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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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2015 - 20192
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Author: NAIPUNYA, J × Start date: 1990 × Type: Thesis × Thesis Type: M.Sc ×
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    ThesisItemOpen Access
    EFFICIENCY OF FUTURES TRADING AND DIRECTION OF TRADE IN SELECTED AGRICULTURAL COMMODITIES
    (Acharya N G Ranga Agricultural University, Guntur, 2019) NAIPUNYA, J; BHAVANI DEVI, I
    The present study entitled “Efficiency of futures trading and direction of trade in selected agricultural commodities” was undertaken to study the growth and instability of futures trading in terms of quantity and value of selected agricultural commodities i.e., maize, chilli and bengal gram which were traded in NCDEX, efficiency of futures trading in terms of price discovery and transmission, extent of volatility in spot market due to futures trading and analysis of direction of trade of maize, chilli and bengal gram. Among the three agricultural commodity exchanges, major share of agricultural commodities was in favour of National Commodity and Derivatives Exchange (NCDEX) i.e., 82.82 and 75.83 per cent in terms of quantity and value respectively. The share of Multi Commodity Exchange (MCX) and National Multi Commodities Exchange (NMCE) was 10.37 and 6.81 per cent in terms of quantity and 18.19 and 5.98 per cent in terms of value respectively. Analysis of growth and instability of maize traded in NCDEX revealed that maximum positive compound growth rates were observed in both quantity (38.91%) and value (43.67%) in 2006 and maximum negative compound growth rates were found both in quantity (-23.85%) and value xv (-23.46%) in 2008. Maximum positive compound growth rates of chilli in both quantity (18.45%) and value (20.78%) were observed in 2009 and maximum negative compound growth rates were observed in both quantity (-40.87%) and value of chilli traded in NCDEX (-41.19%) in 2014. Maximum positive compound growth rates of bengal gram were observed in both quantity (30.62%) and value (34.20%) in 2005 and maximum negative compound growth rates were observed in both quantity (-45.73%) and value (-39.31%) in 2016. Instability analysis of maize futures trade showed very high variation in 2005 in terms quantity (132.61%) and in 2017 in terms of value (112.59%). Futures trade showed least variation in quantity (25.84%) in 2010 and in value (27.10%) in 2011. Instability analysis of chilli futures trade showed very high variation in 2015 in terms quantity (130.47%) and in terms of value (123.32%) and least variation in quantity (11.13%) and in value (14.86%) during 2017. Instability analysis of futures trade of bengal gram showed very high variation in 2008 in terms of value (65.2%) and in quantity (61.62%) in 2016. The same analysis in futures trade showed least variation in quantity (16.38%) in 2007 and in value (16.83%) in 2007. “Seemingly unrelated regression” (SUR) model in maize and bengal gram showed an efficient price discovery where the futures market dominated in the price discovery i.e., Silbers and Garbage value of futures of maize and bengal gram were (0.00283), (-0.0367) and it was nonsignificant. Chilli spot market (Guntur) was efficient in price discovery. The Silbers and Garbage value of futures market was 0.0403 being significant at 1 per cent level (0.0037) indicating that futures market of chilli was inefficient in price discovery. The findings of the ADF test suggested that futures and spot prices of maize, chilli, bengal gram attained stationarity at first difference. The cointegration test revealed the presence of one co-integrating equation and confirmed the long-run equilibrium relationship among futures and spot prices of selected agricultural commodities. The causality test proved the bidirectional causality between futures and spot prices of maize implying that futures prices influenced the spot prices and spot prices influenced futures prices. Futures market showed uni-directional causality in chilli and bengal gram. Maize and bengal gram spot markets came to short-run equilibrium as indicated by level of significance at 1 per cent i.e., (0.001), (0.007) respectively and speed of equilibrium was rapid i.e., any disturbances in prices of maize and bengal gram would get corrected within 20 min and one hour in spot market prices respectively as indicated by co-efficient values. In chilli spot markets came to short-run equilibrium as indicated by level of significance xvi at 5 per cent i.e., (0.022), any disturbances in price would get corrected within 3 hours in spot markets as indicated by co-efficient values. The dynamics of changes in terms of quantity of exports of maize, chilli and bengal gram from India to different exports markets have been measured by employing Markov chain model. The results revealed that Nepal, Bangladesh and others were the most stable importers of the Indian maize with probability of retention of 88.52, 61.09 and 68.90 per cent respectively followed by Sri Lanka and Malaysia, Philippines and United Arab Emirates would be the unstable importers as it could not retain their original share. The changing pattern of chilli exports through transitional probability matrices indicated that Thailand, other countries and Vietnam were stable in importing Indian chilli with probability of retention of 80.52, 69.02 and 67.09 per cent respectively. Malaysia was the most unstable because they could not retain its original share. In bengal gram, Pakistan was one of the stable countries as revealed by the probability of retention of its share i.e., 61.35 per cent and Algeria was also another stable importer it retained its original share of 45.54 per cent fallowed by Turkey 41.13 per cent retained its original share. UAE and Saudi Arabia were the most unstable importers of Indian bengal gram because they could not retain their original share.
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    ThesisItemOpen Access
    ECONOMICS OF RICE BASED CROPPING SYSTEMS IN NELLORE DISTRICT OF ANDHRA PRADESH
    (ACHARYA N.G. RANGA AGRICULTURAL UNIVERSITY, GUNTUR, 2015) NAIPUNYA, J; RAJESWARI, S
    The present study entitled “Economic of Rice Based Cropping Systems in Nellore District of Andhra Pradesh” was under taken to study the input use pattern, costs, returns and resource use efficiency in the different rice based cropping systems. The study covered three mandals and six villages with 90 farmers cultivated rice based cropping systems. The relevant data were collected from both primary and secondary sources. Data for the year 2013-14 were collected through a pretested schedule by survey method. The data were analyzed using tabular and functional analysis. Major Rice based cropping systems identified in the study area were cropping system-I (Paddy and Cotton), cropping system -II (Paddy-PaddyGreen gram) and cropping system-III (Paddy-Paddy-Groundnut). The results showed that total cost was highest in cropping system-I (66,368) followed by cropping system-III (64,741) and cropping system-II (48,826) respectively. Gross returns were maximum in cropping system-I (1,08,000) followed by cropping system-III (96,666) and cropping system-II (70,000). The net returns were highest in cropping system-I (42,179) followed by cropping system-III (31,925) and cropping system-II (21,174) in that order. It was observed that the returns per rupee of expenditure in all the cropping systems were ranged from 1.42 to 1.63. Higher returns per rupee of expenditure in cropping system-I i.e., 1.63 followed by cropping system- III (1.48) and cropping system- II (1.42). The functional analysis revealed that machine power and fertilizer in paddy, human labour and fertilizer in cotton in cropping system-I was significantly contributed to the increase in the crop yields and income. The MVP to MFC ratio was greater than unity for machine power and fertilizer in paddy, human labour and fertilizers in cotton in cropping system- I indicating greater potentiality for further use. In the case of cropping system-II, human labour and machine power seed in kharif paddy, human labour and machine power in rabi paddy significantly contributed to the increase in the crop yields and income. The MVP to MFC ratio was greater than unity for human labour and machine power in kharif paddy, human labour in rabi paddy in the cropping system-II indicating greater potentiality for further use. The same for machine power in rabi paddy, seed in kharif paddy were less than unity indicating lesser potentiality for further use. In the case of cropping system-III human labour and fertilizer were significant in both kharif paddy and rabi paddy. Seed and fertilizer in case of groundnut significantly contributed to the increase in the crop yields and income. The MVP to MFC ratio was greater than unity for human labour in kharif paddy, human labour and fertilizer in rabi paddy and for seed in groundnut indicating greater potentiality for further use. Fertilizer in kharif paddy and groundnut were less than unity indicating lesser potentiality for further use.