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ThesisItem Open Access Dynamics of major oilseeds and pulses in India(CCSHAU, Hisar, 2021-10) Sadhanala Swetha; Mehta, V. P.The study on “Dynamics of Major Oilseeds and Pulses in India” was done with the following objectives: (1) To analyze the trends in the area, production productivity, prices of oilseeds, and pulses, (2) To examine the export and import status of oilseeds and pulses, (3) To study major constraints in the export and import of oilseeds and pulses, (4) To suggest suitable policy measures and implications for the future. The present study was based on secondary data collected from various published sources, viz., indiastat.com, Statistical Abstract, Agricultural Statistics at a Glance, FAOSTAT and Directorate of Economics, and Statistics, Government of India, New Delhi, etc. The area, production, and productivity data were collected for the pulses and oilseeds during 1990-91 to 2019-20. The total period is divided into three periods, i.e., period-I (1990-91 to 1999-00), period-II (2000-01 to 2009-10), and period-III (2010-11 to 2019-20). The compound growth rate (CGR) is calculated for the above three and overall period to analyze the growth in the area, production, and productivity. In period-I, it is observed that there is a positive growth rate in the area for both pulses and oilseeds. In period-II, it is observed that there is a positive growth rate in the area, production, and productivity for both pulses and oilseeds. In period III, it is observed that there is a negative growth rate in the area, a positive growth rate in production and productivity for both pulses and oilseeds. . For the above period, the average compound growth rate (CGR) in major states for Bengal gram as 2.82, 1.34, and 3.5, for Black gram -0.69, 0.53, and 0.215, for Pigeon pea 0.65, 1.29, and 0.61, for Chickpea 1.27, 0.96, and 0.74, and for Green gram -0.71, 0.55, and 0.116 is observed in the area, production, and productivity. The overall growth trend analysis of Sunflower recorded 4.15, 2.05, and 3.75 annually, Soybean recorded 1.05, 0.65, and 0.25, Mustard recorded 2.35, 1.35, and 0.29, Groundnut recorded -0.38, 1.10, and 0.42, Sesame recorded -13.30, 8.18, and -5.75, and Safflower's overall growth trend analysis recorded -3.85, 2.13, and 1.15 annually in area, production and productivity-wise. There have been variations in the growth behavior of different oilseed crops over the years. Crops like groundnut, soybean, and rapeseed-mustard have seen increased production, whereas minor oilseed crops like safflower have seen a decline in area and production. Export and import data is also analyzed for both the pulses and oilseeds. Suitable policy measures are necessary to lift the oilseed economy by pushing the productivity of all major and minor oilseed crops in the major growing states. India has gained a comparative advantage in the export of pulses and a comparative disadvantage in oilseeds.ThesisItem Open Access Agricultural insurance in india vis-à-vis in Haryana: problems and prospects(CCSHAU, Hisar, 2020-07) Punia, Meenu; Kundu, K. KThe present investigation was carried out to study price and yield risk involved in different crops at national and state level, performance of the existing and earlier national agricultural insurance scheme, awareness and knowledge of respondent farmers towards crop insurance schemes, and problems and prospects of agriculture insurance schemes. The required secondary data on production and prices of insured crops were collected from secondary sources. Primary data pertained to Haryana state, which divides into three clusters. Multistage random sampling used and total 240 respondent farmers (120 insured and 120 non-insured) were selected for conducting the study. In case of wheat, area and production followed declining trend and became more stable after Green revolution period. But, in case of wheat at all India level, yield risk were maximum volatile and its value shot up more than 100 per cent, respectively. Further, the instability of yield in case of India rose due to frequent severe droughts during 1981-82 to 2003-04. In case of Bajra, overall risk in area was highest among all the principal crops (i.e. approx. 11%). So, in case of Haryana, gram showing the maximum overall risk in area and production (45.69% and 70.29%) among other crops. Gram has been observed to be the riskiest crop in respect of production as well as yields. This understand the need for addressing risks in farm income by devising area-specific crop insurance or other suitable mechanisms and implementation of Pradhan Mantri Fasal Bima Yojana (PMFBY) in year 2016 is an important tool in addressing this issue. The study revealed that age of the respondent did not show any significant difference between borrower and non-borrower. Respondent farmers suggested for improving existed scheme and they want quick settlement of claims which is usually taking more time. Risk factors faced mostly in agriculture are drought, flood, fire etc. Overall majority of the borrower had opted the Banks/ financial institutions compulsion as the top most motivating factor for taking crop insurance i.e. 35.83 per cent. Second position was taken by the benefit of insurance (26.66%) for their motivation. No one gave others option as motivation factor. Constraints generally faced by the borrower farmer like delay in claim settlement (25.83%), inaccurate yield estimation (20.83%), inadequate implementation (20.00%), delay in claim settlement (25.83%), lack of awareness about the scheme and exclusion of a malicious damage, theft and grazed and destroyed by domestic animals etc. as 3.33 per cent. as major constraints. Further, the claim premium ratio in First Individual Approach Scheme was 8.34, indicating that for every one rupee of premium collected; the scheme paid Rs 8.34 in claims. It means high out go in the scheme. The benefits of CCIS were highly skewed towards few states and many more drawbacks found in different schemes. Under PMFBY from kharif 2016 to kharif 2017, there has been a significant increase in the number of gross premiums, claims paid and farmers benefitted: 21 per cent, 64 per cent and 29 per cent, respectively. The difference between gross premium and claim paid/compensation paid in the Kharif season has reduced and indicated a divergence in the data on the disbursement of claims and the profits made by private insurance companies. While the negative effects, the number of insured farmers has declined by 14 percent from Kharif 2016 to Kharif 2017, and the total area insured has decreased by ten percent over the span of one year. Likewise, from kharif 2017 to kharif 2018 no. of insured farmers has declined further by 4 per cent, and the total area insured has decreased by seven per cent. However, there has been a significant increase in the number of gross premiums as 45 per cent. The PMFBY has therefore failed to achieve its main targets, i.e. increasing the area and the number of farmers insured. Awareness must be created among farmers regarding different insurance schemes available to farmers, procedure for insuring the crops, methods of loss assessment and compensation determined etc. to tackle the problems.ThesisItem Open Access An economic analysis of dairy farming business in Haryana(CCSHAU, Hisar, 2021-08) Loura, Manju; Ghalawat, SumanThe present study was carried out with the objectives to analyze the investment, resource use pattern, profitability and turnover, to examine the extent of adoption of recommended management practices and constraints in the Dairy Farming and SWOT analysis of dairy farming in Haryana. The study was based on primary as well as secondary data. The Haryana state was divided into two agro-climatic regions/zones i.e. eastern and western regions. The eastern and western regions were denoted as Zone-I and Zone-II, respectively in this study. Zone-I included the districts of Kaithal and Karnal. Zone-II comprised Sirsa and Hisar districts. From the selected districts, two blocks from each district were selected randomly for the present study. Twenty-five farmers practising dairy farming were selected randomly from each block as respondents for the study. Therefore, the total sample size for this study was 200 dairy farmers. To achieve the specific objectives, the primary data from the sample dairy farms were collected through survey method on pre-structured schedules designed for the purpose. The data were collected to work out the investment and consumption pattern in dairy production, profitability and turnover of dairy farms, adoption level of recommended management practices and constraints, SWOT analysis of dairy farming in Haryana during 2019-20. The respondents were divided into three categories i.e. small, medium and large herd size on the basis of number of milch animals. Tabular method and descriptive statistics were used by using IBM SPSS software to attain the desired objectives. The outcome of study revealed that average total variable cost per milch animal per day in Zone-I and Zone-II was ` 120.33 and 133.85, respectively. Overall total variable cost per milch animal per day in Haryana was found to be `127.09. On the other hand, average total fixed cost per milch animal per day was ` 178.56 and 173.41 in Zone-I and Zone-II of Haryana. Overall total fixed cost in Haryana was ` 175.98, whereas overall gross cost was ` 298.56 in Zone-I and ` 307.26 in Zone-II of Haryana. Overall gross cost in Haryana was ` 302.91. Milk productivity was 7.91 and 8.09 l/day/milch animal in Zone-I and Zone-II in Haryana, respectively. Overall milk productivity of Haryana was found to be 7.98 l/day/milch animal. It was also revealed that average milk price was ` 53.60 and 53.70 in Zone-I and Zone-II, respectively. Average milk price of Haryana was ` 53.65. It may also be concluded that net returns per milch animal per day in Zone-I were ` 125.67 and ` 128.30 in Zone-II of Haryana. Average net returns per milch animal per day of Haryana were ` 126.57 per milch animal per day. As far as average milk production was concerned it was found to be 72.95 t per month. Average milk production of Haryana per annum was 60.79 t. The average turnover of the dairy units in Haryana was ` 32.81 lakh. Study revealed that among all the recommended management practices animal health practices were followed by majority of the dairy farmers and the corresponding mean value was 1.75 and the rank was 1st, followed by socio-economic management practices (corresponding mean value 2.02 and rank 2nd), hygiene milking practices (corresponding mean value 2.12 and rank 3rd), animal well-being (corresponding mean value 2.23 and rank 4th), nutrition (corresponding mean value 2.56 and rank 5th), and environmental practices with corresponding mean value 2.57, were least preferred or we may say least adopted by dairy farmers hence environmental practices were given rank 6th. On the other hand, among all the constraints, financial were faced by majority of the dairy farmers and the corresponding mean value 1.69 and rank 1st. We concluded that among all the constraints financial constraints were the most important constraint, followed by constraints regarding unavailability of skilled labour (corresponding mean value 1.85 and rank 2nd), production constraints (corresponding mean value 2.45 and rank 3rd), and marketing constraints (corresponding mean value 2.73 and rank 4th). Major strength of dairy sector was high milk production, high per capita availability of milk, availability of best buffalo breed, reasonable market margins, increasing demand of milk and milk products and self-sufficiency in medicine production. Whereas weakness of dairy sector was involvement of more informal channel, quality issues, opposition to cooperatives, scattered milk production, seasonal fluctuation in milk production and lack of infrastructure and major opportunity in dairy sector was high demand of milk and milk products among youth and sports persons, increased awareness about quality products, involvement of huge investment in dairy sector, high export potential and overall positive growth in dairy infrastructure. It was revealed that major threats to dairy sector were scattered milk production, lower educational level of dairy farmers, existence of large numbers of milk vendors, excessive grazing, increase in cost of feed and high transportation charges and excretion of methane gas from dairy farms. On the basis of conclusions of the study, we may suggest that cost of feed and fodder should be minimized, credit facilities should be strengthened, training programs for adoption of good dairy practices should be organized and last but not the least infrastructure for dairy sector should be strengthened.ThesisItem Open Access Spatial and temporal crop diversification in India and their consequences on agriculture(CCSHAU, Hisar, 2020-02) Swamy H. M.; Sharma, U. K.After the independence Indian agriculture focused mainly on the food security issues targeting more of food rains, but in the recent decades Indian agriculture able to meet food demand and became net food grain exporter, this was achieved from technology called green revolution, till then agriculture in India was of subsistence in nature but in the recent decades agricultural concern shifted from food grain crops to commercial or non-food grain crops to meet economic and financial demand of farmers. The results of the analysis indicated that Southern region witnessed composite entropy index value crossing 50 per cent in case of cereals (0.63) and total crop sector (0.62) during 2005-17 periods. While, Western region revealed an average of five periods composite entropy index of 0.53, 0.52 and 0.51 in case of total food grains, oilseeds and total crop sector. Northern region shown significant improvement in diversification index from 0.27 to 0.41 during 1955-65 to 1985-95. Thereafter, downfall in the diversification index was noticed. Exactly the reverse trend was seen in case of pulses and oilseeds. Commercial, fiber crops and over all crop sector revealed consistent increase in diversification index from 0.16 to 0.32, 0.21 to 0.29 and 0.40 to 0.49. In the eastern region cereals and pulses drawn the significant increase in diversification index value from 0.35 to 0.49 and 0.42 to 0.54 during study period. North eastern region all crop groups have showcased remarkable progress in terms of diversification index which was 0.24 to 0.46 in cereals, 0.01 to 0.47 in pulses, 0.24 to 0.46in total food grains, 0.06 to 0.42 in oilseeds, 0.10 to 0.19 in commercial crops, 0.12 to 0.34 in fiber crops and 0.41 to 0.43 during study period. At all India level composite entropy index for cereals, pulses, oilseeds and fiber crops have shown a slight improvement, but commercial and over all crop sector have witnessed significant improvement having diversification value of 0.22 to 0.46 and 0.42 to 0.51 for commercial and overall crop sectors, respectively. Thereby, clarifying a clear message of diversification going on towards commercial crops, at the same time maintaining area under other crops as well, this might be due to increased cropping intensity and other such factors.
