Authentication of beef production systems using a metabolomic-based approach

Osório, Maria Teresa Moreira; Moloney, A.P.; Brennan, Lorraine; Monahan, Frank J.

doi:10.1017/s1751731111001418

Cited by 44 publications

(16 citation statements)

References 36 publications

(35 reference statements)

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“…Geographic differences may also contain the production systems of animals. A study aiming to discriminate the pre-slaughter production system was able to distinguish differences between 1-year cattle fed with barley-based concentrate indoors and with pasture feeding outdoors, using NMR metabolomics followed by PLS-DA, analyzing the longissimus dorsi (LD) muscle [68]. The results suggested that NMR approach is suitable for authentication of cattle production history.…”

Section: Authenticationmentioning

confidence: 99%

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

et al. 2020

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In the past decades, metabolomics has been used to comprehensively understand a variety of food materials for improvement and assessment of food quality. Farm animal skeletal muscles and meat are one of the major targets of metabolomics for the characterization of meat and the exploration of biomarkers in the production system. For identification of potential biomarkers to control meat quality, studies of animal muscles and meat with metabolomics (MEATabolomics) has been conducted in combination with analyses of meat quality traits, focusing on specific factors associated with animal genetic background and sensory scores, or conditions in feeding system and treatments of meat in the processes such as postmortem storage, processing, and hygiene control. Currently, most of MEATabolomics approaches combine separation techniques (gas or liquid chromatography, and capillary electrophoresis)–mass spectrometry (MS) or nuclear magnetic resonance (NMR) approaches with the downstream multivariate analyses, depending on the polarity and/or hydrophobicity of the targeted metabolites. Studies employing these approaches provide useful information to monitor meat quality traits efficiently and to understand the genetic background and production system of animals behind the meat quality. MEATabolomics is expected to improve the knowledge and methodologies in animal breeding and feeding, meat storage and processing, and prediction of meat quality.

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Section: Authenticationmentioning

confidence: 99%

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

et al. 2020

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“…These laboratory methods have measured the fatty acid composition of muscle and subcutaneous fat and the concentration of β‐carotene. [ 8–13 ] The disadvantage of utilising these methods is the inability to perform these tests in a processing facility, as they require extensive sample preparation. These methods, however, can provide a reference test that can be utilised to evaluate the effectiveness of new technologies, which are able to provide rapid results.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Raman spectra for the verification of Australian grass‐ and grain‐fed beef using principal component analysis and partial least square models

Logan

Hopkins

Schmidtke

et al. 2020

J Raman Spectroscopy

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The diet of cattle has been shown to alter both subcutaneous fat and muscle fatty acid composition, and these differences cause a change in the Raman spectra of the fat due to the different chemical bonds associated with these biochemical changes. Because biochemical changes only lead to subtle changes in the Raman spectra, statistical methods based upon chemometric modelling are necessary to extract indicative information on the type of feed consumed. This investigation undertook a feasibility study using a limited sample set derived from two producers in one location to ascertain the potential for Raman spectroscopy to accurately discriminate grain‐fed cattle from grass‐fed cattle and investigated the usefulness of principal component analysis (PCA) and partial least squares discriminate analysis (PLS‐DA) to best discriminate between feeding groups using the information from the Raman spectra. The first two principal components accounted for 83% of the variation in the spectra and demonstrated discrimination of samples by feed type. PLS‐DA resulted in a model that was able to accurately predict grain‐ and grass‐fed carcases with a misclassification rate of 3.5%. Changes in beef cattle diets lead to subtle changes in subcutaneous fat; using Raman spectroscopy with chemometric modelling, these changes can be identified and used to identify the production system of beef products. This study successfully uses Raman spectroscopy as an automated, nondestructive and rapid technique in the range of 600–2000 cm−1 in combination with pattern recognition of unsupervised (PCA) and supervised (PLS‐DA) techniques to classify the production system of cattle between grain and grass fed.

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“…Like other “Omics”, it has been applied in a broad range of applications, such as agriculture, environment monitoring, and medicine [15-17]. In recent years, metabolomics has been successfully applied in disease diagnosis [18].…”

Section: Introductionmentioning

confidence: 99%

Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach

Liang

Miccoli

et al. 2016

Oncotarget

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Papillary thyroid microcarcinoma (PTMC) is a subtype of papillary thyroid carcinoma (PTC). Because its diameter is less than 10 mm, diagnosing it accurately is difficult with traditional methods such as image examinations and FNA (Fine Needle Aspiration). Investigating the metabolic changes induced by PTMC may enhance the understanding of its pathogenesis and provide important information for a new diagnosis method and treatment plan. In this study, high resolution magic angle spin (HRMAS) spectroscopy and 1 H-nuclear magnetic resonance ( 1 H-NMR) spectroscopy were used to screen metabolic changes in thyroid tissues and plasma from PTMC patients respectively. The results revealed reduced levels of fatty acids and elevated levels of several amino acids (phenylalanine, tyrosine, lactate, serine, cystine, lysine, glutamine/glutamate, taurine, leucine, alanine, isoleucine and valine) in thyroid tissues, as well as reduced levels of amino acids such as valine, tyrosine, proline, lysine, leucine and elevated levels of glucose, mannose, pyruvate and 3-hydroxybutyrate in plasma, are involved in the metabolic alterations in PTMC. In addition, a receiver operating characteristic (ROC) curve model for PTMC prediction was able to classify cases with good sensitivity and specificity using 9 significant changed metabolites in plasma. This work illustrates that the NMR-based metabolomics approach is capable of providing more sensitive diagnostic results and more systematic therapeutic information for PTMC.

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Authentication of beef production systems using a metabolomic-based approach

Cited by 44 publications

References 36 publications

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

Analysis of Raman spectra for the verification of Australian grass‐ and grain‐fed beef using principal component analysis and partial least square models

Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach

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