ABSTRACT Prediction of tractor drawbar performance can lead to simulation and optimization of tractor performance, allowing optimum setting of different parameters as well as guiding manufacturer in decision-making for design of new tractors. Twenty different input parameters were selected for drawbar performance prediction. The data used as input to train the network was collected from 141 tractor test reports tested between 1997 and 2013 at the Central Farm Machinery Training and Testing Institute, Budni (M.P.). A back propagation artificial neural network (ANN) was developed using Neural Network Toolbox in Matlab software. Matrix of 1140×20 and 1140×1 was made as input and target values for drawbar prediction in the ANN. The optimum structure of neural network was determined by trial-and-error method, and 30 different structures were evaluated. Highest performance was obtained for the network with two hidden layers, each having 35 neurons, and employed Levenberg-Marquardt training algorithm. Coefficient of determination (R2) and Mean square error (MSE) for this neural network was 0.994 and 1.284, respectively.
ABSTRACT The physical, thermal and flow properties (flowability) of potato flour from Kufri-Chipsona, Kufri Sinduri and Kufri Badshah varieties produced in West Bengal, Rajasthan and Bihar states were evaluated. Moisture content was the important variable affecting these properties. Within moisture ranges of 7.04 % to 56.25 % (d.b.) the bulk, tapped and true density and porosity significantly decreased with increase in moisture content of potato flour of each variety, and ranged from 350-690 kg.m-3, 640-1240 kg.m-3, 1510-1550 kg.m-3 and 54-71 %, respectively. Carr index and Hausner ratio ranged from 24.41-44.50 %, and 1.32-1.77, respectively. Thermal conductivity, specific heat and thermal diffusivity of the flours significantly (p<0.05) increased from 0.125 to 0.230 W.m−1.K−1, 0.092 to 0.124 mm2.s-1 and 1.13 to1.76 MJ.m-3.K-1, respectively, when moisture content of flours increased from 7.04 % to 56.25 % (d.b.).
ABSTRACT Kokum rind was dried from 85.32 % (w.b.) moisture content to 11.17% (w.b.) moisture content in a solar tunnel dryer in 34 h. Ten mathematical drying models were fitted with the experimental data on moisture ratio and time required for drying. Wang and Sing drying model fitted best with r2 value of 0.998 and RMSE of 0.000536. Variation in solar intensity inside and outside of the dryer was 180.51±58.51 W.m-2 and 434.68±120.34 W.m-2, respectively, with the ambient air temperature ranging between 40.9 oC and 55.36 oC, product temperature ranging between 28.76 oC and 55.67 oC, and humidity ranging between 20.00 and 39.99 per cent. Drying efficiency of the solar tunnel dryer was 22.94 per cent. Kokum rind quality parameters as acidity, reducing sugar, non-reducing sugar, protein, carbohydrates, ash, calorific value significantly increased after drying at p≤0.01, while pH, anthocyanin, colour (L, a and b value) significantly decreased at p≤0.01.
ABSTRACT Experimental trials on convective drying of turmeric (Curcuma longa L) rhizomes were conducted using factorial completely randomized design. Turmeric rhizome samples were cured for 30 min in 0.1 % solution of sodium carbonate and dried in a laboratory tray dryer at air temperatures of 50 °C, 60 °C and 70 °C with drying air velocity of 2 m.s-1. Drying air temperature was optimized on the basis of maximum retention of curcumin content, and b value of colour with minimum drying time and specific energy consumption. Optimization of drying parameters was carried out using numerical optimization technique. The optimum temperature for convective drying of turmeric rhizomes was found to be 60 °C with drying time of 29 hours.
Abstract In absence of grid power in most of the production catchments in the North Eastern states of India, coupled with disruptive power situation in areas where it is available, agricultural products are invariably dried under traditional sun drying. Ginger and turmeric with high intrinsic qualities are two major spices produced in a formidable quantity in the region. Truckloads of raw ginger are transported to Delhi and other places, causing huge transit losses. A solar-biomass integrated (IDS) batch drying system was thus designed and developed with a capacity of 100 kg/batch. A compound parabolic solar collector coupled with bio-waste fired combustion and heating assembly was designed and attached to a drying chamber consisting of six trays and a wind turbine on the top to create the necessary draft controlled by butterfly valves and sliding gates. Thin layer drying experiments were carried out for drying of sliced ginger and turmeric. Fluidized bed dryer (FBD), electrical oven (EO) and open sun drying (OSD) were used for comparison. Effective moisture diffusivity in case of turmeric drying was nearly 21% more in comparison to ginger drying. Minimum specific energy consumption (SEC) occurred in IDS, and was 14 and 30 times less compared to FBD and OSD, respectively. Considering total heat available in the plenum chamber and latent heat of vapourization, the IDS showed 36.33% of overall energy utilization efficiency. A run up of 10 years and a break-even of 17.70 % was estimated, reflecting high entrepreneurial possibility of the developed IDS.