Dependency Model for Visible Aquaphotomics

Bozhynov, Vladyslav; Souček, Pavel; Bárta, Antonín; Urbanová, Pavla; Bekkozhayeva, Dinara

doi:10.1007/978-3-030-17938-0_10

Cited by 3 publications

(1 citation statement)

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“…Based on this, it is assumed that the aquaphotomics approach can be applied in the visible range to determine information related to the higher water overtones. We examined the influence of the path length on the water spectral characteristics in the visible range of the spectrum [15] to choose an optimal technical path length and investigated the correlation between water spectral characteristics in the visible range [17] in our previous research. Using this knowledge, the current manuscript shows the accessibility of the visible range of the spectrum for the quantitative analysis of dissolved chemical in water.…”

Section: Introductionmentioning

confidence: 99%

Application of Visible Aquaphotomics for the Evaluation of Dissolved Chemical Concentrations in Aqueous Solutions

et al. 2021

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This paper introduces novel research in aquaphotomics, extending the study of water–light interactions to the visible spectral range. This approach can potentially reduce the cost and increase the speed of spectral measurements, while providing additional information by extending the useful range in spectrophotometry. To demonstrate our method, we investigated the applicability of the visible spectral range for the quantification of NaCl dissolved in aqueous samples. Spectral measurements were conducted using a visible spectrometer in the range of 380–730 nm. The evaluation of molecular species concentration was based on multivariate analysis (MVA). Principal component analysis (PCA) showed a separation of all groups of samples by salt concentration. The partial least squares regression (PLSR) model presented high accuracy and a relationship between spectral variables in the visible range and NaCl concentration in water. The validity of the regression model was confirmed through independent prediction of NaCl concentration values in test samples with unknown concentrations. The presented results demonstrate the success of the approach in evaluating concentration changes in visible light, and thus extend the measurable spectral range of such analysis.

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Section: Introductionmentioning

confidence: 99%