Solving the spectroscopy interference effects of beta-carotene and lycopene by neural networks.
In this study a new computerized approach and linear models (LMs) to solve the UV/vis spectroscopy interference effects of beta-carotene with lycopene analysis by neural networks (NNs) are considered. The data collected (absorbance values) obtained by UV/vis spectrophotometry were transferred into an NN-trained computer for modeling and prediction of output. Such an integrated NN/UV/vis spectroscopy approach is capable of estimating beta-carotene and lycopene concentrations with a mean prediction error 50 times lower than that calculated by the LM/UV/vis spectroscopy approach (without any previous physicochemical knowledge of the process to be modeled).
Torrecilla
José S
JS
Departamentos de Ingeniería Química and Química Analítica, Facultad de Ciencias Químicas, Facultad de Farmacia, Universidad Complutense de Madrid, Avenida Complutense s/n, 28040 Madrid, Spain.
Cámara
Montaña
M
Fernández-Ruiz
Virginia
V
Piera
Guiomar
G
Caceres
Jorge O
JO
D002338:Carotenoids / Q000032:analysis*; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D003198:Computer Simulation; D005638:Fruit / Q000737:chemistry; D000077276:Lycopene; D018551:Solanum lycopersicum / Q000737:chemistry; D016571:Neural Networks, Computer; D013056:Spectrophotometry, Ultraviolet; D019207:beta Carotene / Q000032:analysis*
D019207:beta Carotene; D002338:Carotenoids; D000077276:Lycopene