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201620
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End date: 2016 × Start date: 2016 × Thesis Type: M.Tech. ×
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Now showing 1 - 9 of 20
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    ThesisItemOpen Access
    Processing parameters optimization and shelf life studies for production of barley (Hordeum vulgare) and finger millet (Eleusine coracana) based malted flour using integrated malting unit
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Pandey, Suman; Singh, Anupama
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    ThesisItemOpen Access
    Process optimization for extraction of essential fatty acids from fish using solvent extraction
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Singh, Sudhir Kumar; Shahi, N.C.
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    ThesisItemOpen Access
    Suspended sediment yield modelling using artificial neural networks
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-06) Kushwaha, Daniel Prakash; Devendra Kumar
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    ThesisItemOpen Access
    Implementation of MPTT technique on wind turbine driven PMSG
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-08) Parley, Neha Kumari; Singh, Rajeev
    Of all available renewable energy resources, wind energy has become one of the most attractive energy resources for electricity production. Wind energy is free, clean, and endless. In WECS a wind turbine and power conversion system are used to produce the electrical energy. For this, a number of WECS are implemented as research projects to improve its efficiency. Wind power generation is dependent on various factors which are controllable and uncontrollable. To extract the optimum power point and to get the better efficiency in the WECS, MPPT algorithm has to be implemented. There are many schemes and methods used in MPPT. In this thesis work, a maximum power point tracking technique based on Perturbation and Observation (P&O) are used for wind energy conversion systems using Permanent Magnet Synchronous Generator (PMSG). Due to the continuous variation in wind speed it is difficult to extract maximum power from wind. Therefore this method is incorporated with wind turbine to get maximum power output. The proposed algorithm is proved by MATLAB simulation. The simulation results shows that higher power output with MPPT control using proposed technique compared to without MPPT.
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    ThesisItemOpen Access
    Comparative studies on pretreatments for shelf life enhancement of kinnow under different storage conditions
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Malik, Sheeba; Singh, Anupama
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    ThesisItemOpen Access
    A comprehensive study of imact of contact materials on characteristics of carbon nanotube field effect transfer
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-01) Kohli, Vinod Chandra; Sharma, K.K.
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    ThesisItemOpen Access
    Sensitivity of standardized Penman Monteith evapotranspiration estimates to climate change at Indian sub-humid locations
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Singh, Yadvendra Pal; Tomar, A.S.
    The objectives of this study were, (i) to conduct sensitivity analysis of FAO56-PM model to some climatic variables; (ii) to determine sensitivity coefficient for some climatic variables and compute changes in ET0 with per unit change in them; (iii) to evaluate dominant climatic variables affecting ET0; and (iv) to evaluate trend of change in ET0 estimates on daily, monthly, and seasonal basis. The considered climatic variables were of two types, i.e. observed [maximum temperature (Tmax), minimum temperature (Tmin), maximum relative humidity (RHmax), minimum relative humidity (RHmin), sunshine duration (n), and wind speed at 2 m height (Ws)] and deduced [average temperature (Tav), average relative humidity (RHav), actual vapour pressure (ea), saturation vapour pressure (es), vapour pressure deficit (VPD), and solar radiation (Rs)]. The study was conducted for sub-humid districts of Udham Singh Nagar (Uttarakhand) and Hazaribagh (Jharkhand). The daily weather dataset of 17 years (1995-2015) and 23 years (1990-2012) collected for Udham Singh Nagar and Hazaribagh districts was used as input for calculating daily evapotranspiration (ET0) estimates using FAO56-PM model. For systematic evaluation, year was classified into 12 months (January to December) and three cropping seasons (kharif, rabi, and zaid) by grouping Standard Meteorological Weeks in tune with CWS-1 format suggested by Indian Meteorological Department, Pune, whereas, quality control of weather dataset was ensured by detecting missing data and outliers. The sensitivity analysis was conducted by increasing and decreasing value of different climatic variables from 1 to 5 units (except ea, es, VPD, and Ws). The values of ea, es, and VPD was increased and decreased with 0.4 kPa increments up to 2 kPa, whereas, Ws was increased up to 5 km d-1 only. While changing one variable at a time, no change in other climatic variables was being made to make the analysis mono-criteria. The value of daily sensitivity coefficient for each climatic variable was obtained by dividing the amount of increase or decrease in ET0 by unit change (increase or decrease) in each climatic variable to quantify change in ET0 per unit change at different timescales, whereas, dominant variable among climatic variables were decided on the basis of maximum slope. The analysis revealed that, (i) value of mean and standard deviation of daily FAO56-PM ET0 estimates for sub-humid Udham Singh Nagar and Hazaribagh districts were 3.88 mm, 3.93 mm, and 1.71 mm, 1.54 mm, respectively, (ii) response of unit change in all climatic parameters to change in daily ET0 values at both sub-humid districts was found linear with very satisfactory R² value of ≥ 0.90, except for n, Ws, and VPD for which R² varied in between 0.80 and 0.82, (iii) On the basis of slope, among observed climatic variables, change in daily ET0 was found most sensitive to Ws, followed by Tmax, and n at both districts while VPD and es were obtained as most sensitive deduced climatic variables, (iv) On monthly basis, change in ET0 estimates among observed climatic variables at both districts was found most sensitive to Ws, followed by Tmax, and n, whereas, RHmin was found most insensitive. Similarly, es was found most sensitive, followed by VPD, and Rs to change in daily ET0 estimates among deduced climatic variables, (v) On seasonal (cropping) basis, change in ET0 for rabi and zaid cropping seasons was found most sensitive to Ws, followed by Tmax, and n, while it was found least sensitive to change in RHmin among observed climatic variables, whereas, in case of deduced climatic variables, seasonal ET0 change was found most sensitive to es, followed by VPD and Rs while ea was found least sensitive at both districts. The change in ET0 in kharif in both districts was found most sensitive in decreasing order of n, Tmax, and Ws with RHmin as least sensitive, however, same trend in deduced climatic variables as observed in case of rabi and zaid i.e. es, followed by VPD and Rs was observed with ea as most insensitive and (vi) Recording of Ws, Tmax, n data and calculation of es and VPD should be made with utmost care to determine FAO56-PM estimates accurately at Indian sub-humid regions.
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    ThesisItemOpen Access
    Development and performance evaluation of batch-type induction pasteurizer
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-06) Lamo, Changchuk; Shahi, N.C.
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    ThesisItemOpen Access
    Modeling of freeze drying of mushroom using artificial neural network and subsequent optimization with genetic algorithm
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Tarafdar, Ayon; Shahi, N.C.
    The advancement in food processing technologies calls for the requirement of better instrumentation of processes that produce superior end products. Freeze drying has the potential to decrease the moisture content in foods for preservation and storage with little or no compromise to nutrient contents. It is therefore, considered one of the best methods for drying bio-products. At the same time, the freeze drying process is based on different parameters such as drying time, pressure, sample thickness, primary and secondary drying temperatures and relative humidity. This makes the drying behaviours and the product quality characteristics difficult to comprehend. Therefore, the rationale of this work was to provide an understanding of the freeze drying process parameters and their effect on the physico-chemical characteristics of the drying material. This may also help in increasing the general applicability of the process to a wider range of food products and not just limited to high valued foods. For this study, button mushroom (Agaricus bisporus) was chosen as a drying material as it incurs high nutritive loses during conventional drying methods involving heat treatment. To minimize these loses, freeze drying of mushrooms have been considered which has the ability to retain mineral and nutrient content in heat sensitive materials. The process parameters chosen for this study were primary drying temperature (-2˚C, -5˚C, -8˚C), secondary drying temperature (25˚C, 28˚C, 31˚C), pressure (0.04 mbar, 0.07 mbar and 0.10 mbar) and sample thickness (0.2 cm, 0.5 cm and 0.8 cm). The effect of these parameters on product drying behaviour (moisture content, drying rate) and quality (water activity, rehydration ratio, shrinkage ratio, ascorbic acid content, antioxidant content, colour and protein content) were studied. The parameters most affecting the quality of freeze-dried mushrooms were determined statistically using response surface methodology (RSM). Model equations developed from RSM lacked adaptability and were constrained to a limited set of parameters. These equations were cast into Artificial Neural Network (ANN) models which were more efficient, robust and could define patterns in complex and scattered data. The models were trained using a feed-forward back-propagation network with LevenbergMarquardt (LM) learning rule. A Genetic Algorithm based optimization with ANN models as fitness function were used to provide a recommended set of optimum parameters which may be used for industrial purposes to deliver superior quality dried mushrooms. The optimum set of parameters obtained were observed as -7.5˚C primary drying temperature, 25.03˚C secondary drying temperature, 0.09 mbar pressure and 0.36 sample thickness. The optimized values for responses were observed as 2.01 for rehydration ratio, 0.65 for shrinkage ratio, 19.353 mg/g for ascorbic acid content, 6.1 mg/g for antioxidant content, 4.875 mg/g for protein content and 11.86 for colour (ΔE).