Intentional addition of cheaper oils into olive oil (OL) for economic motivation has been becoming particularly attractive due to the favorable flavor and healthy characteristics of OL, but it is very challenging to identify such adulteration because of the compositional similarity between the oils. In this study, low-field nuclear magnetic resonance (LF-NMR) in combination with multivariate statistical analysis was used to identify the adulterated olive oil with different rations of soybean oil (SO) or corn oil (CO). Significant differences in multi-component relaxation time (T21 and T22) and peak area proportions (S21 and S22) were detected between pure and adulterated OL. As the adulteration ratio increased, S21 and S22 changed linearly, while T21 and T22 only changed slightly. The detection by gas chromatography suggested that T21 and T22 values might be influenced by triacylglycerol components, and the changes of S21 and S22 were attributed to the varied mono-/polyunsaturated fatty acids. In the relaxation time-based pattern recognition models, the authentic OL could be correctly identified from the adulterated ones with at least 20% of SO or CO by principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA). The multi-blended oil could be 100% classified by orthogonal partial least squares discriminant analysis (OPLS-DA) and 98.8% classified by principal component analysis followed by linear discriminant analysis (PCA-LDA) when the adulteration ratio was above 30%, demonstrating a promising technique of LF-NMR combined with pattern recognition in rapid screening of the edible oils.
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Adam BM, Boulard M, Riaublanc A, Mariette F (2011) Evolution of fat crystal network microstructure followed by NMR. J Agric Food Chem 59:1767–1773. https://doi.org/10.1021/jf102734d
Azizian H, Wang SC, Li XQ, Kramer JKG (2018) Improvement of the Fourier transform near infrared method to evaluate extra virgin olive oils by analyzing 1,2-diacylglycerols and 1,3-diacylglycerols and adding unesterified fatty acids. Lipids 53:1097–1112. https://doi.org/10.1002/lipd.12113
Battino M, Forbes-Hernandez TY, Gasparrini M et al (2019) Relevance of functional foods in the Mediterranean diet: the role of olive oil, berries and honey in the prevention of cancer and cardiovascular diseases. Crit Rev Food Sci Nutr 59:893–920. https://doi.org/10.1080/10408398.2018.1526165
Cai Y, Zhang WW, Jin J, Yang X, You X, Yan H, Wang L, Chen J, Xu J, Chen W, Chen X, Ma J, Tang X, Kong F, Zhu X, Wang G, Jiang L, Terzaghi W, Wang C, Wan J (2018) OsPKp alpha1 encodes a plastidic pyruvate kinase that affects starch biosynthesis in the rice endosperm. J Integr Plant Biol 60:1097–1118. https://doi.org/10.1111/jipb.12692
Cao XH, Zhang M, Mujumdar AS, Zhong QF, Wang ZS (2018) Measurement of water mobility and distribution in vacuum microwave-dried barley grass using Low-Field-NMR. Dry Technol 36:1892–1899. https://doi.org/10.1080/07373937.2018.1449753
Chen L, Tian YQ, Sun BH, Wang JP, Tong QY, Jin ZY (2017) Rapid, accurate, and simultaneous measurement of water and oil contents in the fried starchy system using low-field NMR. Food Chem 233:525–529. https://doi.org/10.1016/j.foodchem.2017.04.147
Duarte AM, Aquino JS, Queiroz N, Dantas DLL, Maciel GS, Souza AL (2018) A comparative study of the thermal and oxidative stability of moringa oil with olive and canola oils. J Therm Anal Calorim 134:1943–1952. https://doi.org/10.1007/s10973-018-7651-7
Fan SX, Zhong QD, Fauhl-Hassek C, Pfister MKH, Horn B, Huang ZB (2018) Classification of Chinese wine varieties using 1H NMR spectroscopy combined with multivariate statistical analysis. Food Control 88:113–122. https://doi.org/10.1016/j.foodcont.2017.11.002
Filoda PF, Fetter LF, Fornasier F, Schneider RCS, Helfer GA, Tischer B, Teichmann A, da Costa AB (2019) Fast methodology for identification of olive oil adulterated with a mix of different vegetable oils. Food Anal Methods 12:293–304. https://doi.org/10.1007/s12161-018-1360-5
Foscolou A, Critselis E, Panagiotakos D (2018) Olive oil consumption and human health: a narrative review. Maturitas 118:60–66. https://doi.org/10.1016/j.maturitas.2018.10.013
Gai SM, Zhang ZH, Zou YF, Liu DY (2019) Effects of hydrocolloid injection on the eating quality of pork analyzed based on low-field nuclear magnetic resonance (LF-NMR). J Food Qual 2019:3536824. https://doi.org/10.1155/2019/3536824
Gerhardt N, Schwolow S, Rohn S, Perez-Cacho PR, Galan-Soldevilla H, Arce L, Weller P (2019) Quality assessment of olive oils based on temperature-ramped HS-GC-IMS and sensory evaluation: comparison of different processing approaches by LDA, kNN, and SVM. Food Chem 286:307–308. https://doi.org/10.1016/j.foodchem.2019.01.164
Gil-Solsona R, Raro M, Sales C, Lacalle L, Díaz R, Ibáñez M, Beltran J, Sancho JV, Hernández FJ (2016) Metabolomic approach for extra virgin olive oil origin discrimination making use of ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Food Control 70:350–359. https://doi.org/10.1016/j.foodcont.2016.06.008
Gouilleux B, Marchand J, Charrier B, Remaud GS, Giraudeau P (2018) High-throughput authentication of edible oils with benchtop Ultrafast 2D NMR. Food Chem 244:153–158. https://doi.org/10.1016/j.foodchem.2017.10.016
Guyader S, Thomas F, Portaluri V, Jamin E, Akoka S, Silvestre V, Remaud G (2018) Authentication of edible fats and oils by non-targeted 13C INEPT NMR spectroscopy. Food Control 91:216–224. https://doi.org/10.1016/j.foodcont.2018.03.046
Huang LL, Song YK, Kamal T et al (2017) A non-invasive method based on low-field NMR to analyze the quality changes in caviar from hybrid sturgeon (Huso dauricus, Acipenser schrenckiid). J Food Process Preserv 41:e13256. https://doi.org/10.1111/jfpp.13256
Jiang XY, Li C, Chen QQ, Weng XC (2018) Comparison of 19F and 1H NMR spectroscopy with conventional methods for the detection of extra virgin olive oil adulteration. Grasas Aceites 69:8. https://doi.org/10.3989/gya.1221172
Lastra MM, Izquierdo M, Torreblanca ZA, Aroca SR, Cancilla JC, Sepulveda DJ, Torrecilla JS (2019) Cognitive fluorescence sensing to monitor the storage conditions and locate adulterations of extra virgin olive oil. Food Control 103:48–58. https://doi.org/10.1016/j.foodcont.2019.03.033
Li M, Li B, Zhang WJ (2018) Rapid and non-invasive detection and imaging of the hydrocolloid-injected prawns with low-field NMR and MRI. Food Chem 242:16–21. https://doi.org/10.1016/j.foodchem.2017.08.086
Li MY, Wang HB, Zhao GM, Qiao M, Li M, Sun L, Gao X, Zhang J (2014) Determining the drying degree and quality of chicken jerky by LF-NMR. J Food Eng 139:43–49. https://doi.org/10.1016/j.jfoodeng.2014.04.015
Li XX, Liu SC, Su WM, Cai LY, Li JR (2017) Physical quality changes of precooked Chinese shrimp Fenneropenaeus chinensis and correlation to water distribution and mobility by low-field NMR during frozen storage. J Food Process Preserv 41:e13220. https://doi.org/10.1111/jfpp.13220
Liu J, Feng XY, Wang DS (2019) Determination of water content in crude oil emulsion by LF-NMR CPMG sequence. Pet Sci Technol 37:1123–1135. https://doi.org/10.1080/10916466.2019.1578795
Marigheto N, Duarte S, Hills BP (2005) NMR relaxation study of avocado quality. Appl Magn Reson 29:687–701. https://doi.org/10.1007/bf03166344
Meiri N, Berman P, Colnago LA, Moraes TB, Linder C, Wiesman Z (2015) Liquid-phase characterization of molecular interactions in polyunsaturated and n-fatty acid methyl esters by 1H low-field nuclear magnetic resonance. Biotechnol Biofuels 8:96. https://doi.org/10.1186/s13068-015-0280-5
Merchak N, Rizk T, Silvestre V, Remaud GS, Bejjani J, Akoka S (2018) Olive oil characterization and classification by 13C NMR with a polarization transfer technique: a comparison with gas chromatography and 1H NMR. Food Chem 245:717–723. https://doi.org/10.1016/j.foodchem.2017.12.005
Micklander E, Peshlov B, Purslow PP, Engelsen SB (2002) NMR-cooking: monitoring the changes in meat during cooking by low-field 1H NMR. Trends Food Sci Technol 13:341–346. https://doi.org/10.1016/s0924-2244(02)00163-2
Oates MJ, Fox P, Sanchez RL, Carbonell BA, Ruiz CA (2018) DFT based classification of olive oil type using a sinusoidally heated, low cost electronic nose. Comput Electron Agric 155:348–358. https://doi.org/10.1016/j.compag.2018.10.026
Ozdemir IS, Dag C, Makuc D, Ertas E, Plavec J, Bekiroglu S (2018) Characterisation of the Turkish and Slovenian extra virgin olive oils by chemometric analysis of the presaturation 1H NMR spectra. LWT-Food Sci Technol 92:10–15. https://doi.org/10.1016/j.lwt.2018.02.015
Pereira CG, Leite AIN, Andrade J, Bell MJV, Anjos V (2019) Evaluation of butter oil adulteration with soybean oil by FT-MIR and FT-NIR spectroscopies and multivariate analyses. LWT-Food Sci Technol 107:1–8. https://doi.org/10.1016/j.lwt.2019.02.072
Portarena S, Anselmi C, Zadra C, Farinelli D, Famiani F, Baldacchini C, Brugnoli E (2019) Cultivar discrimination, fatty acid profile and carotenoid characterization of monovarietal olive oils by Raman spectroscopy at a single glance. Food Control 96:137–145. https://doi.org/10.1016/j.foodcont.2018.09.011
Psaltopoulou T, Naska A, Orfanos P, Trichopoulos D, Mountokalakis T, Trichopoulou A (2004) Olive oil, the Mediterranean diet, and arterial blood pressure: the Greek European prospective investigation into cancer and nutrition (EPIC) study American. J Clin Nutr 80:1012–1018
Sales C, Cervera MI, Gil R, Portoles T, Pitarch E, Beltran J (2017) Quality classification of Spanish olive oils by untargeted gas chromatography coupled to hybrid quadrupole-time of flight mass spectrometry with atmospheric pressure chemical ionization and metabolomics-based statistical approach. Food Chem 216:365–373. https://doi.org/10.1016/j.foodchem.2016.08.033
Sales C, Portoles T, Johnsen LG, Danielsen M, Beltran J (2019) Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC-MS and multivariate statistical-based approach. Food Chem 271:488–496. https://doi.org/10.1016/j.foodchem.2018.07.200
Santos PM, Kock FVC, Santos MS, Lobo CMS, Carvalho AS, Colnago LA (2016) Non-invasive detection of adulterated olive oil in full bottles using time-domain NMR relaxometry. J Braz Chem Soc 28:385–390. https://doi.org/10.5935/0103-5053.20160188
Shi T, Zhu MT, Zhou XY, Huo X, Long Y, Zeng XZ, Chen Y (2019) 1H NMR combined with PLS for the rapid determination of squalene and sterols in vegetable oils. Food Chem 287:46–54. https://doi.org/10.1016/j.foodchem.2019.02.072
Sun YN, Zhang M, Fan DC (2019) Effect of ultrasonic on deterioration of oil in microwave vacuum frying and prediction of frying oil quality based on low field nuclear magnetic resonance (LF-NMR). Ultrason Sonochem 51:77–89. https://doi.org/10.1016/j.ultsonch.2018.10.015
Wang C, Su GQ, Wang X, Nie SD (2019) Rapid assessment of deep frying oil quality as well as water and fat contents in french fries by low-field nuclear magnetic resonance. J Agric Food Chem 67:2361–2368. https://doi.org/10.1021/acs.jafc.8b05639
Yalcin H, Toker OS, Ozturk I, Dogan M, Kisi O (2012) Prediction of fatty acid composition of vegetable oils based on rheological measurements using nonlinear models. Eur J Lipid Sci Technol 114:1217–1224. https://doi.org/10.1002/ejlt.201200040
Yang YX, Wang LJ, Wang SM, Liang S, Chen A, Tang H, Chen L, Deng F (2013) Study of metabonomic profiles of human esophageal carcinoma by use of high-resolution magic-angle spinning 1H NMR spectroscopy and multivariate data analysis. Anal Bioanal Chem 405:3381–3389. https://doi.org/10.1007/s00216-013-6774-8
Zang X, Lin ZY, Zhang T, Wang H, Cong S, Song Y, Li Y, Cheng S, Tan M (2017) Non-destructive measurement of water and fat contents, water dynamics during drying and adulteration detection of intact small yellow croaker by low field NMR. J Food Meas Charact 11:1550–1558. https://doi.org/10.1007/s11694-017-9534-1
Zhang Q, Saleh ASM, Shen Q (2013) Discrimination of edible vegetable oil adulteration with used frying oil by low field nuclear magnetic resonance. Food Bioprocess Technol 6:2562–2570. https://doi.org/10.1007/s11947-012-0826-5
Zheng X, Zhao YR, Wu HF, Dong JY, Feng JH (2016) Origin identification and quantitative analysis of honeys by nuclear magnetic resonance and chemometric techniques. Food Anal Methods 9:1470–1479. https://doi.org/10.1007/s12161-015-0325-1
Zhu WR, Wang X, Chen LH (2017) Rapid detection of peanut oil adulteration using low-field nuclear magnetic resonance and chemometrics. Food Chem 216:268–274. https://doi.org/10.1016/j.foodchem.2016.08.051
This work was supported by the National Natural Science Foundation of China (grant No. 82072015, 31671920) and the Natural Science Foundation of Fujian Province of China (grant No. 2018Y0078).
This article does not contain any studies with human participants or animals performed by any of the authors.
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Wang, S., Lai, G., Lin, J. et al. Rapid Detection of Adulteration in Extra Virgin Olive Oil by Low-Field Nuclear Magnetic Resonance Combined with Pattern Recognition. Food Anal. Methods (2021). https://doi.org/10.1007/s12161-021-01973-x
- Olive oil
- Low-field nuclear magnetic resonance
- Pattern recognition
- Gas chromatography