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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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ThesisItem Open Access AN ECONOMIC ANALYSIS OF FARMERS’ INDEBTEDNESS IN VISAKHAPATNAM DISTRICT OF ANDHRA PRADESH(Acharya N G Ranga Agricultural University, Guntur, 2018) AMRUTHA, SAVARAM; RAMA RAO, I.V.Y.Agriculture and natural calamities are going at tandem since time immemorial. But, its severity is increasing now-a-days, thereby, negatively affecting the agriculture production prospects and making the farmers to end up in a debt trap. This led some of the farmers to commit suicides in many states including agro-potential states like Andhra Pradesh, Punjab, Tamil Nadu, Karnataka, Maharashtra etc. The problem of indebtedness is an age-old and the disheartening is that it has aggravated further in the recent years. The present research study entitled, “An Economic analysis of Farmers‟ Indebtedness in Visakhapatnam district of Andhra Pradesh” was taken up with the objectives: to study the extent and magnitude of agricultural credit to the farmers in Visakhapatnam district; to analyse the factors responsible for indebtedness of farmers; to study the impact of Loan Waiver Scheme on farmers and lending agencies and to study the constraints faced by farmers in repayment of loans. In Andhra Pradesh, Visakhapatnam district was selected purposively. Major sources of institutional credit were cooperative and commercial banks. Hence, District Cooperative Central Bank (DCCB) for cooperative sector and State Bank of India (SBI) for commercial sector were selected. The sampling framework consists of one district viz., Visakhapatnam, two institutions viz., DCCB (Co-operative sector) and SBI (Commercial sector), four branches (two each from DCCB and SBI) viz., Kaspa jagannadhapuram and Madugula of DCCB and Kodavatipudi and Narsipatnam ADB of SBI, 30 farmers (15 beneficiaries and 15 non beneficiaries from ADWDRS) from each branch. Thus, in total the sample size was 120 farmer-borrowers. Results emerged-out from analysis revealed that, credit supply by institutional agencies to total agriculture had increased. The share of commercial banks and cooperative banks had increased, whereas, other banks had decreased. Significance of dummy variable for loan waiver scheme in the analysis of factors responsible for indebtedness of farmers shows that there is significant difference between beneficiaries and non-beneficiaries. Other significant independent variables taken into account are viz., Land holding, family expenditure and farming experience. xiv The impact of Loan waiver scheme on lending agencies: Institution wise showed that over dues of the debt waived borrowers and debt relieved borrowers were higher in commercial banks than co-operative banks. While, in borrowers the overdue was higher in debt relieved borrowers than debt waived borrowers. Benefit of ADWDRS (2014-2017) was extended higher by co-operative banks than commercial banks. While, in borrowers debt waived borrowers benefited more than debt relieved borrowers. The major constraints in repayment of debt were adverse climatic conditions, small size of land holdings, rising cost of cultivation, high rate of interest etc. The role of cooperative sector vis-à-vis commercial sector is low. This needs immediate strengthening of co-operative institutions on war-footing. The cumbersome procedure for availing loans from institutional sources should be simplified and further adequate loans should be provided at affordable rates of interest. The educational level and farm experience had positive associations with repayment of debt; there is greater need to educate the farmers on skills of crop rising to improve the productivity. Family expenditure and farming experience were found significant; the policy makers should take into consideration of these factors to formulate the policies in alleviating the debt. The adverse climatic factor was the major factor in non-repayment of debt, hence, government should take necessary measures to speed-up the compensation mechanism, as all crop loanees are insured.ThesisItem Open Access TOTAL FACTOR PRODUCTIVITY AND SUPPLY RESPONSE OF MAJOR CROPS IN ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) DIVYA, K; BHAVANI DEVI, IThe Present study entitled “Total factor productivity and supply response of major crops in Andhra Pradesh” was undertaken to study the productivity growth and acreage response of rice, maize, groundnut, cotton, sugarcane, bengalgram and redgram. Since these crops comprised of almost 50-60 per cent of the cultivated lands in the state. For the estimation of the cropping pattern and growth rates of area, production and yield of the selected crops, data was collected for the period from 1996-97 to 2015-16. The required data for this purpose was collected from various published documents of the Directorate of Economics and Statistics, Government of Andhra Pradesh. The selected period of study was from 1996-97 to 2014-15 for the estimation of total factor productivity (TFP) in the state. Data required for this purpose was collected from the published documents of the xv Cost of Cultivation scheme of Government of India and its website. The required data on the variables chosen as the determinants of TFP in the state were collected from various Statistical Year Books published by the Directorate of Economics and Statistics, Government of Andhra Pradesh. Data Envelopment Analysis (DEA) technique was employed to calculate and decompose the Malmquist TFP indices of the selected crops. DEA helped to decompose the TFP index into various efficiency measures. Multiple regression analysis was carried out by taking the TFP index of individual crop as dependent variable to determine the factors affecting the TFP growth in Andhra Pradesh state and ordinary least square adopted from nerlovian model was used to calculate the supply response for the major crops. The cropping pattern in the state was analysed in terms of the percentage of area under cultivation of the selected crops The gross cropped area in 1991-92 was 82.48 lakh ha while in 2014-15 it was 76.90 lakh ha. Rice was the main cultivated crop in the state in the year 1991-92 with a share of 26.07 per cent of total cultivated area, followed by groundnut (21.90 per cent), cotton (3.35 per cent), sugarcane (1.54 per cent), redgram (1.34 per cent), bengalgram (0.41 per cent) and maize (0.31 per cent). The growth rates of area, production and productivity are assessed in terms of annual compound growth rates (CAGR). Area under rice declined at an annual rate of 0.46 per cent, maize grew at a phenomenal annual rate of 16.39 per cent followed by bengalgram which too registered a very encouraging growth rate of 11.83 per cent. Cotton recorded a growth rate of 6.40 per cent annually. Redgram was another crop which recorded a production growth rate of above unity i.e., 1.85. Production of groundnut declined at an annual rate of 3.61 per cent. Sugarcane one of the important commercial crop grown in the state was observed to have a negative production growth rate of 0.96 per cent. Maize recorded the highest growth xvi rate of productivity with 4.57 per cent followed by cotton (3.73 per cent), bengalgram (2.08 per cent), rice (1.66 per cent) and redgram (1.58 per cent). The growth of all the inputs were in increasing trend except for the human labour and animal labour of all the selected crops from the base year to current year. The contribution of all the inputs are higher in all the selected crops except seed and animal labour inputs that was not impressive to contribute the huge percents to the total factor productivity growth in the state. The results for rice alone the MSP as percentage of cost A2 was 150 per cent during all the years of study, while it was 17 years of study each for maize and cotton, 14 years for sugarcane, 9 years out of 10 years in respect of bengalgram, 9 years in the case of redgram. MSP as percentage of cost C2 was maximum with 140.94 in one only year for rice and 145.82 per cent for cotton in year. Area effect was most responsible factor for an increase in production of sugarcane, groundnut, bengalgram and cotton. Yield effect was most responsible factor for increasing the production of rice and redgram. Increase in maize production was mainly due to interaction effect of area and yield. The decomposition of the TFPch for the corresponding years into EFFch and TECHch revealed that the increase in TFPch, which was due to the improvement in innovation (TECHch) for all the selected crops. The variables area under high yielding varieties and annual rainfall were significantly influencing the growth of TFP. The growth in total output index was higher than the growth in the total input index for rice, maize, groundnut, cotton and redgram. The total input index was highest for rice followed by groundnut, maize, bengalgram, cotton, sugarcane and redgram. xvii The estimates of instability in area, production and yield for major crops revealed that the production (44.29 %) and yield (35.92%) was highly unstable in the case of groundnut, area (32.63%) and production (41.37%) in cotton, production (34.39) in bengalgram and production (35.11%) in redgram was highly unstable. The area, production and yield of remaining crops i.e., rice, maize, sugarcane showed low instability. Acreage, production and yield response of crops were estimated and the results of the study period from 1996-97 to 2015-16 showed that the regression coefficients of the coefficient of lagged price and rainfall was in rice, lagged yield in the case of maize, lagged yield and rainfall in ground nut, rainfall and previous year’s area in cotton, lagged price and lagged area in sugarcane, lagged price, lagged yield and lagged area in bengalgram showed positive and significant influence on acreage. The regression coefficients of the previous year’s, lagged price and Irrigation in maize, rainfall in groundnut, price and rainfall in cotton, previous year’s production and irrigation in sugarcane, previous year’s production and rainfall in bengalgram showed positive and significant influence on production. The variables influencing yield were area under irrigation and lagged yield in rice, total rainfall in maize, total rainfall and lagged yield in groundnut, area under irrigation and lagged yield in cotton and total rainfall in bengalgram and redgram. The short run and long run elasticities of area response obtained from the regression coefficient of one year lagged prices was found to be less responsive to price changes of selected crops except for cotton and bengalgram. The short run and long run elasticities of production response obtained from the regression coefficient of one year lagged prices was found to be less responsive to price changes of selected crops except for maize and xviii cotton. The short run and long run elasticities of production response obtained from the regression coefficient of one year lagged prices was found to be less responsive to price changes of selected crops except for maize and cotton. The short run and long run elasticities of yield response obtained from the regression coefficient of one year lagged prices was found to be less responsive to price changes of all the selected crops. The coefficient of adjustment for rice, maize, groundnut, cotton and redgram was quicker for area response. The adjustment was quicker in the case of cotton and redgram for production response. The adjustment took less time in the case of sugarcane, bengalgram and redgram for yield response. The above mentioned crops indicated that the farmers took less number of years to realize 95 per cent of price effect.ThesisItem Open Access A STUDY ON VIABILITY OF TENANT FARMING IN NELLORE DISTRICT OF ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) VISHNUVARDHAN, P; APARNA, BThe present study entitled “A Study on Viability of Tenant Farming in Nellore district of Andhra Pradesh” was intended to examine the nature of tenurial contracts, costs and returns, resource productivity and profitability on owner cum tenant and tenant farms. The study covered five mandals and ten villages from Nellore district of Andhra Pradesh. A sample of 42 owner cum tenant cultivators and 58 tenant cultivators were selected at random from the ten villages. The primary data for the year 2016-2017 were collected through a pretested schedule by survey method. Conventional analyses was used to analyze the data and arrive at valid conclusions. It was noticed that 64 per cent of the tenant farmers took loans from the money lenders which show dependence of tenant farmers on the Non–institutional sources for agricultural credit. Around 29 per cent of tenant cultivars were able to meet their farming expenses from their owned farms. The total cost of cultivation per hectare for kharif paddy, kharif groundnut, rabi paddy, rabi groundnut and rabi blackgram was ` 1,03,855.56, ` 95,661.65, ` 1,19,115.57, ` 1,13,576.77 and ` 47,041.44 on owner cum tenant farms respectively and it was ` 95,368.06, ` 87,843.95, ` 1,11,775.97, ` 1,04,471.36 and ` 44,021.86 on the tenant farms for the corresponding crops. The proportion of working costs ranged from 74.52 per cent to 84.12 per cent on owner cum tenant farms and 73.78 to 84.55 per cent on tenant farms for the crops under study. xii All the measures of farm income viz., farm business income, family labour income, net income, farm investment income and returns per rupee of investment were higher on tenant farms against owner cum tenant farms. The net income was ` 33,187.93, ` 34,275.85, ` 33,858.52, ` 39,873.22 and ` 4,898.55 from the cultivation kharif paddy, kharif groundnut, rabi paddy, rabi groundnut and rabi blackgram respectively on owner cum tenant farms and the respective figures for tenant farms were ` 41,820.54, ` 42,506.05, ` 41,204.03, ` 49,803.64 and ` 5,420.04. The returns per rupee of investment were estimated and they stood at ` 0.31, ` 0.35, ` 0.28, ` 0.35 and ` 0.10 on owner cum tenant farms and ` 0.43, ` 0.48, ` 0.36, ` 0.47 and ` 0.12 on tenant farms for the crops under study.ThesisItem Open Access A STUDY ON EFFICIENCY OF TENANT FARMING IN CHITTOOR DISTRICT OF ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) VASU DEVA RAO, KAMALA; VANI, NThe present study entitled “A Study on Efficiency of Tenant Farming in Chittoor District of Andhra Pradesh” was intended to examine costs and returns, resource productivity and allocative efficiency on owned and tenant farms. The study covered four mandals and eight villages from Chittoor district of Andhra Pradesh. A sample of 64 owner cultivators and 64 tenant cultivators was selected at random from the eight villages. The primary data for the year 2017-2018 were collected through a pretested schedule by survey method. Conventional and functional analyses were used to analyze the data and arrive at valid conclusions. The total cost of cultivation per hectare for kharif groundnut, kharif paddy, kharif tomato, kharif sugar cane, rabi groundnut and rabi paddy was ` 94,469.94, ` 95,774.34, ` 1,70,623.48, ` 2,21,833.76, ` 91,773.44 and ` 1,61,589.47 on owned farms respectively and it was ` 93,390.34, ` 1,02,614.55, ` 1,76,099.98, ` 2,17,147.82, ` 89,351.31 and ` 1,61,764.38 on the tenant farms for the corresponding crops. The proportion of working costs ranged from 67.44 per cent to 81.59 per cent on owned farms and 67.95 per cent to 81.43 per cent on tenant farms for the crops under study. It is clear that all the measures of farm income viz., farm business income, family labour income, net income, farm investment income and returns per rupee of expenditure were higher on tenant farms against owned farms. The net income was ` 61,375.06, ` 71,475.70, ` 30,836.52, xii ` 59,282.01, ` 74,129.06 and ` 74,723.53 from the cultivation of kharif groundnut, kharif paddy, kharif tomato, kharif sugar cane, rabi groundnut and rabi paddy respectively on owned farms and the respective figures for tenant farms were ` 63,921.66, ` 61,429.45, ` 43,910.02, ` 63,711.01, ` 82,348.69 and ` 59,785.62. The returns per rupee of expenditure were estimated and they stood at ` 0.59, ` 0.68, ` 0.16, ` 0.24, ` 0.73 and ` 0.42 on owned farms and ` 0.62, ` 0.54, ` 0.23, ` 0.27, ` 0.84 and ` 0.33 on tenant farms for the crops under study respectively. Plant protection chemicals, manures and human labour were the factors which exhibited relatively higher potential for increased output on tenant farms. As per the results of MVP/MFC ratio, it was observed that each additional rupee of investment on manures, fertilizers, seed would add 2.59, 3.57, 25.11 on owned farms respectively and 0.59 plant protection chemical and 25.64 seed on tenant farms for aforesaid variables. In case of plant protection chemicals, the ratio was less than one indicating less profitability of further use on tenant farms. The major constraint identified was marketing constraint which was given first rank where the minor noticed was subsidiary constraint.ThesisItem Open Access AN ECONOMIC ANALYSIS OF PRICE BEHAVIOUR OF ONION IN MAJOR MARKETS OF INDIA(Acharya N.G. Ranga Agricultural University, 2018) AREEF, MULLA; RAJESWARI, SThe Present study entitled “An economic analysis of price behaviour of onion in major markets of India” was undertaken to study the price trends of onion, price forecasts and price volatility in selected markets of India. Three markets viz., Lasalgaon, Bangalore and Kurnool were selected based on maximum arrivals. The data pertained to the period from 2003 to 2017. Time series analysis was employed for studying the price behavior of onion for each market. ARIMA, trend analysis, moving average, single exponential smoothing, double exponential smoothing, winter’s multiplicative model, decomposition fit and Artificial Neural Network (ANN) were used for forecasting of prices. Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models are used for analyzing price volatility. The annual increase in prices of onion was found to be the highest in Lasalgaon market (7.33 Rs/qtl) whereas it was the lowest in Kurnool market (6.22 Rs/qtl). Bangalore and Kurnool were found to be statistically significant at 1 per cent level of significance. In these three markets, the contribution of time to change in prices was to the tune of 19 per cent to 26 per cent as indicated by adj-R2. In Lasalgaon market the highest seasonal index was found in October, followed by November and August and the indices stood at 149.01, 139.30 and 122.76 respectively. Lowest seasonal index was recorded in May with 57.23. In Maharashtra harvesting of kharif season onion crop started from October to December. Hence, kharif crop starts arriving at the market in small quantities during the first fortnight of October. The prices in October reach their highest of all the months. It is mainly for the reason that stocks made from earlier rabi season dwindling and there are still some time for main kharif onion crop to enter the market. The limited arrivals fetch a good price and normally the prices during this month are rewarding. Even in November and December months also have highest prices, this is true because farmer respond to the higher prices and bring more produce to sale at market. In Bangalore market the highest seasonal index was found in November, followed by January and August as the indices stood at 130.94, 115.90 and 115.66 respectively. Lowest seasonal index was recorded in April with 70.91. In Kurnool market the highest seasonal index was found in August, followed by November and July as the indices stood at 140.80, 121.31 and 117.07 respectively. Lowest seasonal index was recorded in May with 62.72. In Bangalore and Kurnool markets the early kharif crop starts arriving the market in August month. And the late kharif crop hits the market in October and November months. These months where highest onion arrivals present also have the highest prices. From the results it was found that no price cycles were identified in the selected markets (Lasalgaon, Bangalore and Kurnool) of India for onion crop. Irregular fluctuations did not exhibit any definite periodicity in their occurrence in the Lasalgaon, Bangalore and Kurnool markets. The ARIMA model (0,1,1) (2,1,1) was found to fit the series suitably to forecast prices of onion in Lasalgaon market. According to the forecasts the price of onion would be ranging from Rs. 2879 to Rs. 2748 per quintal for the months from January to June 2018. The ARIMA model (1,1,0) (1,1,1) was found to fit for forecast prices in Bangalore market. According to the forecasts the price of onion would be ranging from Rs. 3495 to Rs. 3395 per quintal for the months from January to June 2018. The ARIMA model (1,1,1) (1,1,1) was found to fit the series suitably to forecast prices in Kurnool market. According to the forecasts the price of onion would be ranging from Rs. 2956 to Rs. 1651 per quintal for the months from January to June 2018. Price volatility results revealed that there was high volatility in onion prices in Lasalgaon market as the sum of alpha and beta values were 0.99 next followed by Bangalore (α+β = 0.94) and Kurnool (α+β = 0.93) during the period from 2004 to 2017. These values were very closer to one, indicated that the volatility shocks were quite persistent in these markets.ThesisItem Open Access ECONOMIC ANALYSIS OF POST HARVEST LOSSES IN CHICKPEA IN PRAKASAM DISTRICT OF ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) LAKSHMI MONIKA, ATCHUTUNI; PAUL, K.S.R.An attempt has been made in this study to examine the economics of post harvest losses in Prakasam district of Andhra Pradesh. The specific objectives of the study were 1. to study the disposal pattern of chickpea in Prakasam district of Andhra Pradesh 2. to measure the extent and quantify post harvest losses in chickpea and to analyze the economic impact of post harvest losses on chickpea farmers 3. to analyze the factors affecting post harvest losses at different stages in supply chain 4. to identify the constraints in minimizing post harvest losses in chickpea Multi-stage sampling technique was employed for selection of final respondents. A sample of 80 farmers, 20 wholesalers and 20 retailers was selected from sixteen villages and four mandals of Prakasam district of Andhra Pradesh. Tabular analysis was carried out to study the disposal pattern of chickpea in the study area. Post harvest losses at district, mandal and village level were also estimated using tabular analysis. Multiple linear regression was carried to study the economic impact and to analyse the factors affecting post harvest losses at different stages in supply chain. To identify the constraints in minimizing post harvest losses, Likert scale technique was used. The primary data were collected from the major pulses producers - farmers, wholesalers and retailers through personal interview method with the help of well prepare schedule for year 2017-18. On an average 92.01 per cent and 91.66 per cent of total production was found to be marketable and marketed surplus respectively. About 46.25 per cent of the farmers sold to wholesalers because of immediate cash payment, 25.00 per cent of the farmers sold to millers because of advance loan borrowed, 17.50 per cent sold to unauthorised brokers because of well known to them and trust worthiness, 11.25 per cent sold to distant markets because of better price given by them. Wholesalers dispose 40.77 per cent of total quantity to distant markets as distant markets pay more. The postharvest losses at the farm level have been estimated to be 7.26 kg/q for chickpea. This leads to an economic loss of Rs.435.6/q. Total estimated quantity of post harvest losses in Prakasam district was 7.36 lakh quintals. The loss percentage obtained in Prakasam district was 7.35 per cent. Economic loss of post harvest losses in Prakasam district estimated to be Rs. 441.78 crore. Harvesting losses were maximum because of shattering of the grain caused by delay in the harvesting. Drying losses were because of unfavourable weather and animal attack in the field. Post harvest losses at intermediaries level were found maximum at transportation i.e. 66.95 per cent followed by storage loss i.e. 33.05 per cent of total post harvest losses. At intermediaries level transportation loss was more compared to storage loss as storage facilities were adequate in the study area. The analysis of economic impact of post harvest losses on chickpea farmers revealed that the explanatory power of the model R2 was 44.3 per cent. This implies that all explanatory variables together were explaining only 44.3 per cent of variation. Harvesting loss and threshing loss were negatively significant at 1 per cent level of significance. Marketing loss was negatively significant at 5 per cent level of significance. Drying loss and storage loss were negative but non–significant. With the increase in harvesting, threshing and marketing losses the per hectare farmers income decreases. The analysis of post harvest losses in chickpea at farm level revealed that the explanatory power of the model R2 was 44.6 per cent. This implies that all explanatory variables together were explaining 44.6 per cent of variation in post harvest losses at farm level. At farm level, weather, transportation and timely labour availability were negatively significant at 1 per cent level of significance. Age, threshing machine and storage were negative but non–significant. Cultivated area in ha, education and production in quintal per ha were positive but non- significant. The explanatory power of the model R2 at intermediaries’ level was 91.4 per cent. This implies that all explanatory variables together were explaining 91.4 per cent of variation in post harvest losses at intermediaries’ level. At intermediaries’ level, age, quantities handled were negatively significant at 5 per cent level of significance. Time of storage was positively significant at 1 per cent level of significance. Transportation was negatively significant at 1 per cent level of significance. Education, experience and storage were positive but non- significant. Late harvesting, unavailability of timely labour, improper machine condition, timely unavailability of machines,unfavourable weather at the time of drying and unavailability of right floor for drying are the major constraints faced by farmers in minimizing post harvest losses. Lack of own conveyance and defective packing at the time of transfer of material are the major constraints faced by the intermediaries in minimizing post harvest losses.ThesisItem Open Access STUDY ON ECONOMIC VIABILITY OF TENANT FARMERS IN SRIKAKULAM DISTRICT OF ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) JHANSI, YIRRI; SUNANDA, NIndian agriculture is predominantly characterized by small and marginal farmers, growing incidence of tenancy, landlessness, high degree of fragmentation and distribution of operated holdings, which have direct impact on farm production and rural household income. The high dependence of the population on agriculture is one of the main reasons for low size of land holding and for low per-capita income as well as high incidence of poverty among agricultural workers. Though all farmers had suffered because of this unprecedented calamity, tenant farmers faced an additional burden of very expensive interest component. They get no insurance cover too because they can submit no land document or other supporting evidence to become eligible for insurance. All these problems fully or partly affect the viability of tenant farmers in agriculture. The research study entitled “Study on Economic Viability of Tenant farmers in Srikakulam district of Andhra Pradesh” was taken up with the following objectives. 1. to examine the existing pattern of tenancy in Srikakulam district 2. to analyze the resource use efficiency of tenant farming 3. to study the economic viability and factors affecting the viability of tenant farming and tenant farm households and 4. to identify the constraints faced by the tenant farmers. Srikakulam district was purposively selected for the research study due to the availability of more number of small and marginal farmers. A total of 120 tenant farmers from 12 villages in six mandals of the district were selected based on the Name of the Author : Y. JHANSI Title of the thesis : STUDY ON ECONOMIC VIABILITY OF TENANT FARMERS IN SRIKAKULAM DISTRICT OF ANDHRA PRADESH Degree : MASTER OF SCIENCE IN AGRICULTURE Department : AGRICULTURAL ECONOMICS Chair person : Dr. N. SUNANDA University : ACHARYA N. G. RANGA AGRICULTURAL UNIVERSITY Year of Submission : 2018 maximum concentration of tenant farmers in the study area. Data on various aspects of tenant farmers of 2016-17 agricultural year was collected through personal interview method. The secondary data on agro economic features of the district were collected from Chief planning Office, Department of agriculture and other agencies. For Rice the average cost of cultivation per ha was Rs.58,292, in case of Rice fallow pulses was Rs.21,333. For Rabi sesamum the cost of cultivation was Rs.29,660. For Maize the total cost of cultivation was Rs. 59,273. Rice, pulses, sesamum, maize are the major crops grown in the study area in that sesamum and maize are the most profitable crops among them. Fixed rent is the most prevailing tenancy pattern followed by fixed produce, share cropping and input sharing. In Rice all the resources used in cultivation i.e, machine labour, human labour, irrigation and manures, chemical fertilizers and plant protection chemicals were positively influencing and significant. Seed was the only non significant factor.In Rice fallow pulses seed was the only significant factor because it is major input for cultivation. Human labour, irrigation, plant protection chemicals and farm size were non significant. All the factors were positively influencing the returns except irrigation and plant protection chemicals. In Sesamum all the variables were positively signed except irrigation cost and seed cost which were negatively influencing the gross returns. Machine labour, farm size, irrigation were significant factors. In maize all the variables were positively signed except labour charges and plant protection chemicals. Labour charges, irrigation, chemical fertilizers are significant factors. Seed and plant protection chemicals were nonsignificant . In the sample of 120 farmers, there are 37 viable farmers and 83 non-viable farmers, the classification is based on the Tendulkar committee criteria i.e, if the annual farm income of the farmers is below Rs.51600 is considered for the classification of farmers above or below poverty line. The farmers whose income is below Rs.51600 were come under non viable class and above is taken as viable farmers.The average net income of the 120 tenant farmers is Rs.6607 which is very low. Without the off farm income i.e. from dairy and wages the net income is negative (-24434).Offfarm income, farm expenditure, farm size and domestic expenditure were the major significant factors effecting the viability of tenant farmers and tenant farm households. The major constrains faced by the respondents are LEC fail to serve the purpose of credit, Beneficiaries of the Government are the actual owners not tenant farmers, indebtedness, small size of the holding, timely unavailiability of the inputs. For ensuring viability of tenant farmers, creation of job opportunities in rural areas along with suitable policy support for development of livestock sector and other allied activities. Indebtedness is the major problem prevailing, as LEC cards are not accepted to provide the credit to the tenant farmers, the suitability of LEC cards for credit is only upto reports, but not in official gazette manner, which has to be amended by the Government. The benefits from the government are not reaching the tenant farmers, so there is a need for providing crop insurance schemes to the tenant farmers also.ThesisItem Open Access ECONOMIC ANALYSIS OF PRODUCTION COSTS AND PRICES OF RICE IN WEST GODAVARI DISTRICT OF ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) PRIYANKA CHOWDARY, MUVVA; HYMAJYOTHI, SThe present study entitled “Economic analysis of production costs and prices of rice in West Godavari district of Andhra Pradesh” was undertaken with the objectives i. to estimate the costs and returns involved in cultivation of rice in West Godavari district of Andhra Pradesh. ii. to compare and examine the relationship among minimum support price, wholesale price, farm harvest price and farmer expected prices. iii. to study the production and marketing constraints faced by farmers in rice cultivation. iv. to make suggestions in order to enhance the effectiveness of MSP and procurement of rice by the government. Multi-stage stratified random sampling technique was employed for selection of final respondents. A sample of 120 farmers was selected from eight villages and four mandals of West Godavari district of Andhra Pradesh. Tabular analysis was carried out to study the costs and returns of rice cultivation in the study area. The cost concepts and income measures were also analysed through conventional analysis using various cost concepts and farm income measures. The prices like minimum support price (MSP), wholesale price (WP), farm harvest price (FHP) and farmers expected price were analysed by compound growth rates. The comparison and the relation between these prices were examined by Nerlovian price expectation model. The problems during production and marketing of rice were identified and analysed using Garrett ranking technique. Finally the suggestions in order to enhance the effectiveness of MSP and the procurement of rice by government were documented. The average cost of cultivation per hectare of rice cultivation was Rs. 74,698.21 for pooled farmers. The average per hectare total cost of cultivation(TCOC) increased with the increase in the size of the holdings from Rs. 72,200.22 on small farms, Rs. 74,356.57 on medium farmers to Rs. 77,007 on large farms indicating a direct relationship with the size of the holding. This was due to intensive use of inputs by large farmers. The proportion of variable costs accounted for a major share in the TCOC on all categories of farms. The total per hectare operational costs ranged from Rs. 54,342.22 (73.88%) on small farms, Rs. 55,279.57 (74.34%) on medium farms to Rs. 57,007 (74.02%) on large farms, with an overall average of Rs. 55,437.93 (74.62%) on pooled farms. Among the different variable costs the cost of human labour was the major cost component with an amount of Rs. 17,950 per hectare accounting for 24.03 per cent of TCOC on pooled farmers. Among the different variable costs the same was Rs. 16,290.54 on small farmers, Rs. 17,200 on medium farmers and Rs. 17,300 on large farmers accounting for 22.56, 23.13 and 22.46 per cents of their respective TCOC followed by machine labour, fertilizers and pesticides. Gross income exhibited a direct relationship with the farm size and it was of the order of Rs. 85,120, Rs. 95,900, Rs. 1,01,388.7 and Rs. 94,080 on small, medium, large and pooled farmers respectively. The gross income was more on large farmers due to highest productivity compared to other categories of farmers. The net income showed a direct relationship with the farm size. Large farmers recorded a higher net income of Rs. 24,381 against Rs. 12,919.78 and Rs. 21,543.43 for small farms and medium farmers respectively. The same was Rs. 19,381.79 on pooled farmers. The benefit cost ratio increased with increase in farm size and in terms of cost, the cost of production decreased with increase in farm size. Compound growth rates of MSP, wholesale price, farm harvest price and farmers expected prices were almost similar but slighter higher for MSP (6.88%) during the period 1997-98 to 2016-17. The analysis of relationship between MSP, wholesale price and farm harvest price showed a positive relation, with significant regression coefficients and a high value of R2. The farmers expected price of rice depends on previous year expected as well as actual prices significantly and positively at 1 per cent level of significance. The farmers expected prices were found to be higher than the previous year MSP. However, the increase in expectation has been narrowing down over time. The major constraints faced by farmers in production were marginal size of holding leading to lesser production with a mean score of 64.18, lack of drainage facilities (61.24), scarcity of labour during production and marketing (59.62) and non availability of sufficient storage space (54.08). The major constraints in marketing were low price for the produce with a mean score of 69.18, MSP after official and unofficial cut (67.22), high marketing cost (45.10) etc.ThesisItem Open Access A STUDY ON PERFORMANCE OF FARMER PRODUCER ORGANIZATIONS IN KRISHNA DISTRICT OF ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) VEDASRI, RAVADA; UMADEVI, KSmallholder agriculture is argued to remain important for economic development and poverty reduction in developing countries, but its development is challenged by the need for institutional innovations to overcome market failures. There is a renewed interest from donors, governments and researchers in cooperative producer organizations as an institutional vehicle to improve smallholder agricultural performance, particularly through improved market participation. Smallholder producers participation in market-oriented production holds potential for diversifying their incomes and increase agriculture productivity, hence promoting food security and poverty eradication. With the numerous farming problems in developing countries, low agricultural productivity has negative effect on the economic welfare of the rural population. Farmers organizations have been suggested as a key tool to improve the living conditions of the resource-poor farmers in developing countries. Farmer groups are important institutions for the transformation of smallholder farming, increase productivity and income, thereby reducing poverty. Farmers Producer Organizations (FPOs) are a legal form of the company and according to 2002 Act passed in parliament, only farmer – producer can become member of FPOs. In the Indian context, the role of farmer organizations is to help smallholder farmers specifically, improve their position in the emerging value chains. FPO helps the farmers in production, harvesting, processing, procurement, grading, pooling, handling, marketing, selling and export of primary produce of the members or import of goods and services for their benefit. FPO renders technical services, consultancy services, training, education, research and development for the promotion of the interests of its members. Keeping this in view, the present study entitled “A Study on Performance of Farmer Producer Organizations in Krishna District of Andhra Pradesh” - was taken with the following objectives. 1. to study the structure, conduct and performance of FPOs in Krishna District 2. to identify the factors influencing performance of FPOs 3. to analyse the impact of FPOs on farmers’ economy 4. to identify the problems faced by the FPOs and suggest measures to improve functioning of FPOs Krishna district has been selected purposively for the research study as it has more number of functional FPOs in all sectors i.e., 16. Out of 16 Registered and functional FPOs in the district, two FPOs with maximum membership and two FPOs with minimum membership were selected purposively. Eighty FPO member farmers constituting twenty member farmers from each village selling their produce to the FPOs and forty non – FPO farmers constituting ten non- FPO members from each village selling their produce in other markets but not in FPOs were selected for the study. Primary data were collected through personal interview method from farmers and directors of FPOs. The secondary data on agro economic features of the district were collected from Chief planning office, Krishna district. The data regarding FPOs were collected from NGO Nestham and from Research report of ICRISAT (2016). The performance of FPOs increased with the increase in the efficiency of FPO by 12 per cent. Market share which was a measure of profitability showed that the profitability of FPOs increased by 42 per cent, Equity to assets ratio (EAR) was 147 which showed that the FPOs were having strong equity base to sustain their business and improve their performance. If age of FPO was more, then the experience and external linkages would increase and this increases the performance by 15 per cent. The heterogeneity in membership increases the performance of FPO by 1.5 per cent. The factors that potentially explain the performance of FPO can be grouped into: (1) Governance and management; (2) Membership commitment; (3) External linkages; (4) Group composition and (5) Type of FPO. The various indicators are used for each of these factor groupings. In case of governance and management registry, known to the political authority and with membership registry are the variables mostly influencing the FPOs. In case of membership commitment, financial and land contribution were the factors influencing the performance. In case of external linkages, asked help was influencing the performance. In case of group composition, proportion of female in membership had influenced the performance. In type of FPOs, village level and age of FPO are variables influencing the performance. In the analysis of the impact of FPOs on farmer’s economy, the results indicate that the coefficient of inverse mills ratio insignificant showing that there was no selection bias. Group membership and market price were positive and significantly influencing factors on farmer’s economy in all the four selected FPOs. In case of Sri Vigneswara FPO the other influencing factors on the farmer’s economy were age, production and labour mandays. In case of both Chandragudem and Baji Baba FPO the factors which were influencing the farmer’s economy were production area and share of crop sold. In case of China Ogirala FPO the factors that showed impact on farmer’s economy was age other than group membership and market price. The sample FPOs faced various problems like big fluctuation in market prices, awareness among the people, competition from other markets, lack of capital to provide sufficient services, lack of backward and forward linkages, moving away from FPOs when there is loss, no storage and ware house facility, poor infrastructure facility and they prioritized competition from other markets as the major constraint with a score of 0.82 followed by big fluctuations in market prices (0.81), lack of capital to provide sufficient services (0.72), awareness among the people (0.66), moving away from FPOs when there is loss (0.47), lack of backward and forward linkages (0.38), poor infrastructure facility (0.37) and no storage and ware house facility (0.29). The various suggestions given for improving the functioning of FPOs are awareness among the people should be built up with the help of scientists, Government has to provide financial support, credit and input provision to farmers, providing storage facilities, business done on commission basis and reducing the transportation cost. They have given highest priority to Government has to provide financial support for the efficiency of FPO(0.70) followed by business done on commission basis(0.66), awareness among the people should be brought with the help of scientists(0.62), by reducing the transportation cost (0.58), improving the credit and input provision to farmers(0.50), by providing the storage facilities(0.48).