RT info:eu-repo/semantics/article
T1 Impact of the pretreatment of ATR-FTIR signals on the figures of merit when PLS is used
A1 Mas, C.
A1 Rubio Martínez, Laura
A1 Valverde Som, Lucía
A1 Sarabia Peinador, Luis Antonio
A1 Ortiz Fernández, Mª Cruz
K1 Pretreatment data
K1 ATR-FTIR
K1 PLS
K1 Oxybenzone
K1 Desirability function
K1 Figures of merit
K1 Química analítica
K1 Chemistry, Analytic
AB The efficiency of the analytical methods based on vibrational spectroscopy has been widely verified in a high number of publications. In addition, it has been recognized that the pretreatment of the original signals is absolutely necessary to obtain enough quality in the subsequent classification and/or regression models. In fact, an inappropriate pretreatment makes the results worse. It is also impossible to give “a priori” rules that guarantee the adequacy of a pretreatment for specific data.The effect of the pretreatments is evaluated through their impact on the quality of the classification and/or regression models built from them due to the double dependence (on the data and on the purpose of the analysis). The effect of the pretreatment has been evaluated using partial least squares regression (PLSR) in some works and the root mean squares in prediction or in cross-validation has been always used as a criterion to evaluate the regression in all these cases. However, it seems appropriate to use quality criteria of the calibration of the analytical method through the figures of merit: the significance of the regression, the absence of constant or proportional bias, the residual standard deviation, the mean of the absolute values of the relative errors and the capability of detection.In this work, the use of these analytical criteria in a desirability function is proposed for the first time with calibration data of oxybenzone obtained by ATR-FTIR and PLSR. This desirability function enables to choose the best pretreatment among the 39 possibilities studied. In addition, it is shown that the same optimum is not obtained if the minimum of RMSEC_CV is considered as a criterion.
PB Elsevier
SN 0169-7439
YR 2020
FD 2020-06
LK http://hdl.handle.net/10259/5300
UL http://hdl.handle.net/10259/5300
LA eng
NO Spanish MINECO (AEI/FEDER, UE) through project CTQ2017‐88894‐R and by Junta de Castilla y León through project BU012P17 (both co‐financed with European FEDER funds). L. Valverde-Som thanks JCyL for her postdoctoral contract through BU012P17 project.
DS Repositorio Institucional de la Universidad de Burgos
RD 26-abr-2024