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.
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...
(guntur, 2022-08-17) GOVINDARAJU; SRINIVASA RAO, V
Coarse cereals are known for nutria-rich content and having characteristics like drought tolerance, photo-insensitivity and resilient to climate change etc. Hence, they form the backbone of dryland agriculture. Coarse cereals include jowar, pearl millet, barley, small millets, maize and ragi. At the turn of millennium, demand for coarse cereals was declining due to changes in food habits and uncertainty of prices in agricultural markets. Farmers are generally believed to be more aware of prices. The decisions of farmers concerning time and place of sale for their farm produce are motivated by price levels. Their decisions affect the pace of arrivals and prices in different markets. Hence, forecasting these prices has a significant role.
This study investigates the secular trend, seasonal indices, and forecasting the prices of coarse cereals. Three major markets for each crop, viz., Ballari, Bangalore and Koppal for bajra and jowar, and Arsikere, Bangalore and Hassan markets for maize and ragi, are considered for this study. The data for the analytical model was mainly from secondary sources. Polynomial curve fitting (least square method) and seasonal indices (ratio to moving average method) were used to analyze the trend and seasonal components of price series. The ANN and ARIMA models were used to forecast the prices of coarse cereals in selected markets of Karnataka.
The findings reveal that prices of coarse cereals have registered a significant increase in trend over the period for all the markets. All the selected markets for coarse cereals have shown a seasonal pattern except for jowar prices in Ballari and ragi prices in Arsikere and Hassan markets. The best fit ANN and ARIMA models were used to forecast the prices of coarse cereals in all the above markets for a duration of twelve
months through a lagged series. Based on the percentage of forecast error, an ideal model was proposed among the ANN and ARIMA models for each selected market. However, ANN models outperform ARIMA in all selected markets except for ragi prices in the Bangalore market where ARIMA outperforms.
The present study entitled “Behaviour of Prices and Arrivals of Major Vegetables
in Selected markets of Tamil Nadu” was mainly aimed at to study the secular trend,
seasonal indices, cyclic variation, irregular variation, association and to forecast the
arrivals and prices by best fitted model. Four major vegetable markets viz., Chennai
Koyambedu market, Oddanchatram Gandhi market, Madurai Paravai market and
Coimbatore wholesale market for three highly consumed vegetables (onion, tomato and
Green chillies) are considered for this study.
The secondary data on monthly modal prices (Rs/qtl) and total monthly arrivals
(qtls) were collected from respective market Committee for the period of 8 years (2011 to
2018). The trend in the data was studied by the principle of least square. For evaluation of
seasonality in arrivals and prices, Multiplicative time series analysis, twelve month
moving average have been calculated.
In Koyembedu market, tomato arrivals and prices were loftier in the month of
November; onion arrivals were maximum in the month of February whereas the prices
were on hike in the month of September; chillies arrivals were high in the month of
November whereas prices reached its peak in the month of June. In Oddanchatram
market, tomato arrivals were loftier in the month of March whereas peak prices were
observed in the month of July; onion arrivals were maximum in the month of March and
the prices were on hike in the month of October; chillies arrivals were high in the month
of March whereas prices reached its peak in the month of March.
In Paravai market, tomato arrivals and prices were loftier in the month of
November; onion arrivals were maximum in the month of May whereas prices were on
hike in the month of October; chillies arrivals were high in the month of February whereas
prices reached its peak in the month of July. In Coimbatore market, the tomato arrivals
were loftier in the month of December whereas peak prices were observed in the month
of June; onion arrivals were maximum in the month of January and the prices were on
hike in the month of November; chillies arrivals were high in the month of November
whereas prices reached its peak in the month of March.
To ascertain the relationship between arrivals and prices in respective market,
correlation coefficient was computed. There was a negative and significant correlation
between arrivals and prices of Chillies in Koyembedu market; Onion in Oddanchatram
market; Tomato in Paravai market and Coimbatore vegetable Market. It was inferred
infers that the negative correlation existed between arrivals and prices for all vegetables
in their respective markets except tomato in Koyembedu and Paravai markets.
Seasonal Auto Regressive Integrated Moving Average models were used for
forecasting the arrivals and prices. At the identification stage, one or more models are
tentatively chosen and the most suitable models were selected based on highest R2 and
least RMSE. The predicted values and actual values were similar to each other in most of
The Present study entitled “Statistical models for prediction of area, production
and productivity of selected oilseeds in Andhra Pradesh” has been undertaken to fit
different trend equations like linear, non-linear and time series models for selected oilseeds
like Groundnut, Niger, Sesame and Castor and also made the future forecast up to 2022-23
AD. The study was carried out for Andhra Pradesh state using time series data from
1965-66 to 2017-18.
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 were fitted to the area, production and productivity of
selected oilseed crops. The best-fitted model for future projection was chosen based upon
highest coefficient of determination (R2) with least RMSE and MAPE values.
The study revealed that the area, production and productivity of Groundnut marked
fluctuating increasing and decreasing trend during the study period 1965-66 to 2017-18;
for the forecasted period i.e. up to 2022-23 area and production showed decreasing trend,
productivity increasing trend . In Niger there was decreasing trend in area and production
whereas productivity showed an increasing trend; the forecasts exhibited an increasing
trend in area and production, slightly increasing trend in productivity. The Sesame crop
revealed that area and production marked decreasing trend but productivity slightly
fluctuating increasing and decreasing trend; forecasts of area, production and productivity
depict increasing trend. Whereas Castor crop area and productivity showed decreasing
trend and production showed fluctuating increasingand decreasing trend during the study
period; forecasts exhibited that area as decreasing trend but production and productivity