Modeling carbon dioxide solubility in fruit and vegetable juices for supercritical carbon dioxide pasteurization

Supercritical carbon dioxide (SC-CO 2 ) is a promising non-thermal technology for pasteurizing fruit juice and liquid products, assuring microbial stabilization with minimal impact on quality. A key factor influencing its efficacy is the solubility of CO 2 in the juice matrix. In this study, a predictive model for CO 2 solubility was developed using a factorial experimental design with additional points, evaluating five variables: pressure (10–14 MPa), temperature (35–45 °C), glucose (0–15 g/100 mL), sodium chloride (0–3 g/100 mL), and citric acid (0–6 g/100 mL). A total of 21 experimental conditions were tested with model solutions replicating typical fruit juices composition. CO 2 solubility was measured using a high-pressure system with validated sampling protocol. Values ranged from 3.832 to 5.730 gCO 2 /100 g. The resulting linear regression model (R 2 = 0.897; RMSE = 0.148 gCO 2 /100 g), identified glucose and sodium chloride as significant negative factors affecting solubility, while citric acid was excluded from the model due to its lack of significant impact. The model was validated on eight real fruit and vegetable juices, with CO₂ solubility predictions based on °Brix and ash content as proxies for glucose and salt. Validation showed good agreement with measured values, yielding a mean absolute error of 0.141 g CO 2 /100 g and an R 2 of 0.85 calculated on the mean of three replicates per sample. These results confirm the model's accuracy and practical applicability, supporting its use in process design and optimization for SC-CO 2 pasteurization. This study contributes to a better understanding of CO 2 behavior in real juice matrices and provides a practical tool for tailoring SC-CO 2 processes based on juice composition. • Empirical model predicts CO 2 solubility in juice-like media. • Glucose and NaCl significantly reduce CO 2 solubility in aqueous matrices. • Citric acid had no measurable effect on CO 2 solubility within tested ranges. • Predictions in real juices matched experimental data using °Brix, ash and acidity.

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Publication Details

Journal
Food and Bioproducts Processing
Published
2025-07-18
DOI
https://doi.org/10.1016/j.fbp.2025.07.006
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
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article

Modeling carbon dioxide solubility in fruit and vegetable juices for supercritical carbon dioxide pasteurization

Food and Bioproducts Processing
Mycorrhizal Fungi and Plant Interactions
article

Modeling carbon dioxide solubility in fruit and vegetable juices for supercritical carbon dioxide pasteurization

article en

Abstract

Supercritical carbon dioxide (SC-CO 2 ) is a promising non-thermal technology for pasteurizing fruit juice and liquid products, assuring microbial stabilization with minimal impact on quality. A key factor influencing its efficacy is the solubility of CO 2 in the juice matrix. In this study, a predictive model for CO 2 solubility was developed using a factorial experimental design with additional points, evaluating five variables: pressure (10–14 MPa), temperature (35–45 °C), glucose (0–15 g/100 mL), sodium chloride (0–3 g/100 mL), and citric acid (0–6 g/100 mL). A total of 21 experimental conditions were tested with model solutions replicating typical fruit juices composition. CO 2 solubility was measured using a high-pressure system with validated sampling protocol. Values ranged from 3.832 to 5.730 gCO 2 /100 g. The resulting linear regression model (R 2 = 0.897; RMSE = 0.148 gCO 2 /100 g), identified glucose and sodium chloride as significant negative factors affecting solubility, while citric acid was excluded from the model due to its lack of significant impact. The model was validated on eight real fruit and vegetable juices, with CO₂ solubility predictions based on °Brix and ash content as proxies for glucose and salt. Validation showed good agreement with measured values, yielding a mean absolute error of 0.141 g CO 2 /100 g and an R 2 of 0.85 calculated on the mean of three replicates per sample. These results confirm the model's accuracy and practical applicability, supporting its use in process design and optimization for SC-CO 2 pasteurization. This study contributes to a better understanding of CO 2 behavior in real juice matrices and provides a practical tool for tailoring SC-CO 2 processes based on juice composition. • Empirical model predicts CO 2 solubility in juice-like media. • Glucose and NaCl significantly reduce CO 2 solubility in aqueous matrices. • Citric acid had no measurable effect on CO 2 solubility within tested ranges. • Predictions in real juices matched experimental data using °Brix, ash and acidity.

Food and Bioproducts ProcessingVol. 153
University of Padua (IT)
Zero hunger
Openalex Percentile: Top 58%
Mycorrhizal Fungi and Plant Interactions
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