Robust models for spectrophotometer optimisation

• A guide to optimal absorbance ranges for precision in spectrophotometry. • A robust method for UV–Vis precision tested across multiple spectrophotometers. • Based on a weighted log-quadratic function derived from first principles. • Identifies instrument-specific deviations overlooked by Poisson-based precision models. • Identifies instruments with flat precision curves and constant variability. Absorbance precision in spectrophotometers has a well-developed theory with best case precision limited by a Poisson distribution. However, this best case is not generally observed in modern commercial instruments and robust empirical models of their behaviour are unavailable. This study evaluated seven models across eight commercial spectrophotometers using a simple method for quantifying absorbance precision between 220 and 640 nm. Replicate measurements of standards were collected to obtain means and relative standard deviations (RSDs). Models were evaluated using root mean square error (RMSE), residual sum of squares (RSS), Akaike information criterion (AIC), and Bayesian information criterion (BIC), and checked for over fitting and robustness. On balance, the most robust and widely applicable model was a weighted log-quadratic function, fitting data from six of eight instruments. The two remaining instruments apply correction mechanisms which our model identifies and can notify the user. Adopting this model can ensure spectrophotometer precision criteria are evaluated and met at each wavelength and working ranges evaluated for any required precision. Our approach enables users to input a desired precision, or percentage relative standard deviation (%RSD), for a spectrophotometer to obtain the absorbance and wavelength range meeting this requirement. Consequently, standard and sample concentrations can be adjusted without compromising instrument precision. Furthermore, if measurements occur outside the desired range, the approach can alert the user and estimate the resulting precision. This readily automatable method enables reporting accurate precision tailored to individual spectrophotometers and wavelengths of interest.

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Publication Details

Journal
Measurement
Published
2025-12-17
DOI
https://doi.org/10.1016/j.measurement.2025.120133
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
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article

Robust models for spectrophotometer optimisation

Quentin S. Hanley, David P. A. Kilgour, Golnaz Shahtahmassebi, Bruna Falgueras Vallbona
Measurement
Water Quality Monitoring and Analysis
article

Robust models for spectrophotometer optimisation

Quentin S. Hanley, David P. A. Kilgour, Golnaz Shahtahmassebi, Bruna Falgueras Vallbona
article en

Abstract

• A guide to optimal absorbance ranges for precision in spectrophotometry. • A robust method for UV–Vis precision tested across multiple spectrophotometers. • Based on a weighted log-quadratic function derived from first principles. • Identifies instrument-specific deviations overlooked by Poisson-based precision models. • Identifies instruments with flat precision curves and constant variability. Absorbance precision in spectrophotometers has a well-developed theory with best case precision limited by a Poisson distribution. However, this best case is not generally observed in modern commercial instruments and robust empirical models of their behaviour are unavailable. This study evaluated seven models across eight commercial spectrophotometers using a simple method for quantifying absorbance precision between 220 and 640 nm. Replicate measurements of standards were collected to obtain means and relative standard deviations (RSDs). Models were evaluated using root mean square error (RMSE), residual sum of squares (RSS), Akaike information criterion (AIC), and Bayesian information criterion (BIC), and checked for over fitting and robustness. On balance, the most robust and widely applicable model was a weighted log-quadratic function, fitting data from six of eight instruments. The two remaining instruments apply correction mechanisms which our model identifies and can notify the user. Adopting this model can ensure spectrophotometer precision criteria are evaluated and met at each wavelength and working ranges evaluated for any required precision. Our approach enables users to input a desired precision, or percentage relative standard deviation (%RSD), for a spectrophotometer to obtain the absorbance and wavelength range meeting this requirement. Consequently, standard and sample concentrations can be adjusted without compromising instrument precision. Furthermore, if measurements occur outside the desired range, the approach can alert the user and estimate the resulting precision. This readily automatable method enables reporting accurate precision tailored to individual spectrophotometers and wavelengths of interest.

MeasurementVol. 263
Aberystwyth University (GB), University of Derby (GB), Nottingham Trent University (GB)
Openalex Percentile: Top 52%
Water Quality Monitoring and Analysis
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