RT Journal Article
T1 Artificial intelligence applied to flavonoid data in food matrices
A1 Guardado Yordi, Estela
A1 Koelig, Raúl
A1 Matos, Maria João Correia Pinto Carvalho de
A1 Pérez Martínez, Amaury
A1 Caballero, Yailé
A1 Santana Penín, María Lourdes
A1 Pérez Quintana, Manuel
A1 Molina, Enrique
A1 Uriarte Villares, Eugenio
K1 Flavonoid
K1 Artificial intelligence
K1 Total antioxidant capacity
AB Increasing interest in constituents and dietary supplements has created the need for moreefficient use of this information in nutrition-related fields. The present work aims to obtain optimalmodels to predict the total antioxidant properties of food matrices, using available informationon the amount and class of flavonoids present in vegetables. A new dataset using databases thatcollect the flavonoid content of selected foods has been created. Structural information was obtainedusing a structural-topological approach called TOPological Sub-Structural Molecular (TOPSMODE).Different artificial intelligence algorithms were applied, including Machine Learning (ML) methods.The study allowed us to demonstrate the effectiveness of the models using structural-topologicalcharacteristics of dietary flavonoids. The proposed models can be considered, without overfitting,effective in predicting new values of Oxygen Radical Absorption capacity (ORAC), except in theMulti-Layer Perceptron (MLP) algorithm. The best optimal model was obtained by the RandomForest (RF) algorithm. The in silico methodology we developed allows us to confirm the effectivenessof the obtained models, by introducing the new structural-topological attributes, as well as selectingthose that most influence the class variable
PB MDPI
YR 2019
FD 2019
LK http://hdl.handle.net/10347/23034
UL http://hdl.handle.net/10347/23034
LA eng
NO Guardado Yordi, E.; Koelig, R.; Matos, M.J.; Pérez Martínez, A.; Caballero, Y.; Santana, L.; Pérez Quintana, M.; Molina, E.; Uriarte, E. Artificial Intelligence Applied to Flavonoid Data in Food Matrices. Foods 2019, 8, 573
NO This research received no external funding and the APC was funded by the Universidad Estatal AmazónicaThe authors thank the Belgian Development Cooperation for funding through VLIR-UOS(Flemish Interuniversity Council - University Cooperation for Development) in the context of the TEAM VLIR CU2017TEA433A102 Project: “Installation of a center of excellence in the central region-Eastern Cuba for the development of research and the production of plant bioactives”, between the University of Antwerp and Camagüey “Ignacio Agramonte Loynaz”, and Xunta da Galicia and Galician Plan of research, innovation and growth 2011–2015 (Plan I2 C, ED481B 2014/086–0 and ED481B 2018/007
DS Minerva
RD 24 abr 2026