Kinetic Models of Color Degradation, Total Difference Color, and Brown Index of Soursop (<scp><i>Annona muricata</i></scp> L.) Slices During Heat Pump Drying by Pilot Equipment

ABSTRACT Tea color is a key factor in consumer purchasing decisions and reflects product quality. Thus, modeling and controlling the soursop slices drying process are essential to enhance sensory value and reduce investigation costs. In this study, mathematical techniques were applied to evaluate the changes in color values ( L *, a *, b *, ∆ E *, and BI) during heat pump drying using a high‐capacity pilot drying equipment. Experimental data were collected from assessing color changes at drying temperatures of 20°C, 30°C, 40°C, and 50°C over time. The data were fitted into regression equations to assess the kinetics of the process. Results revealed that each kinetic model could appropriately describe the color value changes for one or more drying processes at different temperatures. Notably, both fractional conversion and Zero‐order models were chosen to describe the change in L * value during drying at 20°C and 30°C, while the Power‐law model was used for L * value changes at 40°C and 50°C. At the same temperature ranges, another finding showed that the experimental data for a * and b * values followed the Combined kinetic model ( R 2 &gt; 0.92). Kinetic models describing the changes in BI and ΔE* during drying at various temperatures were also identified based on statistical parameters ( R 2 , χ 2 , and RMSE). The activation energy required for changes in color values was calculated, revealing that the a * value was the most sensitive to temperature, whereas the sensitivities of L *, b *, ∆ E *, and BI were comparable. The study discussed the nature, modeling methods, and optimization of drying processes, offering insights into both quantity and quality.

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Publication Details

Journal
Journal of Food Process Engineering
Published
2025-03-01
DOI
https://doi.org/10.1111/jfpe.70081
Citations
2
Primary Topic
Food Drying and Modeling
Type
article
Field-Weighted Citation Impact
2.32

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article

Kinetic Models of Color Degradation, Total Difference Color, and Brown Index of Soursop (Annona muricata L.) Slices During Heat Pump Drying by Pilot Equipment

Binh An Pham, Ngoc Duc Vu, Tri Nhut Pham, Long Bao Huynh et al.
2 citations
Journal of Food Process Engineering
Food Drying and Modeling
2.32
article

Kinetic Models of Color Degradation, Total Difference Color, and Brown Index of Soursop (Annona muricata L.) Slices During Heat Pump Drying by Pilot Equipment

Binh An Pham, Ngoc Duc Vu, Tri Nhut Pham, Long Bao Huynh, Dzung B. Diep
article en
2 citations

Abstract

ABSTRACT Tea color is a key factor in consumer purchasing decisions and reflects product quality. Thus, modeling and controlling the soursop slices drying process are essential to enhance sensory value and reduce investigation costs. In this study, mathematical techniques were applied to evaluate the changes in color values ( L *, a *, b *, ∆ E *, and BI) during heat pump drying using a high‐capacity pilot drying equipment. Experimental data were collected from assessing color changes at drying temperatures of 20°C, 30°C, 40°C, and 50°C over time. The data were fitted into regression equations to assess the kinetics of the process. Results revealed that each kinetic model could appropriately describe the color value changes for one or more drying processes at different temperatures. Notably, both fractional conversion and Zero‐order models were chosen to describe the change in L * value during drying at 20°C and 30°C, while the Power‐law model was used for L * value changes at 40°C and 50°C. At the same temperature ranges, another finding showed that the experimental data for a * and b * values followed the Combined kinetic model ( R 2 &gt; 0.92). Kinetic models describing the changes in BI and ΔE* during drying at various temperatures were also identified based on statistical parameters ( R 2 , χ 2 , and RMSE). The activation energy required for changes in color values was calculated, revealing that the a * value was the most sensitive to temperature, whereas the sensitivities of L *, b *, ∆ E *, and BI were comparable. The study discussed the nature, modeling methods, and optimization of drying processes, offering insights into both quantity and quality.

Journal of Food Process EngineeringVol. 48(3)
Trường ĐH Nguyễn Tất Thành (VN), Ho Chi Minh City University of Industry and Trade (VN), Nong Lam University Ho Chi Minh City (VN)
Quỹ Đổi mới sáng tạo Vingroup
Openalex Percentile: Top 14%
Food Drying and Modeling
2.32
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