioning

confidence: 99%

Validation of multivariate classification methods using analytical fingerprints – concept and case study on organic feed for laying hens

Alewijn

Voet

Ruth

2016

Journal of Food Composition and Analysis

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Please cite this article as: Alewijn, Martin., van der Voet, Hilko., & van Ruth, Saskia., Validation of multivariate classification methods using analytical fingerprints − concept and case study on organic feed for laying hens.Journal of Food Composition and Analysis http://dx. 2Highlights  A validation procedure for multivariate classification methods is proposed  Combined validation of sample set composition, analytical method and performance  Class probability scores give more performance insight than classification results  Future correct classification rate derived from combined probability distributions  A case study on organic feed shows the new validation approach in practice AbstractMultivariate classification methods based on analytical fingerprints have found many applications in the food and feed area, but practical applications are still scarce due to a lack of a generally accepted validation procedure. This paper proposes a new approach for validation of this type of methods. A part of the validation procedure requires a description of qualitative aspects: the method's goal and purpose and adequateness of the sample sets used. The required quantitative performance is assessed from probabilistic data. Probability distributions are generalized using kernel density estimates, which allow meaningful interpolation and direct comparison and combination of different distributions. We propose inclusion of a permutation test, and provide suggestions for the assessment of the analytical repeatability in the method's probabilistic units. The latter can serve as a quality control measure. For assessment of the method's overall performance, we propose to apply the combined cross validation and external validation set probability distributions in order to obtain the best estimate for the method's performance on future samples. Qualitative and quantitative aspects are to be combined into a validation dossier stating performance for a well-defined purpose and scope. The proposed validation approach is applied to a case study: a binary classification discriminating organic from conventional laying hen feed based on fatty acid profiling that is essential to ensure the organic status of eggs for human consumption. For this case study, an expected accuracy for organic feed recognition of 96% is obtained for an explicitly defined scope.

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Section: Introductionmentioning

confidence: 99%

Validation of multivariate classification methods using analytical fingerprints – concept and case study on organic feed for laying hens

Alewijn

Voet

Ruth

2016

Journal of Food Composition and Analysis

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“…The new object x belongs to a class which encompasses most of the k empirically chosen neighbors. An increase in the value of k reduces the impact of errors, whereas its decrease worsens classification (Pérez‐Caballero et al., ; Reinholds, Bartkevics, Silvis, van Ruth, & Esslinger, ). This value is related to the number of neighbors (“votes”) to poll for future classifications, such that k = 1 provides a good classification rule.…”

Section: Chemometrics In Food‐related Disciplinesmentioning

confidence: 99%

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

Granato

Putnik

Kovačević

et al. 2018

Comp Rev Food Sci Food Safe

356

202

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In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.

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“…For example, the commercialization of defatted paprika as integral paprika (with all its components) (ASTA, ). On the other hand, it can be added “extenders,” which are parts of the same plant added in the spices to gain weight or increase the volume (Galvin‐King et al., ; Reinholds, Bartkevics, Silvis, van Ruth, & Esslinger, ). For example, the addition of nonspice vegetable matters like stamens and safflower in pure saffron (Petrakis & Polissiou, ).…”

Section: Herbs and Spices: Common Adulterants And Geographical Originmentioning

confidence: 99%

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

110

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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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Analytical techniques combined with chemometrics for authentication and determination of contaminants in condiments: A review

Cited by 117 publications

References 136 publications

Validation of multivariate classification methods using analytical fingerprints – concept and case study on organic feed for laying hens

Validation of multivariate classification methods using analytical fingerprints – concept and case study on organic feed for laying hens

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

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

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