The effect of temperature and slice thickness on drying kinetics tomato in the infrared dryer

Sadin, Rasool; Chegini, Gholamreza; Sadin, Hassan

doi:10.1007/s00231-013-1255-3

Cited by 85 publications

(66 citation statements)

References 15 publications

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“…The reason for this phenomenon is the higher thermal energy for the evaporation of moisture from the samples (Ghasemi, Sadeghi, & Mireei, ). These results were similar to previous study for infrared‐ convective tomato slice dehydration (Sadin et al, ). The results of Table showed that the value of the heat transfer coefficient ( h m ) decreased as the dehydration air temperature increased from 45 to 75°C due to increased thermal energy.…”

Section: Resultssupporting

confidence: 93%

Numerical simulation of vitamin C degradation during dehydration process of fresh tomatoes

Ghasemi

Chayjan

2019

J Food Process Engineering

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In this study, the kinetics of vitamin C degradation is simulated by the development of a model based on the numerical approach of heat and mass transfer processes and the degradation rate of vitamin C during the dehydration of tomato slices at 45, 60, and 75°C. The results achieved by experimental data were consistent with those obtained by the numerical model (R2 > 0.88 and RMSE < 0.27). So, it is concluded that the rate of vitamin C degradation was increased at the beginning of the dehydration process when the temperature of the inner sample layers was raised and then its value decreased with the reduced moisture content at the stable temperature conditions. During the dehydration process, the highest concentrations of vitamin C were obtained at the surface layer of the tomato slice with the least moisture content and the lowest of its value was obtained at the sample center with the highest moisture content. Practical Applications Some of the essential nutrients are degraded during the dehydration process. Understanding factors effective on nutrient degradation is important to optimize the dehydration conditions to produce healthy food. Since vitamin C is an indicator for determining the health food, modeling of its degradation kinetics is an efficient method for understanding the effective factors of retaining nutritional components during the dehydration operation. In this research, a novel method developed to simulate the vitamin C degradation in different layers of a tomato slice during a thermal process. The result of this method is used to interpret the factors affecting on degradation of food component. After the dehydration process, the concentration of vitamin C at the surface node was approximately 47.9, 22.1, and 9.9% higher than its value at the center node at 45, 60, and 75°C, respectively. The effective moisture diffusivity was the most sensitive parameter in the modeling of vitamin C degradation kinetics.

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Section: Resultssupporting

confidence: 93%

Numerical simulation of vitamin C degradation during dehydration process of fresh tomatoes

Ghasemi

Chayjan

2019

J Food Process Engineering

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“…The reason for a reduction of drying rate might be due to a reduction in the porosity of samples due to shrinkage with advancement, which increased the resistance to movement of water leading to a further fall in drying rates (Singh et al 2006). The results were consistent with observations made by different authors on drying of various agricultural products (Kayisoglu & Ertekin 2011;Ponkham et al 2012;Kumar et al 2013;Sadin et al 2014).…”

Section: Resultssupporting

confidence: 93%

Characteristics of thin-layer infrared drying of green bean

Doymaz¹,

Kıpçak²,

Pişkin³

2015

Czech J. Food Sci.

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Doymaz I., Kipcak A.S., Piskin S. (2015): Characteristics of thin-layer infrared drying of green bean. Czech J. Food Sci., 33: 83-90.The effect of infrared (IR) power on drying kinetics, rehydration, and colour of green beans was investigated. The drying experiments were carried out at 83, 104, 125, 146, 167, and 188 W. It is observed that drying characteristics, rehydration, and colour of bean slices were greatly influenced by infrared power. The drying data were fitted with five thin-layer drying models available in the literature. Results showed that Midilli et al. and Aghbashlo et al. models are superior to the other models for explaining the drying kinetics of green bean slices. Effective moisture diffusivity was calculated in the range of 6.57 × 10 -10 to 4.49 × 10 -9 m 2 /s. Activation energy was estimated by a modified Arrhenius type equation and found to be 11.379 kW/kg.

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“…The effect of the sample thickness on the drying time can be interpreted as that increasing the thickness resulting in increased diffusion path of moisture within the samples and following that the increase the conductive resistance and the moisture gradient of the sample due to it led to an extension in drying time. It would seem that with an increase in the sample thickness, the rate of moisture transfer reduces owing to an enhancement of mass transfer resistance (Figures and a), thereby leading to the higher moisture content of infrared‐dried pumpkin samples, as found in previous studies for fruits and vegetables (Abano et al, ; Doymaz, ; Nowak & Lewicki, ; Sadin et al, ; Sharma et al, ).…”

Section: Resultsmentioning

confidence: 63%

Mathematical modeling of infrared radiation thin‐layer drying of pumpkin samples under natural and forced convection

Sadeghi

Movagharnejad

Asl

2019

J Food Process Preserv

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A comparative study was carried out between a large number of mathematical models and artificial neural networks to estimate the drying curves. Diamente et al. model and modified two‐term exponential‐V model were determined as the best ones describing drying curves for natural and forced drying air systems, respectively. The ANNs with 4‐9‐9‐1 and 3‐9‐1 topologies, log‐sigmoid, and hyperbolic tangent sigmoid transfer functions, and Levenberg–Marquardt training algorithm presented the best results for the former and latter systems, respectively. Furthermore, it was found that ANN modeling had much better performance in prediction of drying curves with respect to statistical analyses. Moisture diffusivity values were obtained in a range of 0.932×10-10-11.976×10-10normalm2/s and 2.209×10-10-9.848×10-10normalm2/s for the systems, respectively. Activation energies were determined as 88,509, 60,344, and 44,806 W/kg for the former system and 36.88, 29.66, and 18.59 kJ/mol for the latter system with an increase in the thickness of samples. Practical applications The main aim of drying food products is the reduction of moisture content up to a certain level to achieve the smallest possible amount of the microbiological spoilage. This process has a considerable effect on the drying kinetics and quality of the dried product as well. Infrared (IR) heating, as an alternative drying method for agricultural products, is efficient to preserve the main characteristics and to shorten drying time. It is important to investigate the effect operating parameters of IR dryer on the mentioned cases. Our studies have clearly displayed that IR heating of pumpkin samples can result in high heating rate and fast drying. Therefore, this alternative approach could be employed as an energy saving drying method along with improved drying efficiency and better product quality in comparison with the common drying methods. Study results are useful for producers of not only dried pumpkins but also other agricultural products.

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The effect of temperature and slice thickness on drying kinetics tomato in the infrared dryer

Cited by 85 publications

References 15 publications

Numerical simulation of vitamin C degradation during dehydration process of fresh tomatoes

Numerical simulation of vitamin C degradation during dehydration process of fresh tomatoes

Characteristics of thin-layer infrared drying of green bean

Mathematical modeling of infrared radiation thin‐layer drying of pumpkin samples under natural and forced convection

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