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Acharya N G Ranga Agricultural University, Guntur

The Andhra Pradesh Agricultural University (APAU) was established on 12th June 1964 at Hyderabad. The University was formally inaugurated on 20th March 1965 by Late Shri. Lal Bahadur Shastri, the then Hon`ble Prime Minister of India. Another significant milestone was the inauguration of the building programme of the university by Late Smt. Indira Gandhi,the then Hon`ble Prime Minister of India on 23rd June 1966. The University was renamed as Acharya N. G. Ranga Agricultural University on 7th November 1996 in honour and memory of an outstanding parliamentarian Acharya Nayukulu Gogineni Ranga, who rendered remarkable selfless service for the cause of farmers and is regarded as an outstanding educationist, kisan leader and freedom fighter. HISTORICAL MILESTONE Acharya N. G. Ranga Agricultural University (ANGRAU) was established under the name of Andhra Pradesh Agricultural University (APAU) on the 12th of June 1964 through the APAU Act 1963. Later, it was renamed as Acharya N. G. Ranga Agricultural University on the 7th of November, 1996 in honour and memory of the noted Parliamentarian and Kisan Leader, Acharya N. G. Ranga. At the verge of completion of Golden Jubilee Year of the ANGRAU, it has given birth to a new State Agricultural University namely Prof. Jayashankar Telangana State Agricultural University with the bifurcation of the state of Andhra Pradesh as per the Andhra Pradesh Reorganization Act 2014. The ANGRAU at LAM, Guntur is serving the students and the farmers of 13 districts of new State of Andhra Pradesh with renewed interest and dedication. Genesis of ANGRAU in service of the farmers 1926: The Royal Commission emphasized the need for a strong research base for agricultural development in the country... 1949: The Radhakrishnan Commission (1949) on University Education led to the establishment of Rural Universities for the overall development of agriculture and rural life in the country... 1955: First Joint Indo-American Team studied the status and future needs of agricultural education in the country... 1960: Second Joint Indo-American Team (1960) headed by Dr. M. S. Randhawa, the then Vice-President of Indian Council of Agricultural Research recommended specifically the establishment of Farm Universities and spelt out the basic objectives of these Universities as Institutional Autonomy, inclusion of Agriculture, Veterinary / Animal Husbandry and Home Science, Integration of Teaching, Research and Extension... 1963: The Andhra Pradesh Agricultural University (APAU) Act enacted... June 12th 1964: Andhra Pradesh Agricultural University (APAU) was established at Hyderabad with Shri. O. Pulla Reddi, I.C.S. (Retired) was the first founder Vice-Chancellor of the University... June 1964: Re-affilitation of Colleges of Agriculture and Veterinary Science, Hyderabad (estt. in 1961, affiliated to Osmania University), Agricultural College, Bapatla (estt. in 1945, affiliated to Andhra University), Sri Venkateswara Agricultural College, Tirupati and Andhra Veterinary College, Tirupati (estt. in 1961, affiliated to Sri Venkateswara University)... 20th March 1965: Formal inauguration of APAU by Late Shri. Lal Bahadur Shastri, the then Hon`ble Prime Minister of India... 1964-66: The report of the Second National Education Commission headed by Dr. D.S. Kothari, Chairman of the University Grants Commission stressed the need for establishing at least one Agricultural University in each Indian State... 23, June 1966: Inauguration of the Administrative building of the university by Late Smt. Indira Gandhi, the then Hon`ble Prime Minister of India... July, 1966: Transfer of 41 Agricultural Research Stations, functioning under the Department of Agriculture... May, 1967: Transfer of Four Research Stations of the Animal Husbandry Department... 7th November 1996: Renaming of University as Acharya N. G. Ranga Agricultural University in honour and memory of an outstanding parliamentarian Acharya Nayukulu Gogineni Ranga... 15th July 2005: Establishment of Sri Venkateswara Veterinary University (SVVU) bifurcating ANGRAU by Act 18 of 2005... 26th June 2007: Establishment of Andhra Pradesh Horticultural University (APHU) bifurcating ANGRAU by the Act 30 of 2007... 2nd June 2014 As per the Andhra Pradesh Reorganization Act 2014, ANGRAU is now... serving the students and the farmers of 13 districts of new State of Andhra Pradesh with renewed interest and dedication...

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2014 - 20164
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Subject: Agricultural Statistics and Informatics × End date: 2016 × Type: Thesis × Thesis Type: M.Sc ×
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    ThesisItemOpen Access
    CROP-YIELD WEATHER RELATIONSHIP OF PRAKASAM DISTRICT IN ANDHRA PRADESH
    (Acharya N.G. Ranga Agricultural University, 2016) HEROLD DEEPAK ROY, B; SHAIK NAFEEZ UMAR
    Rainfall is one of the important climatic factor that influences crop production in particular and agriculture in general. Here, the distribution of rainfall can be studied by fitting suitable statistical distribution to the monthly rainfall data recorded over 15 years (2000-01 to 2014-15) for Prakasam district in Andhra Pradesh. It revealed that most of the months follow ‘Type I’ (or) Beta distribution while the months of July and September assumed Pearsonian “Type II” (or) “Type VII” i.e., Normal distribution and the month of November shown “Pearsonian Type IV” distribution. Statistically, estimation of a crop yield-weather relationship is fitting a multiple regression equation with yield as the dependent variable and weather parameters during the crop growth period as the independent variables. The analysis has been carried out on the basis of crop yields and weather variables for 15 years of monthly time series data (2000-01 to 2014-15). Weather impact on the crop yields was studied on the basis of rainfall, temperature (maximum and minimum) and relative humidity (AM and PM). In fitting the crop yield-weather relationships, the assumption of a continuous time trend was found to be inappropriate when the impact of new technology may exists in the form of quantum jumps over time which is termed as discrete time effect. For this situation, concept of control charts was applied using one sigma limits and sub-periods were identified. These sub-periods were formed with the year of quantum jump as the cut-off point. Nature of time trend in the sub-periods and overall yields was investigated by fitting time trend regression equation respectively. All the crops revealed ‘differential’ trend effect in the yields of the two sub-periods indicating that there could be a differential weather response of the crop. Hence, it is appropriate to fit the crop yield-weather relationships separately for each of the two sub-periods as well as for overall period. It was observed that an overall relationship may not be appropriate to explain the yield variations as it consisted of certain irrelevant regressors. Considering this behaviour, separate relationships were fitted for the different subperiods existing in the crop yield data and the analysis revealed the existence of a differential response of the yields to weather. The variables identified in these relations suitably explain the weather response with respect to the crop growth stages. Hence, it was concluded that yields under a given technology only could be forecasted (based on weather variables) on the basis of the corresponding subperiod relationship (equation).
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    ThesisItemOpen Access
    ANALYSIS OF SPATIAL AND TEMPORAL VARIATIONS IN AREA, PRODUCTION AND PRODUCTIVITY OF TOBACCO IN ANDHRA PRADESH
    (Acharya N.G. Ranga Agricultural University, 2016) SRI RAMA JOGAMBA, J; SRINIVASA RAO, V
    An attempt was made to study the spatial and temporal variations in area, production and productivity of tobacco in the major tobacco growing districts of Andhra Pradesh viz., Prakasam, Guntur, East Godavari, West Godavari and the Andhra Pradesh state as a whole. The study was based on 28 years of tobacco data from 1987 to 2014. The graphical analysis was used to study the variations in area, production and productivity of tobacco. An attempt was also made to measure the growth in area, production and productivity of tobacco with due consideration of discontinuity in the data. Generally, the time series data on production of crops often exhibits a discontinuity in the year to year variations. These disturbances are mainly due to the impact of technological innovations in the crop. Under this situation, the conventional time trend models fail to provide efficient forecasts, as these models are based on the assumption of uniformity in the year to year variations. To deal with this situation, the spline models were explored for forecasting the tobacco production, as discontinuity in the year to year variations is the fundamental assumption in these models. The graphical analysis indicated that the time series data on area, production and productivity of tobacco exhibited a discontinuous trend in all the districts as well as in the state as whole. The growth analysis revealed that the area of tobacco was increasing in the districts of Prakasam and West Godavari and there is a considerable decline in Guntur and East Godavari districts and in the whole state of Andhra Pradesh. Production of tobacco was increasing in all the districts, except in the district of East Godavari and there was a considerable increase in the average level of productivity over the years due to the technological innovations in the crop. The spline models were found to be relatively efficient than the conventional trend fitting models in forecasting of tobacco
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    ThesisItemOpen Access
    STATISTICAL ANALYSIS ON ARRIVALS AND PRICES OF COTTON IN SELECTED MARKETS OF ANDHRA PRADES
    (ACHARYA N.G. RANGA AGRICULTURAL UNIVERSITY, GUNTUR, 2015) CHAITHANYA KUMAR, G; MOHAN NAIDU, G
    The present study “Statistical analysis on arrivals and prices of cotton in selected markets of Andhra Pradesh” was mainly aimed at to study the secular trend, seasonal, cyclic fluctuations, association and to forecast the arrivals and prices of cotton in the selected markets of Andhra Pradesh. Five markets were selected for the study viz., Adoni, Jammikunta, Karimnagar, Khammam and Warangal based on maximum quantity of arrivals. The secondary data on monthly total arrivals (Qtls) and modal prices (Rs/Qtls) were collected for the period from April 2000-01 to March 2013-14 (14years) for the selected markets. The method of least squares, twelve months ratio to centered moving average, correlation analysis and ARIMA model were used. xiv The results revealed that in the long run all the selected markets showed an increasing trend except in Warangal market with regard to cotton arrivals whereas the trend in prices of cotton were almost similar (increasing) in selected markets. In the case of seasonal indices of arrivals and prices of cotton in Adoni market revealed that the highest arrivals was noticed in month of January and the lowest arrivals was noticed in the month of July. The highest price was noticed in the month of September and the lowest price was noticed in the month of December. In Jammikunta market, the highest arrivals in month of November and lowest in the month of September while highest prices was observed in the month of July and lowest prices in October. In Karimnagr market, maximum arrivals in month of December and minimum in September whereas the highest prices was the month of March and the lowest prices in May. In Khammam market, the highest arrivals were noticed in month of November and the lowest in September while highest prices were observed during the month of July and the lowest prices in the month of October. In Warangal market, the peak arrivals were noticed in month of November and the lowest arrivals in the month of September whereas the highest prices were noticed in the month of September and lowest prices in the month of November. Well defined cycles could not be discerned in all the selected markets of cotton. The cyclical trend in selected markets showed that there were no constant period between the cycles in both arrivals and prices. The correlation coefficient was computed to ascertain the pattern of association between market arrivals and prices of cotton in selected markets. A positive and significant relationship was recorded in Adoni, Karimnagar and Khammam markets where as in Jammikunta market positive and non significant relationship was observed. The negative and non significant relationship was noticed in Warangal market. The arrivals and price were forecasted from April, 2014 to March, 2015 in the selected markets and the results indicated that the arrivals were ranging from 11627 to 284891 quintals of cotton whereas the prices ranged from 4236 to 5166 Rs/Quintals.
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    ThesisItemOpen Access
    TIME SERIES ANALYSIS OF AREA, PRODUCTION AND PRDOUCTIVITY OF MAJOR COARSE CEREALS IN ANDHRA PRADESH
    (ACHARYA N.G. RANGA AGRICULTURAL UNIVERSITY, 2014) NIREESHA, VAKA; SRINIVASA RAO, V
    The Present study entitled “Time Series Analysis of area, production and productivity of major coarse cereals in Andhra Pradesh” has been undertaken to fit different trend equations like linear, non-linear and time series models for major coarse cereals like Maize, Sorghum, Pearl millet and Finger milet and also made the future forecasts by 2020 AD. The study was carried out for Andhra Pradesh state using time series data from 1966 to 2012. For forecasting purpose ten linear and non-linear growth models viz., linear, logarithmic, inverse, quadratic, cubic, compound, power, s-curve, growth and exponential and time series models like ARIMA and Exponential Smoothing models were fitted to the area, production and productivity of selected crops and influence of weather parameters like Maximum temperature (0C), Minimum temperature (0C), Rainfall (mm), Morning Relative Humidity (RH1) (%), Evening Relative Humidity (RH2) (%) on productivity were calculated by using statistical analysis like Karl Pearson’s Correlation analysis and Multiple Linear Regression Analysis. the best-fitted model for future projection was chosen based upon highest Theil’s U-Statistic, coefficient of determination (R2) and significant Adjusted R2 with least MAPE values. The study revealed that the area, production and productivity of maize marked increasing trend during the study period 1966-2012 the same trend was continued for the forecasted period i.e up to 2020. In sorghum there was an increasing trend followed by decreasing trend in area and production whereas productivity showed an increasing trend; the forecasts also exhibited an increasing trend. The pearl millet crop revealed that area showed decreasing trend but production and productivity showed slightly increasing trend. Whereas finger millet crop area and production showed decreasing trend and productivity showed slightly increasing trend during the study period. Forecasts also exhibited the same trend. From correlation analysis where RH2 showed significant correlation with productivity of Maize crop. In sorghum crop, only RH1 showed significant correlation with productivity. In pearl millet, RH1 and RH2 showed significant correlation with productivity. In case of finger millet for productivity only RH1 showed significant correlation. The Multiple Linear Regression Analysis revealed that the predicted models for all the crops were significant in RH1. It was also identified that other than weather parameters many factors are influencing Productivity of these crops.