Influence of Geographical Origin on Isotopic and Elemental Compositions of Pork Meat

Dehelean, Adriana; Feher, Ioana; Romulus, Puscas; Magdas, Dana Alina; Covaciu, Florina-Dorina; Kasza, Angela Maria; Curean, Victor; Cristea, Gabriela

doi:10.3390/foods12234271

Cited by 3 publications

(1 citation statement)

References 56 publications

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“…The explanation consists in the fact that backyard egg producers, usually, have their farms in the rural regions, covering many areas of the country. Precipitation that falls in a site will be transmitted to the drinking water from respective location, which will be given to hens, and then the isotopic ngerprint of extracted water from egg yolk will be related to that territory (Camin et al 2016;Dehelean et al 2023). Barn eggs are coming from industrial poultry farms, these farms are not so scattered through the country, thus the range of variation for water isotopes is narrower.…”

Section: Isotopic Ngerprints Of Terrestrial Plants Have Different Val...mentioning

confidence: 99%

Backyard vs. barn eggs: differentiation and prediction models for two growing systems of hens based on isotopic, elemental, and fatty acid profiles of egg yolk

CRISTEA,

COVACIU,

FEHER

et al. 2024

Preprint

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Establishing the provenance of eggs from backyard growing system of hens can be challenging, in the context of high-value commercial products (the price of an egg from backyard chicken rearing system is double comparing with one from barn rearing regime). In this study, 90 egg yolk samples were investigated from isotopic, elemental and fatty acids profiles point of view. To identify the egg production system (backyard versus barn), three pattern recognition techniques were applied: linear discriminant analysis (LDA), k-nearest neighbor (k-NN) and multilayer perceptron artificial neural networks (MLP-ANN). LDA revealed a perfect separation for initial classification, while a percentage of 98.9% in cross-validation procedure was reached. From k-NN analysis, the overall classification rate was 98.4% for training set and 85.7% for testing set. After running the MLP-ANN, an overall percent of 100% for training set was obtained, while for the testing step decreased up to 92.3%, two samples being misclassified.

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Section: Isotopic Ngerprints Of Terrestrial Plants Have Different Val...mentioning

confidence: 99%

Backyard vs. barn eggs: differentiation and prediction models for two growing systems of hens based on isotopic, elemental, and fatty acid profiles of egg yolk

CRISTEA,

COVACIU,

FEHER

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics – a review

Erasmus,

Sohaib,

Revilla

et al. 2024

J Sci Food Agric

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Provenance is becoming increasingly important in meat supply chains as it lends products higher perceived quality. However, its precise definition and interpretation along with its associated characteristics factors have remained somewhat elusive. This review meticulously defines meat provenance while dissecting the essential factors and associated quality attributes that constitute its essence and are subsequently employed to establish pertinent markers for provenance. Meat provenance emerges as a multi‐dimensional construct stemming from the adept management of a constellation of factors relating to geographical origin, farm production system, traceability, and authenticity. Through intricate interactions, these factors unveil innate originality that not only forges a distinct reputation but also imparts a unique typicity to the meat product. Gaining insights into a meat product's provenance becomes attainable by scrutinizing its pertinent composition and organoleptic quality traits. Trace elements and stable isotopes stand out as provenance markers, forging a direct connection to both geographical origin and dietary sources. While somewhat less direct in linkage, other markers such as plant biomarkers, fatty acid composition, pH levels, flavour and aromatic compounds along with organoleptic characteristics contribute to the overall understanding of provenance. Additionally, the identification of animal species and breeds serves as key markers, particularly in the context of protected geographical indications. The study findings are useful for the various stakeholders of how the information for meat provenance can be linked with intrinsic and extrinsic factors for meat quality and protecting the integrity of the supply chain with special reference to traceability and authenticity.This article is protected by copyright. All rights reserved.

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Multivariate Modelling Based on Isotopic, Elemental, and Fatty Acid Profiles to Distinguish the Backyard and Barn Eggs

Cristea,

Covaciu,

Feher

et al. 2024

Foods

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The ability to trace the origin of eggs from backyard-raised hens is important due to their higher market value compared to barn-raised eggs. This study aimed to differentiate eggs from these two rearing systems using isotopic, elemental, and fatty acid profiles of egg yolks. A total of 90 egg yolk samples were analyzed, analytical results being followed by statistical tests (Student’s t-test) showing significant differences in δ18O, several elements (Mg, K, Sc, Mn, Fe, Ni, Cu, Zn, As, Cd, Ba, Pb), and fatty acids compositions (C23:0, C17:0, C18:0, C16:1n7, C18:1n9, C18:2n6, C20:1n7, C20:4n6, C20:5n3, C22:6n3), as well as in the ratios of SFA, PUFA, and UFA. The results indicated a nutritional advantage in backyard eggs due to their lower n-6 polyunsaturated fatty acid content and a more favorable n-6 to n-3 ratio, linked to differences in the hens’ diet and rearing systems. To classify the production system (backyard vs. barn), three pattern recognition methods were applied: linear discriminant analysis (LDA), k–nearest neighbor (k–NN), and multilayer perceptron artificial neural networks (MLP–ANN). LDA provided perfect initial separation, achieving 98.9% accuracy in cross-validation. k-NN yielded classification rates of 98.4% for the training set and 85.7% for the test set, while MLP–ANN achieved 100% accuracy in training and 92.3% in testing, with minor misclassification. These results demonstrate the effectiveness of fusion among isotopic, elemental, and fatty acid profiles in distinguishing backyard eggs from barn eggs and highlight the nutritional benefits of the backyard-rearing system.

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Influence of Geographical Origin on Isotopic and Elemental Compositions of Pork Meat

Cited by 3 publications

References 56 publications

Backyard vs. barn eggs: differentiation and prediction models for two growing systems of hens based on isotopic, elemental, and fatty acid profiles of egg yolk

Backyard vs. barn eggs: differentiation and prediction models for two growing systems of hens based on isotopic, elemental, and fatty acid profiles of egg yolk

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics – a review

Multivariate Modelling Based on Isotopic, Elemental, and Fatty Acid Profiles to Distinguish the Backyard and Barn Eggs

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