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Open Access
Comparative evaluation of calibrated temperature-, and radiation-based ET0 equations developed for semi-arid climatic conditions based on standardized FAO56-PM model
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-08) Bind, Shyam Murari; Tomar, A.S.
The present study was undertaken to calibrate, validate and evaluate different temperature-, and radiation-based ET0 equations on daily, weekly, monthly, and seasonal (crop and weather) basis for semi-arid climatic conditions of Parbhani and Udaipur in comparison to standard FAO56-PM model with two specific objectives as, (i) to calibrate, validate and evaluate performance of various temperature-, and radiation-based ET0 equations in comparison to FAO56-PM model, and (ii) to calibrate and evaluate performance of all considered ET0 equations by using MicrosoftTM Excel Solver in comparison to FAO56-PM model. In this study, individual year was converted into 52 Standard Meteorological Weeks (SMWs), 12 months, three crop seasons (rabi, zaid and kharif) and three weather seasons (winter, summer and monsoon) in tune with CWS-1 format suggested by Indian Meteorological Department, Pune. The MicrosoftTM Excel was used as computing tool for conducting analysis and draw fruitful inferences from them. Prior to analysis, quality control of daily weather was also ensured by detecting missing data and outliers. The results showed that at all timescales, almost all calibrated ET0 equations performed well and extended better results in comparison to their original versions. Further, it was found that, calibrated Hargreaves-Samani M3 equation was found best at both places on daily, weekly, monthly, and weather season basis, while Hargreaves-Samani M1 performed best at both places on crop season basis. Among temperature-based ET0 equations, Romanenko equation was found worst at all timescales for both the places. Among radiation-based ET0 equations, Valiantzas (2) equation performed best while Irmak-Rn ET0 equation performed worst at all timescales for both places. Determination of calibration coefficient of different temperature- and radiation-based ET0 equations by using MicrosoftTM Excel Solver was found at-par in comparison of tedious and time-consuming MicrosoftTM Excel utility.
Open Access
Process optimization for retarding enzymatic browning in apple slices using ohmic heating
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Gururani, Prateek; Lohani, U.C.
Open Access
Groundwater modeling in Bijnor district using adaptive neuro-fuzzy inference system (ANFIS) and Support Vector Machine (SVM)
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-08) Bohra, Mamta; Shiv Kumar
The present study was undertaken in Bijnor district of Uttar Pradesh to investigate the groundwater behavior and to assess the groundwater utilization development stage; and to develop the groundwater models using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM) to predict the seasonal depth to water table using net recharge, net discharge, net rainfall, net draft through minor irrigation structures, net recharge due to return flow of irrigation and depth to water table as input parameters. MATLAB R2016a was used to develop the Adaptive NeuroFuzzy Inference System (ANFIS) based models and e1071 package in R- 3.4.3 and R Studio- 1.1.419 was used to develop the Support Vector Machine (SVM) based models. During the study period of 25 years, out of 39 hydrograph stations, the water table trend at 22 stations was found to be neither rising nor falling, whereas 13 hydrograph stations were under falling trend and 4 hydrograph stations were under rising trend during pre-monsoon seasons. During the period of post-monsoon season, 25 hydrograph stations were under neither rising nor falling trend whereas 10 hydrograph stations were under falling trend and 4 hydrograph stations were under rising trend. There was significant increase in the number of minor irrigation structures except Rahats and open wells. The cropping pattern revealed an increasing trend of area under high water demanding crops like sugarcane and rice while area under minor crops except vegetables were found to be decreasing. The groundwater balance studies indicated that during the study period, out of eleven blocks, one block namely Afzalgarh transformed from lower category (Safe) to higher category (Semi-critical); two blocks namely Haldaur and Kiratpur transformed from higher category (Critical) of groundwater utilization development stage to lower category (Semi-critical). However remaining eight blocks remained in the same category of groundwater utilization development stage. The ANFIS and SVM based models were developed and the values of performance indicators such as R2, r, MAE, RMSE, MAPE, RMSPE, RRSE, and RAE were calculated to evaluate the performance of Adaptive Neuro-Fuzzy Inference System and Support Vector Machine based models. Based on global ranking obtained from the values of performance indicators, out of eight ANFIS based models, ANFIS-Model 4 and ANFIS-Model 7 were selected for the prediction of depth to water table during pre-monsoon and post-monsoon seasons, respectively while out of eight SVM based models, SVM-Model 3 and SVM-Model 8 were selected for the prediction of depth to water table during premonsoon and post-monsoon seasons, respectively. It was found that SVM based models were better than ANFIS based models during pre-monsoon whereas both ANFIS and SVM based models were almost on the same level of performance during post-monsoon season. It was concluded that, both ANFIS and SVM based models were able to predict the depth to water table within reasonable accuracy and both ANFIS and SVM based models established their potential to predict the depth to water table within reasonable deviation. Recharging structures like series of check dams, percolation tanks, bunds, renches and stream modifications were also suggested in problematic regions of the study area.
Open Access
Optimal land and water resources planning in upper Bhakra Canal Command area using genetic algorithm
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Yadav, Pooja; Harish Chandra
Soil and water are the two most important prerequisite of agriculture. The productivity of agricultural crop largely depends on these resources. The growing demand for food in the country can only be met through by optimum utilization of available water resources and efficient allocation of available land to different crops. Keeping this in view the present study was conducted in the command area of Upper Bhakra canal in the Udham Singh Nagar district, Uttarakhand. To estimate the irrigation water requirement of different crops being grown in the area; to develop an area allocation model by considering canal water availability along with three (3, 6 and 9) running of tubewells for different rainfall conditions (drought, normal and surplus) for maximizing the net return from the canal command area. Gumbel distribution function was best fitted for 1st to 15th, 17th, 19th, 20th, 22nd, 23rd, 24th, 33rd, and 37th, from 39th to 47th and from 49th to 51st standard meteorological weeks, in weeks 13th, 16th, 25th, 26th, 27th, 30th, 32nd, 34th, 35th, 36th and 38th Gamma distribution function was fitted best. Similarly, in the standard meteorological weeks 18th, 21st, 31st, 48th and 52nd Normal distribution function was fitted best, in the standard meteorological weeks 28th and 29th fitted with Lognormal distribution function and in 33rd week Exponential probability distribution function was found to be the best fit. The total ground water recharge in the Upper Bhakra canal command area was found 308.73 ha-m and total ground water draft was found 235.50 ha-m. The ground water balance in the command area was found 97.60 ha-m and stage of development is 62.82% which comes under safe category of ground water utilization. Genetic Algorithm was used to allocate the optimal crop area under different rainfall conditions, tubewells running hours along with canal water supply. Nine different crop plans with crop area constraints were developed considering three different probability levels of rainfall occurrence and available canal water supply along with three different tubewells running hours per day (i.e. 3, 6 and 9 hour). Out of all optimal plans, the Plan II (considering canal water along with 6 hour of tubewells running for surplus condition) and III (considering canal water along with 9 hour of tubewells running for surplus condition) gave 7.16% and 57.58% higher net return than the net return obtained for existing pattern, under safe limit of groundwater utilization for surplus rainfall condition. The optimal cropping pattern under Plan II is rice (638.89 ha), wheat (695.40 ha), pea (18.84 ha), sugarcane (181 ha), potato (25.12 ha), lentil (10.17 ha), soya bean (24.67 ha), black gram (12.67 ha) and mustard (23.88 ha) with the net return of Rs. 93.92 million. The crops appeared in Plan III are rice (662.38 ha), wheat (722.58 ha), pea (18.84 ha), sugarcane (181 ha), potato (25.12 ha), lentil (10.17 ha), soya bean (24.67 ha), black gram (12.67 ha) and mustard (23.88 ha) with the net return of Rs. 96.52 million. In normal rainfall condition the Plan V (considering canal water along with 6 hour of tubewells running for normal condition) gives 42.39% higher net return than the net return obtained for existing cropping pattern and utilizes groundwater under the safe limit of groundwater utilization. The crops appeared in the optimal Plan V are rice (573.37 ha), wheat (589.11 ha), pea (18.84 ha), sugarcane (181 ha), potato (25.12 ha), lentil (10.17 ha), soya bean (24.67 ha), black gram (12.67 ha) and mustard (23.88 ha) with the net return of Rs. 84.87 million.
Open Access
Application of microwave treatment to enhance the shelf life of flaxseed oil using rosemary oleoresin
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-08) Tomar, Mahipal Singh; Khan Chand
Flaxseed oil is an important vegetable oil which is richest source of omega-3 fatty acids. It has high nutrional value which makes it most healthy and beneficial oil. It plays an important role n improving eye health, build up of brain and nervous system in infants, reducing the possibility of hypercholestrol, hypertension, cancer and coronary heart diseases. But due to presence of large amount of polyunsaturated fatty acid it is prone to oxidation and develops rancidity soon. Therefore present research was taken with the aim to extract the oil using microwave extraction technique and increase its oxidative stability by blending natural antioxidant rosemary oleoresin in it. For storage study of flaxseed oil, experiments were conducted using Box-behnken design with three independent variable at three levels. Variables selected for the experiment were microwave power, treatment time and rosemary oleoresin concentration. Responses selected were acid value (mg KOH/g), iodine value (I2/100 g), peroxide value (meq/kg) and shelf life (days). The data from all 17 experiments were analysed using Design Expert 10.0.1 and the response functions were developed using multiple regression analysis. Before blending of rosemary oleoresin in the flaxseed oil, effect of microwave extraction parameters on oil recovery and oil quality were studied. For extraction of oil, independent variable selected were microwave power and treatment time with three levels and effect of these extraction parameters on oil recovery (%), acid value (mg KOH/g), iodine value (I2/100g) and peroxide value (meq/kg) were studied. The results show that oil recovery varied from 74.2% to 89.56%. quality parameters were within recommended range with acid value, iodine value and peroxide value ranging from 3.04-3.77 meq /kg, 181.32 to 177.32 I2/100g and 0.82-1.61 mg KOH/g respectively. Shelf life of blended flaxseed oil ranged varied from 25 to 38 days and significantly (p<0.01) affected by both microwave power and rosemary oleoresin concentration. It was found that acid value was significantly (p<0.01) affected by both microwave power and treatment time where as iodine value was significantly (p<0.01) affected by microwave power and rosemary oleoresin concentration. Peroxide value of blended flaxseed affected by all three independent variables. Optimum value of variables were 480.4 W microwave power, 3.04 treatment time and 4995.8 ppm rosemary oleoresin concentration with responses value of 1.28 mg KOH/g, 18.75 meq /kg, 168.54 I2/100g and 39 days of acid value, peroxide value, iodine value and shelf life.
Open Access
Comparative study of artificial neural network (ann) and Adaptive Neuro-fuzzy Inference System (ANFIS) based models for solar radiation forecasting
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Gaur, Indramani Pratap Singh; Pravendra Kumar
Solar radiation is a electromagnetic radiation which we get from the Sun. Solar radiation is converted into solar energy by the uses of different techniques which include solar thermal energy, photovoltaics and solar heating. In this study an effort has been made for the development of artificial neural network (ANN) and Adaptive neuro-fuzzy inference system (ANFIS) models for daily solar radiation forecasting of Allahabad in Uttar Pradesh, India. The latitude, longitudes and elevation of study station are 25° 28' 22'' N, 81° 52' 42'' E and 98 m above mean sea level. The total geographical area of Allahabad district is 5482 Km2 according to census 2011. The daily meteorological data of 11 years (3 March, 2006 - 20 May, 2016) were collected from meteorological observatory located at Sam Higginbottom Institute of Agriculture, Technology and Science (SHIATS), Allahabad. The 70 percentage data (3 March, 2006 - 24 April, 2013) were used for model calibration and remaining 30 percentage data (25 April, 2013 - 20 May, 2016) were used for validation. The best combination of input variables was selected on basis the of Gamma statistic. In ANN model, back-propagation algorithm and log sigmoid activation function were used to train and test the models while in ANFIS models, triangular, trapezoidal, Gaussian and Generalized bell membership functions were used. The performance of the models were evaluated qualitatively by visual observations and quantitatively using various performances indices Viz. RMSE, correlation coefficient, MAPE, coefficient of efficiency and pooled average relative error. Finally, it can be concluded from the results that the performance of the ANFIS model (Gauss, 4) is better than the ANN model (11-20-1). The result showed that the current day solar radiation depends on the current day’s vapor pressure and sunshine hours, current day and one lag day of relative humidity and current day, one lag day and two lag day of temperature and wind speed.
Open Access
Optimal scheduling plan of rotational canal: a case study of Nandpur minor of Udham Singh Nagar district
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Tiwari, Deeksha; Vinod Kumar
Canal scheduling is the most important activity among the management practices and has a high impact on the performance of irrigation canal system in terms of equity, dependability, uniformity and efficiency. With increasing demand of water resources, it has become necessary to develop planning model for the irrigation and optimize scheduling of irrigation so that with limited water resources, maximum water requirements could be fulfilled efficiently. Keeping these factors in view the present study was undertaken for Nandpur minor canal located in Gadarpur Development Block of District Udham Singh Nagar, Uttarakhand to work out the optimal canal operation schedules for maximum benefits from the culturable command area of the minor canal. The 47 years (1971-2017) rainfall data were analyzed for determining the rainfall pattern of the study area. By arranging the daily rainfall data to weekly, monthly and yearly basis the probability of wet, normal and dry rainfall spells was estimated. The analysis revealed that the week 23 to 39 received normal to above normal (wet) rainfall whereas the remaining weeks experienced below normal (dry) rainfall. The annual rainfall analysis showed that the probability of getting normal rainfall in the study area was 55.31%. In the decadal rainfall analysis, the continuous decrease and increase of monthly rainfall during the month of July and September, respectively, indicated a late onset and withdrawal of monsoon in the region during 1975-2004. The linear programming optimization model was developed and employed for the allocation of the land and water resources optimally. The gross irrigation water requirement for cultivated crops was estimated using CROPWAT ver.8.0 software. Three rotations of canal operation, namely 14 days (7 days “OFF” and 7 days “ON”), 21 days (7 days “OFF” and 14 days “ON” or 14 days “OFF” and 7 days “ON”) and 28 days schedule (7 days “OFF” and 14 days “ON” or 14 days “OFF” and 14 days “ON” or 7 days “OFF” and 21 days “ON) for full and 75% of design discharge capacity of minor canal under normal and dry rainfall conditions were tested to arrive at the optimal scheduling of the canal. The global optimal schedule for Nandpur minor was obtained as 28 days (21 days “ON”) at full canal capacity and normal rainfall conditions having net return from the command as Rs. 47.78 Million and having entire area of 577 ha under cropping activities (59.07%, 10.94% and 29.98% area under Wheat, Pea and Sugarcane, respectively). The 21 days (14 days “ON”) operation schedule at full canal apacity and normal rainfall conditions having net return of Rs. 46.67 Million with 64.95%, 5.06% and 29.98% area under Wheat, Pea and Sugarcane, respectively and no land left for allocation appeared at second rank.
Open Access
Temporal trend analysis of monthly reference evapotranspiration and climatic variables by non-parametric methods
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Bikesh Kumar; Singh, Praveen Vikram
Open Access
Design, development and performance evaluation of laboratory scale hydrodynamic cavitator
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Bhore, Nilesh Shivaji; Lohani, U.C.
The present study entitled, “Design, Development and Performance Evaluation of Laboratory Scale Hydrodynamic Cavitator” was conducted in the department of Post-Harvest Process and Food Engineering, G.B.P.U.A.T, Pantnagar, Uttarakhand during 2016-18. Agriculture is the backbone of the Indian economy because 75% of India’s population depends on agriculture or agro-industries for livelihood. Thus, there is a huge amount of agricultural residues generated in Indian farms which are either unutilized or burnt in open farms causing environmental problems. With the annual Indian production of fruits and vegetables alone estimated as 243 million tons, assuming the processing levels at 2% for the organized sector and 30% residue generation, one could expect generation of about 1.45 million tons of fruits and vegetables processing waste annually in India alone. One of the most beneficial approaches is to recover the bioactive constituents, especially the phenolic compounds, making full use of them in the nutraceuticals/functional foods, medicines, pharmaceuticals and cosmetics industries. Hydrodynamic cavitation is one such innovative technology which can be used for extraction of valuable bioactive compounds from agricultural and horticultural waste. Therefore, the present research work was undertaken for design, development and performance evaluation of laboratory scale throttle valve based hydrodynamic cavitator. The experiments were conducted to study the effect of process parameters on cavitation characteristics for optimum performance of cavitator. A full factorial design with three independent variables at three levels was used for conducting the experiments. The independent variables selected were throttle valve open area (22, 42 and 62%), number of passes (5, 10 and 15) and downstream elevation (2, 2.5 and 3 m). The cavitation number, cavitation yield (g/J), and output product temperature (ºC) were analysed. The data from all 27 experiments were analysed using Design Expert 10.1.1 and the response functions were developed using multiple regression analysis. The optimum level of variables of process parameters obtained for optimum performance of cavitator were 22% throttle valve open area, 5 number of passes and 3 m downstream elevation. The optimum values of responses were of 0.5 cavitation number, 2.76 x10-7g/J of cavitation yield and 33.1ºC output product temperature. Significant (p<0.05) effect of process parameters were found in all responses. On validation of the model for optimum performance of cavitator, it was found that the model was accurate as the prediction error was only in the range of - 4.16 to 13.2%.

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