Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 545411
Title No more nutmegging with nutmeg : Analytical fingerprints for distinction of quality from low-grade nutmeg products
Author(s) Ruth, Saskia M. van; Silvis, Isabelle C.J.; Alewijn, Martin; Liu, Ningjing; Jansen, Marc; Luning, Pieternel A.
Source Food Control 98 (2019). - ISSN 0956-7135 - p. 439 - 448.
DOI https://doi.org/10.1016/j.foodcont.2018.12.005
Department(s) Food Quality and Design
RIKILT - BU Authenticity & Nutrients
VLAG
RIKILT - BU Toxicology Bioassays & Novel Foods
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) Adulteration - Aroma - FI-ESI-MS - Fraud - PTR-MS - Spices
Abstract

Quality nutmeg is characterized by a delicate aroma. Next to quality nutmeg, other – lower - grades exist on the market, such as extracted material (spent) or ground shell or dried fruit pulp. Strong fluctuations in the price of nutmeg lead to rapid changes in market dynamics and marketing opportunities, and unfortunately results in illegal commingle of ground quality nutmeg with low-grade material. In this study, we examined fingerprints of volatile and non-volatile compounds of high quality and low-grade nutmeg material by Proton Transfer Reaction Mass Spectrometry and Flow Infusion ElectroSpray Ionization Mass Spectrometry, respectively. They were compared with data from classical measurements such as total ash, acid insoluble ash, moisture and volatile oil contents. Differences in composition were examined by univariate and multivariate statistical methods. Furthermore, one-class classification models for quality nutmeg were estimated using different algorithms and their performances were examined with quality nutmeg and low-grade material, as well as mixtures thereof. Distinct differences between quality nutmeg and low-grade nutmeg samples were observed for both their volatile and non-volatile fingerprints. Intensities of volatiles and non-volatiles are highly correlated, but this phenomenon diminishes gradually and even reverses with rising molecular mass of the non-volatiles. Results showed that both techniques allowed a nearly 100% correct prediction of quality nutmeg and low-grade nutmeg samples. Therefore, both approaches are promising and with further database extension, they may become a valuable addition to the analytical authentication toolbox in addition to the classical methods and help to detect future ‘nutmeggers’.

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