Reassessment of Thin-Layer Drying Models for Foods: A Critical Short Communication

Modeling the thin-layer drying of foods is based on describing the moisture ratio versus time data by using a suitable mathematical model or models. Several models were proposed for this purpose and almost all studies were related to the application of these models to the data, a comparison and selecting the best-fitted model. A careful inspection of the existing drying data in literature revealed that there are only a limited number of curves and, therefore, the use of some models, especially the complex ones and the ones that require a transformation of the data, should be avoided. These were listed based on evidence with the use of both synthetic and published drying data. Moreover, the use of some models were encouraged, again based on evidence. Eventually, some suggestions were given to the researchers who plan to use mathematical models for their drying studies. These will help to reduce the time of the analyses and will also avoid the arbitrary usage of the models.

DRYING CHARACTERISTICS, MINERAL CONTENT, TEXTURE AND SENSORIAL PROPERTIES OF PUMPKIN FRUIT LEATHER

The objective of this study was to investigate the influences of hot air (HAD: 50, 60, 70°C), vacuum (VD: 50, 60, 70°C at 300 mbar) and microwave methods (MWD: 90, 180W) on drying characteristics, effective moisture diffusivity (Deff), mineral content, texture, and sensorial properties of pumpkin pestils. MWD led to the highest drying rate and the lowest drying time in all methods. Page and Modified Page were ideally fitted to experimental results among seven thin layer drying models. Mineral content (Ca, K, Na, P, Mg, Fe, Zn, Cu, Mn) of the pestils showed higher values than non-dried (paste) mixture. Significant differences were determined between textural features of the pestils (p < 0.05). Furthermore, products dried with HAD and VD were preferred rather than MWD in terms of sensorial properties.

Statistical prediction of the drying behavior of blanched ginger rhizomes

ARS-680 environmental chamber was employed in this study to determine the drying behavior of sliced ginger rhizomes. Blanched and unblanched treated ginger rhizomes were considered at drying temperature of 40 °C for a period of 2 – 24 h. Linear and non-linear regression analyses were employed to establish the correlation that exits between the drying time and the moisture ratio. Correlation analysis, root mean square error (RMSE) and standard error of estimate (SEE) analysis were chosen in selecting the best thin layer drying models. Higher values of determination coefficient (R2) show goodness of fit and lower values of SEE implies better correlation; and RMSE values were also utilized in determining the goodness of fit. The drying data of the variously treated ginger samples were fitted into the twelve thin layer drying models and the data obtained were fitted by multiple non-linear regression technique. Blanched treated sample exhibited a better drying behavior losing about 82.87 % moisture content compared with unbleached sample that lost about 62.03 % of moisture content. Two-term exponential drying model proved to be the most suitable model for predicting the drying behavior of ginger rhizome. The model exhibited high R2 values of 0.9349-0.9792 (which are close to unity) for both blanched and unbleached samples. Also, it recorded relatively low values of RMSE and SEE (3.6865 - 2.0896 and 3.6564-2.7486 respectively) for both treatments.

Evaluation and Selection of Thin-layer Drying Models for Paddy Dried in Static Flat-bed Batch Dryer

A Static flat-bed batch dryer was developed for drying paddy from harvesting moisture content (20 – 22%) to 12% for safe storage. The dryer mainly consisted of Blower, Heating chamber, Plenum chamber and drying chamber. Twenty kg paddy was dried in the developed dryer at two different inlet air flow rate (1 m3/min. and 1.26 m3/min). The machine has a capacity of 20 kg and temperature of drying air was 60 and 55°C respectively. The moisture content was recorded at every 15 minutes interval and moisture ratio plots were generated. The experimental data were fit in 8 different thin-layer drying models and statistical parameters along with the model constants were obtained. It was found that the Wang and Singh model with the highest values for R2 and the least values of RMSE in selected drying conditions has the best fit. Henderson & Pabis and Newton models were also found suitable for describing the drying kinetics of paddy in the developed dryer.

NONLINEAR MODELS FOR INFRARED DRYING OF MINT

In this paper, 105 different semitheoretical and empirical thin layer drying models were used for describing the drying process of the mint leaves. Comparisons of the overall goodness of fit were based on Coefficient of Determination (R2), Root Mean Square Error (RMSE), Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). It was concluded that five parameter Cedergreen-Ritz-Streibig modified log-logistic functions with alpha equal to 0.25 (CRS5C) model describe the infrared drying process of the mint leaves. Furthermore, temperature effect was investigated by using reduction test. Finally, it was found that the effect is statistically significant and the model with separate trends fits these data better.

Drying Characteristics of Soybean (Glycine Max) Using Continuous Drying and Intermittent Drying

The effects of drying temperature by continuous and intermittent drying on the drying characteristics of soybean were determined in this study. Among the thin-layer drying models, the Midilli–Kucuk model showed the best fit (R2> 0.99) to describe the drying of soybean. At 300 min of the effective drying time, the moisture content of continuous drying at 35, 40, and 45 ºC were 9.38 (±0.00), 8.69 (±0.17), and 7.70 % (±0.48), respectively; while the moisture content of intermittent drying at 35, 40, and 45 ºC were 8.28 (±0.21), 7.31 (±0.41), and 6.97 % (±0.07), respectively. The image analysis method for detection of the crack in soybean demonstrated that at the target moisture content (7.7 %), cracked grain ratios with intermittent drying at 35, 40, and 45 ºC were reduced by 52.08, 27.59, and 18.24 %, respectively. With the effective drying time, the activation energy for intermittent drying (9.33 kJ/mol) was significantly lower than that value for continuous drying (21.23 kJ/mol).

Dehydration Kinetics of Cassava, Yam and Potato Slices Using a Refractance WindowTM Dryer

This study aims to investigate the drying characteristics of cassava, yam, and potato slices using a laboratory scale batch Refractance Window™ (RW) dryer. The experimental dryer was constructed by modifying a laboratory water bath. The bath was covered with a transparent Polyethylene terephthalate (PET) plastic film held in-place with angled edges. The cassava, yam, and potato slices were dried on the Refractance WindowTM dryer, and the variation of the moisture content of the slices during the drying process was measured. The water temperature beneath the plastic film was maintained at 60oC. The dehydration data were fitted to thin-layer drying models. Regression analysis suggested that the Haghi and Ghanadzadeh model best describes the dehydration behaviour for the 3 mm thick slices for the cassava, yam, and potato tubers. The coefficient of determination (R2) values of 0.999, 0.998, and 0.998 for the cassava, yam, and potato slices respectively were reported in all the models studied. The drying curves, the drying rate curves, and the Krischer curves, from the experimental drying data, was plotted. Observations indicate that the cassava, yams, and potatoes slices dried to below 0.11 g water/g-solid moisture content in about 150 min. This study was performed to facilitate the understanding of the design, modelling, and operations of a continuously operating RW dryer. Keywords: Refractance Window Drying, Thin Layer Drying Models, Yams, Cassava, Potatoes.