Scientific papers

RO

Scientific papers

2023

  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
  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
  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

2022

  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
  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
  3. A. R. Hațegan, 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
  4. R. C. Suciu, F. Guyon, D. A. Magdas, Application of emission–excitation 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
  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

2021

  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 

Book chapters:

  1. A.M. Pintea, D.A. Magdas (2022) Chapter „Analytical Techniques for the Biochemical Profiling in Seabuckthorn” in „The Seabuckthorn Genome, Compendium of Plant Genomes”, Springer Nature, 1-36
  2. D.A. Magdas, C. Berghian‐Grosan (2021) Chapter „Raman Spectroscopy” in „Electromagnetic Technologies in Food Science”, John Wiley & Sons Ltd., 310-336.