01791nas a2200205   4500008004100000245009000041210006900131520101500200100002101215700002601236700002601262700001701288700002401305700002301329700002301352700002401375700002101399700002001420856014501440       2022                        eng d00aHoney discrimination based on the bee feeding by Laser Induced Breakdown Spectroscopy0 aHoney discrimination based on the bee feeding by Laser Induced B3 aIn the present work, the effects of artificial feeding of bees on the honey are investigated by employing for the first time, Laser Induced Breakdown Spectroscopy (LIBS) by analyzing the emission spectral characteristics of the plasma created on the surface of honey samples. Correlation plots indicating the importance of spectral lines of elements as e.g., Calcium (Ca), Magnesium (Mg), Sodium (Na) and Potassium (K) are constructed, while machine learning algorithms based on Linear Discriminant Analysis (LDA) and Random Forest Classifiers (RFC) are employed to classify the honey samples in terms of the bee food used. The constructed machine learning
models were validated by both cross-validation and external validation, while the obtained accuracies exceeded 90% of correct classification, indicating the potential of LIBS technique for honey discrimination. The obtained results by LIBS were also validated by HPLC-RID, which is the standard technique used for the analysis of the main honey sugars.1 aStefas, Dimitris1 aGyftokostas, Nikolaos1 aKourelias, Panagiotis1 aNanou, Eleni1 aTananaki, Chrysoula1 aKanelis, Dimitrios1 aLiolios, Vasileios1 aKokkinos, Vasileios1 aBouras, Christos1 aCouris, Stelios  uhttp://telematics.upatras.gr/telematics/publications/honey-discrimination-based-bee-feeding-laser-induced-breakdown-spectroscopy?language=el