Abstract

In this study, we employed multivariate control techniques to detect outliers in the determination of ethylene in impact polypropylene samples by near-infrared (NIR) spectroscopy and multivariate calibration partial least-squares (PLS). We also applied an algorithm which identifies those spectral variables responsible for the outlier behavior and that can indicate the source of this behavior. The outliers in the prediction step may be due to three possible situations: errors associated with the prediction of analyte concentrations in samples that have the same characteristics as the calibration set, but that are beyond the concentration range; changes in the matrix composition; and instrumental errors. We show that the proposed techniques make it possible to detect whether or not an analyte belongs to the reference set. In addition, we apply an algorithm that identifies the variables that cause outlier behavior and assigns them to a class.

Evaluation of univariate and multivariate calibration strategies for the direct determination of total carbon in soils by laser-induced breakdown spectroscopy: tutorial

Wesley Nascimento Guedes, Diego Victor Babos, Vinícius Câmara Costa, Carla Pereira De Morais, Vitor da Silveira Freitas, Kleydson Stenio, Alfredo Augusto Pereira Xavier, Luís Carlos Leva Borduchi, Paulino Ribeiro Villas-Boas, and Débora Marcondes Bastos Pereira Milori
J. Opt. Soc. Am. B 40(5) 1319-1330 (2023)

Nondestructive detection model of soluble solids content of an apple using visible/near-infrared spectroscopy combined with CARS and MPGA

Yong Chen, Chaoyuan Cui, and Yun Wu
Appl. Opt. 60(27) 8400-8407 (2021)

Rapid detection of talc content in flour based on near-infrared spectroscopy combined with feature wavelength selection

Changhao Bao, Changhao Zeng, Jinming Liu, and Dongjie Zhang
Appl. Opt. 61(19) 5790-5798 (2022)

Outlier modeling for spectral data reduction

Farnaz Agahian and Brian Funt
J. Opt. Soc. Am. A 31(7) 1445-1452 (2014)

Rapid detection of cellulose and hemicellulose contents of corn stover based on near-infrared spectroscopy combined with chemometrics

Na Wang, Longwei Li, Jinming Liu, Jianfei Shi, Yang Lu, Bo Zhang, Yong Sun, and Wenzhe Li
Appl. Opt. 60(15) 4282-4290 (2021)