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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 TRADE COMPETITIVENESS AND EXPORT PERFORMANCE OF SHRIMPS IN INDIA WITH SPECIAL REFERENCE TO ANDHRA PRADESH(Acharya N G Ranga Agricultural University, Guntur, 2019) KUMARI SIRISHA, K. J. V.; SUBBA RAO, D.VAquaculture in India is an important sector of food production, providing nutritional security to the food basket, besides contributing to the exports. It employs fourteen million people in different activities in the country. The total fish production during 2017-18 was 12.60 million tons of which nearly 65% was from inland sector. The total seafood exports during the period 2017-18 was 13.8 lakh tonnes as compared to 11.3 lakh tonnes in the previous year 2016-17. In rupee terms exports were valued at Rs. 45,106.89 crore in 2017-18 as against Rs. 37,870.90 crore in 2016-17, indicated of 21.35 per cent growth. Frozen shrimp maintained its position as the key contributor to the seafood export basket, accounting for 41 per cent in quantity and 68.46 per cent of the total dollar earnings. This indicates that major part of income from marine fishery flows from the export performance of shrimps. The Government of Andhra Pradesh created a policy for the rapid growth in fisheries and aquaculture for the period 201520, with a vision of promotion of “Andhra Pradesh as the Aqua hub of India”. Hence the present research work on “Trade competitiveness and export performance of shrimps in India with special reference to Andhra Pradesh” was undertaken with the following objectives: 1. to study the growth rates of shrimp production and exports in India and Andhra Pradesh 2. to analyze the direction and structural stability of Indian shrimp exports 3. to analyze the trade competitiveness of India’s shrimp exports in the world market 4. to analyze the factors influencing the export performance and trade competitiveness of shrimps in Andhra Pradesh. xx The secondary data on aqua products and shrimps in terms of quantity and value for India and Andhra Pradesh were collected from Marine Product Export Development Authority MPEDA, Food and Agriculture Organization (FAO) and trade Map data base developed by International Trade Centre (ITC), Geneva, Switzerland. Primary data was collected from Andhra Pradesh because it is the hub of aquaculture in India along Visakhapatnam, Nellore and West Godavari districts were selected based on export potential and processing of shrimp. Thirty exporters were selected randomly. The growth rates registered for shrimp exports were positive and significant in both India and Andhra Pradesh. In India the observed registered growth rate in shrimp exports were 7.03 per cent in terms of quantity and 10.73 per cent in terms of value during the period 1995-96 through 2017-18. In Andhra Pradesh during the observed registered growth rate in shrimp exports were 12.4 per cent in terms of quantity and 14.8 per cent in terms of value during the same period. The instability is increasing in nature for both seafood exports and shrimp exports in India and Andhra Pradesh respectively during the overall period, 1995-96 to 2017-18 i.e. 0.11 and 0.3 seafood and shrimp exports respectively in India, 0.47 and 0.52 seafood and shrimp exports respectively in Andhra Pradesh. The average unit price for Indian shrimps in USA market was higher than Japan, South East Asia, EU markets and Middle East. The share of shrimp exports during 2009-10 to 2017-18 was 7.8 per cent of the total world shrimp exports. The direction of trade indicates that the European Union and other pooled countries were found to be highly loyal markets for Indian shrimp. Followed by USA, Japan and South East Asia, whereas China and Middle East were found be most unstable markets for Indian shrimp exports. The Indian shrimp has relatively better comparative advantage in South East Asia and Middle East markets, whereas it was low in developed markets like European Union, USA and Japan. However there is a need to improve export competitiveness of Indian shrimp in developed markets like EU, USA and Japan to achieve high unit price realization. The shrimp exports from Andhra Pradesh had a significant comparative advantage in India. It reflects greater scope for the expansion of seafood export industry. The shrimp exporters they give most preferences to those attributes which influence the shrimp exports in Andhra Pradesh are, the raw (frozen) form is a major influence on exports than other forms like value added products. This is due to the greater demand from South East Asian countries for raw (frozen) products. Certification and labeling plays a vital role in promoting the export of shrimps. Price attribute has a strong influence on exports if the quality of shrimp increases. The exporters are highly preferable for exporting large sized shrimps. In case branding foreign buyers’ brand had major influence on exports than own branding. Apart from these translucent with dusky bands colour with strong marine odour shrimps are more preferable for the exports. xxi Years of experience in shrimp processing, BAP star rating and quantity of exports from A.P. were positively significant on revenue of shrimp industry in Andhra Pradesh whereas business operation was negatively significant. The availability of quality raw material was the most important constraint for the exporters followed by high cost of investment, lack of diversified products, poor technical advancement, uncertainty in prices, lack of research and development and competition among the exporters.ThesisItem Open Access IMPACT OF CLIMATE CHANGE ON PULSE CROPS IN ANDHRA PRADESH: AN ECONOMIC ANALYSIS(ACHARYA N G RANGA AGRICULTURAL UNIVERSITY, GUNTUR, 2019) PRAVEEN KUMAR, N. S.; RADHA, YAgriculture plays a crucial role in India’s economic development and provides food and livelihood to majority of the Indian population. In developing countries like India, climate change could represent an additional stress on ecological and socioeconomic systems. Climate change is likely to have larger impact on predominantly rainfed crops like pulses that are grown in marginal production environment. Pulses are an integral part of many diets across the globe and they have great potential to improve human health, conserve our soils, protect the environment and contribute to global food security. The United Nations, declared 2016 as “International Year of Pulses” (IYP) to heighten public awareness of the nutritional benefits of pulses as part of sustainable food production aimed at food security and nutrition. India is the largest producer (25% of global production), consumer (27% of world consumption) and importer (14%) of pulses in the world. The present study has been taken up with the overall objective of analyzing the impact of climate change on pulse crops in Andhra Pradesh with the specific objectives as to analyze the growth and instability of area, production and productivity of major pulse crops in Andhra Pradesh, to estimate the vulnerability index of all the districts of Andhra Pradesh, to assess the impact of climate variability on yield and area of pulse crops, to study the farmers’ perceptions of climate change and identify the adaptation strategies in pulse production to mitigate climate change and to suggest suitable policy measures to promote pulses production. The present study was conducted in three districts viz., Anantapur, Prakasm and Srikakulam which were selected based on the highest area under pulses and more vulnerability. The primary data pertains to the year 2015-16. The present study mainly focused on four major pulse crops viz., red gram, bengal gram, green gram and black gram. The sample farmers were selected at random with 80 farmers from each selected district, thus constituting a total sample of 240 farmers for collection of primary data. xii Secondary data on location of district, soil type, rainfall pattern, demographic pattern, land use pattern, cropping pattern, irrigation facilities, credit, etc were obtained from the office of the Assistant Statistical Officer and Statistical Handbooks of respective districts. Besides this the time series data on maximum temperature, minimum temperature, and rainfall data were also collected for the period of 30 years from 1986 to 2016 from IMD and Directorate of Economics and Statistics. Growth rate and instability analysis were carried out to find out the trends in area, production and yield of major pulse crops in Andhra Pradesh during the periods 1996-2005 and 2006-2015. The methodology followed by Iyengar and Sudarshan (1982) was used for identification of vulnerable districts of Andhra Pradesh. Ricardian regression model was employed to study the impact of climatic variables on the yield and area of major pulse crops. Multinomial logit (MNL) model was used to analyze the determinants of farmers’ choice on adaptation strategies. The results of compound growth rate indicated that from 1996-2015, production and yield of redgram, bengalgram, blackgram and greengram were positive and that of the area of red gram and bengalgram were positive where as for greengram and blackgram it was negative. The results of instability analysis indicated that the highest instability in area was recorded in redgram and lowest instability in bengalgram. The highest instability in production was recorded in red gram where as for yield it was highest in bengalgram .The lowest instability in production and yield was recorded in blackgram. The study revealed that among the thirteen districts of Andhra Pradesh, Anantapur district was very highly vulnerable and East Godavari district was less vulnerable during period I (1986-1995) and period II (1996-2005), whereas in period III (2006-2015) the Anantapur district was very highly vulnerable and Nellore was less vulnerable. Anantapur district continued to be in very highly vulnerable group in all the periods under study. Education levels of farmers in the study area indicated that about 35 per cent of the farmers were educated up to high school level. Land holding pattern of the sample farmers revealed that majority (45 per cent) of the farmers were marginal farmers. Farmers having farming experience less than 15 years dominated in all size categories. About 37.91 per cent of the farmers were having experience of less than 15 years. Majority of the farmers borrowed credit from Cooperative society which contributed to an extent of 30.83 per cent. Ricardian regression model for yield of bengalgram, greengram and blackgram indicated that the coefficients of rabi maximum temperature, area, farming experience, extension services were showing a significant influence on yield whereas in case of redgram, kharif maximum temperature, kharif maximum temperature square, kharif rainfall and kharif rainfall square, area, farming experience and extension services were significantly influencing the yield of redgram. Ricardian area regression model for bengalgram, greengram and blackgram indicated that rabi maximum temperature, education, yield, extension services, information on climate were significantly influencing area whereas in case of redgram, kharif rainfall, kharif rainfall square, yield and extension services were significantly influencing area of the redgram. xiii About 36.25 per cent of the farmers perceived decrease in rainfall over the years and more than three-fourth of the farmers, perceived an increase in temperature over the years. Majority of the farmers (15.83 per cent) resort to changing the sowing followed by off-farm activities and change in cropping pattern respectively to cope with the changing climatic conditions. The results of the multinomial logit model revealed that educational attainment, farming experience, farm income and knowledge on climate adaptation of the farmer increased the probability of adapting to climate change. Majority of the farmers opined that reduction in yield was the major impact of climate change. Lack of knowledge and lack of sufficient credit facilities were identified as the major constraints for adaptation of strategies against climate change. Farmers opined that introduction of drought tolerant and heat resistant varieties (73.33 per cent) were the most important intervention required for pulse growing farmers, with provision of adequate and timely institutional credit for crop production. The area under pulse crops should be increased by offering certain incentives to the pulse growing farmers mainly targeting small and marginal farmers. As all the districts in an agro- climatic zone do not fall under the same category of vulnerability, it exemplifies the need for developing location specific measures to overcome the adverse impacts of climate change. The institutional credit flow to small and marginal farmers would help to adapt short and long term strategies effectively need to be strengthened and streamlined. Awareness campaigns and trainings to sensitize the farmers about climate change and its likey impacts on pulse crops shall be arranged by the extension agencies. Weather based crop plans and contingency plans for rainfed areas and weather based crop insurance coverage with low premium to increase the production of pulses shall be provided.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 STUDY ON THE DYNAMICS OF AGRICULTURAL DEVELOPMENT IN ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) MAYURI, KORIPALLI; VISHNU SANKAR RAO, DThe present study is carried out to analyze the growth performance, presence of structural change and determinants of structural change in agricultural sector and finally the impact of structural transformation on agricultural development in Andhra Pradesh state. The study was carried out for 40 years period i.e., from 1970-71 to 2010-11, which was based on time series secondary data. The period was divided into two main sub-periods i.e., i) pre-reform period 1970-71 to 1989-90 and ii) reform period 1990- 91 to 2010-2011. The period was also studied under four sub-periods i.e., period I (1970-71 to 1979-80), period II (1980-81 to 1989-90), period III (1990-91 to 1999- 2000) and period IV (2000-01 to 2009-10). The data collected were analyzed using percentage change, index numbers, exponential growth model and Cuddy and Della instability index to study growth and instability. For studying presence of structural change and determinates of agricultural growth Chow test and regression analysis employing Cobb-Douglas production function by including dummy variables were used. The GSDP and NSDP exhibited significant positive growth rates during both pre-reform and reform period. The growth rate during reform period was more compared to pre-reform period. The overall growth rate during the study period was 5.3 per cent for both GSDP and NSDP. The agricultural GSDP and NSDP showed significant positive growth rate during both pre-reform and reform period. The growth rate during reform period was more compared to pre-reform period. The overall growth rate during the study period was 2.8 per cent for both agricultural GSDP and NSDP. x The gross cropped area, growth rate during pre-reform period (-0.1) was negative while the reform period exhibited positive growth of 0.005 per cent and 0.1 per cent during the overall study period. The gross irrigated area exhibited growth rate of 1.3 per cent during pre- reform period, 0.8 per cent during reform period and 1.1 per cent during the overall study period. The growth trend of area, production and productivity of food grains, pulses and oilseeds revealed that their growth in pre-reform period was better compared to reform period. The area of cereals and production, productivity of coarse cereals was better during reform period than pre-reform period. The area of coarse cereals and production, productivity of cereals was better during pre-reform period than that of reform period. There was a drastic increase in the area under the land put to non-agricultural use. During 1970’s the land put to non-agricultural use as a percentage of total geographical area was 7.70 per cent which gradually increased over decades. In 1980’s it increased to 8.10 per cent in 1990’s to 8.90 per cent and in 2000’s increased to 9.50 per cent. The total food crops area decreased from 78 per cent (99.58 lakh ha.) in 1970’s to 66.70 per cent (87.31 lakh ha.) of gross cropped area in 2000’s whereas the non-food crops increased from 22 per cent (28.01 lakh ha.) to 33.30 per cent (43.52 lakh ha.) of gross cropped area from 1970’s to 2000’s. The overall scenario of distribution of operational land holding in Andhra Pradesh revealed a gradual increase in area as well as number of marginal, small and semi-medium holdings whereas, the area and number of medium and large farmers declined over the study period. In total rural workforce, the share of cultivators reduced from 36 per cent in 1971 to 14.47 per cent in 2011, whereas the share of agricultural labourers increased from 43.35 per cent in 1971 to 47.89 per cent in 2011. The share of agricultural workers in total rural work force increased from 1971 (79.34%) till 1991 (81.37%) and then reduced in 2001 (75.15%) and 2011 (62.36%). The results of the Chow test revealed the presence of structural break in the agricultural sector by taking agricultural GSDP as dependent variable and land, labour and capital as independent variables. The tests with factor values as well as factor productivities indicated the presence of structural break. The results of regression analysis by including dummy variables technique for slope parameters - agricultural land, labour and capital regressed on agricultural GSDP, during pre-reform period, the land and agricultural labour factors are significant at one per cent level showing significant influence on agricultural GSDP. During the reform period all the three independent variables, gross cropped area, agricultural credit and agricultural labour had no significant influence on agricultural GSDP. The results of regression analysis by including dummy variables technique for slope parameters - agricultural land productivity, labour productivity and capital productivity regressed on agricultural GSDP, during pre-reform period, all of them showed significant effect on agricultural GSDP. During the reform period, only agricultural land productivity (-0.03) showed a significant but negative effect on agricultural GSDP.ThesisItem Open Access A STUDY ON THE IMPACT ASSESSMENT OF KRISHI VIGYAN KENDRAS IN ANDHRA PRADESH(Acharya N.G. Ranga Agricultural University, 2018) MALATHI, B; VISHNU SANKAR RAO, DThe present study attempts to evaluate the impact of Krishi Vigyan Kendras With the following objectives: 1. To study the impact of Krishi Vigyan Kendras in productivity enhancement by bridging the yield gaps. 2. To evaluate the impact of vocational training programmes conducted by Krishi Vigyan Kendras in the study area. 3. To assess the economic benefits from the adoption of improved technologies. 4. To assess the factors contributing to the adoption of improved technologies by the farmers. Andhra Pradesh state was purposively selected for the study. Three KVKs, one KVK from SAUs (KVK-Amadalavalasa, Srikakulam district), one from ICAR (KVK-Kalavacharla, East Godavari district) and one from NGOs (KVK-Yagantipalli, Kurnool district) were selected for the study which has completed minimum five years of functioning. A total of 360 farmers constituting 180 beneficiaries and 180 non-beneficiaries of the improved technology provided by the sampled KVKs, and 150 trainees were selected randomly making a total sample size of 510. Both primary and secondary data were collected for the present investigation. The analytical models used for analyzing the data were technology adoption index, Cobb-Douglas type of production function, regression, decomposition analysis, Lorenz curves and Gini concentration ratio. Impact of Krishi Vigyan Kendras on crop yields and returns revealed that, in KVK-Amadalavalasa increase in yield (12.80 q ha-1 ) and per cent increase in net returns (42.94 %) over farmers practice were highest in case of mechanized system of rice intensification. Zero tillage maize technology resulted in increased net returns of Rs. 18,106 per hectare over farmers practice. In KVKYagantipalli, the results of frontline demonstrations in rice revealed that the increase in yield was highest in case of management of problematic soils i.e. reclamation of sodic soils with gypsum application as per soil test results (20.88 %) followed by foliar application of zinc (14.98 %) and integrated weed management (9.59 %) over farmers’ practice. In redgram improved technology registered overall 25.34 per cent increase in yield over the farmers’ practice with increase in net income of 44.56 per cent. Under KVK - Kalavacharla, in rice the yield of demonstration plots exceeded that of farmer's plots in all FLDs. In case of banana, it was found that increase in yield was highest (38.03 percent) in nutrient management with direct feeding of banana bunches, which resulted healthy fingers in banana. Factors affecting productivity estimated by Cobb-Douglas production function for the improved technology/ variety revealed that seed in STCR paddy (0.162), HYV redgram (0.378) and planting material in direct feeding of nutrients and skirting of bunches in banana (0.944) were positively significant. Machine labour in MSRI rice (0.219) and human labour in STCR rice (1.945), HYV rice (0.26) and direct feeding and skirting of bunches in banana (0.104) were positively significant. Nitrogen was positively significant in zero tillage maize (0.138), HYV redgram (0.44) while it was negatively significant in STCR rice (-0.159). Phosphorous was positively significant in HYV rice (0.666) and MSRI rice (0.259). Potash was positively significant (0.162) in farmers’ practice of rice in KVK-Amadalavalasa, STCR rice (0.204), HYV redgram (0.138) and farmers’ practice (0.25) and direct feeding and skirting of banana bunches in banana (0.035). Irrigation was found to be positively significant in zero tillage maize (0.112), HYV rice (0.24) and direct feeding and skirting of bunches in banana (0.094). The decomposition analysis of yield gap between the improved technology/ variety and the farmers’ practice/ local variety indicated that the technology gap was the major contributing factor in the total difference in productivity in all the crops among all the three KVKs which was highest in case of soil test crop response (STCR) in paddy (392.98 %) in KVK-Yagantipalli of Kurnool district. All the vocational trainings have given a boost to trainees by giving supplementary income and employment. Lorenz curves and Gini concentration ratios depicted that there were comparatively lesser inequalities in distribution of income obtained from improved cultivation practices of crops when compared with the inequalities in distribution of income obtained from farmer’s practices. The technological adoption index (TAI) calculated for 180 technology adopting farmers indicated that all the farmers belonged to medium and high adoption category. Age of the farmer was a negative contributor in all the crops which revealed that with the increase in age of the farmer technology adoption level decreases. Educational level of the farmer had positive and significant contribution in the technology adoption of MSRI and STCR technology in rice. KVK training is the major contributor in the technology adoption whose impact was positive in all the three KVKs. The important policy implications from the study are: Forward linkages in terms of post-harvesting, transportation, packaging and marketing are necessary for new products or high yield products. KVK should focus on post harvest techniques to support farmers especially processing to encourage them to adopt new technologies. KVKs should be developed as resource centres which can provide/facilitate the access to inputs for farmers which are the crucial factor in the adoption of new technology. Krishi Vigyan Kendra in the district need to provide proper technical support to the farmers through different educational and extension methods to reduce the extension gap for better production in the district by creating awareness among the farmers about new technologies. Modernization of soil testing labs, keeping the farmers’ needs in focus while providing training, focus upon new emerging areas like climate change, pro-harvest management and non-farm activities are need to be considered by the KVKs, host organizations and ICAR (Indian Council of Agricultural Research). Measures to be adopted to increase the outreach of KVKs by adopting innovative techniques viz. forming farmers groups, train farmers-trainer, redefining cluster approach, continuous interaction at village level, need based training, use of ICT (Information and Communication Technology), etc. To cope with the future challenges of technical advancement, the existing vocational and technical training system needs to be improved and marked with the needs of the economy. To support and to mobilize entrepreneurial skills of the farmers, KVKs should coordinate to start agribusiness centres by the farmers in villages. Better feedback mechanism is needed and KVKs should follow up the trainee farmers, rural youth and women after the completion of training programmes to make sure that they will adopt the newly acquired skill in creation of employment which will eventually lead to increased income levels and livelihood security. The study leads to the observation that KVKs are playing a pro-active role in transferring new technology at field level and with beneficial impacts, but a lot is yet to be done to bridge the yield gaps in crops and entrepreneurial development of rural community.