{"id":58,"date":"2023-03-22T10:05:24","date_gmt":"2023-03-22T10:05:24","guid":{"rendered":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/?page_id=58"},"modified":"2023-12-09T18:33:00","modified_gmt":"2023-12-09T18:33:00","slug":"scientific-papers","status":"publish","type":"page","link":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/?page_id=58","title":{"rendered":"Scientific papers"},"content":{"rendered":"\n
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RO<\/a><\/div>\n<\/div>\n\n\n\n
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Scientific papers<\/h3>\n\n\n\n

2023<\/h4>\n\n\n\n
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  1. A. R. Hategan, M. David, A. Dehelean, G. Cristea, R. Puscas, A. J. Molnar, D. A. Magdas, Impact of Pre-Processing Methods for the Identification of the Botanical Origin of Honey Based Upon Isotopic and Elemental Profiles, Analytical Letters, 56(2), 231-243 (2023) https:\/\/doi.org\/10.1080\/00032719.2022.2044347<\/a><\/li>\n\n\n\n
  2. C. Berghian-Grosan, A. R. Hategan, M. David, D. A. Magdas, Untargeted metabolomic analysis of honey mixtures: Discrimination opportunities based on ATR-FTIR data and machine learning algorithms, Microchemical Journal, 188, 108458 (2023) https:\/\/doi.org\/10.1016\/j.microc.2023.108458<\/a><\/li>\n\n\n\n
  3. D. A. Magdas, C. Berghian-Grosan, Botanical honey recognition and quantitative mixture detection based on Raman spectroscopy and machine learning, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 293, 122433 (2023) https:\/\/doi.org\/10.1016\/j.saa.2023.122433<\/a><\/li>\n<\/ol>\n\n\n\n

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    2022<\/h4>\n\n\n\n
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    1. M. David, A. R. Hategan, D. A. Magdas, C. Berghian-Grosan, B. Simionescu, Botanical Origin Assessment of Honey Based on ATR-IR Spectroscopy: A Comparison between the Efficiency of Supervised Statistical Methods and Artificial Intelligence. Applied Sciences, 12(19), 9645 (2022) https:\/\/doi.org\/10.3390\/app12199645<\/a><\/li>\n\n\n\n
    2. M. David, A. R. Hategan, C. Berghian-Grosan, D.A. Magdas, The Development of Honey Recognition Models Based on the Association between ATR-IR Spectroscopy and Advanced Statistical Tools. International Journal of Molecular Sciences, 23(17), 9977 (2022) https:\/\/doi.org\/10.3390\/ijms23179977<\/a><\/li>\n\n\n\n
    3. A. R. Ha\u021began, D. A. Magdas, R, Puscas, A. Dehelean, G. Cristea, B. Simionescu, Machine Learning Algorithms in Corroboration with Isotope and Elemental Profile – An Efficient Tool for Honey Geographical Origin Assessment, Applied Sciences, 12(21), 10894 (2022) https:\/\/doi.org\/10.3390\/app122110894<\/a><\/li>\n\n\n\n
    4. R. C. Suciu, F. Guyon, D. A. Magdas, Application of emission\u2013excitation matrices in parallel with factor analysis with other chemometric techniques for honey classification, Journal of Food Composition and Analysis 107, 104401 (2022) https:\/\/doi.org\/10.1016\/j.jfca.2022.104401<\/a><\/li>\n\n\n\n
    5. A. R. Hategan, F. Guyon, D. A. Magdas, The improvement of honey recognition models built on 1H-NMR fingerprint through a new proposed approach for feature selection, Journal of Food Composition and Analysis, 114, 104786 (2022) https:\/\/doi.org\/10.1016\/j.jfca.2022.104786<\/a><\/li>\n<\/ol>\n\n\n\n

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      2021<\/h4>\n\n\n\n
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      1. A. R. Hategan, R. Puscas, G. Cristea, A. Dehelean, F. Guyon, A. J. Molnar, V. Mirel, D. A. Magdas. Opportunities and Constraints in Applying Artificial Neural Networks (ANNs) in Food Authentication. Honey – A Case Study. Applied Sciences 11, 6723 (2021): https:\/\/doi.org\/10.3390\/app11156723<\/a> <\/li>\n<\/ol>\n\n\n\n
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        Book chapters:<\/strong><\/h4>\n\n\n\n
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        1. A.M. Pintea, D.A. Magdas (2022<\/strong>) Chapter \u201eAnalytical Techniques for the Biochemical Profiling in Seabuckthorn\u201d<\/em> in \u201eThe Seabuckthorn Genome, Compendium of Plant Genomes\u201d, <\/em>Springer Nature, 1-36<\/li>\n\n\n\n
        2. D.A. Magdas, C. Berghian\u2010Grosan (2021<\/strong>) Chapter \u201eRaman Spectroscopy<\/em>\u201d in \u201eElectromagnetic Technologies in Food Science<\/em>\u201d, John Wiley & Sons Ltd., 310-336.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

          Scientific papers 2023 2022 2021 Book chapters:<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-58","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=\/wp\/v2\/pages\/58","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=58"}],"version-history":[{"count":16,"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=\/wp\/v2\/pages\/58\/revisions"}],"predecessor-version":[{"id":167,"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=\/wp\/v2\/pages\/58\/revisions\/167"}],"wp:attachment":[{"href":"https:\/\/www.itim-cj.ro\/PNCDI\/honeyomics\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=58"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}