Differentiation of meat species of raw and processed meat based on polar metabolites using 1H NMR spectroscopy combined with multivariate data analysis

Decker, Christina; Krapf, Reiner; Kuballa, Thomas; Bunzel, Mirko

doi:10.3389/fnut.2022.985797

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…[17][18][19] High recognition rates have already been described for the differentiation of meat species. 20,21 We demonstrate the benefit of 1 H NMR spectroscopy for fish species discrimination using five different sample groups and prove the robustness of this method in the presence of typical additives such as citrate, even when their signals stay are included in the data analysis.…”

Section: Introductionmentioning

confidence: 68%

1H NMR metabolic profiling for the differentiation of fish species

Saglam

Paasch

Horns

et al. 2023

Preprint

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The determination of fish species is an important task for food control, especially in the case of very similar and processed fish or fish products. Typically, this analysis is carried out by DNA-based methods. However, especially for small sample series the effort for sample preparation and the required analysis time are not satisfactory. We show that by means of a simple extraction and analysis of the 1H NMR spectra of these extracts a fast discrimination of fish species is possible. For this purpose, 69 samples consisting of five sample groups iridescent shark, European plaice, rock sole, witch flounder and common sole were analysed. The large differences in the 1H spectra could be further highlighted with a principal component and led already to a graphical differentiation of most sample groups. The performed classification of the samples using a subspace discriminant algorithm showed a recognition rate of 100% for all samples, regardless of additives like citric acid or lysine. These results show that 1H NMR spectroscopy is a robust, simple and rapid method for the recognition of the fish species studied.

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Section: Introductionmentioning

confidence: 68%

1H NMR metabolic profiling for the differentiation of fish species

Saglam

Paasch

Horns

et al. 2023

Preprint

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“…The L-carnosine content of meat varies considerably between different animal species and different meat parts. Therefore, the amount of exogenous L-carnosine depends primarily on personal dietary choices [1,2]. The health benefits of L-carnosine to prevent and treat various medical conditions have been demonstrated in a large number of studies.…”

Section: Introductionmentioning

confidence: 99%

Electrophoretic Determination of L-Carnosine in Health Supplements Using an Integrated Lab-on-a-Chip Platform with Contactless Conductivity Detection

Pukleš,

Páger,

Sakač

et al. 2023

IJMS

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The health supplement industry is one of the fastest growing industries in the world, but there is a lack of suitable analytical methods for the determination of active compounds in health supplements such as peptides. The present work describes an implementation of contactless conductivity detection on microchip technology as a new strategy for the electrophoretic determination of L-carnosine in complex health supplement formulations without pre-concentration and derivatization steps. The best results were obtained in the case of +1.00 kV applied for 20 s for injection and +2.75 kV applied for 260 s for the separation step. Under the selected conditions, a linear detector response of 5 × 10−6 to 5 × 10−5 M was achieved. L-carnosine retention time was 61 s. The excellent reproducibility of both migration time and detector response confirmed the high precision of the method. The applicability of the method was demonstrated by the determination of L-carnosine in three different samples of health supplements. The recoveries ranged from 91 to 105%. Subsequent analysis of the samples by CE-UV-VIS and HPLC-DAD confirmed the accuracy of the obtained results.

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Evaluation of NMR-based strategies to differentiate fresh from frozen-thawed fish supported by multivariate data analysis

Kaltenbach,

Kuballa,

Schröder

et al. 2023

Eur Food Res Technol

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The differentiation of fresh and frozen-thawed fish is a relevant authenticity aspect as in the European Union fish holds a high statistical risk of being adulterated. Here, nuclear magnetic resonance spectroscopy (NMR) in combination with principal components analysis followed by linear discriminant analysis (PCA-LDA) was used for a non-targeted based differentiation of fresh from frozen-thawed fish. To identify the most promising NMR approach(es), six different approaches were applied to 96 fish samples (mackerel, trout, cod). These approaches included different sample preparation procedures and different NMR methods to investigate both the lipid fraction and the polar fraction of the fish samples. After cross-validation embedded in a Monte Carlo resampling design, six independent classification models were obtained. Evaluation of the multivariate data analysis revealed that the most promising approaches were the 1H NMR analysis of the lipid fraction (correct prediction of about 90.0%) and the 1H NMR based screening of minor components of the lipid fraction with a correct prediction of about 91.9%. 1H NMR analysis of the water extract of the fish samples showed a correct prediction of about 82.6%. Hence, a general differentiation of fresh from frozen-thawed fish via non-targeted NMR is feasible, even though the underlying sample batch contained different fish species. Additional fish samples need to be analyzed with the three most promising NMR approaches to further improve the developed classification models.

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Differentiation of meat species of raw and processed meat based on polar metabolites using 1H NMR spectroscopy combined with multivariate data analysis

Cited by 4 publications

References 51 publications

1H NMR metabolic profiling for the differentiation of fish species

1H NMR metabolic profiling for the differentiation of fish species

Electrophoretic Determination of L-Carnosine in Health Supplements Using an Integrated Lab-on-a-Chip Platform with Contactless Conductivity Detection

Evaluation of NMR-based strategies to differentiate fresh from frozen-thawed fish supported by multivariate data analysis

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