Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology

Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative, raising health, safety, and ethical concerns for consumers. In this study, we i...

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Main Authors: Gatmaitan, Abigail N., Lin, John Q., Zhang, Jialing, Schiavinato Eberlin, Livia
Format: Other/Unknown Material
Language:unknown
Published: American Chemical Society (ACS) 2021
Subjects:
Online Access:http://dx.doi.org/10.26434/chemrxiv.13515860
https://ndownloader.figshare.com/files/26051846
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spelling cracsoc:10.26434/chemrxiv.13515860 2024-04-07T07:51:12+00:00 Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology Gatmaitan, Abigail N. Lin, John Q. Zhang, Jialing Schiavinato Eberlin, Livia 2021 http://dx.doi.org/10.26434/chemrxiv.13515860 https://ndownloader.figshare.com/files/26051846 unknown American Chemical Society (ACS) https://creativecommons.org/licenses/by-nc-nd/4.0/ posted-content 2021 cracsoc https://doi.org/10.26434/chemrxiv.13515860 2024-03-08T00:19:31Z Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative, raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 seconds per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Metabolic predictors of meat type selected included several metabolites previously described reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is as a promising alternative analytical method for the investigation of meat fraud. Other/Unknown Material Atlantic salmon ACS Publications Sockeye ENVELOPE(-130.143,-130.143,54.160,54.160)
institution Open Polar
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description Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative, raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 seconds per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Metabolic predictors of meat type selected included several metabolites previously described reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is as a promising alternative analytical method for the investigation of meat fraud.
format Other/Unknown Material
author Gatmaitan, Abigail N.
Lin, John Q.
Zhang, Jialing
Schiavinato Eberlin, Livia
spellingShingle Gatmaitan, Abigail N.
Lin, John Q.
Zhang, Jialing
Schiavinato Eberlin, Livia
Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology
author_facet Gatmaitan, Abigail N.
Lin, John Q.
Zhang, Jialing
Schiavinato Eberlin, Livia
author_sort Gatmaitan, Abigail N.
title Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology
title_short Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology
title_full Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology
title_fullStr Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology
title_full_unstemmed Rapid Analysis and Authentication of Meat Products using the MasSpec Pen Technology
title_sort rapid analysis and authentication of meat products using the masspec pen technology
publisher American Chemical Society (ACS)
publishDate 2021
url http://dx.doi.org/10.26434/chemrxiv.13515860
https://ndownloader.figshare.com/files/26051846
long_lat ENVELOPE(-130.143,-130.143,54.160,54.160)
geographic Sockeye
geographic_facet Sockeye
genre Atlantic salmon
genre_facet Atlantic salmon
op_rights https://creativecommons.org/licenses/by-nc-nd/4.0/
op_doi https://doi.org/10.26434/chemrxiv.13515860
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