Abstract
The multiple assignment recovered analysis (MARA) on nuclear magnetic resonance (NMR) spectra is here presented with the aim to provide the quantitative label of chemical mixtures such as foodstuff. The method takes advantage from the multiple NMR signals generated by any chemical; these will be all proportional to the concentration of the parent compound. In a well-known system, the selection of many integration regions enables the development of simple relationships fulfilled just by specific quantitative values of the expected components. As long as the number of equations is bigger than the known quantitative variables, MARA-NMR best-fitting algorithm will be suitably designed to output trustworthy and robust results. This is definitely demonstrated for the extra-virgin olive oil (EVOO) taken as case study: MARA-NMR showed consistency with traditional analytical measurements over 30 specimens recording satisfactory repeatability. The minimization procedure is applied by tuning the quantitative variables; these are affecting the function ρ which represents the experimental lapse from the corresponding theoretical dataset. MARA-NMR is an effective, innovative, and quick method for food labeling; unlike other analytical techniques, it is self-consistent smoothing out random instrumental outliers or unpredictable anomalies. MARA is customized in order to be versatile paving the way for new updated, extended, and refined labeling protocols and also for the extension of this approach on the study of whichever matrix.


Similar content being viewed by others
References
Alonso-Salces RM, Moreno-Rojas JM, Holland MV, Reniero F, Guillou C, Héberger C (2010) Virgin olive oil authentication by multivariate analyses of 1H NMR fingerprints and δ13C and δ2H data. J Agric Food Chem 58:5586–5596
Barison A, Pereira da Silva CW, Ramos Campos F, Simonelli F, Lenz CA, Ferreira AG (2010) A simple methodology for the determination of fatty acid composition in edible oils through 1H NMR spectroscopy. Magn Reson Chem 48:642–650
Carvalho MS, Mendonça MA, Pinho DMM, Resckc IS, Suarez PAZ (2012) Chromatographic analyses of fatty acid methyl esters by HPLC-UV and GC-FID. J Braz Chem Soc 23(4):763–769
Castejón D, Mateos-Aparicio I, Molero MD, Cambero MI, Herrera A (2014) Evaluation and optimization of the analysis of fatty acid types in edible oils by 1H-NMR. Food Anal Methods 7:1285–1297
Castejón D, Fricke P, Cambero MI, Herrera A (2016) Automatic 1H-NMR screening of fatty acid composition in edible oils. Nutrients 8:93. https://doi.org/10.3390/nu8020093
Cevallos-Cevallos JM, Reyes-De-Corcueraa JI, Etxeberria E, Danyluka MD, Rodrick GE (2009) Metabolomic analysis in food science: a review. Trends Food Sci Technol 20:557–566
Dugo G, Rotondo A, Mallamace D, Cicero N, Salvo A, Rotondo E, Corsaro C (2015) Enhanced detection of aldehydes in Extra-Virgin Olive Oil by means of band selective NMR spectroscopy. Physica A 420:258–264
EU No. 29/2012 Commission Implementing Regulation. Available online: http://eur-lex.europa.eu/legalcontent/EN/ALL/?uri=CELEX%3A32012R0029 (accessed on 27 July 2018)
EU No. 1833/2015 (2015) European Union Commission. Off. Regulation EU no. 1833/2015 on the characteristics of olive oil and olive-residue oil and on the relevant methods of analysis. Off J Eur Communities L266:29–52
Jiang B, Xiao M, Liu HL, Zhou ZM, Mao XA, Liu ML (2008) Optimized quantitative DEPT and quantitative POMMIE experiments for C-13 NMR. Anal Chem 80:8293–8298. https://doi.org/10.1021/ac8015455
Laghi L, Picone G, Capozzi F (2014) Nuclear magnetic resonance for foodomics beyond food analysis. Trends Anal Chem 59:93–102
Laincer F, Iaccarino N, Amato J, Pagano B, Pagano A, Tenore G, Tamendjari A, Rovellini P, Venturini S, Bellan G, Ritieni A, Mannina L, Novellino E, Randazzo A (2016) Characterization of monovarietal extra virgin olive oils from the province of Béjaïa (Algeria). Food Res Int 89:1123–1133
Liland KH (2011) Multivariate methods in metabolomics – from pre-processing to dimension reduction and statistical analysis. Tr Anal Chem 30(6):827–841
Mannina L, Sobolev AP (2011) High resolution NMR characterization of olive oils in terms of quality, authenticity and geographical origin. Magn Reson Chem 49:S3–S11
Mannina L, Luchinat C, Patumi M, Emanuele MC, Rossi E, Segre A (2000) Concentration dependence of 13C NMR spectra of triglycerides: implications for the NMR analysis of olive oils. Magn Reson Chem 38:886–890
Marcone MF, Wang S, Albabish W, Nie S, Somnarain D, Hill A (2013) Diverse food-based applications of nuclear magnetic resonance (NMR) technology. Food Res Int 51:729–747
Monakhova YB, Kuballa T, Lachenmeier DW (2013) Chemometric methods in NMR spectroscopic analysis of food products. J Anal Chem 68(9):755–766
Monakhova YB, Tsikin AM, Kuballa T, Lachenmeier DW, Mushtakova SP (2014) Independent component analysis (ICA) algorithms for improved spectral deconvolution of overlapped signals in 1H NMR analysis: application to foods and related products. Magn Reson Chem 52:231–240
Naccari C, Rando R, Salvo A, Donato D, Bartolomeo G, Mangano V, Lo Turco V, Dugo G (2017) Study on the composition and quality of several Sicilian EVOOs (harvesting year 2015). Riv Ital Sostanze Gr 94:231–237
Pauli GF, Jaki BU, Lankin DC (2005) Quantitative 1H NMR: development and potential of a method for natural products analysis. J Nat Prod 68:133–149
Rongai D, Sabatini N, Del Coco L, Perri E, Del Re P, Simone N, Marchegiani D, Fanizzi FP (2017) 1H NMR and multivariate analysis for geographic characterization of commercial extra virgin olive oil: a possible correlation with climate data. Foods 6:96. https://doi.org/10.3390/foods6110096
Retief L, McKenzie JM, Koch KR (2009) A novel approach to the rapid assignment of 13C NMR spectra of major components of vegetable oils such as avocado, mango kernel and macadamia nut oils. Magn Reson Chem 47:771–781
Rotondo A, Salvo A, Gallo V, Rastrelli L, Dugo G (2017) Quick unreferenced NMR quantification of squalene in vegetable oils. Eur J Lipid Sci Technol 119(11):1–6. https://doi.org/10.1002/ejlt.201700151
Rotondo A, Salvo A, Giuffrida D, Dugo G., Rotondo E. (2011) NMR analysis of aldehydes in sicilian extra-virgin olive oils by DPFGSE techniques. Atti Accademia Peloritana dei Pericolanti ISSN: 1825–1242, 89(C1A8901002):1–7; https://doi.org/10.1478/C1A8901002
Ruiz-Aracama A, Goicoechea E, Guillén MD (2017) Direct study of minor extra-virgin olive oil components without any sample modification. 1H NMR multisupression experiment: a powerful tool. Food Chem 228:301–314
Salvo A, Rotondo A, La Torre GL, Cicero N, Dugo G (2017) Determination of 1,2/1,3-diglycerides in Sicilian extra-virgin olive oils by 1H-NMR over a one-year storage period. Nat Prod Res 31:822–828
Simmler C, Napolitano JG, McAlpine JB, Chen S-N, Pauli GF (2014) Universal quantitative NMR analysis of complex natural samples. Curr Opin Biotechnol 25:51–59
Vlahov G, Schiavone C, Simone N (2001) Quantitative 13C NMR method using the DEPT pulse sequence for the determination of the geographical origin (DOP) of olive oils. Magn Reson Chem 39:689–695
Zhang H, Wang Z, Liu O (2015) Development and validation of a GC–FID method for quantitative analysis of oleic acid and related fatty acids. J Pharm Analysis 5:223–230
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
Archimede Rotondo declares that he has no conflict of interest; Luisa Mannina declares that she has no conflict of interest; Andrea Salvo declares that he has no conflict of interest.
Ethical Approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed Consent
Not applicable.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Rotondo, A., Mannina, L. & Salvo, A. Multiple Assignment Recovered Analysis (MARA) NMR for a Direct Food Labeling: the Case Study of Olive Oils. Food Anal. Methods 12, 1238–1245 (2019). https://doi.org/10.1007/s12161-019-01460-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12161-019-01460-4