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Nguyen DD, Solah VA, Hunt W, Daubney S, Meek J, Gray N, Du X. Fatty acid profiling of Western Australian pasteurised milk using gas chromatography-mass spectrometry. Food Res Int 2024; 180:114050. [PMID: 38395566 DOI: 10.1016/j.foodres.2024.114050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 01/14/2024] [Accepted: 01/24/2024] [Indexed: 02/25/2024]
Abstract
The fatty acid composition of Western Australian commercial pasteurised milk was profiled using gas chromatography-mass spectrometry (GC-MS). A total of 31 fatty acids (FA) were identified in the milk samples. The majority of FA were medium-chain fatty acids (MCFA) with 6-13 carbon atoms and long-chain fatty acids (LCFA) with 14-20 carbon atoms. The results of principal component analysis (PCA) showed significant differences in the levels of MCFA and LCFA in the different milk samples. The levels of MCFA and LCFA ranged from 10.09 % to 12.12% and 87.88% to 89.91% of total FA, respectively. C10:0 and C12:0 were the major components of MCFA comprising 3.46% and 4.22% of total FA, while C16:0 and C18:1 (cis 9-octadecenoic acid) represented the majority of LCFA with the levels of 26.18% and 23.34% of total FA, respectively. This study provides new insight into the FA composition of Western Australian pasteurised milk and differences in FA profiles which influence human health.
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Affiliation(s)
- Duc Doan Nguyen
- Food Science and Nutrition, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Western Australia 6150, Australia; Food Science and Nutrition, School of Medical, Molecular & Forensic Sciences, College of Environmental & Life Sciences, Murdoch University, Western Australia 6150, Australia.
| | - Vicky Ann Solah
- Food Science and Nutrition, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Western Australia 6150, Australia; Food Science and Nutrition, School of Medical, Molecular & Forensic Sciences, College of Environmental & Life Sciences, Murdoch University, Western Australia 6150, Australia
| | - Wendy Hunt
- Food Science and Nutrition, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Western Australia 6150, Australia; Food Science and Nutrition, School of Medical, Molecular & Forensic Sciences, College of Environmental & Life Sciences, Murdoch University, Western Australia 6150, Australia
| | - Suzanne Daubney
- Bannister Downs Dairy, Northcliffe, Western Australia 6262, Australia
| | - Julie Meek
- Food Science and Nutrition, School of Medical, Molecular & Forensic Sciences, College of Environmental & Life Sciences, Murdoch University, Western Australia 6150, Australia
| | - Nicola Gray
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Western Australia 6150, Australia
| | - Xin Du
- Harry Butler Institute, Murdoch University, Western Australia 6150, Australia
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Chico Retrato MD, Qiu S, Lundquist A, Muratovic AZ, Rad FM, Ubhayasekera SJKA, Bergquist J. Simultaneous determination of 22 fatty acids in total parenteral nutrition (TPN) components by gas chromatography-mass spectrometry (GC-MS). ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:2480-2489. [PMID: 37183597 DOI: 10.1039/d3ay00407d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Evaluating total parenteral nutrition (TPN) products for quality assurance and quality control is crucial due to the chemical complexity of its components. With the advent of exploring different approaches for analysing TPN components using tandem mass spectrometry techniques, there is still a need for a robust and reproducible method for industrial routine analyses. This study allows simple, simultaneous determination of 22 fatty acids (FAs) commonly found in TPN components using gas chromatography-mass spectrometry (GC-MS). Five different transesterification techniques were applied for the FA standards and the sodium methoxide in methanol-dimethyl carbonate method was selected due to its good methylation efficiency. Fatty acid methyl esters (FAMEs) were separated in gas chromatography using an HP-5MS UI column with helium as the carrier gas. Mass spectrometry was used to fragment and quantify FAMEs using electron ionization (EI) and selected ion monitoring (SIM) mode. The analytical method was evaluated using the guidelines from the US Food and Drug Agency (FDA) and European Medicines Agency (EMA) in compliance with the International Council for Harmonization (ICH) document Q2(R2). Correlation coefficients (R2) of the calibration curves for FAMEs were 0.99, except for C24:1 n-9 and C24:0, both R2 = 0.98. The limits of detection (LOD) and quantification (LOQ) were found to be 1.69 μg mL-1 and 5.14 μg mL-1, respectively. The linear range was from 3.10-179.9 μg mL-1 for most FAMEs, except for C18:1 n-7 (3.96-224.9 μg mL-1) and C18:1 n-9 (6.30-349.57 μg mL-1). The intra-day and inter-day precision coefficients of variance (CV) of the method were less than 11.10% and 11.30%, respectively. Freeze-thaw cycles and ambient temperature measurements were performed for assessing sample stability. The validated method was applied to analyse major TPN components-fish and olive oils, and an unidentified lipid sample. The presented GC-MS method is simple and robust in the identification and quantification of 22 fatty acids simultaneously in the tested TPN components.
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Affiliation(s)
- Mark Dennis Chico Retrato
- Department of Chemistry - Biomedical Center, Analytical Chemistry and Neurochemistry, Uppsala University, Uppsala, Sweden.
- Innovation and Development Department, Fresenius-Kabi, Uppsala, Sweden
| | - Siyuan Qiu
- Department of Chemistry - Biomedical Center, Analytical Chemistry and Neurochemistry, Uppsala University, Uppsala, Sweden.
| | - Anna Lundquist
- Innovation and Development Department, Fresenius-Kabi, Uppsala, Sweden
| | | | - Farshid Mashayekhy Rad
- Department of Chemistry - Biomedical Center, Analytical Chemistry and Neurochemistry, Uppsala University, Uppsala, Sweden.
| | - S J Kumari A Ubhayasekera
- Department of Chemistry - Biomedical Center, Analytical Chemistry and Neurochemistry, Uppsala University, Uppsala, Sweden.
| | - Jonas Bergquist
- Department of Chemistry - Biomedical Center, Analytical Chemistry and Neurochemistry, Uppsala University, Uppsala, Sweden.
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Arroyo-Cerezo A, Jimenez-Carvelo AM, Gonzalez-Casado A, Ruisanchez I, Cuadros-Rodriguez L. The potential of the spatially offset Raman spectroscopy (SORS) for implementing rapid and non-invasive in-situ authentication methods of plastic-packaged commodity foods – Application to sliced cheeses. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Stable isotope ratio analysis of lactose as a possible potential geographical tracer of milk. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Arifah MF, Irnawati, Ruslin, Nisa K, Windarsih A, Rohman A. The Application of FTIR Spectroscopy and Chemometrics for the Authentication Analysis of Horse Milk. INTERNATIONAL JOURNAL OF FOOD SCIENCE 2022; 2022:7643959. [PMID: 35242875 PMCID: PMC8888094 DOI: 10.1155/2022/7643959] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/18/2022] [Accepted: 01/25/2022] [Indexed: 12/02/2022]
Abstract
Expensive milk such as horse's milk (HM) may be the target of adulteration by other milk such as goat's milk (GM) and cow's milk (CM). FTIR spectroscopy in combination with chemometrics of linear discriminant analysis (LDA) and multivariate calibrations of partial least square regression (PLSR) and principal component regression (PCR) was used for authentication of HM from GM and CM. Milk was directly subjected to attenuated total reflectance (ATR) spectral measurement at midinfrared regions (4000-650 cm-1). Results showed that LDA could make clear discrimination between HM and HM adulterated with CM and GM without any misclassification observed. PLSR using 2nd derivative spectra at 3200-2800 and 1300-1000 cm-1 provided the best model for the relationship between actual values of GM and FTIR predicted values than PCR. At this condition, R 2 values for calibration and validation models obtained were 0.9995 and 0.9612 with RMSEC and RMSEP values of 0.0093 and 0.0794. PLSR using normal FTIR spectra at 3800-3000 and 1500-1000 cm-1 offered R 2 for the relationship between actual values of CM and FTIR predicted values of >0.99 in calibration and validation models with low errors of RMSEC of 0.0164 and RMSEP of 0.0336 during authentication of HM from CM. Therefore, FTIR spectroscopy in combination with LDA and PLSR is an effective method for authentication of HM from GM and CM.
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Affiliation(s)
- Mitsalina Fildzah Arifah
- Center of Excellence, Institute for Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
| | - Irnawati
- Faculty of Pharmacy, Halu Oleo University, Kendari 93232, Indonesia
| | - Ruslin
- Faculty of Pharmacy, Halu Oleo University, Kendari 93232, Indonesia
| | - Khoirun Nisa
- Research Division for Natural Product Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia
| | - Anjar Windarsih
- Research Division for Natural Product Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia
| | - Abdul Rohman
- Center of Excellence, Institute for Halal Industry and Systems, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
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Multivariate modelling of milk fatty acid profile to discriminate the forages in dairy cows' ration. Sci Rep 2021; 11:23201. [PMID: 34853357 PMCID: PMC8636629 DOI: 10.1038/s41598-021-02600-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 11/15/2021] [Indexed: 12/18/2022] Open
Abstract
Although there are many studies on the importance of fatty acids (FA) in our diet and on the influence of dairy diets on FA metabolism, only a few investigate their predictive capacity to discriminate the type, amount and conservation method of farm forages. This research quantifies differences in milk FA concentrations and, using a supervised factorial discriminant analysis, assesses potential biomarkers when replacing maize with other silages, grass/lucerne hays or fresh grass. The statistical modelling identified three main clusters of milk FA profiles associated with silages, hays and fresh grass as dominant roughages. The main implication of a dairy cow feeding system based on poliphytic forages from permanent meadows is enhancing milk’s nutritional quality due to an increase in beneficial omega-3 polyunsaturated FA, conjugated linoleic acids and odd chain FA, compared to feeding maize silage. The study also identified a small but powerful and reliable pool of milk FA that can act as biomarkers to authenticate feeding systems: C16:1 c-9, C17:0, C18:0, C18:3 c-9, c-12, c-15, C18:1 c-9, C18:1 t-11 and C20:0.
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Use of GC–MS and 1H NMR low-level data fusion as an advanced and comprehensive metabolomic approach to discriminate milk from dairy chains based on different types of forage. Int Dairy J 2021. [DOI: 10.1016/j.idairyj.2021.105174] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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