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ThesisItem Open Access ECONOMIC EVALUATION OF LIVESTOCK-BASED FARMING SYSTEMS IN SALINE AND NORMAL AREAS OF WEST BENGAL(ICAR-NDRI, KARNAL, 2022) ARGHYADEEP DAS; RAJU R.Saline soils already occupied 44 per cent area of our country, covering 12 states and one Union Territory. Every year nearly 10 per cent additional area is getting salinized, and by 2050, around 50 per cent of the arable land would be salt-affected which will hamper the food security of our country. The Indo-Gangetic Plains (IGP) are well known to provide nearly 50 per cent of the total food consumption to feed 40 per cent of the country’s population. The plains are agriculturally the most fertile region and contain nearly 36 per cent of the bovine population of the country. This region is also suffering from soil salinity, out of the total saline areas in the IGP region (5,59,719 ha), 78.84 per cent area (4,41,272 ha) is under West Bengal. The major part of the coastal saline areas in West Bengal is in the Sundarban area of district South 24 Parganas and parts of North 24 Parganas district and Purba Midnapore district. Within the selected districts, 17 blocks of South 24 Parganas, 6 blocks of North 24 Parganas and 10 blocks of Purba Midnapore are having saline areas. The rest of the blocks i.e., 12 blocks of South 24 Parganas, 16 blocks of North 24 Parganas and 15 blocks of Purba Midnapore come under normal areas. Blocks like Basanti, Namkhana and Canning II from South 24 Parganas; Hingalganj from North 24 Parganas; Khejuri II and Nandigram I from Purba Midnapore were randomly selected for saline areas. For normal areas, randomly selected blocks were Mograhat I and Mograhat II from South 24 Parganas; Barasat I and Bongaon from North 24 Parganas; Bhagwanpur I and Bhagwanpur II from Purba Midnapore. A total sample of 240 households was selected; 120 households were selected from each of the saline and normal areas within these districts. Farming systems identified in saline areas were S1 (Sheep+ Poultry), S2 (Goat+ Poultry), S3 (Cattle+ Goat+ Crop+ Fish) and S4 (Cattle+ Poultry+ Crops+ Fish) and in normal areas were N1 (Cattle+ Goat+ Poultry+ Crop), N2 (Cattle+ goat+ Crop) and N3 (Cattle+ Poultry+ Crop). Saline areas are dominated by the indigenous cow and normal areas by the crossbreed jerseys. The milk yield of the crossbreed jerseys was lower in saline areas (4.90 litres/day) than in normal areas (8.10 litres/day). This was due to a shortage of green fodder in saline areas. Due to the cultivation of indigenous salt-tolerant varieties such as Dudhersar, Lal Dhan, Rupsai and Patnai rice yield was lower in saline areas (5.60 quintals/acre) than in normal areas (8.25 quintal/acres), where high yielding varieties such as Khitish, Swarna Mahsuri and Sada Swarna were cultivated. Garole sheep rearing and backyard fish farming were the unique components found under farming systems only in saline areas. Black Bengal goat and poultry birds like Vanaraja, Rhode Island Red and Khaki Campbell were common in both saline and normal areas. Backyard fish cultivation is common in saline areas where the Indian major carps, Catla, Rohu and Mrigal were mostly cultivated. The share of labour was highest (56% to 58%) in total cost in crop enterprises and feed and fodder costs had a major share (53% to 79%) in total cost for livestock enterprises. Due to low maintenance costs, S1 and S2 farming systems have the output-input ratios close to 2. In case of other farming systems, the output-input ratios were close to 1.5. Among different resources labour, fodder and fertilizer were over-utilized and concentrate and veterinary services were underutilized. Return to scale (RTS) of farming systems in saline areas was constant (S1 and S2) and decreasing for S3 and S4 but it was increasing for N1 (1.30) and N2 (1.43) and constant for N3 (1.03) for normal areas. In saline areas, households under all the farming systems except S3 were on an average less than 70 per cent efficient, but in normal areas, the households under different farming systems were on an average 70 per cent or more efficient. Irrespective of the saline and normal areas, it is found that age, level of education, farming experience, household size, number of animals, land under cultivation, access to credit and access to information had a negative effect on profit inefficiency. Optimal solution under few farming systems had over-achieved the second (maximizing self-financial support) and third goal (minimizing income risk of the farm). However, the first goal (maximizing gross margin) was achieved in case of all the farming systems.ThesisItem Open Access WOMEN EMPOWERMENT AND ITS CONTRIBUTION TO LIVELIHOOD OF LIVESTOCK BASED HOUSEHOLDS IN ODISHA(ICAR-NDRI, KARNAL, 2022) JAGRUTI DAS; AJMER SINGHThe livestock sector especially dairying in India is a female dominated enterprise. Livestock acts a major hinge contributing to the food as well as nutritional security Since women are the major players in deciding the household’s food intake, the major aim of women empowerment is the attainment of household food security (Moyo et al., 2012).Hence, livestock could be seen as an important medium for women empowerment, thereby strengthening the livelihood, food security and nutritional security of the households. The present investigation entitled “Women empowerment and its contribution to livelihood of livestock based households in Odisha” was undertaken .This study measured the levels of women empowerment in the study area using the Women Empowerment in Agriculture Index followed by identification of dominant dimensions and sub-dimensions of women empowerment using the Principal Component Analysis. The factors of women empowerment promoting self-reliance of primary women in the study area was assessed using Multinomial Logit. Similarly, HFIAS (Household Food Insecurity Access Scale) followed by Ordered Logit was used to determine the food security status. The vulnerability of the livestock based household to food insecurity and impact of women empowerment on the livelihood outcomes of the sampled households was also studied. The study was carried out in the state of Odisha. The state of Odisha has been divided into ten agro-climatic zones. So, from each agro-climatic zone of Odisha, one district was selected on the basis of highest Rural Female Labour Force Participation Rate (RFLFPR) purposively. Two villages from each of the selected districts were sampled randomly i.e. Simple Random Sampling (SRS). Three hundred farm households were selected from the chosen villages based on Probability Proportional to Size (PPS). Both econometric and tabular analysis was used to achieve the objectives of the study. The results of this study revealed that , that the women involved in the livestock enterprises in tribal areas of Odisha are more empowered in all the domains (5DE) than those of central and coastal regions whereas the coastal regions fair well in terms of Gender Parity Index (GPI). Increase in crop and livestock production skills of the primary woman makes her more self reliant thereby reducing the dependence of the household of remittances and social grants by 54 and 52 per cent respectively. Similarly, the enhancement of crop and livestock management skills of the primary woman reduces the dependence of the households on remittances and social grants by 49 and 53 per cent respectively. The present study has found that that the likelihood of women with high levels of vocational empowerment, the reliance of the primary woman on remittances decreases by 40.8 per cent. Thus, training and educational programmes related to livestock sectors need to be designed keeping in view the convenience and need of women beneficiaries. It was also discovered that dependency ratio increases the likelihood of a household being vulnerable to food insecurity by 29 per cent. Dependency ratio of the sampled household was seen as a major constraint towards self-reliance and food security in the study area. Increase in Economic Agency of the primary woman in terms of enhancement of the bargaining power, motivation, confidence and self-reflection of women reduces the likelihood of the household to be in the SFI category by 56 per cent and increases the likelihood of being in MFI2 and FS categories by 31 and 21 per cent respectively. Enhanced Social Capital Empowerment of the primary female reduces the likelihood of the household to be in the Severely Food Insecure (SFI) category reduces by 16 per cent and increases the likelihood of being in Mildly Food Insecure (MFI2) and Food Secure (FS) categories by 9 and 6 per cent respectively. This study has found that livestock based enterprises are a viable option for the upliftment of women through collective action.ThesisItem Open Access EXTENT OF POVERTY AND ITS DETERMINANTS IN RURAL HOUSEHOLDS OF BIHAR: A MULTIDIMENSIONAL APPROACH(ICAR-NDRI, KARNAL, 2021) MANJISHA SINHA; SENDHIL R.Bihar has achieved a growth rate of 10.53 per cent (constant price) in 2019-20 which is higher than the nation’s growth rate. Though inclusiveness has always been a focal point of several welfare programs of the state, still Bihar homes (33.7 % of the population) highest number of country’s poor. Poverty is a multifaceted, highly complex and interrelated phenomenon. Bihar lags far behind in attaining several sustainable development goals showing that a majority are undernourished, less educated etc. This implies that growth has not trickled down to other facets of welfare and enumerating deprivation in these dimensions is the need of hour. With this background, present study on “Extent of Poverty and its Determinants in Rural Households of Bihar: A Multidimensional Approach” has been undertaken with specific objectives i.e. estimating the extent of multidimensional poverty at the district level in Bihar, determining the status of multidimensional poverty of the households engaged in agriculture and livestock activities in different incident regions, analyzing the determinants of multidimensional poverty in rural households and identifying the potential interventions for multidimensional poverty reduction. For estimating the multidimensional poverty at district level, secondary data obtained from the demographic and health survey (DHS) (2015-16) was used. Using Alkire and Foster’s method, the multidimensional poverty index (MPI) of rural Bihar was estimated at 0.278. The intra state MPI varied from 0.19 in Rohtas to 0.39 in Araria. The multidimensionally poor were deprived in 4 to 5 out of 10 weighted indicators. Deprivation in living standard was the highest (more than 45 %) contributing dimension to the MPI, followed by health (25%) and education (20%). On the basis of MPI, 38 districts in Bihar were divided into 3 categories, i.e. low (<0.251:12 districts), moderate (0.251-0.307:13 districts) and high multidimensional poverty zones (>0.307:13 districts). From each category, one district and subsequently two villages were selected randomly. As the availability of secondary data limits the inclusion of dimensions and indicators, a primary survey was undertaken to determine the MPI of rural households in the sample districts. The MPI was highest in Kishanganj (0.442), followed by Bhagalpur (0.383) and Patna (0.371). Around 75 per cent of the rural population in every district were multi-dimensionally poor. Financial inclusion (36.8 %) was the highest contributing dimension to the MPI, followed by health (27.3 %), education (19.30%) and living standard (16.7%) in Patna. In Bhagalpur, education (29.1%) was the highest contributing dimension, followed by financial inclusion (26.7%), health (25.7%) and living standard (18.4%). In Kishanganj, a majority were deprived in education (27.6%), health (26.8%), financial inclusion (26.3%) and living standard (19.3%). Heckman’s analysis indicated that higher education (above higher secondary), ownership of assets, and large land holding have a significant negative effect on deprivation score implying the positive effect on reducing the poverty level. Although non-significant, owning dairy animals has a positive multidimensional poverty reducing effect. Using analytical hierarchy process, potential strategies to reduce the MPI were identified. Remedial teaching and conditional cash transfer under education, physical and human capital formation, and incentivizing mothers under health, increasing the access to credit, SHG formation, creating long term non-farm employment and supporting entrepreneurs under financial inclusion and living standard dimensions, respectively should be prioritized for reducing the multidimensional poverty in rural Bihar.ThesisItem Open Access IMPACT OF PUBLIC RESEARCH INVESTMENT ON LIVESTOCK PRODUCTIVITY IN INDIA(ICAR-NDRI, KARNAL, 2022) BABITA KATHAYAT; ANIL K. DIXITIndian livestock sector is mainly characterized by small herd size and production is driven by a large livestock population rather than productivity. The input-led growth will not be very sustainable in the long run, especially when faced with persistent challenges of declining land resources and rising human population. Improving productivity will necessitate significant investment in livestock research by the public and private sector. The success of crop genetic research in enhancing productivity is well acknowledged but little work has been carried out to establish the contribution of livestock research. Therefore, the present study was undertaken with an objective to estimate the impact of public research investment on livestock productivity in India. The study was entirely based on secondary data. A total of 45 institutions were identified which included 19 central institutions, 15 state veterinary universities and 11 veterinary colleges, part of already existing State Agricultural Universities (SAUs). Whole country was divided into five zones based on the location of institutions namely; North, East, West, South, and Central to estimate livestock research and education expenditure series. Growth rate and congruence analysis was done to analyse the trends and distribution of research funding. To understand the productivity trend, estimation of Total Factor Productivity (TFP) and its decomposition was done using Malmquist Productivity Index. To identify the sources of TFP and their relative contribution, fixed effects panel regression model was employed. Marginal Internal Rate of Returns (MIRR) was calculated to provide estimates of economic returns to livestock research investment. Total livestock research and education expenditure was estimated to be `12.6 billion in current prices in 2018-19. When measured in constant 2011-12 base prices, it increased from `2.5 billion in 1994-95 to `8.8 billion in 2018-19 at an annual rate of 5.02 per cent. South zone had the largest share in total expenditure while the central zone had the lowest share. Overall livestock research intensity measured as a share of AgGDP was 0.04 and the share of livestock research and education expenditure in total agricultural research and education expenditure was just about 15 per cent. Analysis of congruence ratio (CR) revealed that all zones were underinvested. The CR was in the following order: North (0.64)> Central (0.61)> South (0.53)> East (0.50)> West (0.41), indicating that North zone and West zone were most and least efficient zone, respectively, under the existing pattern of allocation. Evidence of productivity improvement in the livestock sector was indicated by a positive mean TFP index value of 1.03. Technical progress (1.04) was identified as the main productivity growth driver while the efficiency change (0.99) component had either remained stagnant or declined. Despite a high positive correlation between TFP and GVA growth, livestock output was largely input-driven. Livestock research was found to be contributing significantly to TFP. With a one unit increase in research stock, TFP increased by 19.8 per cent. Regional analysis showed the highest impact for the north zone, where one unit rise in research stock increased TFP by 64 per cent, 19 per cent in the south, 10 per cent in the east, and about 7per cent in the west. Veterinary Infrastructure, AI and Road density had a positive impact on TFP growth but were statistically insignificant. The relative contribution of livestock research in TFP (56%) was highest followed by AI (24%), Veterinary Infrastructure (14%) and Road Density (6%). Overall MIRR was reported to be 41 per cent. Zonewise, the highest MIRR was observed in the North zone (49.5%) followed by the East (38.2%), South (37.3%), and West zone (36.7%). MIRR was high enough to warrant additional investment in livestock research. The study concludes that livestock research has a significant positive impact on TFP but low adoption of livestock technologies at the farm level could hamper technological progress. Therefore investments in livestock research need to be given priority. This will encourage productivity-led growth which in turn will contribute to output growth and dependence on limited inputs could be reduced.ThesisItem Open Access A COMPARATIVE STUDY ON PERFORMANCE AND IMPACT OF DAIRY CO-OPERATIVES IN MAINLAND AND SAURASHTRA-KUTCH REGIONS OF GUJARAT(ICAR-NDRI, KARNAL, 2022) DARSHNABEN P MAHIDA; B.S. CHANDELIn the largely scattered milk production system of India, the institutional mechanism of dairy co-operatives is proven to be a potential tool for improving the livelihood of dairy farmers, especially for landless labourers, and small and marginal farmers. However, their performance and impact have varied regionally over the time period due to various reasons which are external and internal to the co-operatives. In this context, the present study entitled “A comparative study on performance and impact of dairy cooperatives in Mainland and Saurashtra-Kutch regions of Gujarat” was taken up to calculate a composite performance index (CPI) of dairy co-operative societies (DSCs), estimate the factors and decompose their contribution to the performance and finally analyze the impact of co-operatives on net returns and productivity of the dairy farmers. A random sample of a total of 120 registered DCS working since 2009 or before was selected from four selected milk unions (MUs), two each from the Mainland and Saurashtra-Kutch regions of the state using a probability proportionate to size approach. To analyze the impact of DCSs performance on farmers’ net income and productivity,30 dairy co-operatives members and 30 non-members from two best performing DCSs in four MUs each, forming a total sample of 240 dairy farmers were selected. The collected data were analysed by using Iyengar and Sudarshan approach for calculating composite index, logistic regression analysis, two-stage Heckman method, and Blinder-Oaxaca decomposition approach to achieve the pre-determined objectives. The study found that the overall performance of DCSs has improved by 33.15 per cent from a CPI value of 0.253 (2011-12 to 2014-15) to 0.336 (2015-16 to 2018-19). The CPI was higher for the DCSs of Kaira (0.468) and Mehsana (0.448) MUs of the Mainland region than the DCSs of Surendranagar (0.282) and Junagadh (0.186) MUs in Saurashtra-Kutch region. Over time, milk union-wise the performance (CPI) of DCSs in Surendranagar MU (42.51%) have progressed the most followed by Kaira (33.42%) and, Mehsana (30.11%), MUs. The study observed that better physical performance augments the probability (0.278) of DCSs to have good financial performance and concludes that physical performance is a prelude to the financial performance of DCSs. The logistic regression results revealed that the probability of DCSs to have high-performance increases by 1.10 per cent, 62 per cent, and 12.90 per cent with the decrease in the proportion of poor households and with an increase in AI service coverage and annual bonus, respectively. The impact analysis showed that in Mainland, the net returns per SAU including bonus increase by ` 7.45 and ` 9.95 with a per unit increase in animal milk productivity and access to information, respectively. On the other hand, the co-operative membership (0.458) and access to information (0.469) had a significant positive impact on animal productivity. In the Saurashtra-Kutch region dairying experience, access to information, herd size, and animal milk productivity were the factors that significantly enhanced the net returns of the farmers. The decomposition results revealed that overall, the endowment gap explained 65.99 per cent of the total gap in the performance of both the regions. Thus, the endowment of DCSs must be enhanced by bringing in operational diversity and improving the germplasm of dairy animals through selection and crossbreeding programs.ThesisItem Open Access IMPACT EVALUATION OF ANIONIC MINERAL MIXTURE SUPPLEMENTATION ON MILK PRODUCTION AND THE MILK FEVER: A RANDOMIZED CONTROLLED TRIAL(ICAR-NDRI, KARNAL, 2022) A. G. ADEETH CARIAPPA; B.S. CHANDELUpon parturition or calving, due to rapid drain of calcium (Ca) into colostrum and increased milk production in bovines, Ca requirement is 10 times more than the dry period. If this requirement is not fulfilled, Ca deficiency leads to a condition called hypocalcaemia or milk fever. Milk fever is a gateway for other diseases; a cow with milk fever is 8 times more likely to experience mastitis, 3 times more likely to have dystocia and have a retained placenta. Milk fever causes annual economic losses upto ₹ 873 crores in Haryana. Findings from experimental research stations suggest that feeding anionic diet pre-partum improves Ca concentration and reduces milk fever while improving reproductive and productive performance of dairy animals. With this background, the effect of ‘Anionic Mineral Mixture’ (AMM) supplementation for preventing milk fever was evaluated. The specific objectives were to evaluate the effect of AMM supplementation, estimate price sensitivity of its demand and forecast the cost and benefits of implementing an AMM distribution scheme. The randomized controlled design was used with 200 dairy animals (100 cows and 100 buffaloes). Economic surplus model was used to estimate the overall welfare gains of the technology under different adoption and success rates. The study found a significant reduction in milk fever incidence (from 21% to 2%) and improvements in milk yield (14%) and farmer’s profit (35%) with AMM supplementation. The impact was higher on farmers with older animals, small herd size (< 6 animals) and among those farmers who were having formal training on dairying. Demand for AMM was highly sensitive to prices. A one per cent increase in prices led to an 18.4 per cent fall in demand. At ₹ 100, 200, 300, 400 and 500, the predicted willingness to pay, the demand was 44, 25, 18, 19 and 18 per cent, respectively. Total cost incurred to supplement AMM in the study was ₹ 2133 per animal. Cost incurred per unit of milk fever averted was calculated to be ₹ 14,217 and for every additional gain of milk yield was ₹ 5 per litre. If an AMM scheme was to be implemented in Haryana to prevent milk fever cases, the annual cost to be incurred was estimated at ₹ 611 crores. Potential economic welfare to the extent of ₹ 4,862 crores could be generated if all the farmers adopt the technology and if AMM is 100 per cent successful. Taking into account the price sensitivity, costs of implementation and the impact of AMM, it was found that the welfare gains is more than the costs in Haryana if 18 per cent (@ 71% success rate) of the dairy farmers adopt the technology. To achieve the 18 per cent adoption level, the AMM should be distributed at a minimum of 60 per cent subsidy.ThesisItem Open Access ECONOMIC LOSSES DUE TO CLINICAL MASTITIS AND REPRODUCTIVE DISORDERS IN CROSSBRED COWS: A STUDY IN AHMEDNAGAR DISTRICT (MAHARASHTRA)(ICAR-NDRI, KARNAL, 2021) NITIN SUDHAKAR WAKCHAURE; MALHOTRA, RAVINDERDairying is becoming robust and most sustained profession with the advent of mechanization and technological interventions. Due to increase in market demand for milk and milk products, the present economic scenario of dairy farm managemental practices demands that the individual dairy animal should not be only a high producer but also profitable. This put extra pressure on dairy animals to produce increased milk yield which further leads to increase in risk of incidence of diseases and reduced reproductive performance over a period of time. Therefore, better herd management can reduce the occurrence of diseases and fertility problems but this may increase the cost of milk production, thus reducing the profit of the dairy farmers. The present study comprises of secondary data of total 2168 calving and 2004 lactation records over a period of 20 years from 1995 to 2014 in Phule Triveni crossbred cows at RCDP on cattle farm, MPKV Rahuri, Maharashtra, and primary data of crossbred cows that suffered from clinical mastitis was collected from high, medium and low rainfall region of Ahmednagar district from 180 households. In this way, the present study “Economic losses due to clinical mastitis and reproductive disorders in crossbred cows: A study in Ahmednagar district (Maharashtra)” was taken up with the specific objectives (1) To estimate the economic losses due to clinical mastitis and reproductive disorders in crossbred cows, (2) To examine the factors affecting clinical mastitis and reproductive disorders in crossbred cows at an organized farm, and (3) To project the economic losses due to clinical mastitis in crossbred cows in the Ahmednagar district. The study mainly focused on clinical mastitis and reproductive disorders such as calving abnormalities, uterine health problems and fertility problems. The calving abnormalities comprised of abortion and dystocia; uterine health problems included retention of foetal membrane, metritis and prolapse, while fertility problems comprised of repeat breeding and anestrus. The number of cases of clinical mastitis, abortion, dystocia, retention of fetal membrane (RFM), metritis, prolapse, repeat breeding and anestrus were 472, 126, 50, 98, 110, 18, 240 and 130, respectively. The corresponding figures for incidence rate were 23.55, 5.81, 2.3, 4.52, 5.07, 0.83, 11.07 and 6.00, respectively. The highest incidence rate of clinical mastitis was 28.34 per cent during the rainy season. Late stage of lactation and high milk producing animals exhibited higher incidence rate of 26.54 and 28.48 per cent, respectively. Per animal treatment cost due to clinical mastitis turned out to be ` 1443.09 however the total cost including production cost (` 904.0) during the clinical mastitis was ` 2348.86. The average total loss due to abortion was highest i.e., ` 2271.73 during rainy season. The maximum total loss of ` 2438.65 was observed in 4th parity due to dystocia. The highest total loss and treatment cost of ` 606.00 and ` 562.03, respectively was noted in high milk producing cows in RFM. The highest average total loss of ` 1423.28 was observed in very low milk producing cows in repeat breeding. Level of production showed a positive, while parity for the occurrence of abortion exhibited a negative association at significance level (P≤0.01). Parity had negative and significant (P≤0.01) effect on probability of occurrence of RFM. The probability of occurrence of metritis was negatively associated with parity, while it was positively associated with level of production. Season had positive and parity had negative association with occurrence of anestrus at significance level (P≤0.01). The projected economic losses due to clinical mastitis in Ahmednagar district and in Maharashtra state was ` 14.19 crore and ` 49.03 crore, respectively. It was concluded from the present study that non-genetic factors such as rainy season, multiparty, late stage of lactation and very high milk producing cows are predisposing factors for more occurrence of clinical mastitis in Phule Triveni crossbred cows, so more emphasis should be given to managemental practices followed at farm as well as field level. Treatment cost is the main component of economic losses due to clinical mastitis, so early diagnosis of clinical mastitis will prevent the extent of economic losses by proper selection of antibiotics. Many of the reproductive disorders, such as dystocia, prolapse, metritis and repeat breeding showed maximum total economic losses in summer season. It is concluded that summer season requires more care of animals to manage stress level of animals due to hot climatic conditions and prevent the chances of incidence of reproductive disorders.ThesisItem Open Access ECONOMIC ANALYSIS OF DAIRY FARMER COLLECTIVES IN SAURASHTRA AND KUTCH REGION OF GUJARAT(ICAR-NDRI, KARNAL, 2021) UDITA CHAUDHARY; MALHOTRA, R.The study titled “Economic Analysis of Dairy Farmer Collectives in Saurashtra and Kutch Region of Gujarat” is undertaken to assess the determinants and impacts of membership of dairy farmer collective organizations, namely, dairy cooperative and milk producer company, and to evaluate their comparative financial performance. Gujarat is purposely selected for the work, as it has well-established cooperatives (under the Gujarat Cooperative Milk Marketing Federation Ltd. or GCMMF/AMUL) as well as milk producer company (Maahi Milk Producer Company Ltd. or MPPCL), and being the pioneer state of the Operation Flood Programme, it also has a progressive dairy setup with well-aware dairy farmer producers. Primary data collected from 416 dairy farming households encompassing 127 members of a member cooperative union of GCMMF, 119 members of Maahi, and 170 non-members, were used to calculate cost and returns in milk production for members as well as for the non-members, and to evaluate determinants and impacts of membership of the farmer collective organizations. Tabular analysis, standard cost and return estimation formulae, Probit regression and Propensity Score Matching (PSM) techniques were applied for the purpose. Secondary data from six years’ financial statements of Maahi and the cooperative union were compiled from their annual reports to calculate relevant financial ratios to assess their financial performance. The results reveal that collectivization is especially profitable for the members with small (1-3 Standard Animal Units or SAU) and medium (3-6 SAUs) herd size with net return of ` 8/- and ` 14/- per litre, as opposed to ` 7/- and ` 9/- per litre for the nonmembers of the same categories, respectively. Variables of age, size of household, and access to govt. schemes (MGNREGA, BPL) are negatively and significantly associated with probability of membership of a dairy farmer collective, while livestock as main source of income, access to mass media, marketed surplus (of milk) and contact with extension have positive and significant effect on their membership. The main determinants of membership of a cooperative are social group that the farming household belongs to, distance from main market, access to govt. schemes and contact with extension and input supply. Annual income of a household has a negative and significant effect while size of landholding has a positive and significant effect on cooperative membership. In case of membership of producer company, apart from the important variables cited above, income of a household has a positive and significant effect while size of landholding has a negative and significant effect. The evaluation of impacts of membership reveals that the local cow labour cost, total labour cost, local cow feed cost, total feed cost, local cow total variable cost and the overall total variable cost decrease by 29 per cent, 14 per cent, 25 per cent, 9 per cent, 20 per cent, and 8 per cent, respectively, for the members. The cost per litre for local cow decreases by 16 per cent for the members. For the members of farmer collectives, the annual net returns from local cow and buffalo increase by ` 3714/- and ` 6430/-, respectively. The overall net returns from dairy exhibit an increase of ` 10,143/-. The share of dairy in income increases by 14 per cent and the share of milk sold increases by 1.4 per cent for the members. There are no significant effects of membership on buffalo milk production and on quantity of milk produced. The comparison of financial ratios of the two farmer collectives shows that Maahi MPC exhibits better liquidity compared to the cooperative union. The union is more leveraged than Maahi, which means it has more debt than equity, and this difference in terms of indebtedness is highly significant. In profitability, the rate of return to equity after taxes ratio, and the rate of total capital employed before interest and taxes ratio, both differ significantly for the two farmer collectives.ThesisItem Open Access VULNERABILITY OF RURAL HOUSEHOLDS TO DROUGHT AND ITS MANAGEMENT STRATEGIES IN TAMIL NADU(ICAR-NDRI, KARNAL, 2020) BALAGANESH G; MALHOTRA, RAVINDERDrought has become a major problem globally affecting crop and dairy production. In India, Tamil Nadu is one of the states most vulnerable to drought impacting agriculture and allied activities. In the milieu, the research entitled “Vulnerability of rural households to drought and its management strategies in Tamil Nadu” has been undertaken with the specific objectives “(1) to assess the district level composite vulnerability to drought in Tamil Nadu, (2) to examine the vulnerability status of rural farm households in drought prone areas, (3) to find out the extent of adoption and determinants of drought management strategies and (4) to analyse the effect of management strategy on crop and dairy output and constraints faced by farmers”. The first objective was aimed to develop a new composite drought vulnerability index (CDVI) comprising of both crop and dairy indicators for 30 districts of Tamil Nadu based on the Intergovernmental Panel on Climate Change (IPCC) approach using exposure, sensitivity and adaptive capacity. Secondary data have been used here. The districts were classified as high, moderate and less vulnerable on the basis of magnitude of the index. The CDVI was highest in Kanchipuram (0.88), lowest in Erode (0.45) and moderate in Thanjavur (0.73). Vulnerability mapping showed 12, 8 and 10 districts as high, moderate and less drought vulnerable. Geographically, districts in north eastern and southern zones were highly vulnerable. No district had higher adaptive capacity than sensitivity and exposure put together. Post estimation analysis of CDVI showed that shares of gross sown area (37.13%) and bovine population (43.47%) were highest in high vulnerable category districts. The second objective was attempted to compute new household drought vulnerability index (HDVI) using exposure, sensitivity and adaptive capacity indices having both crop and dairy indicators for 300 rural farm households of Tamil Nadu. Both primary data (agricultural year 2017-18) and secondary data were used in the analysis. By using CDVI, three districts were randomly selected among 30 districts of Tamil Nadu for this study, i.e., Ramanathapuram, Nagapattinam and Erode from high, moderate and less vulnerable category, respectively. From each district, two blocks were chosen randomly and from each block, a cluster of villages were chosen randomly. From each cluster of villages, 50 rural households comprising both paddy crop and dairy were chosen randomly. Thus, from each selected district 100 farm households were chosen which added up to a sample of 300 households from the whole state. The results of HDVI revealed that about 117 (39%), 69 (23%) and 114 (38%) households were categorized as high, moderate and less vulnerable to drought, respectively. The district wise mean value of HDVI was highest in Ramanathapuram (0.86), followed by Nagapattinam (0.60), while it was lowest in Erode (0.34). The vulnerability mapping also showed that more households in Ramanathapuram (82%) were high vulnerable to drought, whereas more households in Erode (84%) were less vulnerable. This may be due to high exposure and sensitivity along with low adaptive capacity in Ramanathapuram, whereas Erode has high adaptive capacity coupled with low exposure and sensitivity. The third objective has analyzed extent of adoption and determinants of drought management strategies. There were 6, 7 and 5 paddy drought management strategies identified in Ramanathapuram, Nagapattinam and Erode, respectively, whereas 6 dairy management strategies were indentified in each district. Among district wise overall mean value of intensity of adoption, the highest value was observed in Erode (0.52), followed by Ramanathapuram (0.51) and Nagapattinam (0.44). Age, education, farm size, herd size, number of family members employed in farming and dairying, access to credit, membership in organizations and extension contact were some of the important socio-economic variables, which influenced probability and intensity of adoption in different districts. The final objective has analyzed the effect of management strategy on crop and dairy output and constraints faced by farmers. In case of paddy crop, seed drill sowing, direct (line) sowing and System of Rice Intensification (SRI) method were the most important drought management strategies in Ramanathapuram, Nagapattinam and Erode, respectively. In case of dairy, mineral mixture supplementation was the most vital management strategy in all the districts. Change in income was mainly due to technological change, followed by change in inputs, except seed drill sowing of Ramanathapuram. Efficient use of inputs leads to increase gross income and reduce costs in both paddy and dairy farming. Lack of adequate irrigation facilities during drought and decline in product sale price were major constraints in paddy, whereas lack of availability of feed and fodder was major constraint in dairy. To mitigate drought vulnerability, government could focus and aid in developing regional level adaptation strategies such as direct sowing and water conserving techniques/ farm pond in both high and moderate vulnerable districts, whereas SRI in low and moderate districts as well as mineral mixture supplementation to dairy animals in all vulnerable districts. Vulnerability can also be reduced by increasing irrigation sources, crop diversification and livestock rearing.
