Mathematical modelling of drying of thin layer rough rice

Hacıhafızoğlu, Oktay; Cihan, Ahmet; Kahveci, Kamil

doi:10.1016/j.fbp.2008.01.002

Cited by 65 publications

(31 citation statements)

References 25 publications

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“…Longer drying times were recorded by Koyuncu et al (2004) (2012), in a study on drying green beans, parsley, spinach leaves and grape bagasse, respectively. Several authors also demonstrated good fit to the mathematical modeling when studying the drying kinetics of agricultural products, such as apples (Menges and Ertekin, 2006), rice grains (Hacihafizoglu et al, 2008), green beans (Doymaz, 2005), spinach leaves (Doymaz, 2009), chili peppers (Pontes et al, 2009), peas (Doymaz and Kocayigit, 2011), coffee beans (Resende et al, 2009;2010;Corrêa et al, 2010), parsley (Lema et al, 2007), salvia (Radünz et al, 2010), pumpkin seeds (Jittanit, 2011), yellow lantern chili (Reis et al, 2011) and grape bagasse (Ferreira et al, 2012).…”

Section: Methodsmentioning

confidence: 99%

Mathematical modeling for the annatto (Bixa orellana L.) seed drying process

Santos

Queiroz

Figueirêdo

et al. 2013

Chilean J. Agric. Res.

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The pigment extraction process using annatto (Bixa orellana L.) seed produces a large amount of seed waste. Although most of these seeds are discarded, a number of studies report promising results with their use in animal feed. The good fiber content also suggests human nutrition applications, with possible incorporation in dietary foods. In the present study, annatto seeds derived from color extraction were dried, with and without the layer of oil left over from the process. Seeds were dried at 40, 50, 60 and 70 °C. Drying data were fitted to the Diffusion Approximation, Two Term, Midilli, Page and Thompson models. Drying was carried out up to a moisture content of approximately 5% wet basis. All the models studied exhibited adequate fit to the drying kinetics data of the annatto seeds, with coefficients of determination above 0.98 and root mean squared error (RMSE) below 1.0. Seeds with oil had longer drying times at 40 and 50 °C and shorter times at 60 and 70 °C. The coefficients of diffusion showed values between 2.67 × 10 -11 and 9.50 × 10 -11 m 2 s -1 and between 2.7 × 10 -11 and 6.21 × 10 -11 m 2 s -1 , while activation energies for liquid diffusions were 38.04 and 23.52 kJ mol -1 , for residual seed drying with and without oil, respectively.

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Section: Methodsmentioning

confidence: 99%

Mathematical modeling for the annatto (Bixa orellana L.) seed drying process

Santos

Queiroz

Figueirêdo

et al. 2013

Chilean J. Agric. Res.

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“…Most of the models in Table 1 were derived by simplifying the general solutions of the Fick's second law or the modification of the simplified models. Therefore, most of them were not arbitrarily chosen models; on the contrary, they were based on the physiological bases (Hacıhafızŏglu et al 2008).…”

Section: Methodsmentioning

confidence: 99%

Drying characteristics of paddy in an integrated dryer

2014

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Drying characteristics of paddy (long grain variety PR-118 procured from PAU, Ludhiana) in an integrated dryer using single as well as combined heating source was studied at different air temperatures. The integrated dryer comprises three different air heating sources such as solar, biomass and electrical. Drying of paddy occurred in falling rate period. It was observed that duration of drying of paddy from 22 to 13 % moisture content (w.b.) was 5-9 h depending upon the source of energy used. In order to select a suitable drying curve, six thin layer-drying models (Newton, Page, Modified Page, Henderson and Pabis, Logarithmic and Wang and Singh) were fitted to the experimental moisture ratio data. Among the mathematical models investigated, Wang and Singh model best described the drying behaviour of paddy using solar, biomass and combined heating sources with highest coefficient of determination (r 2 ) values and least chi-square, χ 2 , mean bias error (MBE) and root mean square error (RMSE) values. However, Page model adequately described the drying behavior of paddy using electrical heating source.Keywords Paddy . Integrated paddy dryer . Drying models . Moisture ratio Paddy or rough rice (Oryza Sativa L.), the most widely grown food grain crop, is the staple food of over 3 billion people. World and Indian rough rice production in 2010 was 700 million tonnes and 143.9 million tonnes respectively (FAOSTAT 2010). Rice provides more calories per hectare than any other cereal crops. Its nutritional value is high among cereals and grains. Though the protein content of rice is less than that of wheat, the protein digestibility and biological value of rice protein are the highest among wheat and other cereals. After harvesting, paddy normally goes through two moisture treatments; one is drying that may be required for safe storage, and the other is water absorption in preparation for further processing. Quality deterioration takes place if fresh paddy is not immediately dried to safe moisture level. Drying reduces bulk quantity, thus, facilitates in transportation, handling and storage. Although sundrying is economical, mechanical drying speeds up the process, prevents losses, ensures use of safer drying temperatures and produces superior product compared to sun drying (Mudahar and Bains 1982). In view of high cost and non-renewable nature of the present conventional electrical energy source, different renewable energy sources such as solar and bio mass may be employed for paddy drying. The combining of conventional and non-conventional energy sources for paddy drying will be helpful for exploiting solar and bio mass sources as much as possible.The drying characteristics of food is a complex phenomenon and requires simple representations to predict

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“…Various theoretical, semitheoretical, and empirical models have been examined to describe the thin-layer drying behavior of cocoa beans, [16][17][18] chillies, [19] green peas, [20] and rough rice. [21] Most of these thin-layer drying studies considered falling rate period and different drying models were claimed to be the best fitted models by the respective authors based on the product type, product moisture, and drying air temperature and relative humidity range. Krokida et al [22] reviewed the literature for drying constants from 35 different food materials using thin-layer empirical models and concluded that enough data existed only for limited materials for successful regression analysis.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study of Wheat Drying in Thin Layer and Mathematical Simulation of a Fixed-Bed Convective Dryer

et al. 2009

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Drying of wheat (Algerian cultivar: Hadba03) in thin layers was studied and mass flux phenomenon was used to characterize the thin-layer drying process. Thin-layer drying of wheat was determined for drying air temperature range of 40-60 C, relative humidity of drying air from 10 to 30%, air velocity of 0.7 m/s, and initial grain moisture from 26 to 31% (dry basis). Equilibrium moisture content of wheat was determined using desorption isotherms obtained from the thin-layer drying data. An equilibrium model for a stationary deep bed with drying air moving vertically upward was developed using mass and energy balance between grain and drying air in the bed and drying air characteristics obtained from thin-layer drying experiments. The developed model was validated by drying wheat in a laboratory dryer using different drying air temperatures and initial moisture contents.

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Mathematical modelling of drying of thin layer rough rice

Cited by 65 publications

References 25 publications

Mathematical modeling for the annatto (Bixa orellana L.) seed drying process

Mathematical modeling for the annatto (Bixa orellana L.) seed drying process

Drying characteristics of paddy in an integrated dryer

An Experimental Study of Wheat Drying in Thin Layer and Mathematical Simulation of a Fixed-Bed Convective Dryer

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