Hyperspectral Luminescence Imaging in Combination with Signal Deconvolution Enables Reliable Multi-Indicator-Based Chemical Sensing
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Hyperspectral Luminescence Imaging in Combination with Signal Deconvolution Enables Reliable Multi-Indicator-Based Chemical Sensing. / Zieger, Silvia E.; Mosshammer, Maria; Kühl, Michael; Koren, Klaus.
In: ACS Sensors, Vol. 6, No. 1, 2021, p. 183-191.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Hyperspectral Luminescence Imaging in Combination with Signal Deconvolution Enables Reliable Multi-Indicator-Based Chemical Sensing
AU - Zieger, Silvia E.
AU - Mosshammer, Maria
AU - Kühl, Michael
AU - Koren, Klaus
PY - 2021
Y1 - 2021
N2 - Although real-time monitoring of individual analytes using reversible optical chemical sensors (optodes) is well established, it remains a challenge in optical sensing to monitor multiple analyte concentrations simultaneously. Here, we present a novel sensing approach using hyperspectral imaging in combination with signal deconvolution of overlapping emission spectra of multiple luminescent indicator dyes, which facilitates multi-indicator-based chemical imaging. The deconvolution algorithm uses a linear combination model to describe the superimposed sensor signals and employs a sequential least-squares fit to determine the percent contribution of the individual indicator dyes to the total measured signal. As a proof of concept, we used the algorithm to analyze the measured response of an O2 sensor composed of red-emitting Pd(II)/Pt(II) porphyrins and NIR-emitting Pd(II)/Pt(II) benzoporphyrins with different sensitivities. This facilitated chemical imaging of O2 over a wide dynamic range (0-950 hPa) with a hyperspectral camera system (470-900 nm). The applicability of the novel method was demonstrated by imaging the O2 distribution in the heterogeneous microenvironment around the roots of the aquatic plant Littorella uniflora. The presented approach of combining hyperspectral sensing with signal deconvolution is flexible and can easily be adapted for use of various multi-indicator-or even multianalyte-based optical sensors with different spectral characteristics, enabling high-resolution simultaneous imaging of multiple analytes.
AB - Although real-time monitoring of individual analytes using reversible optical chemical sensors (optodes) is well established, it remains a challenge in optical sensing to monitor multiple analyte concentrations simultaneously. Here, we present a novel sensing approach using hyperspectral imaging in combination with signal deconvolution of overlapping emission spectra of multiple luminescent indicator dyes, which facilitates multi-indicator-based chemical imaging. The deconvolution algorithm uses a linear combination model to describe the superimposed sensor signals and employs a sequential least-squares fit to determine the percent contribution of the individual indicator dyes to the total measured signal. As a proof of concept, we used the algorithm to analyze the measured response of an O2 sensor composed of red-emitting Pd(II)/Pt(II) porphyrins and NIR-emitting Pd(II)/Pt(II) benzoporphyrins with different sensitivities. This facilitated chemical imaging of O2 over a wide dynamic range (0-950 hPa) with a hyperspectral camera system (470-900 nm). The applicability of the novel method was demonstrated by imaging the O2 distribution in the heterogeneous microenvironment around the roots of the aquatic plant Littorella uniflora. The presented approach of combining hyperspectral sensing with signal deconvolution is flexible and can easily be adapted for use of various multi-indicator-or even multianalyte-based optical sensors with different spectral characteristics, enabling high-resolution simultaneous imaging of multiple analytes.
KW - chemical imaging
KW - chemometrics
KW - hyperspectral imaging
KW - image analysis
KW - linear unmixing
KW - planar optodes
U2 - 10.1021/acssensors.0c02084
DO - 10.1021/acssensors.0c02084
M3 - Journal article
C2 - 33337140
AN - SCOPUS:85098946829
VL - 6
SP - 183
EP - 191
JO - ACS Sensors
JF - ACS Sensors
SN - 2379-3694
IS - 1
ER -
ID: 255553233