Bøger af Ram Krishna Pandey

Project Report from the year 2009 in the subject Engineering - General, grade: Bachelor of Technology, , language: English, abstract: In this study an attempt was made to analyse the fruit arrival and price patterns in a wholesale fruit market (Haldwani Mandi) for trend and seasonality in order to develop forecasting models for the fruit arrival process so as to rationalize an important input to fruit mandi system design. Historical time series data on monthly arrivals and average monthly prices was collected from the Haldwani mandi records for the period January, 1990 to April, 2009. Arrivals and prices of five fruits (Mango, Banana, Apple, Peach and Orange) were considered. A program in MATLAB 7.0 was developed for trend and seasonal analysis. For forecasting, these trend models were extended and seasonal index were applied for each month. Forecasting models were developed on the basis of first 204 months (January 1990 to December 2006) data using time series analysis technique. Forecasts were generated for the next 36 months (January 2007 to December 2009). These forecasts were compared with the actual arrivals for January 2007 to April 2009. Results of the present investigation have shown that arrival of Apple was observed in the month of July, Banana arrived maximum in October, whereas Mango, Orange and Peach recorded maximum arrival in the months of July, April and May respectively. Seasonal indices corresponding to these peak arrivals were 626.66, 136.29, 876.06, 371.17 and 439.89 respectively. In the case of Apple, arrivals and prices were inversely correlated; i.e., prices were low during peak arrival. However, in the case of banana, there was very little correlation; one major reason for this seems to be that the prices of Banana did not vary throughout the year. There was a increasing trend in the case of prices. In the trend analysis, it was observed that the arrival of Apple and Orange had a decreasing trend for the years under analysis, whereas Mango and Banana had an increasing trend for this period. The monthly arrival of Peach almost remained the same. Future forecasts were developed for the monthly arrival and average monthly prices of these selected commodities. Maximum error for each forecast was calculated on the basis of peak arrival/ prices in a year and maximum error was obtained as 26.89% in forecasting the arrival of Apple.

Scientific Study from the year 2015 in the subject Engineering - General, , language: English, abstract: Green Bitter gourds (Momordica charantia L.) belong to ¿cucurbitacceae¿ family and are commonly called as bitter gourd, papailla, karalla, balsam apple and balsam pear etc. in different part of the world Bitter gourd contains an array of biologically active plant chemicals including triterpenes, protein and steroids. Bitter gourd have extremely low amount of calories but have a lot of valuable nutrients. In India, bitter gourd stored in the dried form. The indigenous practice is to dry the sliced vegetable in sun during October-November and used up to the month of May. However, the quality of the dried product is rather poor.Experiment were conducted in TNAU fluidized bed dryer to study the drying characteristic of green bitter gourd slices at five level of temperature (50,55,60,65,700C), five level of sample (100,125,150,175,200 g) and three level of air velocity (1.5,2,2.5 m/sec). Bitter gourd slice was dried in hot air dryer. Moisture loss data were recorded periodically at an interval of five minutes for the first forty minutes and consequently fifteen minutes intervals. Quality characteristics of bitter gourd slice were determined in terms of rehydration ratio, color, ash content. The data were analyzed to study drying characteristics of a bitter gourd.The effect of various factors was analyzed using analysis of variance (ANOVA) technique. Second order model was fitted in the responses and independent variables using regression analysis. The drying behaviour of Bitter gourd was mathematically analyzed using Page¿s, Logarithmic and Exponential models. The goodness of fit of the model was tested using coefficient of determination (R2),and standard error of estimate (SEE).The effect of drying temperature, air velocity, sample weight and their interactions were significant on drying time at 5% level of significance. Logarithmic model was found to describe the drying behaviour of Bitter gourd better as compared to Page¿s and Exponential model. The optimum level of independent variable for drying of green gourd obtained by using numerical optimization of multiple responses viz, drying time, dehydration ratio, ash content, and color were temperature of 550C ,velocity 2.5m/sec sample size of 100g. These optimum values are recommended for drying of Bitter gourd.