Characteristics of thin-layer infrared drying of green bean

Doymaz, İ̇brahim; Kıpçak, Azmi Seyhun; Pişkin, Sabriye

doi:10.17221/423/2014-cjfs

Cited by 57 publications

(64 citation statements)

References 35 publications

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“…During the drying process, drying rates were higher at the beginning of the process, and after that they decreased with a decrease of moisture content in the samples. 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 water movement leading to a further fall in drying rates (Singh et al 2006;Doymaz et al 2015).…”

Section: Resultsmentioning

confidence: 99%

“…The experimental moisture loss was fitted to nine thin-layer models as shown in J. Food Sci., 33, 2015 (4): 367-376 doi: 10.17221/566/2014-CJFS the model to forecast the drying characteristics of green bean slices (Doymaz et al 2015). The rehydration ratio and the results of colour statistical analysis conducted by one-way ANOVA are shown in Table 3 and 4, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…(4). The solution of diffusion equation for an infinite slab was given by Crank (1975), and uniform initial moisture distribution, negligible external resistance, constant diffusivity, and negligible shrinkage were supposed (Doymaz et al 2015): For long drying times, only the first term in Eq. (4) is significant and the equation simplifies to:…”

Section: Methodsmentioning

confidence: 99%

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Microwave drying of green bean slices: drying kinetics and physical quality

Doymaz¹,

Kıpçak²,

Pişkin³

2015

Czech J. Food Sci.

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Doymaz I., Kipcak A.S., Piskin S. (2015): Microwave drying of green bean slices: drying kinetics and physical quality. Czech J. Food Sci., 33: 367-376.Several microwave power settings were applied to green beans in order to determine the effect on the drying kinetics along with the rehydration ratio and colour values. In the experiments, several microwave power settings were studied as 180, 360, 600, and 800 W. From the results, it is seen that the level of microwave power affected the drying kinetics, rehydration ratio, and colour of the beans slightly. The nine best known thin-layer drying models that were used in literature were applied to the experimental data and the results showed that Midilli et al. model best fits the experimental data for the drying kinetics of green bean slices. Effective moisture diffusivity was found to be between 1.387 × 10 -8 and 3.724 × 10 -8 m 2 /s. Using modified Arrhenius type equation the activation energy was found as 19.185 kW/kg. The rehydration ratio of samples dried at 800 W was higher than those of samples at other power settings. It was observed that an increase in the microwave power increased the brightness and yellowness, on the contrary, it decreased the greenness of the dried samples. L -half-thickness of slices (m); MR -moisture ratio (dimensionless); M e -equilibrium moisture content (kg water/kg dry matter -DM); M 0 -initial moisture content (kg water/kg DM); M t -moisture content at any time (kg water/kg DM); M t+Δt -moisture content at t+ Δt (kg water/kg DM); N -number of observations; n -positive integer, empirical constant; P -microwave power (W); P -probability; R -universal gas constant (kJ/(mol.K)); R 2 -coefficient of determination;RR -rehydration ratio; RMSE -root mean square error; T -temperature (°C); t -drying time (min, s); W 1 -weight of dried matter (g); W 2 -weight of moisture in the material (g); z -number of constants; c 2 -reduced chi-square

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Microwave drying of green bean slices: drying kinetics and physical quality

Doymaz¹,

Kıpçak²,

Pişkin³

2015

Czech J. Food Sci.

Self Cite

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“…When it was not possible to measure the quantity of temperature in the radiation power level during the drying process, a product mass and power level‐dependent Arrhenius‐type diffusivity was employed to compute the activation energy by numerous researchers in different drying systems (Darvishi et al, ; Doymaz, , , , , ; Doymaz et al, , ):

D_{eff} = D_{1} \exp (- \frac{E_{a} m}{P_{m}})

…”

Section: Introductionmentioning

confidence: 99%

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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“…1); (1) Where M t is the moisture content of drying material at any time, t; M o is the initial moisture content of drying material (t=0); M e is the equilibrium moisture content (t→∞). However, in literature it was simplified to M t /M o , since M e is relatively small compared to M t and M o and accepted to be negligible [23][24][25] .…”

Section: Drying Processmentioning

confidence: 99%

Evaluation of Two Fitting Methods Applied for Thin-Layer Drying of Cape Gooseberry Fruits

Karacabey

2016

Braz. arch. biol. technol.

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Drying data of cape gooseberry was used to compare two fitting methods: namely 2-step and 1-step methods. Literature data was also used to confirm the results. To demonstrate the applicability of these methods, two primary models (Page, Two-term-exponential) were selected. Linear equation was used as secondary model. As well-known from the previous modelling studies on drying, 2-step method required at least two regressions: One is primary model and one is secondary (if you have only one environmental condition such as temperature). On the other hand, one regression was enough for 1-step method. Although previous studies on kinetic modelling of drying of foodswere based on 2-step method, this study indicated that 1-step method may also be a good alternative with some advantages such as drawing an informative figure and reducing time of calculations.

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Characteristics of thin-layer infrared drying of green bean

Cited by 57 publications

References 35 publications

Microwave drying of green bean slices: drying kinetics and physical quality

Microwave drying of green bean slices: drying kinetics and physical quality

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

Evaluation of Two Fitting Methods Applied for Thin-Layer Drying of Cape Gooseberry Fruits

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