[1] [1] Musumeci G, Trovato F M, Pichler K, et al. Extravirgin olive oil diet and mild physical activity prevent cartilage degeneration in an osteoarthritis model: an in vivo and in vitro study on lubricin expression[J]. Journal of Nutritional Biochemistry, 2013, 24(12): 2064-2075.

[2] [2] Loganathan R, Nagapan G, Teng K T, et al. Diets enriched with palm olein, cocoa butter, and extra virgin olive oil exhibited similar lipid response: a randomized controlled study in young healthy adults[J]. Nutrition Research, 2022, 105: 113-125.

[7] [7] Wang H P, Wan X. Effect of chlorophyll fluorescence quenching on quantitative analysis of adulteration in extra virgin olive oil[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2021, 248, 119183.

[8] [8] Wang H P, Xin Y J, Wan X. Spectral detection technology of vegetable oil: Spectral analysis of porphyrins and terpenoids[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2021, 261, 119965.

[9] [9] Steven W, Narciso C, Artificial Neural Networks, Editor(s): Robert A. Meyers, Encyclopedia of Physical Science and Technology (Third Edition)[M], Academic Press, 2003: 631-645.

[10] [10] Biancamaria S, Paola G, Marco T, et al. Combining untargeted profiling of phenolics and sterols, supervised multivariate class modelling and artificial neural networks for the origin and authenticity of extra-virgin olive oil: A case study on Taggiasca Ligure[J]. Food Chemistry, 2023, 404, Part A, 134543.

[11] [11] Wu X, Gao S, Niu Y, et al. Identification of olive oil in vegetable blend oil by one-dimensional convolutional neural network combined with Raman spectroscopy[J]. Journal of Food Composition and Analysis, 2022, 108, 104396.

[12] [12] Venturinia F, Sperti M, Michelucci U, et al. Physico-chemical properties extraction from the fluorescence spectrum with 1D-convolutional neural networks: application to olive oil[J]. 2022, ArXiv, abs/2203.07229.

[13] [13] Wu X, Gao S, Niu Y, et al. Quantitative analysis of blended corn-olive oil based on Raman spectroscopy and one-dimensional convolutional neural network[J]. Food Chemistry, 2022, 385: 132655.

[14] [14] Pradana-Lopez S, Perez-Calabuig A M, Cancilla J C, et al. Convolutional capture of the expansion of extra virgin olive oil droplets to quantify adulteration[J]. Food Chemistry, 2022, 368: 130765.

[15] [15] Cosio M S, Ballabio D, Benedetti S, et al. Geographical origin and authentication of extra virgin olive oils by an electronic nose in combination with artificial neural networks[J]. Analytica Chimica Acta, 2006, 567(2): 202-210.

[16] [16] Stefas D, Gyftokostas N, Kourelias P, et al. Discrimination of olive oils based on the olive cultivar origin by machine learning employing the fusion of emission and absorption spectroscopic data[J]. Food Control, 2021, 130(19): 108318.

[17] [17] Scatigno C, Festa G. A first elemental pattern and geo-discrimination of Italian EVOO by energy dispersive X-ray fluorescence and chemometrics[J]. Microchemical Journal: Devoted to the Application of Microtechniques in all Branches of Science, 2021, 171, 106863.

[18] [18] Fang P P, Wang H P, Wan X. Olive oil authentication based on quantitative -carotene Raman spectra detection[J]. Food Chemistry, 2022, 397, 133763.

[19] [19] Lu C H, Li B Q, Jing Q, et al. A classification and identification model of extra virgin olive oil adulterated with other edible oils based on pigment compositions and support vector machine[J]. Food Chemistry, 2023, 420, 136161.

[20] [20] Portarena S, Anselmi C, Leonardi L. et al. Lutein/-carotene ratio in extra virgin olive oil: An easy and rapid quantification method by Raman spectroscopy[J]. Food Chemistry, 2023, 404(Pt B), 134748.

[21] [21] Senizza B, Ganugi P, Trevisan M. et al. Combining untargeted profiling of phenolics and sterols, supervised multivariate class modelling and artificial neural networks for the origin and authenticity of extra-virgin olive oil: A case study on Taggiasca Ligure[J]. Food Chemistry, 2023, 404(Pt A), 134543.

[22] [22] Rotich V, Riza D F A, Giametta F. et al. Thermal oxidation assessment of Italian extra virgin olive oil using an UltraViolet (UV) induced fluorescence imaging system[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2020, 237, 118373.

[23] [23] Gulsah O S. Detection of adulteration in extra virgin olive oil by selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics[J]. Food Control, 2020, 118, 107433.

[24] [24] Caterina A, Nelson M. Food genomics for the characterization of PDO and PGI virgin olive oils[J]. European Journal of Lipid Science and Technology, 2019, 121(3), 1800132.

[25] [25] Ning X R, Ivan W S, Laurent D. Chromatogram baseline estimation and denoising using sparsity (BEADS)[J]. Chemometrics and Intelligent Laboratory Systems, 2014, 139(15), 156-167.

[27] [27] Johnson R D. NIST Computational Chemistry Comparison and Benchmark Database[DB/OL]. (2022-5-22)[2023-10-8]. http://cccbdb.nist.gov/.

[29] [29] Zhang X F, Zou M Q, Qi X H, et al. Quantitative detection of adulterated olive oil by Raman spectroscopy and chemometrics[J]. Journal of Raman Spectroscopy, 2011, 42(9): 1784-1788.

[30] [30] Barros I H. A. S., Santos L P., Filgueiras P R, et al. Design experiments to detect and quantify soybean oil in extra virgin olive oil using portable Raman spectroscopy[J]. Vibrational Spectroscopy, 2021, 116, 103294.