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A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural
This study analyzes potassium sorbate fluorescence in solutions, revealing a consistent characteristic peak. A novel Particle Swarm Optimization-Back Propagation (PSO-BP) neural network method accurately determines its concentration in orange juice.
Area of Science:
- Analytical Chemistry
- Spectroscopy
- Chemometrics
Background:
- Potassium sorbate is a widely used food preservative.
- Accurate determination of potassium sorbate concentration is crucial for food safety and quality control.
- Existing methods for potassium sorbate analysis may have limitations in complex matrices like orange juice.
Purpose of the Study:
- To investigate the fluorescence spectra properties of potassium sorbate in aqueous solution and orange juice.
- To develop a novel, accurate method for determining potassium sorbate concentration in orange juice.
- To evaluate the feasibility of a Particle Swarm Optimization-Back Propagation (PSO-BP) neural network for this application.
Main Methods:
- Characterization of potassium sorbate fluorescence spectra in different solutions.
- Two-dimensional fluorescence spectral analysis to understand intensity-concentration relationships.
- Development and application of a PSO-BP neural network model for concentration prediction.
- Validation of the method using relative error analysis.
Main Results:
- Potassium sorbate exhibits a characteristic fluorescence peak at λ(ex)/λ(em) = 375/490 nm in both aqueous solution and orange juice.
- A complex, non-linear relationship exists between fluorescence intensity and potassium sorbate concentration.
- The PSO-BP neural network achieved high accuracy, with relative errors of 1.83% and 1.53% in predicted concentrations.
- The method demonstrated feasibility for measuring potassium sorbate in the range of 0.1-2.0 g·L⁻¹.
Conclusions:
- The characteristic fluorescence peak of potassium sorbate is identifiable across different matrices.
- A non-linear model is necessary for accurate concentration determination due to complex spectral responses.
- The PSO-BP neural network offers a robust and accurate approach for quantifying potassium sorbate in orange juice.
- This method provides a valuable tool for food quality control and preservative monitoring.
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