Acharya N. G. Ranga Agricultural University, Guntur (AP)

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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Open Access
A STUDY ON INCOME INEQUALITIES AMONG AGRICULTURAL HOUSEHOLDS IN ANDHRA PRADESH STATE
(guntur, 2022-08-04) AREEF, MULLA; RADHA DEPARTMENT, Y.
For this study, primary data on agricultural households were collected through personal interview method for the agricultural year 2018-19 from Andhra Pradesh state to analyse the agricultural household’s annual income from different sources, determinants of different income sources, construction & decomposition of the income inequality and the consumption expenditure pattern across landholding size of farmer households. Totally 300 agricultural households were selected with 100 farmers each from three selected districts (viz., Srikakulam, Guntur and Ananthapuramu) based on highest number of operational holding. One hundred farmers in each district were further distributed among top two mandals with highest operational holding by adopting the proportionate stratified random sampling method. To meet the objectives of present study, fifty farmers in each mandal were conveniently distributed among five categories of landholdings with ten farmers in each category. The descriptive statistics and various cost concepts (Cost A, B, C) were used to calculate the agricultural household’s income from different sources viz., cultivation, agricultural wages, livestock, business/ services, off-farm and other sources and analysed total annual net income of different landholding categories of farmers in the study area. Ogive Index (OI), Simpson Index (SI) and Herfindahl-Hirschman Index (HHI) were employed to capture the number of income generating activities. Seemingly Unrelated Regression Estimator (SURE) model was used to identify factors which help in distribution of income among various sources. Lorenz curve, Gini ratio, Atkinson’s coefficient, Mean Log Deviation (MLD) and Theil’s index were employed to measure the income inequality for agricultural households across landholding categories. Lerman and Yitzhaki (1985) methodology was followed to decompose the Gini coefficient of total income by income sources and XIII regression based inequality decomposition (Shorrocks, 1982) approach was employed to identify each factor contribution to income inequality. Average propensity to consumption (APC) was formulated to know the proportion of income consumed by agricultural households and Engel ratio was estimated to know the difference in expenditure on each of food and non-food items separately by the agricultural households. Lorenz curve, Gini ratio, Atkinson’s coefficient, MLD and Theil’s index were employed to measure the consumption expenditure inequality for agricultural households across landholding categories. For marginal and small farmer households, income from livestock and agricultural wages combinedly contributed to nearly 50 per cent of total income. Semi-medium, medium and large farmer households received nearly 50 per cent of income from cultivation only. Access to credit, access to extension services, access to irrigation, access to price information, age of household head, education, farming experience, non-farm income earning members, number of animals, family size of household, size of landholding, size of operational holding and value of farm assets were the major determinants to access various income sources among agricultural households. Across the landholding size wise categories, except large farmers higher unequal distribution of income was reported by other sources. Gini, Atkinson, MLD and Theil indices vary across the landholding size categories. Among different sources, the highest proportion of income inequality share was contributed by cultivation across the landholding size categories except marginal farmer households. Similarly, among the factors analysed, the highest proportion of income inequality share was contributed by access to credit followed by access to irrigation, age of household head, etc. Medium farmer households were observed with highest consumption expenditure share on high value commodities followed by large, small, marginal farmers and semi-medium farmer households. Marginal farmer households were recorded with lower monthly income and showed higher average propensity to consumption expenditure. However large farmers were with higher monthly income but lower average propensity to consumption expenditure. Diversification of income earning activities towards cultivation and animal husbandry will be useful to marginal and small farmer households to maintain minimum level of income per month. There is a need to emphasize on intensification as well as diversification of fragmented landholdings especially for marginal and small farmer households. Village level remunerative price realization (viz., FHP, MSP, etc.) may act as a push factor to enhance farmers income. Income received from non-farm activities, if reinvested in business activities through purchase of raw materials will improve the farmer’s income from non-farm activities. Government should focus on improving public provisioning of quality medical services and education, so as to reduce the share of expenditure on non-food items and enhance the consumption expenditure on high value commodities, among the food items.
Open Access
AN ECONOMIC ANALYSIS OF CROP INSURANCE IN RISK MITIGATION OF FARMERS IN ANDHRA PRADESH
(guntur, 2022-08-04) SHWETHA, SOJU; RADHA, Y.
The study was conducted to include crop insurance data collected from the selected sample and the state of Andhra Pradesh as a whole. The selected sample consists of 30 farmers each from Peddapasapula village of Peddamudium mandal of Kadapa district, Naganathana Halli village of Adoni mandal of Kurnool district, Upputur village in Parchur mandal of Prakasam, Jaganathapuram village in Tadepalligudem mandal of West Godavari district, Tajangi village of Lambasinghi mandal of Visakhapatanam and Ammanoru village in Regidi Amadala Valasa mandal of Srikaklam, hence there are 180 farmers sampled from 6 villages. The primary data collected from the farmers was pertained to the period of 2017-18. The study consists of analysis of the performance of crop insurance in Andhra Pradesh involving data of area covered, farmers covered, farmers benefitted and insurance premium for the years 1985-86 to 2016-17. The sources of secondary data include Handbook of Statistics on the Indian Economy, Statistical Abstracts, Season and Crop Reports published by Directorate of Economics and Statistics, Government of Andhra Pradesh and NSSO Reports, Books, Journals, Periodicals, Websites etc. The collected raw data were classified and computed according to the objective requirements of the study. The study was conducted primarily to determine the risk associated with crop production at farm level in Andhra Pradesh, the impact of crop insurance on the farm economy. The growth and performance of the Crop Insurance schemes through the years of 1985-86 to 2016-17 was studied and the constraints in adoption and implementation of crop insurance in the sampled villages and districts were analysed. The crops raised in the sampled villages and districts were found to varying in a scale in moderate to highly by the Cudde Della Valle Instability Index. The crops that were raised rainfed showed maximum instability while the irrigated crops of West Godavari district exhibited moderate instability. xii The statistics of numbers of farmers and area covered under Crop insurance, the sum insured and premium collected were found to show steady growth from 1985-86 to 2016-17; while the claims approved and farmers benefitted from the crop insurance scheme showed frequent peaks and lows as it depends on the incidence of crop losses and extent of adoption of crop insurance scheme. The various indicators of performance of crop insurance, such as beneficiary ratio, claims to sum insured ratio and premiums to sum insured, also showed favourable results regarding the effectiveness in operation and growth of the crop insurance schemes. While the premium to sum insured shows dismal inference on the non sustainability of the operating crop insurance. All farming systems that had adopted crop insurance gave an optimum solution for crop production, while the cropping systems of non adopter farmers were not feasible, implying a stark contrast between the insured and uninsured. Thus crop insurance impact cropping systems of farmers in achieving optimum production according to the MOTAD model. The factors affecting the adoption of crop insurance were mostly the age of the farmer, the access to non institutional credit, size of the land holding, etc. Separate regressions were carried out for each zone to see how the various factors affected the adoption of crop insurance in these zones of differing cropping systems. In the districts of Kadapa, Kurnool, Prakasam and Visakhapatanam, the status of irrigation of the crops also favoured adoption of crop insurance. In the district of Visakhapatanam, the presence of an off farm source of income also enabled the adoption of crop insurance by the farmers. The rate of premium collected from the farmers was found to have no significant effect in the adoption or lack of it by the farmers. The major constraints in adoption of crop insurance by the farmer were: the lack of definite demarcation of notified area, resulting in overlapping areas of coverage and the inability to disburse the indemnity on time before the next cropping season. The major constraint in implementation of crop insurance by the Lead banks and the Mandal Agriculture office was the inadequacy in filing details regarding the farmers, which in turn affects timely disbursement of indemnity to the farmers and the unclear demarcation of the notified units of land area in the districts.
Open Access
STUDY ON PERFORMANCE OF DAIRY SECTOR IN ANDHRA PRADESH
(guntur, 2022-08-04) VYKHANESWARI, K.; SUNIL KUMAR BABU, G.
India surpassed the major milk producing countries and continued as the largest milk producing nation with milk production 187.7 MT in 2018-19 by contributing about 22% of the world‟s milk production. The dairy sector contributes significantly to generating employment opportunities and supplementing the income of small and marginal farmers and landless labourers of rural India, besides providing food security. Cooperative and private dairy industries play a major role in the procurement, processing, and marketing of milk and milk products. As dairying is gaining more importance in providing livelihood to a large number of farmers and various disputes are being faced in the existing situation of the dairy sector. Hence, the present study entitled “Study on performance of the dairy sector in Andhra Pradesh” was taken up with the following objectives 1. to study the growth and performance of dairy sector in Andhra Pradesh 2. to study the structural changes in dairy sector of Andhra Pradesh 3. to identify and analyse the factors influencing the performance of cooperative vis-à-vis private dairy industries of Andhra Pradesh and 4. to identify the problems faced by the different stake holders in dairy sector of Andhra Pradesh. A multistage sampling technique was used for the study and Andhra Pradesh state was purposively selected. Three districts based on the highest milk production were selected viz., Krishna, Guntur, and Kurnool. Three cooperative and three private dairy industries were selected, two from each district includes one cooperative and one private dairy industry. A total of 180 xi farmers were selected, 30 from each dairy industry i.e., 60 from each district. A number of 30 wholesalers, 30 retailers and 30 consumers were selected as five from each dairy industry. The primary data was collected through interview schedule in the agricultural year of 2018-19 and secondary data from various sources like the department of animal husbandry, websites, chief planning office of the district, reports, etc. The overall compound growth rate of the livestock population was observed to be 0.99%, a positive and significant. It was observed that a positive and significant growth rate was recorded for the buffalo population from 1956 to 2019 with a growth rate of 0.57%. The cattle population was recorded with a negative growth rate of -0.44% from 1956 to 2019. Milk production in Andhra Pradesh has been increased from 4036 to 15044 „000 metric tonnes during the period of 2000-01 to 2018-19. The compound annual growth rate of milk production was observed to be positive and significant from 2000-01 to 2018-19 with 7.6%. The compound growth rate of milk yield (kg/day) was noticed to be 3.2% which was positive and significant from 2000-01 to 2018-19. The overall compound annual growth rate of milk production density (kg/day/sq.km) showed a positive and significant growth rate of 7.5% for the entire period. The overall compound annual growth rate of dairy cooperative societies from 2000-01 to 2018-19 was observed to be a positive and significant growth rate of 0.33%. The compound annual growth rate of veterinary institutions was observed to be a positive and significant rate of 0.49%. The highest annual growth rate was recorded with 27.21 % in the year2010-11 and the lowest with -22.79% in the year 2014-15. The overall compound annual growth rate of AI centres was recorded to be positive and significant with 5.28%. The number of AIs done showed a positive and significant growth rate of 4.00% for the overall period of 2000-01 to 2018-19. The area under fodder development („000 acres) has increased from 285.63 (2000-01) to 538.63 (2018-19). The overall compound annual growth rate of the area was recorded at 3.59%. Chow test was employed to study the structural change in the dairy sector of Andhra Pradesh. The outcome of the Chow test shows that F calculated value is greater than F table value at 5% level of significance which concluded that there exists a structural change in the two sub-periods. Differential slope coefficients of bovine population (X1) and average procurement price per litre (X4) variables were found to be positive and negative significant, with coefficient values of 3.64 and -0.28, respectively. The statistically significant differential slope coefficients indicate that the two sub-periods have a different slope. It can be noticed that differential intercept was significant at 1% level of significance with the value of -12.38 indicates the existence of the structural change between the two sub-periods. xii KMO and Bartlett‟s test was used to indicate the suitability of the data for structure detection. Initial eigen values display the amount of variance that can be explained by a given principal component. The number of extracted four components contributed to 60.465 per cent of the total variance. The overall analysis showed the performance of different dairy industries branched under four components with related aspects of their performance. The extensive constraint faced by the cooperative dairy was high competition among other dairy industries Maintenance costs of the entire dairy industry was the dominant constraint faced by the private dairy industries. Less remunerative price was the major constraint as the farmers were not getting the reasonable price for their produce sold to the cooperative dairy industries. The predominant constraint faced by the private dairy farmers was the inadequate availability of feed and fodder. Maintenance cost was the major impediment faced by the wholesalers and retailers. The major constraint faced by the consumers was product availability i.e., required products were not available at all the time. The focal point of the study was productivity per animal has to be increased. Initiative should be taken to provide uniform price based on fat content by the both cooperative and private dairy industries. To reduce the cost of feed & fodder and increase its availability, time for the dairy farmers to rely on hydroponics system of fodder cultivation and farmers should concentrate more on growing wide varieties of fodder.
Open Access
INCREASING PRODUCTIVITY AND PROFITABILITY OF OILSEEDS BASED PRODUCTION SYSTEMS IN ANDHRA PRADESH
(Acharya N.G. Ranga Agricultural University, Guntur, 2022-12-22) KRISHNA TEJA, I.; KRISHNA TEJA, I.; RAMANA RAO DEPARTMENT OF, S.V.; RAMANA RAO DEPARTMENT OF, S.V.
The present study aims for increasing productivity and profitability of oilseeds based production systems in Andhra Pradesh. The primary data from the farm households across the state with respect to groundnut, sesame and sunflower based oilseeds production systems was collected and evaluated using stratified multi staged random sampling methodology. Eight districts out of 13 districts in the state were identified, where the oilseed crops are grown predominantly and these districts were stratified according to high area, low productivity and low area, high productivity categories. From each selected district, two mandals were selected based on the area criteria and from each mandal, two representative villages were selected on area basis. From each village, 10 farmers were selected on random basis. The data on the supply chain and value chain aspects was collected from market intermediaries of at least 30 per district from the most relevant Agricultural Product Market Committee (APMC)/trading point. Spatio-temporal performance of the crops under the study along with castor, safflower and niger was evaluated using Compound Annual Growth Rates (CAGR) and decomposition analysis. It was found that, majority of crops exhibited frequent decline in growth rates of area and production, especially in post-liberalization period. In particular, the growth performance of sunflower was meagre in the state. Examination of costs, returns and farm efficiency measures revealed conspicuous differences xvii in profitability among the districts. Cobb-Douglas and stochastic frontier production functions were employed to assess allocative and technical efficiencies respectively. Among the districts, for respective crops under the study, significant inefficiencies were noticed. Supply chain scenarios and value chains of the three oilseeds were documented and noticed conspicuous differences between profit margins of stakeholders at district level. Based on geographical location of the district, resource endowments, growth performance of area, production and yield of oilseeds, costs and returns structure; economics of competing crops, mean technical efficiencies, supply chain scenario and value chains; presence of value chain players, profit margins of stake holders in sub value chains of the major edible oilseeds grown in Andhra Pradesh, Srikakulam and Vizianagaram districts in North coastal zone were identified to have potential to develop as organic oilseed hubs, while YSR Kadapa and Kurnool districts in Southern and Scarce rainfall zones, respectively were identified to have potential to develop as production and processing hubs. SPSR Nellore district in Southern zone was identified to have potential to develop as seed and export hub. Institutional refurbishments that require immediate intervention for operational value chains like convergence of all stakeholders (both public and private) towards technology assemblage, multi-institutional approach for conversion of the proven research outputs to outcomes at the farm level etc., were suggested. Policies, targeted towards enhancing oilseeds contribution to the state’s Gross Domestic Product (GDP), like region specific intercropping, risk diversification, addressing low capacity utilization, emphasis of value addition, evolve mechanisms for involving Farmer Producer Organizations (FPO’s)/Self Help Groups (SHG’s) towards value chains involving oilseeds, promoting start-up ecosystem and incubation activities, designing a robust mechanism for creation of value chain hubs etc., were proposed.

Acharya N. G. Ranga Agricultural University, Guntur (AP)

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