Hot Air Impingement Drying Enhanced Drying Characteristics and Quality Attributes of Ophiopogonis Radix

Zhou, Zheng; Wang, Shanyu; Zhang, Chujie; Wu, Min; Cui, Dezhou; Fu, Xiaosong; Gao, Lei; Li, Aichao; Wei, Qing; Liu, Ziliang

doi:10.3390/foods12071441

Cited by 15 publications

(12 citation statements)

References 35 publications

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“…When the temperature rises, the movement within the molecules is intense, which leads to an increase in the destruction of pigments, enzymes, and other substances in the yam slices, causing the color of the slices to increase as a result. Zhang et al [ 41 ] found that lower temperatures were able to reduce the color difference of dry products to some extent. At lower temperatures, the chemical reaction rate of the dried products was slowed down, thus reducing the possibility of color change.…”

Section: Results and Analysismentioning

confidence: 99%

Effect of Combined Infrared Hot Air Drying on Yam Slices: Drying Kinetics, Energy Consumption, Microstructure, and Nutrient Composition

Zhang

Zheng

Xiao

et al. 2023

Foods

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Using hot air drying (HAD) and combined infrared hot air drying (IR-HAD) test devices, the drying kinetics, unit energy consumption, color difference values, rehydration rate, microstructure, and changes in polysaccharide and allantoin contents of yam slices were examined at various temperatures (50 °C, 55 °C, 60 °C, 65 °C, and 70 °C). The findings demonstrated that each of the aforementioned parameters was significantly impacted by the drying temperature. IR-HAD dries quicker and takes less time to dry than HAD. The Deff of IR-HAD is higher than that of HAD at the same temperature and increases with the increase in temperature. The activation energy required for IR-HAD (26.35 kJ/mol) is lower than that required for HAD (32.53 kJ/mol). HAD uses more energy per unit than IR-HAD by a factor of greater than 1.3. Yam slices treated with IR-HAD had higher microscopic porosity, better rehydration, lower color difference values, and higher polysaccharide and allantoin levels than HAD-treated yam slices. The IR-HAD at 60 °C had the greatest comprehensive rating after a thorough analysis of the dried yam slices using the coefficient of variation method. Three statistical indicators were used to evaluate six thin-layer drying models, and the Weibull model was most applicable to describe the variation of drying characteristics of yam slices.

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Section: Results and Analysismentioning

confidence: 99%

Effect of Combined Infrared Hot Air Drying on Yam Slices: Drying Kinetics, Energy Consumption, Microstructure, and Nutrient Composition

Zhang

Zheng

Xiao

et al. 2023

Foods

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“…Furthermore, the application of lower temperatures additionally contributes to the preservation of natural pigments and nutrients in dried products, hence further diminishing the likelihood of color alterations (Zheng et al, 2023). The appropriate equation and R 2 = 0.998 may be found in Equation 31.…”

Section: Resultsmentioning

confidence: 99%

“…When the drying air flow was held constant, the overall color change of the pods increased with increasing infrared intensity but reduced when the airflow was held constant. The total color difference decreases with increasing air velocity in infrared drying, which may be due to heat loss in the drying chamber when the air cools the Furthermore, the application of lower temperatures additionally contributes to the preservation of natural pigments and nutrients in dried products, hence further diminishing the likelihood of color alterations (Zheng et al, 2023). The appropriate equation and R 2 = 0.998 may be found in Equation 31.…”

Section: Color Parametersmentioning

confidence: 99%

Theoretical and experimental analysis of the drying kinetics of okra using infrared dryer

El‐Mesery,

Kamel,

Shawir

et al. 2023

J Food Process Engineering

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In this research, the thin‐layer drying characteristics and quality parameters of okra pods were investigated by subjecting it to drying using an infrared drier. The drying process was achieved at three different radiation intensities of 0.167, 0.235, and 0.520 W/cm2 and included three air velocities of 0.3, 0.5, and 0.7 m/s. A detailed analysis of their drying kinetics (drying curve, drying rate curve, effective moisture diffusivity, and mathematical modeling), shrinkage and rehydration, and total color change were performed. Results showed the drying process occurred in the falling‐rate period. The drying time was reduced with rising infrared intensity and declining air velocity. The Midilli et al. model provided the best fitting for each drying curve (coefficient of determination (R2) > 0.99, reduced chi‐square (χ2), and root mean square error [RMSE] closer to zero). The effective moisture diffusivity values among various drying conditions ranged from 2.89 to 12.23 × 10−10 m2/s, which were within the normally predictable range for food materials. The rehydration ratio increased as air velocity increased and decreased as infrared radiation intensity increased. The phenomenon of shrinkage ratio had a positive relationship with higher levels of infrared radiation and a negative association with faster airflow. As the air velocity and radiation intensity rose, there was an observed increase in the overall color difference between fresh and dried okra. The current study's results will provide additional insights into the optimal drying conditions for preparing okra as a snack, breakfast item, or other culinary applications.Practical applicationsOkra is important commodity in terms of global agricultural production. As okra is a perishable product with a short shelf life, the food industry has been forced to find methods, such as drying, that extend its storage life by months. The conventional system of hot air dying displays many disadvantages. Infrared drying intended a substitute way to improve the quality of dehydrated products. However, infrared is rarely expended alone as a drying method and is frequently combined with other drying systems. The main goal of this work is to study an innovative process to extend the storage life of okra reducing energy and time consumption and ensuring sample quality.

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“…The air-impingement dryer is a technology that realizes drying by impinging and heating the material with pressurized hot air ( Zheng et al., 2023 ). Figure 2 shows the operation principle diagram of the air-impingement dryer.…”

Section: Principles and Methodsmentioning

confidence: 99%

Moisture content online detection system based on multi-sensor fusion and convolutional neural network

Yang,

Zheng,

Xiao

et al. 2024

Front. Plant Sci.

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To monitor the moisture content of agricultural products in the drying process in real time, this study applied a model combining multi-sensor fusion and convolutional neural network (CNN) to moisture content online detection. This study built a multi-sensor data acquisition platform and established a CNN prediction model with the raw monitoring data of load sensor, air velocity sensor, temperature sensor, and the tray position as input and the weight of the material as output. The model’s predictive performance was compared with that of the linear partial least squares regression (PLSR) and nonlinear support vector machine (SVM) models. A moisture content online detection system was established based on this model. Results of the model performance comparison showed that the CNN prediction model had the optimal prediction effect, with the determination coefficient (R2) and root mean square error (RMSE) of 0.9989 and 6.9, respectively, which were significantly better than those of the other two models. Results of validation experiments showed that the detection system met the requirements of moisture content online detection in the drying process of agricultural products. The R2 and RMSE were 0.9901 and 1.47, respectively, indicating the good performance of the model combining multi-sensor fusion and CNN in moisture content online detection for agricultural products in the drying process. The moisture content online detection system established in this study is of great significance for researching new drying processes and realizing the intelligent development of drying equipment. It also provides a reference for online detection of other indexes in the drying process of agricultural products.

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Hot Air Impingement Drying Enhanced Drying Characteristics and Quality Attributes of Ophiopogonis Radix

Cited by 15 publications

References 35 publications

Effect of Combined Infrared Hot Air Drying on Yam Slices: Drying Kinetics, Energy Consumption, Microstructure, and Nutrient Composition

Effect of Combined Infrared Hot Air Drying on Yam Slices: Drying Kinetics, Energy Consumption, Microstructure, and Nutrient Composition

Theoretical and experimental analysis of the drying kinetics of okra using infrared dryer

Moisture content online detection system based on multi-sensor fusion and convolutional neural network

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