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Subject: Processing and Food Engineering × End date: 2009 × Start date: 2007 ×
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    ThesisItemOpen Access
    Modeling and optimization of process parameters for hot air drying of banana (Musa paradisiaca L.) slices
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2009-08) Dinkar, Vairat Amita; Pandey, R.K.
    The Banana (Musa paradisiacal L.) is a crop of tropical climate and is grown for its fruit, fiber or foliage. Green banana is perishable and deteriorates after harvesting. Drying prolongs the shelf life of banana. The hot air drying characteristics of green banana slices were studied at drying temperature (40-800C), air velocity (1.5-5.5 m/s) and slice thickness (2-6 mm) in the laboratory scale hot air dryer. Drying was found to occur in the falling rate period only. Higher drying rate were observed with the higher temperature level and minimum level of slice thickness. Drying rate increases with increase in air velocity upto 3.5 m/s after that there was no profound effect on drying rate. The drying behavior of the banana slices was mathematically analyzed using models namely page’s, exponential and logarithmic model. The experimental validity of models were done on the basis of maximum R2 and minimum SEE, and RMSE. The page’s model described the drying behaviour of banana slices better as compared to exponential and logarithmic model. The results reveled that, the temperature, air velocity, slice thickness had significant effect on various quality parameters of dried banana slices viz. rehydration ratio, hardness, shrinkage, ascorbic acid and color whereas carbohydrate and ash content had non-significant effect. The optimum level of independent variables for banana drying obtained by using numerical optimization of multiple responses viz. drying time, rehydration ratio, shrinkage, hardness, ascorbic acid and L and b value were temperature-600C, air velocity- 3.5 m/s and slice thickness- 2mm. These optimum values are recommended for hot air drying of banana.
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    ThesisItemOpen Access
    Drying characteristics and process optimization of spinach (Spinacia oleracea L.) using response surface methodology
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2009-07) Asaram, Padvi Chandrarekha; Pandey, J.P.
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    ThesisItemOpen Access
    Drying characteristics and quality changes during tray and fluidized bed drying of carrot shreds
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2009-08) Keshri, Satish Kumar; Kulshreshtha, Manoj
    A study on drying characteristics and quality changes during tray and fluidized bed drying of carrot shreds was under taken. Experiments were conducted to study the drying kinetics of carrot shreds, to compare the predictive models and to evaluate the quality, and b-carotene loss during tray and fluidized bed drying. Tray drying experiments were conducted under unblanched and blanched conditions, with and without turning at 50, 60 and 700C, and loading density of 1.5, 3.0 and 4.5 kg/m2. Fluidized bed drying experiments were carried out in unblanched and blanched conditions at 50, 60 and 700C with a sample size of 100, 200 and 300g at velocities of 2.22 and 1.81 m/s that corresponded to full and half opening of flap. Quality was studied in terms of moisture content, bulk density, true density, porosity, rehydration ratio, rehydration fraction, color and b-carotene content. In both tray and fluidized bed drying, Page’s model performed best in describing the drying behavior, while the Power law model did not fit the drying data. Drying took place under falling rate and there was no constant drying period. Analysis of variance indicated that in case of tray drying loading density had most significant effect on overall drying rate followed by turning, and temperature. In case of fluidized bed drying; only sample size and temperature had significant effect. Blanching did not have a significant effect on the drying rate in any case. Drying rate was 3-4 times higher in fluidized bed drying than in tray drying. In case of tray drying, turning had a significant effect on drying rate while flap opening did not have a significant effect on drying rate. Total drying time in tray drying ranged from 2-12h, while it was 0.5-2.5h in fluidized bed drying indicating a substantial saving of time in fluidized bed drying compared to tray drying. Physical characteristics (bulk density, true density, porosity) of dried shreds were similar in tray and fluidized bed drying. Rehydration ratio was higher for blanched sample, dried at lower temperature in both tray and fluidized bed drying. Rehydration ratio and rehydration fraction were slightly higher in fluidized bed drying. Blanching and temperature had a significant effect on quality of dried products. b-carotene was more in blanched samples dried at lower temperature in both cases. There was no significant difference on b-carotene and color in fluidized bed dried shreds and tray dried shreds. Overall there is no significant advantage in fluidized bed drying over tray drying in terms of quality of dried shreds.
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    ThesisItemOpen Access
    Hot air drying characteristics of sweet potato (Ipomoea batatas L.) cubes, its modeling using artificial neural network (Ann) and quality changes during storage of dried product
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2009-06) Singh, Ngankham Joykumar; Pandey, R.K.
    Sweet potato (Ipomoea batatas L.), rich in carbohydrate and other protective nutrients like vitamin A, carotene, calcium and phosphorus and contains small quantity of fat, protein, riboflavin, niacin and vitamin C etc, is an important tuber crop which is widely used in ready-to-eat foods, etc. Sweet potatoes have a very poor shelf-life and undergo spoilage due to deterioration of vascular and parenchymal tissues due to formation of blue vascular streaks. Hot air-drying characteristics of sweet potato cubes were investigated in a laboratory scale hot air dryer. The thin-layer drying was carried out under five air temperatures 50, 60, 70, 80 and 90oC, five air velocities of 1.5, 2.5, 3.5, 4.5 and 5.5 m/s and three sweet potato cube sizes of 5, 8 and 12 mm. Empirical models namely page’s, generalized exponential and logarithmic were fitted to drying data of moisture ratio. The model was selected on the basis of maximum R2 and standard deviation (SD). Page’s model gave better prediction for moisture ratio. Artificial Neural Network model was fitted in drying data. ANN modeling was done at two hidden layer (1 and 2) and ten neurons (2, 4, 6, 8 and 10). The optimum architecture of ANN for training at different drying characteristics such as moisture content, drying rate and moisture ratio was found to be two hidden layers with 8 and 4 nodes in first and second hidden layer, 2 nodes in first and 8 in second layer and 2 in hidden layer and 4 nodes in second layer, respectively. Hardness, Springiness, cohesiveness and resilience decreased slightly with increase in temperature and increased with increase in cube thickness; however adhesiveness and gumminess increased slightly with drying temperature. Based on quality attributes, the optimum conditions recommended for drying of sweet potato were 70oC drying air temperature, 5.5 m/s air velocity and 0.5 cm cube size. Dried sweet potato cubes could be stored in sealed polythene package for more than six months without much deterioration in its quality. Vacuum packaging resulted in better quality of stored sweet potato cubes as compared to the normal packaging method.