Measurement of Glass Transition of Food Products by Differential Scanning Calorimeter
Applications | 2024 | ShimadzuInstrumentation
Understanding the glass transition behavior of food products is critical for controlling texture, mouthfeel and processability. The transition from a glassy brittle state to a rubbery soft state impacts product hardness, shelf life and handling characteristics. Accurate measurement of glass transition temperature (Tg) enables food scientists and quality control teams to predict and optimize the mechanical properties of confections and other moisture‐sensitive foods.
This study employs differential scanning calorimetry (DSC) to:
The measurements were performed using a DSC-60 Plus equipped with a TAC-60i electric auto‐cooling attachment. Samples were sealed in aluminum pans and scanned under a nitrogen flow (50 ml/min). A standard heating and cooling rate of 10 °C/min was applied across the range of -40 °C to 140 °C.
Candy samples (soft and hard) and pure saccharides underwent two‐stage scans: initial heating to target temperature followed by cooling and a second heating cycle. Only the second heating traces were analyzed for Tg onset, midpoint and endset. Soft candy samples were further subjected to heat treatments at 110 °C for 5 min and 30 min to reduce moisture, with content determined by weight loss up to 120 °C via thermogravimetric analysis.
Soft candy exhibited a Tg onset at 0.39 °C, indicating a rubbery state at ambient temperature, while hard candy showed an onset at 53.30 °C, consistent with a brittle glassy state.
Saccharide Tg onset values followed the trend: fructose (5.37 °C) < glucose (34.57 °C) < sucrose (60.37 °C). This hierarchy explains how sugar composition influences product softness at room temperature.
Heat treatment of soft candy reduced moisture from 1.6 % to 0.8 % (5 min) and 0.7 % (30 min), shifting Tg onset from -17.09 °C in untreated samples to 1.38 °C and 3.74 °C respectively. Lower moisture raises Tg and increases hardness.
These findings enable food developers to:
Advancements may include integrating real‐time DSC monitoring in continuous processing lines, coupling Tg data with predictive shelf‐life models, and expanding glass transition analysis to complex food matrices such as emulsions and biopolymer blends. Machine learning approaches can further correlate compositional variables with thermal behavior.
This work demonstrates that DSC‐60 Plus effectively distinguishes glass transition differences due to composition and moisture content in candies and sugars. Glass transition measurements provide a reliable indicator of product texture, supporting formulation design and quality control in the food industry.
Thermal Analysis
IndustriesFood & Agriculture
ManufacturerShimadzu
Summary
Significance of the Topic
Understanding the glass transition behavior of food products is critical for controlling texture, mouthfeel and processability. The transition from a glassy brittle state to a rubbery soft state impacts product hardness, shelf life and handling characteristics. Accurate measurement of glass transition temperature (Tg) enables food scientists and quality control teams to predict and optimize the mechanical properties of confections and other moisture‐sensitive foods.
Objectives and Study Overview
This study employs differential scanning calorimetry (DSC) to:
- Compare glass transition temperatures of commercially available soft and hard candies.
- Measure Tg values of three common saccharides: fructose, glucose and sucrose.
- Investigate the effect of moisture reduction via heat treatment on Tg in a soft candy.
Instrumental Setup
The measurements were performed using a DSC-60 Plus equipped with a TAC-60i electric auto‐cooling attachment. Samples were sealed in aluminum pans and scanned under a nitrogen flow (50 ml/min). A standard heating and cooling rate of 10 °C/min was applied across the range of -40 °C to 140 °C.
Methodology
Candy samples (soft and hard) and pure saccharides underwent two‐stage scans: initial heating to target temperature followed by cooling and a second heating cycle. Only the second heating traces were analyzed for Tg onset, midpoint and endset. Soft candy samples were further subjected to heat treatments at 110 °C for 5 min and 30 min to reduce moisture, with content determined by weight loss up to 120 °C via thermogravimetric analysis.
Main Results and Discussion
Soft candy exhibited a Tg onset at 0.39 °C, indicating a rubbery state at ambient temperature, while hard candy showed an onset at 53.30 °C, consistent with a brittle glassy state.
Saccharide Tg onset values followed the trend: fructose (5.37 °C) < glucose (34.57 °C) < sucrose (60.37 °C). This hierarchy explains how sugar composition influences product softness at room temperature.
Heat treatment of soft candy reduced moisture from 1.6 % to 0.8 % (5 min) and 0.7 % (30 min), shifting Tg onset from -17.09 °C in untreated samples to 1.38 °C and 3.74 °C respectively. Lower moisture raises Tg and increases hardness.
Benefits and Practical Applications
These findings enable food developers to:
- Predict product hardness and mouthfeel based on measured Tg.
- Optimize formulations by selecting sugars with target transition temperatures.
- Control moisture levels during processing to achieve desired texture.
Future Trends and Applications
Advancements may include integrating real‐time DSC monitoring in continuous processing lines, coupling Tg data with predictive shelf‐life models, and expanding glass transition analysis to complex food matrices such as emulsions and biopolymer blends. Machine learning approaches can further correlate compositional variables with thermal behavior.
Conclusion
This work demonstrates that DSC‐60 Plus effectively distinguishes glass transition differences due to composition and moisture content in candies and sugars. Glass transition measurements provide a reliable indicator of product texture, supporting formulation design and quality control in the food industry.
References
- K. Kawai, 'Glass Transition Properties and Quality Control of Food', Japan journal of food engineering, Vol. 19, No. 1, pp. 9–14, March 2018.
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