PRODUCTION AND MARKETING OF MILK IN BUDALUR BLOCK OF THANJAVUR DISTRICT OF TAMILNADU
Thesis submitted to the Bharathidasan University for the award of the Degree of DOCTOR OF PHILOSOPHY IN ECONOMICS
By P. JAYAKUMAR (Ref. No. 004940/Ph.D.2/Eco/PT/July 2007)
Under the Guidance of Dr. D. KUMAR, M.A., M.Phil., B.Ed., DPMIR., Ph.D., M.B.A.,
P.G. AND RESEARCH DEPARTMENT OF ECONOMICS JAMAL MOHAMED COLLEGE (AUTONOMOUS) (Re-Accredited at ‘A’ Grade by NAAC – CGPA 3.6 out of 4.0) TIRUCHIRAPPALLI – 620 020 TAMIL NADU, INDIA.
DECEMBER – 2010
PG & RESEARCH DEPARTMENT OF ECONOMICS JAMAL MOHAMED COLLEGE (AUTONOMOUS) THIRUCHIRAPPALLI - 620 020
Dr. D. KUMAR Office : 0431 - 2331235 Reader in Economics & Research Advisor, Resi : 0431-2455757 Mobile:9443470242 Email : [email protected] [email protected]
CERTIFICATE
This is to certify that the thesis entitled “PRODUCTION AND MARKETING OF MILK IN BUDALUR BLOCK OF THANJAVUR DISTRICT OF TAMILNADU” SUBMITTED BY P. JAYAKUMAR (Ref No. 004940 / Ph.D.2/ Eco / PT / July’2007) is a bonafide record of research work done by him under my guidance in the Department of Economics, Jamal Mohamed College, Thiruchirappalli and that the thesis has not previously formed the basis for the award to the candidate of any degree or any other similar title. The thesis is the outcome of personal research work done by the candidate under my overall supervision.
(D. KUMAR)
Date : Station:
DECLARATION
I hereby declare that the work embodied in this thesis has been originally carried out by me under the guidance and supervision of Dr. D. Kumar, Reader in
Economics & Research Advisor, Department of Economics, Jamal Mohamed College,
Thiruchirappalli-620020. This work has not been submitted either in whole or in part for any other degree or diploma at any university.
(P. JAYAKUMAR)
ACKNOWLEDGEMENT
At the outset, I wish to express my heartfelt gratitude to Dr. D. Kumar, M.A., M.Phil., B.Ed., DPMIR., Ph.D., M.B.A., Department of Economics Jamal Mohamed College Tiruchirappalli, for his expertise guidance and invaluable help throughout the study. Mere words would not be sufficient to explain his greatness in giving encouragement, advice and helping hand to me in the completion of this research. It is a great pleasure and excellent experience to work under his guidance. I am thankful to Dr. M. Sheik Mohamed, M.Com., M.Phil., Ph.D., principal and the secretary, management committee for having granted permission to do Ph.D. (Part-Time) programme in Jamal Mohamed College, Tiruchirappalli-620 020. I also extend my sincere gratitude to Dr. P.N.P. Mohamed Sahaputheen, M.A., M.Phil., Ph.D., Reader and Head of Department of Economics, Jamal Mohamed College, Tiruchirappalli, and all the Faculty members, Department of Economics, Jamal Mohamed College Tiruchirappalli for their timely help and moral support. I express my sincere thanks to Dr. K. Shanmugavadivel, M.Sc., M.Phil., Ph.D., Reader in the Department of Statistics, St. Joseph College, Tiruchirappalli I am extremely thankful to Dr. Gnanasekaran, M.A, M.Phil., Ph.D., Reader and Head of Department of Economics St. Joseph’s College, Tirchirappalli and Dr. P. Stanly Joseph Micheal Raj, M.A., M.Phil., Ph.D., Reader in the Department of Economics St. Joseph’s College, Tirchirappalli for their valuable suggestions. I am indeed very much thankful to Mrs. K. Senthil Selvi, M.Sc., M.Phil., Assistant Professor, Department of Computer Science, EVR College (Autonomous), Tiruchirappalli for her constant encouragement. I cannot forget the support and help rendered by my colleagues Dr. T. Sudakar, Dr. George Clement, Dr. B. Mohamed Rafeeq, Research scholars of the Department of Economics, Jamal Mohamed College, Tiruchirappalli.
My sincere thanks to Dr. V.R. Mathiazhagan, Reader in Economics, National College (Autonomous), Tiruchirappalli. I am thankful to the Librarian and staff members of the libraries of Bharathidasan University, Tiruchirappalli, Jamal Mohamed College, Tiruchirappalli and St. Joseph’s College, Tiruchirappalli. I am thankful to Dr. Durairajan, Librarian of St. Josephs College, Tirchirappalli, Madras Institute of Development Studies, Madras, and Tamil Nadu Veterinary University, Tamil Nadu Agriculture University and M.S. Swaminathan Research Foundation, Madras. No word would suffice to express my deep gratitude to Mr. D. Thomas, M.A., P.G.D.T.E., Lecturer (S.G.) in English (Rtd.), St. Joseph’s College, Tiruchirappalli, for his kindly help in correcting the proof of this report and for giving valuable suggestions for the successful completion of this work. I am indebted to all the respondents, Avin Milk Co-Operative Society in Thanjavur, for helping me and co-operating with me in collecting the necessary data available for the research. I am also thankful to all the officials in the Directorate of Animal Husbandry, Department of Statistics Thanjavur, Agriculture, Revenue etc., for providing me with important secondary data for this research. I express my gratitude to veterinary dispensary in Thirukkattuppalli, Budalur and Sengipatti for giving me sufficient information regarding the research. I am indeed duty bound to express my sincere thanks to my beloved sister P. Annamary for being the foundation to my educational process. I also would like to express my genuine thanks to my beloved wife J. Ruba and my cheerful son J. Joshan Kingsley for their constant encouragement. Last but not the least, I owe a great deal to my beloved Grand father, Parents, Sisters and Brother for their self less and constant help. And I express my heartfelt thanks to all the members and friends for their valuable help. Finally I thank M/s. Golden Net Computers, Tiruchirappalli for their whole hearted cooperation and neat finish of the thesis. P. Jayakumar CONTENTS
Chapter Page Title No. No.
Certificate
Declaration
Acknowledgement
List of Tables
List of Diagrams
1.1 Introduction 1
1.2 Need for the Study 2
1.3 Research gap 3
1.4 Motivation for the study 4
1.5 Statement of the Problem 4
1.6 Research questions 6
1.7 Objectives 6
1.8 Hypotheses 6
1.9 Theoretical framework for the Study 6
1.10 Limitations of the study 11
1.11 Plan of the study 12
II Review of Literature 13
2.1 Review of literature related to characteristics of the milk 13 producers
2.2 Review of literature related to the cost and productivity in the 26 milk production 2.3 Review of literature related to channels of marketing 46
2.4 Review of Literature related to constraints in milk production 57 and marketing
III Profile of the study area and Methods and Materials 69
3.1 Profile of the Study area 69
3.2 Definition and concepts 85
3.3 Definitions of various categories of incomes 87
3.4 Data base and period of the study 88
3.5 Sampling design 88
3.6 Statistical tools used 91
IV Analysis of the characteristics of the milk producers in 92 Budalur block
4.1 Analysis of characteristics of the respondents 92
4.2 Analysis of the standard of living of milk producers in the study 112 area.
4.3 Analysis of the bovine population and ownership of the 123 respondents in the study area
V Analysis of factors determining milk production income 132
VI Analysis of the cost and productivity of milk production in 150 the study area.
6.1 Analysis of the cost of milk production in the study area 150
6.2 Analysis of the productivity of the bovine in the study area 160
VII Analysis of the various channels of marketing and problems 175 of milk production in the study area.
7.1 Analysis of the various channels of marketing of milk 175 production in the study area
7.2 Analysis of the constraints experienced by the milk producers in 179 the study area
VIII Findings, Suggestions and Conclusion 189
8.1 Major Findings of the Study 189
8.2 Suggestions 194
8.3 Conclusion 195
8.4 Area for the further research 196
Bibliography B1
Appendix – I A1 Trends in Milk Production in Tamil Nadu District wise milk production in Tamil Nadu in 2007-08 Bovine Population in Tamil Nadu Sampling Selection Budalur Block Population Veterinary Dispensary and Hospitals
Appendix – II A11 Interview Schedule
Appendix – III A22 Photo Plates
Appendix – IV A30 Papers Published
LIST OF TABLES
Table Page Title No. No. 3.1 Land use pattern 72 3.2 Demographic data 73 3.3 SC / ST, OBC and minorities 74 3.4 Work Force 74 3.5 Total worker classification 74 3.6 Animal Husbandry 77 3.7 Budalur block at a glance 79 3.8 Area and Population 80 3.9 Literacy rate 80 3.10 Workers details 80 3.11 Bovine details of the study area 81 4.1.1 Religion wise distribution of the respondents 93 4.1.2 Community wise distribution of the respondents 93 4.1.3 Sex wise distribution of the respondents 95 4.1.4 Age wise distribution of the respondents 95 4.1.5 Education wise distribution of the respondents 96 4.1.6 Area wise house distribution of the respondents 98 4.1.7 Area wise family expenditure distribution of the respondents 100 4.1.8 Area wise saving pattern of the respondents 103 4.1.9 Area wise investment pattern of the respondents 106 4.1.9.1 ANOVA 108 4.1.9.2 Area wise comparison of investment in bovine population 109 4.1.10 Borrowing status of the respondents 109 4.1.11 Sources of borrowing 110 4.2.1 Standard of living of the respondents 113 4.2.2 Area wise standard of living of the respondents 113 4.2.3 Correlation between type of land and standard of living 115 4.2.4 Bovine Population wise standard of living of the respondents 116 4.2.5 Sex wise standard of living of the respondents 117 4.2.6 Age wise standard of the living of the respondents 118 4.2.7 Marital status wise standard of living of the respondents 119 4.2.8 Religion wise standard of living of the respondents 120 4.2.9 Community wise standard of living of the respondents 121 4.2.10 Education wise standard of living of the respondents 122 4.3.1 Bovine possessed by the respondents 124 4.3.2 Area and bovine population wise distribution of the respondents 125 4.3.3 Bovine population number wise distribution of the respondents in 127 Thirukkattuppalli area 4.3.4 Bovine population number wise distribution of the respondents in 128 Budalur area 4.3.5 Bovine population number wise distribution of the respondents in 129 Sengipatti area 4.3.6 Bovine population number wise distribution of the respondents 130 4.3.7 Area wise bovine population shelter distribution of the respondents 131 5.1 Income received from bovine population 132 5.2 Income comparison of the respondents 133 5.3 Sex wise income distribution of the respondents 135 5.4 Area wise income distribution of the respondents 136 5.5 Area wise income comparison of the respondents 139 5.6 Area and bovine population wise income distribution of the 140 respondents 5.7 Area and education wise income status of the respondents 142 5.8 Area wise average total income of the respondent 144 5.9 Education wise average total income of the respondents 145 5.10 Bovine population wise average total income from milk production 146 5.11 Area wise total income from milk production 148 6.1.1 Feed cost of indigenous cow in the study area 150 6.1.2 Feed cost of cross breed cow in the study area 151 6.1.3 Feed cost of buffalo in the study area 151 6.1.4 Labour cost of indigenous cow in the study area 152 6.1.5 Labour cost of cross breed cow in the study area 152 6.1.6 Labour cost of buffalo in the study area 153 6.1.7 Health cost of indigenous cow in the study area 153 6.1.8 Health cost of cross breed cow in the study area 154 6.1.9 Health cost of buffalo in the study area 154 6.1.10 Area wise employment details of men 155 6.1.11 Area wise wage and employment status 158 6.2.1 Area wise indigenous cow feed intake 161 6.2.2 Area wise cross breed cow feed intake 163 6.2.3 Area wise buffalo feed intake 165 6.2.4 Area wise milk yield per day by type of bovine population 167 6.2.5 Regression analysis for indigenous cow milk yield on feed intake 168 6.2.6 Regression analysis for cross breed cow milk yield on feed intake 169 6.2.7 Regression analysis for buffalo milk yield on feed intake 169 6.2.8 Milk lactation period of the indigenous cow 170 6.2.9 Calving interval period of the indigenous cow 171 6.2.10 Milk lactation period of crossbreed cow 173 6.2.11 Calving interval period of cross breed cow 173 6.2.12 Milk lactation length of buffalo 174 6.2.13 Calving interval period of the buffalo 174 7.1.1 Marketing channels 175 7.1.2 Average milk price 178 7.2.1 Common land using for bovine population 179 7.2.2 Doctors attended the respondents’ place 180 7.2.3 Distance between respondents’ house and the veterinary dispensary 182 7.2.4 Expectation of milk price by the respondents 184 7.2.5 Problems faced by the respondents 186 7.2.6 Cattle insurance taken by the respondents 188
LIST OF DIAGRAMS
Diagram Page Title No. No.
4.1.1 Community wise distribution of the respondents 94
4.1.2 Education wise distribution of the respondents 97
4.1.3 Area wise house distribution of the respondents 99
4.1.4 Area wise saving pattern of the respondents 105
4.1.5 Sources of borrowing 111
4.2.1 Area wise standard of living of the respondents 114
4.3.1 Area and bovine population wise distribution of the respondents 126
5.1 Income comparison of the respondents 134
5.2 Area wise income distribution of the respondents 138
5.3 Bovine population wise total income from milk production 147
6.1.1 Area wise employment details of men 156
6.1.2 Area wise wage and employment status 159
6.2.1 Area wise indigenous cow feed intake 162
6.2.2 Area wise cross breed cow feed intake 164
6.2.3 Area wise buffalo feed intake 166
6.2.4 Calving interval period of the indigenous cow 172
7.1.1 Marketing channels 177
7.2.1 Doctors Attended The Respondents’ Place 181
7.2.2 Distance between respondents’ house and the veterinary dispensary 183
7.2.3 Expectation of milk price by the respondents 185
7.2.4 Problems faced by the respondents 187
Chapter - I
Introduction 1
CHAPTER – I INTRODUCTION
Dairying provides livelihood to millions of Indian farmers and generates additional income and employment for a large number of families in the countryside. Dairy industry is the single largest contributor to India’s GDP and with its profound social impact, involves over 80 million small farming households. However, India with about18.36 per cent of the world’s total cattle and buffalo population accounts for only about 14.5 per cent of the world’s total milk production. Our livestock are roughly half as efficient as the average milk animals in the world and probably only one-fifth as efficient as those in the advanced countries. Although milk production in India has shown a rising trend ever since the inception of ‘Operation Flood (OF)’ programme in 1970-71, the Indian dairy industry acquired substantial growth from eighth plan onwards with rise in milk production from 58 million tonnes in 1992-93 to 108.5 million tonnes in 2008-09. This has not only placed Indian dairy industry on top of the world but also led to sustained growth in the availability of milk and milk products for the burgeoning population of the country. India has acquired the position of the largest producer of milk in the world despite constraints like rearing of livestock under sub optimal conditions due to low economic status of dairy owners. The development of Indian dairy sector is an unprecedented success story as it is based on millions of small producers. The subsidies provided by the developed countries to their dairy farmers have helped them to lower the prices of dairy products, affecting in turn, the farming community in the developing world. Traders are now free to import milk products and thereby earn high profits at the expense of farmers belonging to developing countries like India. India has attained the first rank in milk production in the world. The first five countries in the world producing maximum milk are India, USA, Russia, Germany and France. India has produced 13.1 per cent of the total milk produced in the world. To maintain our first position in milk production, India will have to face healthy competition from other countries. For this, only producing largest quantity is not sufficient, but the quality of milk and other factors also need to be borne in mind, the 2
"operation flood" programme will have to be supported by quality improvement and quality maintenance. Dairying has brought about socio-economic transformation in Tamil Nadu and is playing a significant role in strengthening rural economy. Majority of milk producers are small farmers, marginal farmers and downtrodden. Dairying has vast potential to generate employment and has helped in alleviating poverty in rural belt. Dairying provides definite and regular income and employment to millions of rural families throughout the year, improving the quality of their life. The milk producers in the Co-operative sector collectively on an average get daily income of Rs.262 lakh (Rs.95, 630 lakh annually) for the milk they supply to the dairy societies which show the importance of this sector in the rural economy. Tamil Nadu is one of the front line states in milk production and stands at number one position in the coverage of more than 50 per cent of revenue villages under Co-operative ambit. There are 7833 functional primary milk societies with 22.10 lakh members. During 2007-08 average milk procurement by Dairy Co-operative was 26.27 lakh litres per day (LLPD). Dairying and agriculture are bound together by a set of mutual input- output relationships. Dairying is not an adjunct to the crop-mix of Indian farms, but an integral part of the total farming system. Hence, treating dairy cattle as the backbone of the livestock wealth of our country would not be an exaggeration. Though the dairy industry in India has undergone considerable transformation over the years and is considered the secondary source of income for millions of rural households, in terms of per capita consumption of milk, India still compares poorly among the nations of the world. Therefore in view of ensuring food security, livelihood security and rural development, the Indian dairy sector is a strategic one.
1.2. Need for the study The need for promotion of dairying in India arises due to several considerations such as low per capital availability of milk prevalence of large scale unemployment and under employment discouraging mixed farming for further utilization of farm products and wastages and increasing the living condition of rural poor, achieving self-sufficiency in the production of milk, milk products and save valuable foreign 3
exchange. In the ultimate analysis, the need for dairy development in India arises due to various main reasons which stand out prominently as supply of adequate quantity of milk at reasonable price to urban consumers, lack of marketing facilities and extension services. There is poor perception of the farmers towards commercial dairy enterprise as an alternative to other occupations. Owing to lack of proper veterinary extension system there is poor perception to the farmers towards dairy enterprise as a viable alternative to crop husbandry. An equally important sector is dairy, which needs some support. A majority of the small farmers in India, who do not have good land for agriculture, depend on dairy for supplementary income. Therefore, promotion of dairy sector with cattle and buffalo can generate employment for small farmers throughout the year. Fortunately, India has the largest population of livestock in the world and with the increasing demand for livestock produce, while in 2008-09 the milk production was 108.5 million tonnes, the demand in the year 2022 is likely to rise to 180 million tonnes. This will provide greater opportunity to small farmers to expand their dairy sector. The dairy sector in its potential, is making impact on the dairy economy, and recommends areas to be encouraged more for research work where it is highly needed. Changes in animal management and animal feeding practices, especially by small dairy farmers, can be instrumental in raising milk yields in the short run. The attempts to enhance production of smallholder dairying are not only important for raising milk yield in the country; they could also become an effective tool of raising incomes of impoverished rural households. Dairy sector is giving self-employment and generating income and livelihood of the rural people therefore, there is a need to improve the production and marketing structure in dairy sector.
1.3. Research gap The present study covers the production and marketing of milk in the Budalur Block. So far no research has been conducted in the block, particularly in milk production. Studies have been undertaken to analyse the function of co-operative societies but the unorganized sectors were not taken for any other study. Therefore the milk produced by the people in the Block is not accounted for. So the milk that is produced by the producers in that area is being marketed to the household, tea stalls and the milk vendors are not accounted for. 4
1.4. Motivation for the study The dairy sectors have made a visible impact on nutritional security and have set models to be emulated by other sectors of agriculture. Dairying, which makes up over 65 per cent of the livestock sector as a whole in value terms, has particularly grown remarkable in onward linkages for collection, processing, marketing. Dairying is part of agriculture, it is far more profitable than any other part of agriculture. In fact, it is more prosperous to be a dairy farmer instead of just being an agriculturist. The cow eats what is wasted in the field and converts the same as a value added product in the form of milk. Today milk commands better advantage when compared to any other agricultural crop. One of the most effective instruments for supplementing farmers’ income and generating employment in the rural sector is dairying. Dairy animals, apart from their role in milk supply, contribute huge quantity of organic manure, which is one of the major inputs in our agriculture. Dairy farming is also a very important subsidiary occupation. It provides employment to millions of unemployed and under-employed and particularly small farmers and landless labourers. The proponents of the dairy development programme feel that such activity does indeed raise the level of income of the rural poor. In India more than 80 per cent of milk produced in the country in fact comes from small holding and landless farmers. This sector provides additional income and generates job opportunities for 80 million farmer families. In this context this research work has been undertaken to study the production and marketing of milk in Budalur block of Thanjavur district in Tamilnadu.
1.5. Statement of the problem India is the largest milk producer in the world. The milk production of this country has increased from 17 million tonnes in 1950-51 to 108.5 million tonnes in 2008-09 and the per capita availability of milk has also increased from 112 grams / day in 1968-69 to 258 grams / day during 2008-2009. But still it is low compared to the world average of 265 grams/day. About 80 per cent of the milk produced in the country is handled in the unorganized sector and the remaining 20 per cent is shared equally by cooperative and private dairies. The productivity of the animal is also low 5
when compared to the world countries. This deficit which is of a very serious nature may affect the health and vitality of the nation, as milk is the only source of animal protein for a large number of people in this country. To meet the nutritional requirements of the people, there is an urgent need to boost milk production. Low productivity has been a major problem of Indian dairying for a long time. It is important to know what policies, and what steps need to be taken for productivity enhancement before investing scarce capital in certain factors which affect productivity. In Tamil Nadu, the production of milk is low compared to the other states. The milk production has increased from 4752 thousand tonnes in 2003-04 to 5586 thousand tonnes in 2007-08. The per capita availability of milk has also increased from 209 grams/day in 2003-04 to 233 grams/day in 2007-08. In Thanjavur district the milk production was low and not impressive (196.748 thousand tones) in 2007-08 compared to Salem (450.613), Villupuram (334.215) and Coimbatore (333.225) districts. This deficit is due to the cross-breeds is cow in this district and buffalo milk production was also low. The disparity in dairy sector persists with respect to other indicators of dairy development, such as, proportion of crossbreed population, breeding, feeding and marketing facilities for dairy as well. The growth of milk production is important not merely to improve milk availability, but for improving the livelihood status for the bulk of rural poor in this state. The balanced growth in dairy sector apart from the other factors is also influenced by the Government expenditures and regulations in the sector. The main objective of dairy development is to improve the milch cattle, to provide remunerative price to milk, improvement of the socio-economic conditions of the milk producers, to maintain an effective supply system of the milk and milk products at reasonable price for the consumers. In this context this investigation aims to study the production and marketing of milk in Budalur Block of Thanjavur district and know the problems encountered in the dairy sector on productivity, finance, marketing, feeding, infrastructure, and other problems. 6
1.6. Research questions 1. What are the characteristics of milk producers in the study area? 2. What is the cost and profitability of milk production in the study area? 3. What are the channels of marketing adopted by the milk producers in the study area? 4. What are the problems faced by the milk producers in study area?
1.7. Objectives The overall objectives of the present study are to investigate the “Production and Marketing of Milk in Budalur Block of Thanjavur District of Tamilnadu”. With this view in mind the following specific objectives are framed. Ø To study the characteristics of the milk producers in the study area. Ø To estimate the cost and productivity of milk production in the study area. Ø To examine the various channels of marketing adopted by the milk Producers Ø To examine constraints experienced by the milk producers in production and marketing and Ø To suggest appropriate measures to strengthen the milk production and marketing in the study area.
1.8. Hypotheses 1. There is a insignificance relationship between education level and standard of living of the milk rearers in the study area. 2. There is a positive relationship between feed intake of milch animal and milk yield.
1.9. Theoretical framework for the study Milk production is predominantly the domain of small holder in a mixed farming system. The milk production in India has increased from 17 million tonnes in 1950-50 to 108.5 million tonnes in 2008-2009. Dairy development in India started from marketing end. Efforts were taken to increase production also. In fact, the Anand cooperative society with its own encouragement to milk producing members in 7
the form of compounded feed, artificial insemination for breed improvement, health care and insurance together with the training of rural producers, helped the members to reap the socio-economic benefits from such a world in the largest rural dairy development programme popularly known as “Operation flood”.
Operation Flood, a programme that Dr. Verghese Kurien implemented as chairman of the National dairy Development Board in three phases over a 26-year span, created a flood of milk, which eventually led to India becoming the world's largest milk producer, overtaking the US in 1998. Dr. Kurien made innovative use of a World Bank loan, EEC food aid and the internal resources of NDDB to usher in the White Revolution.
Operation Flood: Phase one was during the 1970's. Dairy products were piling up as a major surplus in Europe, a phenomenon in which Dr. Kurien saw both a threat and an opportunity. In the event of these surpluses being dumped in India at rock bottom prices, it would have prematurely destroyed the fledgling dairy sector of the country. The large quantities that India was already importing had eroded domestic markets to the point where dairying was not viable. Kurien ingeniously turned this double-edged sword to his advantage and incorporated it as a golden opportunity into the Operation Flood strategy. It was for the first time in the history of economic development that food aid was seen as an important investment resource. Working as an anti-inflationary measure, it provided a buffer stock to stabilise the Indian market, and was used to prime markets that would later be supplied by domestic production. Funds generated through sale of these commodities were used in the development of 18 rural milk sheds in 10 states and for setting up dairies in the rural hinterlands and in Mumbai, Delhi, Kolkata and Chennai. This led to a 60-per cent increase in milk production, which rose from an estimated 20-million metric tonnes in 1970 to 32 million metric tonnes in 1978. A year-round remunerative market for the milk producers was created and the sale of milk in the major urban demand centers rose by 140 per cent. During this phase, Operation Flood linked 18 of India's premier milk sheds with consumers in India's four major metropolitan cities: Delhi, Mumbai, Kolkata and Chennai. 8
Operation Flood: Phase two, impressed by the success of the first phase of the project, the government of India decided to continue with dairy development through cooperatives but on a greatly expanded scale. The second phase of the programme was implemented with a World Bank credit of $150 million and commodity assistance from EEC (216,584 metric tonnes of SMP, 62, 402 metric tonnes of butter oil and 16577 metric tonnes of butter) and Rs.280.87 crore which NDDB raised out of its own resources during 1985 to 1987.
The third phase of Operation Flood, undertaken from 1987 to 1996 aimed at consolidating the gains of the earlier phases. The main focus of the programme was on achieving financial viability of the milk unions/ state federations and adopting the salient institutional characteristics of the Amul Pattern or Amul Model Cooperatives. This phase of the programme was funded by a World Bank credit of $365 million, Rs.222.6 crore of food-aid (75,000 metric tonnes of milk powder and 25,000 metric tonnes of butter / butter oil) by the EEC and Rs.207.6 crore by NDDB's own resources. At the end of May 1995, Rs.1, 578 crore had been invested under the three phases of Operation Flood programme. At the conclusion of the third phase of Operation Flood three in 1996, 72,744 district cooperative societies in 170 milk sheds of the country, with a total membership of 93.14 lakh had been organised. The targets set had either been effectively achieved or exceeded.
Phase three (1985-1996) enabled dairy cooperatives to expand and strengthen the infrastructure required to procure and market increasing volumes of milk. Veterinary first-aid health care services, feed and artificial insemination services for cooperative members were extended, along with intensified member education. Operation Flood Phase three consolidated India's dairy cooperative movement, adding 30,000 new dairy cooperatives to the 42,000 existing societies organised during Phase two. Milk sheds peaked to 173 in 1988-89 with the number of women members and 'women's dairy cooperative societies' increasing significantly. Phase three gave increased emphasis to research and development in animal health and animal nutrition. Innovations like vaccine for Theileriosis, bypass protein feed and urea- molasses mineral blocks, all contributed to the enhanced productivity of milk animals. Phase three of Operation Flood (1985-1996) enabled dairy cooperatives to rapidly 9
build up the basic infrastructure required to procure and market more and more milk daily. Facilities were created by the cooperatives to provide better veterinary first-aid health care services to their producer members. The farmer owned Amul cooperative in Anand (in Kaira district, Gujarat) was a milestone in the dairy scene because of its integrated approach for production procurement processing and marketing of milk through co-operatives. As this pattern was considered a model for dairy development, the current government has taken steps to replicate Anand pattern throughout our country as a result the NDDB (National Dairy Development Board) was established in 1965 to transplant the spirit of Anand pattern organizations in many other places of India. Then the NDDB started a project called “Operation Flood” during the period 1970-1996 and its aim was the creation of flood of milk in our villages with funds got from foreign food donations. Producers’ co-operatives were the central plant of the project which sought to link dairy development with milk marketing. The Anand model co-operatives bring the producers in direct contact with consumers eliminating the middleman. A major programme for genetic improvement, the National Project for Cattle and Buffalo Breeding (NPCBB), was launched in October 2000 to be implemented over a period of 10 years in two phases of five years each with an allocation of Rs. 402 crore and 775.9 crore for phase I phase II respectively. NPCBB envisages genetic upgradation and development of indigenous breeds on priority basis. At present, 28 states and one union territory are participating in the project. Financial assistance to the tune of Rs.398.38 crore was released to these states up to 2007-08. During the financial year 2008-09 Rs.87.37 crore has been released for the implementing agencies under the scheme. NDDB’s biotechnology laboratory has been a pioneer in animal breeding and genetics, nutrition and feed technology and animal health. The strategy is to upgrade cattle breeds through the integration of artificial insemination. NDDB is supporting ongoing studies to identify mineral deficiencies specific to local areas so that the feed can be supplemented with appropriate minerals. An NDDB initiated fodder seed production programme implemented by farmers helps increase the cultivation of quality fodder through distribution of high yielding seeds. 10
In the dairy sector quality begins with each individual farmer, NDDB’s clean milk production programme involves intensive training, including the motivation and skills needed for correct milking and milk handling related activities which include preparation of baseline data on raw milk bacteriological quality, raising awareness of good hygienic practices, establishment of models for quality assurance, and the promotion and financing of such stainless steel vessels. Quality assurance programmes have been introduced in a number of dairy plants such as equipment automates processes, reducing risk of contamination. NDDB is supporting milk unions which seek to achieve international standards through ISO/HACCP accreditation. Milk trade is a cottage industry providing employment opportunity in rural areas, particularly to the women folk thereby supplementing the family income. The milk producers’ cooperative societies eliminate the middlemen and protect the interest of the producers. The farmers are assured of remunerative price and market support. The institutional frame has three-tier structure with 10041 primary milk producers’ cooperative societies at the village level, the union producers’ cooperative societies at the district level and the federation of district cooperative milk producers’ union at the state level in 2001-02. Under the brand name of Aavin, the cooperative milk producers’ federation (TNCMPF) has made a tremendous achievement in Tamil Nadu. The data on milk products sold (in MTS) during the period 1998-2001 is given below.
Milk Products Sold Milk Products 1998 – 99 1999 – 2000 2000 – 01 Skimed milk powder (SMP) 1,250 5,146 7,427 Butter 3,043 3,592 2,987 Ghee 3,890 4,414 4297
While the milk production has reached an all time high in Tamil Nadu, the producers encounter marketing constraints. The infrastructure available for procurement, processing of milk and marketing network are inadequate. Only 15 per cent to 20 per cent of the total milk produced in the state is handled by the organized sector. As most of the milk producers are small and marginal farmers and landless agricultural labourers, they are forced to sell their product at a low price, as the commodity is perishable by nature. 11
There are 20 dairies functioning at present in Tamil Nadu. 16 of them, function under the control of district cooperative milk producers’ union (DCMPU) and four under the control of Tamil Nadu Cooperative Milk Producers’ Federation (TCMPF). The (TCMPF) has two sperm stations, one at Ootacamund, is meant for cattle and other at Erode is meant exclusively for buffaloes. Out of the 10,041 registered primary milk cooperative societies in Tamil Nadu 7,368 societies are effectively functioning. As of 1999-2000, there are 22.12 lakhs members. Out of total milk production of 45.74 lakh tones, a quantity of 6.22 lakh tones alone (13.6 per cent) is procured by the federation in 1999-2000. With regard to utilization of cow’s milk 88.2 per cent is sold, 8.1 per cent is used for own consumption and 3.7 per cent is converted into milk products as of 1999-2000. The respective figures for buffaloes are 82.7,13 and 4.3. This is a good ratio because selling milk as milk product is more remunerative than selling milk in the form of milk products only. Responding to the challenges raised by the WTO, the milk federation / unions in Tamil Nadu approach the national dairy development board for assistance to develop a plan document-vision 2010. They seek to improve the quality of the milk procured, the productivity of the animals, the marketing of the milk and milk products, strengthening the institutional base of the cooperatives and establishing network information. Quality and availability of cattle feed determine the quality and milk yield of the cattle and buffaloes. There is a fodder shortage in the state, of 30 per cent in the case of dry fodder and 79 per cent in respect of green fodder. As of 1999-2000, the total area brought under fodder cultivation is in the order of 5,888 ha.
1.10. Limitations of the study The period for the study was too short, covering only one session. It is therefore possible that due to seasonal variations in input cost and the production level, the cost of milk on the farm may be different for other seasons. Majority of milk producers generally do not keep much records hence, the information collection was based on mental recollection of recent event such as procurement rates. The inputs provided by the farmers therefore could not be checked for authenticity. Since schedule was prepared for data collection by enumerators, there may be difference 12
between actual and recorded data as perceived by enumerators. The rates related to non milk income e.g. income from cow dung etc. were assumed on the basis that there would be assured market accessible to the farmers. No concurrent study was conducted to collect data from market / intermediaries regarding input and milk prices for cross verification. Limited focused sensitization program was organized amongst the milk producers both prior and during the study period. Information related to ownership could not be verified.
1.11. Plan of the study The thesis is divided into eight chapters. The first chapter includes introductory aspects such as need for the study, research gap, motivation for the study, statement of the problem, research questions, objectives, hypotheses, theoretical framework for the study, Limitations and Plan of the study. The second chapter deals with the review of Literature. The third chapter brings out the profile of the study area, the definitions and concepts, definition of various categories of incomes, database and period of the study, sampling design and statistical tools used. The fourth chapter gives an analysis of characteristics of milk producers in Budalur block. The fifth chapter deals with the analysis of factors determining milk production income. The sixth chapter deals with the analysis of cost and productivity of milk producers in the study area. The seventh chapter brings out the analysis of the various channels of marketing and problems of milk production in the study area. And the last chapter furnishes the major findings, suggestions and conclusions. A small note on the areas for further research is also given. Chapter - II
Review of Literature 13
CHAPTER - II REVIEW OF LITERATURE
This chapter records the findings of the research studies conducted previously on the dairy production and marketing in various parts of India and other countries.
2.1. REVIEW OF LITERATURE RELATED TO CHARACTERISTICS OF THE MILK PRODUCERS
Dhanabalan. M. (2009)1 opined that dairy has an important role in improving the overall economic conditions of rural India. To maintain the ecological balance, there is need for sustainable and balanced development of agriculture and allied sectors. From our first plan onwards, planners have given priority to allied sector for the economic development of the rural sector. Dairy farming is described as a small industry which provides gainful employment opportunities. It comprises of about six per cent of the national income. Mandeep Singh and Joshi.A.S. (2008)2 reported the economic analysis of dairy farming has been reported for marginal and small farmers in Punjab for the year 2003-04. It has been found that a majority of the farm households are not able to meet their requirements from their income from crops. Further dairy farming has emerged as a major allied enterprise for supplementing the income of marginal and small farmers in Punjab. Income from off-farm sources has been identified another important factor contributing significantly to the disposable income of these farm households. The study has suggested to further exploit the potential of off-farm sources towards meeting the domestic expenditure. Also, the technical efficiency of crops and dairy farming should be improved to provide more income to farmers. Islam. S., Goswami. A. and Mazumdar. D. (2008)3 have analysed Tehatta-II block of Nadia district in West Bengal. There were 17 blocks in the Nadia district of
1 Dr. Dhanabalan. M. (2009), “Productive Efficiency of Milk Production In Tamil Nadu”, Indian Journal of Marketing, Volume XXXIX, Number 12, P-21. 2 Mandeep Singh and Joshi. A.S. (2008), “Economic Analysis of Crop Production and Dairy Farming on Marginal and Small Farms in Punjab” Agricultural Economics Research Review, Vol. 21, Issue: 2, P-30. 3 Islam. S., Goswami. A. and Mazumdar. D. (2008), “Comparative Profitability of Cross Breed and Indigenous Cattle in West Bengal” Indian Res. J. Ext. Edu, Vol. 8(1), Pp- 28-30. 14
which Tehatta-II block was selected purposely. The block consisted of 7 gram panchayats and 2 gram panchayats namely Palsunda-I and Barnia were selected randomly. Fifty dairy farmers were selected from each gram panchayats based on judgement sampling. The study area was more or less homogenous with respect to animal husbandry practices, socio-cultural conditions, facilities for service and critical inputs. Most of the dairy farmers in study areas were unorganized in milk production. Relevant information from the individual milk producers (dairy farmers) has been collected through personal interrogation method with the help of a structured interview schedule prepared for the study. The study revealed that crossbred cows were more economical and gave higher yield than the indigenous cows and inclusion of a few crossbred cows can increase the income of a dairy entrepreneur and provide gainful and round the year employment. Family labour work was carried out in the mill pocket areas of eight districts of Marathwada region. About 59 percent of the dairy farmers belong to general (unreserved) category, 25 percent were backward class and only 8 percent each of SC and ST. The landless dairymen equally contributed with dairymen having (large) land; 13 landless dairymen reported comparable lactation yield as the number of milch animals increased, the herd lactation performance decreased. The animals maintained by joint family were not properly cared for while they were cared for properly by singly family. Sintayehu Yigrem, et al. (2008)4 studied about two hundred forty dairy producers. Both rural and urban producers in the four major towns representing the Shashemene–Dilla area in southern Ethiopia, were selected using a multi-stage sampling techniques, with the objective of characterizing dairy production, processing/handling, marketing systems as well as to prioritize constraints and opportunities for dairy development in the area. To characterize dairy marketing systems in the study area, a Rapid Market Appraisal (RMA) technique was employed. Dairy marketing systems were studied with the help of topical guidelines. Dairy producers were interviewed using a pre-tested and structured formal questionnaire. Two major dairy production systems, namely the urban and mixed crop–livestock
4 Sintayehu Yigrem, et al. (2008), “Dairy production, processing and marketing systems of Shashemene - Dilla area, South Ethiopia” – abstract of the project on Improving Productivity and Market Success (IPMS) of Ethiopian farmers project, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia. 15
systems were identified, and again classified into two categories based on the major crops grown as a cereal crop producing and earnest-coffee producing areas. The average family size of urban and rural dairy producers was 7.19 ± 0.26 and 7.58 ± 0.23 persons, respectively. Dairy contributed about half of the income of urban producers but it made up only 1.6% of the total income of families in the mixed crop- livestock production system. Average farm size of households in the mixed system was 1.14 ± 0.99 ha, while more than 97% of the urban producers use their own residence compound for dairying, which is only 200–400 square meters. Average herd size per household in the cereal based mixed system (3.8 ± 0.42) was higher than in the earnest - coffee based systems (2.3 ± 0.36). Out of the total herds of urban producers, 32% of cattle were local cows while 19% were crossbred. Husbandry practices like feeding, watering, housing, breeding, milking, calf rearing, waste management, and record keeping were also different between the two production systems. An estimated total of 9,645,020 litres of milk was produced annually from 4463 small and medium farms in the four towns. The majority of producers (61.7%) in the mixed crop–livestock system process produced milk for home, while the majority of urban producers (79.2%) produced milk for sale. Radha Krishnan, Nigam.S, and Shantanu Kumar (2008)5 in their opinion growing human population, rising per capita income and increasing urbanization are fuelling rapid growth in the demand for food and animal origin in developing countries. India possesses the largest livestock population in the world. Contrary to the large population of livestock in India productivity of Indian livestock is low compared to many developing countries. Waghmare P.R. and Hedgire D.N. (2007)6 opined that Milk productions in India during 1950-51 was 17 million tonnes which has reached 78 million tonnes in 1997-98. Presently India ranks first in the world in milk production. The Operation Flood Programme was instrumental in dairy development activities. These programmes are useful in upgrading the standard of living of farmers.
5 Radha Krishnan, Nigam. S. and Shantanu Kumar (2008), “Contribution of livestock in Indian Scenario”, Agricultural Situation in India, Vol. 66, Issue 1, April, Pp. 25-28. 6 Waghmare P.R. and Hedgire D.N. (2007), “Econometric analysis of integrated dairy development Programme in Parbhani District”, Agricultural Situation in India, Vol. 64, Issue 3, Pp. 97-101. 16
Hasan Cicek, et al. (2007)7 examined to determine the technical and socio- economic factors that may affect the cost in dairy enterprises. In this context, the annual production records (2005-2006) if 77 dairy enterprises running in Western Turkey were examined. Data were analyzed by using multiple regression models. Results showed that the parameters such as education of the producers, scale of the enterprise, feed consumption, feed procuring and litter size had significant effect (P < 0.05) on the average milk costs. On the other hand, marketing, main occupation and age of the producer were found to be statistically insignificant (P > 0.05). In conclusion controlling the technical and socio-economic factors were found to have important effect on decreasing the cost of the production as well as increasing the profitability of the enterprise. Karmakar K.G. and Banerjee G.D. (2006)8 pointed out that growth in milk production is likely to continue at the present rate of 4.4% in the near future. Who is going to handle this incremental milk? We must bear in mind is both income and price. We must bear in mind both income & price elasticity account for approximately 15% of the total expenditure of food. Demand for milk, at current rate of income growth is estimated to grow at 7% per annum. Interestingly, demand for milk is expected to grow steadily over the next two decades as the low income rural and urban families who have higher expenditure elasticity would also increase their income due to new economic environment. Dash. H.K., Sadangi. B.N. and Pandey. H. (2006)9 evaluated “Women Dairy Project - Balasore and Bharak districts of Orissa” sponsored by Ministry of Women and Child Development, Government of India in the year 2005. The Women dairy funded under STEP envisaged formation of women dairy co-operative societies and supporting the societies and members by way of creating marketing infrastructure, supplying physical inputs for dairy development and arranging training for office bearers and members. The project created a good impact on dairy sector as a whole
7 Hasan Cicek, et al. (2007), “Effect of some technical and Socio-Economic Factors on Milk Production Costs in Dairy Enterprises in Western Turkey” World Journal of Dairy and Food Sciences, Vol. 2, No. 2, Pp. 69-73. 8 Karmakar K.G. and Banerjee G.D. (2006), “Opportunities and Challenges in The Indian Dairy Industry”, Technological Change, Issue 9, Pp.24-26. 9 Dash. H.K., Sadangi. B.N. and Pandey. H. (2006), “Impact of Women Dairy Project-A Micro Level Study in Orissa”, Indian Journal of Agricultural Economics, Vol. 61, No. 3, July- Sept, Pp. 550-557. 17
and on cross section of beneficiaries. It provided an assured market to milk producers, released them from the clutches of unscrupulous middle men by offering them a fair and transparent deal. The project, thus, created a favorable environment for higher production of milk. During two year period the milk production increased by 81 percent with the average daily production per pourer increasing from 2.6 litres to 4.7 litres. However, the impact was differential on different categories of farmers with big farmers gaining up to the maximum. The project also introduced several technological changes such as artificial insemination, fodder cultivation, urea treated straw, improved health care and dairy management in the dairy sector, the adoption of which is likely to pick up in coming days. Similarly, the project contributed to the capacity building of members in terms of awareness generation, gain in knowledge, skill development through orientation and training albeit to a varying degree. The project has created a motivating and enabling environment for the members to move ahead and for women leadership to grow. Ramakrishnappa. V. and Jagannatha Rao. R. (2006)10 opined that the dairy enterprise is an established sector in rural India and is playing a vital role in generating additional income and employment. In Karnataka, dairy development is a positive and significant as state contributes towards milk production, marketing, and processing of various dairy products in India. The microfinance programmes extended in dairy sector are helpful to take up dairy as main occupation among economically backward communities in the state. In this paper, an attempt was made to analyze the different aspects of microfinance scheme (New Swarnima) implemented by KBCDC. The implementation of New Swarnima Scheme, one of the most popular microfinance schemes in the state to promote dairy among backward communities, was assessed at micro level by selecting 18 beneficiaries belonging to landless labourers, marginal and small farmers in Kolar district in Karnataka state. The study found that the microfinance scheme has positive impact on income and employment generation, and has improved the natural resource management options.
10 Ramakrishnappa. V. and Jagannatha Rao. R. (2006), “Emerging microfinance issues in dairy development: a case study from Karnataka, India”, International Journal of Agricultural Resources, Governance and Ecology, Vol. 5, Issue 4, Pp. 399-412. 18
Jacques Somda, Mulumba Kamuanga and Eric Tollens (2005)11 suggested that the domestic milk production has been for a long time hindered by many factors including lack of interest from decision makers, distorted economic policy and biotechnical constraints. For the last 20 years, many developing countries have been attempting to develop the domestic milk production sector. However, research on the basic realities and the viability status of enterprises within this sector remain largely unproved in many developing countries. This study focuses on the characteristic of smallholder milk producers in Gambia. Data were collected from 90 smallholder farm households to characterise milk producers and evaluate the profitability and viability status of this activity. Based on current typology of farms and gross margin analyses at farm level, the study identified two resource-based types of smallholder farms. The current milk production system is surely viable. Constraints to increased productivity include lack of improved technology at farm level and weak institutional support. Despite the low viability status, it is shown that milk production generates reliable incomes, which could be a departure for most farmers to intensify farming systems, particularly in areas where no loan schemes exist for purchasing agricultural inputs. Isabelle Schluep Campo and John Beghin (2005)12 explored and investigate Japanese dairy markets. We first provide an overview of consumer demand and how it evolved after World War II. Using historical data and econometric estimates of Japanese dairy demand, we identify economic, cultural, and demographic forces that have been shaping consumption patterns. Then we summarize the characteristics of Japanese milk production and dairy processing and policies affecting them. We next describe the import regime and trade flows in dairy products. The analysis of the regulatory system of the dairy sector shows how its incentive structure affects the long-term prospects of various segments of the industry. The paper concludes with policy recommendations of how to reform the Japanese dairy sector.
11 Jacques Somda, Mulumba Kamuanga and Eric Tollens (2005), “Characteristics and economic viability of milk production in the smallholder farming systems in The Gambia” Agricultural Systems, Volume 85, Issue 1, July, Pp. 42-58. 12 Isabelle Schluep Campo and John Beghin (2005), “Dairy Food Consumption, Production, and Policy in Japan”, Center for Agricultural and Rural Development (CARD) at Iowa State University, Pp. 44-55. 19
Jeyachandra Reddy M., Reddy Y.V.R. and Ramakrishna Y.S. (2004)13 studied and analysed the economics of milk production in three areas, viz., Chittoor district in Andhra Pradesh, Erode District in Tamil Nadu and Kolar district in Karnataka involving aspects related to existing cost structure of milk production, profitability of crossbred dairy cows in the three states under the changed socio economic political scenario and also suggest methods to improve the viability and profitability of these enterprises. The data were collected by survey method during the year 2003. Seventy five farmers were selected at each location giving due importance in the selection of all categories of households. The number of dairy cows studied were 108 in Chittoor, 178 in Erode and 84 in Kolar districts. The net cost of maintenance of a cross bred cow per day worked out to Rs.38.99, Rs.49.36 and Rs.48.88 in Andhra Pradesh, Tamil Nadu and Karnataka respectively. The cost per litre of milk worked out to Rs.5.48, Rs.7.20 and Rs.5.84 in the same order. Feed cost was the major component in gross cost which accounted for 63.88 per cent in Andhra Pradesh. 72.14 per cent in Tamil Nadu and 71.62 per cent in Karnataka. The net profitability varied from 43 per cent in Tamil Nadu. 70 per cent in Andhra Pradesh and 83 per cent in Karnataka. The variations among the three studied locations are due to variation in breed, feeding pattern, maintenance of animals, etc. The study has further brought out the fact that higher fat content provides higher price as milk is priced based on fat and solid-Net-Fat (SNF) content by dairies. Hence proper scientific breeding procedure is to be followed to improve fat content in the milk as well as milk production per animal. Besides, scientific breeding, feeding, treatment and veterinary care and management would not only increase milk production and fact content in addition to reduction in cost, but also incomes of farmers. Thus dairy farming is considered an instrument for socio economic change in rural areas.
13 Jeyachandra Reddy M, Reddy Y.V.R and Ramakrishna Y.S. (2004), “A Comparative Study of Cost of Milk production under Different Agro-Climate Regions in Semi-Arid Regions”, Indian Journal of Agricultural Economics, Vol. 59, No. 3, July-Sep., Pp. 611. 20
Rakesh Saxena (2002)14 in his view, Milk production in India is characterized by a large number of milch animals, a large number of milk producers, mixed farming and low productivity of milk per animal. Most of the total milk production in the country comes from indigenous cows (27%), crossbred cows (15%) and buffaloes (54%). Goats and other animals contribute only a minor share (4%) to the total milk production. The population of crossbred cows and buffaloes is kept largely for milk production while the population of indigenous cows is maintained for producing both milk and drought animals. About 58 per cent of the total population of cattle and buffaloes in India in this study uses the LCA approach to estimate the environmental impact of milk production in terms of methane emissions. The study focuses only on bovine milk production as it accounts for about 96 per cent of the total milk production in India. The methane emissions in the study are estimated at the level of indigenous cows, crossbred cows and buffaloes instead of the usual two categories of cows and buffaloes. The analysis of methane emissions in terms of per kg of milk production has been extended to methane emissions per rupee worth of milk production, as the prices of cow and buffalo milk are very different due to the different fat content. The environmental impact has been assessed in two steps: (1) inventory analysis and (2) impact assessment. Under the first step, an inventory has been taken of raw materials and associated emissions. The impact of these raw materials and emissions has been assessed under the second step. The raw materials used by cattle and buffaloes are divided into two categories, namely (1) concentrates and (2) roughages. The roughages are sub-divided further into green fodder and dry fodder. The emissions of methane associated with bovine milk production take place mainly at three stages, namely (1) enteric fermentation, (2) manure management, and (3) use of dung as domestic fuel. The study has used IPCC guidelines and is based largely on the secondary data available from various sources. Triveni Dutt (2001)15 opined that the Cattle and buffalo production is an integral form of rural economy and contributes substantially to the family income. Milk provides 63% of animal protein and almost 100% of animal fat in the daily diet
14 Rakesh Saxena (2002), “Life Cycle Assessment of Milk Production in India”, Int J LCA, Vol.7(3), Pp. 1- 89. 15 Triveni Dutt (2001), “Improving milk production in Cattle and buffaloes- vision and challenges”, Indian Farming, January, Pp. 61-66. 21
of an average Indian. Milk contributed 66.8% of the total value of output from livestock (1998-99). In addition to milk and milk products for human consumption, cattle and buffaloes also provide animal power for agricultural operations and rural transport needs. The draught animal power, which is valued at Rs.4000-95000 million is not included in the total value of output from livestock. The 75 million draught animals (mostly cattle and buffaloes) contribute 20% of energy input into crop farming. Although there has been large reduction in contribution of draught (DAP) from 72% in 1961 to 23% in 1991 mainly due to mechanization, the requirement of DAP shall continue to be around 20% in years to come. Milk production in 1998-99 was estimated to be 74.7 million tonnes, which is less than 10% of world production. Around 54% of this total milk comes from buffaloes, 42% from cows and 4% from goats. Large increase in milk production has been due to increase in numbers and change in composition of cattle population mainly due to increase in number of crossbreds. Hegde. H.G. (2001)16 pointed out that there is very little breathing time for Indian farmers to face the challenge of importing milk and milk products under WTO. Our farmers are not prepared to solve them well on time. It is necessary to reduce the cost of milk production by increasing the productivity of our animals. We also need to reduce the cost of handling of milk and processing by reducing intermediary agencies and by adding value to the produce. The quality of the milk should be of international standard which can be improved through screening of the livestock against important diseases and maintaining clean surroundings in the dairy farm. Finally, the policy of producing low fat milk for general consumption while the high fat buffalo milk can be supplied to a selected category of customers interested in high butter fat. We need to discuss with the farmers and understand their problems and solve them at the earliest. Surely, we also need to strengthen our farmers associations to acquire new technologies understand the milk marketing scenario at the international level and find suitable solutions. We hope the task is within our reach for solving.
16 Hegde. H.G. (2001), “WTO Challenges for Indian Dairy Farmers”, Yojana, Vol. 45, Dec., Pp. 34-35. 22
Rawal and Vikas (2001)17 analysed that the comparison of caste, education and land holding of MS farmers with NMS farmers points to a larger proportion of households belonging to the backward caste, being less educated and holding lower size of land are not able to participate in dairying. A recent study of two dairy co-operatives in Gujarat argued that inequality in land ownership, caste, illiteracy and undemocratic functioning of co-operatives are the barriers to entry. Illiteracy might not be a factor in Kerala but land ownership could be one, as among the lower size- class of land owners smaller proportion seem to be keeping cattle. Gautam Kakaty and Moromi Gogoi (2001)18 animal husbandary plays a pivotal role in the agrarian economy of India. It is closely interlinked with the socio- economic matrix of rural society. The development of livestock sector has been receiving significant priority in India in the last two to three decades. Dairy sector contributes significantly in generating employment opportunities and supplementing the income of small and marginal farmers providing by them food security. Narayana (2001)19 opined that the work status of the adult population has no significant difference between MS farmers and NMS farmers could be observed. Women, however, devoted considerable amount of time for dairying, irrespective of whether they reported as working or not working and giving the reason as housewife. Obviously, the categories of work status and employment often used are not very useful in capturing the work input of women in dairying. Time disposal studies do help to bring this aspect of work and show that women’s role in cattle keeping is great. The initiatives undertaken such as Malabar Rural Development Foundation for improving the quality of dairy farmers are welcome as they go beyond the landless as their participation in dairying is low. This needs to be kept in mind while planning welfare interventions.
17 Rawal and Vikas (2001), “Participation of the Rural Poor in Dairy Co-operatives: A Case Study from Gujarat”, Indian Journal of Agricultural Economics, Vol. 57, No. 4, October- December, P.712. 18 Gautam Kakaty and Moromi Gogoi (2001), “Employment and income opportunity in Dairy enterprises of Assam - A Case Study”, Agricultural situation in India, Vol. 66, No. 2, May, P.69. 19 Narayana (2001), “Dairying in Malabar: A Venture of the Landowning based on Women’s work?”, Indian journal of Agricultural Economics, Vol. 57, No. 4, October - December, P.712. 23
Manob Kanti Bandyopadhyay (1996)20 pointed out that maximum people of thickly populated India live in villages. Majority of them are involved in agriculture in India as the old method of cultivation is still vogue here. Rearing of cattle animal is also an additional source of income of the villagers in our country. We get from our ancient history that the domestication of the cow and the buffalo dates back to nearly 4000 years. Scriptures of India refer to the wealth through the world Godhan’. Maximum properties of cows and buffaloes of the world are seen in India. This amount is too inadequate to meet the country’s demand. The supply of milk in some parts of India is higher than the local demand. On the other hand, supply of milk in the rest f the country as well as urban areas is much lower than the demand. In 1965, National Dairy Development Board (N.D.D.B) was set up with the object of meeting the increasing demand of milk specially in urban areas as well as developing the rural economy through the enhancement of the milk production in the country. Miriam Sharma and Urmila Vanjani (1993)21 are of their opinion that following the proclaimed success of cooperative dairy schemes in other parts of India (Operation Flood based on the Amul model), the Rajasthan government is attempting a similar scheme. A key theme of the project is to bring women into the mainstream of dairy development in order to improve their economic, nutritional, and social status. For this purpose a special program was initiated to train poor rural women in 'dairy camps' on how to care for their milch animals. Successful completion of such 'camp' training then qualifies the woman for a loan to buy an animal in her name. It is hoped that a part of the milk obtained will go to the village dairy cooperative. The major aims of this program are to: remove milch animals from the cities; encourage production of more milk for the cooperative dairies; encourage modern techniques of animal care; put control of the income from milk-selling in the hands of the women who care for the animals by permitting them to own the animals and hence contribute to their 'independence' and 'development;' and to encourage self-sufficiency for the
20 Manob Kanti Bandyopadhyay (1996), “Dairy Co-operation and Rural Development (with special reference to comparative study between the Kaira District Co-operative Milk producers’ Union limited and the Himalayan Co-operative Milk producers’ Union Limited)”, Finance India, Vol. 10, No. 2, June, Pp. 406-411. 21 Miriam Sharma and Urmila Vanjani (1993), “When more means less: Assessing the impact of dairy 'development' on the lives and health of women in rural Rajasthan (India)”, Social Science and Medicine, Vol. 37, Issue 11, Pp. 1377-1389. 24
weaker sections by providing loans to the poor. Data for this paper were collected during fieldwork in a village in Alwar District, Rajasthan and specifically from observation and participation in the two-week dairy 'camp' there. Eighteen women were selected on poverty criteria to participate in the program. The general situation of these women is analyzed within the context of a critical discussion of the dairy movement in India, in general, and the intended effects on the lives of the village women, in particular, with special attention to the impact on their workload, nutritional intake and, ultimately, overall health. Concluding remarks are addressed to the broad issues of government development programs and why more of the same type of development strategies persist in the face of often-repeated failures. Uma Shankari (1989)22 opined that in the given the context of a prolonged drought, in which the little income they derived from dairying went a long way in meeting their survival needs, it is no wonder that the farmers of Chittoor district in Andhra Pradesh who studied here had a positive attitude to the crossbreed programme. But while the crossbreed cow is clearly a superior milch animal to the local breed and the local breed cow is fast becoming redundant for all categories of farmers, the fact that the bullocks cannot be dispensed with drives at least a few of the farmers to maintain bullocks. The losses from the bullocks are made up by the gains from the crossbreed cows. The landless, however, tend to maintain local breed cows even if it means far lower incomes since the investments and risks involved are smaller. Moran. J.B. (1987)23 viewed that cattle and buffalo play an important role in the agriculture of South East Asia, providing both milk and meat and also traction for ploughing and transport. The native breeds vary considerably in their characteristics, not only in their inherent qualities but in their response to varying systems of management, some very primitive. Improvement is clearly possible by cross-breeding, but it appears that this is most likely to be achieved within existing native breeds, rather than by introducing exotic ones developed to thrive under very circumstances.
22 Uma Shankari (1989), “What is Happening to Cows and Bulls of Sundarapalle?” Economic and Political Weekly”, May 27, P.1164. 23 Moran. J.B. (1987), “The Indigenous Cattle and buffalo of South East Asia: their past, present, and Future” Outlook on Agriculture, Vol. 16, No. 3, P. 116. 25
Babita Bohr124 opined that dairy farming, one of the most important economic activities in the rural mountain areas of Uttaranchal, is closely intertwined with farming systems. Rural communities fondly relish dairy products. Dairying again is the main purpose of animal husbandry in mountain areas. Apart from ensuring nutrient supplies to the families owning dairy farms, dairying also offers promising employment opportunities and handsome economic returns. In Uttaranchal mountains, dairying is especially a promising economic activity for smallholders who constitute the majority of farming communities in the region. Smallholder dairy farming is increasingly gaining importance as a source of family income in mountain areas for quite some. However, contributions of smallholder dairy farming accrued to the community and farming system are still not well recognized. India’s emerging as the top milk producer in the world is largely due to smallholder, rather than intensive, dairy farming linked with the marketing system.
24 Babita Bohr1, “Milk production, marketing and consumption pattern at peri urban dairy farms in the mountains: a case from lohaghat in Uttaranchal”, ENVIS Bulletin, Vol. 12(1). 26
2.2. REVIEW OF LITERATURE RELATED TO THE COST AND PRODUCTIVITY IN THE MILK PRODUCTION
Saravanakumar. V. and Jain. D.K. (2009)25 viewed that “The two-axes pricing policy is followed normally in the dairy business centres of Tamil Nadu. Though it is scientifically rational, it ignores the input prices, technology and government policies. For sustaining the growth momentum and achieving an annual average growth of 7-8 per cent in the next five years and considering that dairying is practised as a component of mixed farming systems, it becomes imperative to take into account the interrelationship among the enterprises and general economic factors while fixing the milk price. In this study, development of a price determination model has been reported. It is based on the cost of production and takes into account price and non-price factors, viz. technology, and projected different price scenarios of milk for the coming years. The study undertaken in Tamil Nadu state, is based on primary data collected for the year 2002-03 and has used normalized restricted quadratic profit function analysis and price determination models. It has been found that to maintain constant returns to the production cost of milk, the milk price would need an upward adjustment of 9.97 per cent, whereas to provide constant net monetary income, the milk price would need an upward adjustment by 10.30 per cent for buffalo milk. Considering 2002-03 as the base year, the estimated price for milk per litre is expected to be Rs.23.64 at constant monetary income and Rs.23.15 at constant return to production cost in the year 2009-10. The results of the paper are illustrative of the utility approach in generating consistent price sets for milk in response to alternative policy interventions. Haese M.D., et al. (2009)26 analysed the efficiency on dairy farms in Reunion Island, a French overseas district located in the Indian Ocean. On this island, dairy farming is promoted with financial and technical support from the European Union, with the French and local governments aiming at reducing dependency on imports of milk powder and dairy products and creating employment. A critical factor for
25 Saravanakumar. V. and Jain. D.K. (2009), “Evolving Milk Pricing Model for Agribusiness Centres: An Econometric Approach”, Agricultural Economics Research Review, Vol.22, Issue 1, P. 28. 26 Haese M.D, et al. (2009), “Efficiency in milk production on Reunion Island: Dealing with land scarcity” Journal of Dairy Science, Volume 92, Issue 8, August, Pp. 3676-3683. 27
increasing the local milk production is the limited availability of arable land because of the small size and the volcanic nature of the island. In this paper, we study the efficiency levels of dairy production of 34 farms by using a data envelopment analysis approach. The average technical efficiency score of farms, assuming constant returns to scale, was 0.927, with 19 out of 34 farms not being efficient. The technical efficiency with variable returns to scale specification was 0.951. The efficiency with which farmers used their land (subvector efficiencies) was estimated in the second model. The average subvector efficiencies calculated with constant returns to scale and variable returns to scale models were lower than the technical efficiencies. The farmers on the efficiency frontier had a relatively higher milk production, milk production per cow, and land surface more than those who were less efficient. A policy promoting better use of the land on inefficient farms should increase the milk production-to-land ratio. Possible on-farm strategies improved feeding systems, farms having their own heifer breeding, and improved genetics. Mathialagan, Chandrasekaran. D.C. and Manivannan. A. (2009)27 in their study conducted with the objective of training the farmers on feeding technologies for improving the SNF content of milk in milch animals and to assess its impact at the field level. About 159 women dairy farmers cum self help group members belonging to ten different villages of Namakkal district were selected for the study. A benchmark survey was conducted for all the women dairy farmers on cost effective feeding practices for dairy cattle, feeding of chopped fodder on the animals and supplementing diet with minerals. The results indicate that 46.37% of cow milk samples had less than 8.0% of SNF content. When the SNF content falls below 8.0% the payment for the milk will be calculated based on the fat content of the milk as per the price policy of milk co-operative societies. In such cases, the farmers would get a lower price of Rs.6.50/- per litre instead of Rs.8.75 / litre of milk. Rhone. A., Ward. R., De Vries and Elzo. M.A. (2008)28 analysed and investigated determinates of how milk pricing system, farm location, farm size, and
27 Mathialagan, Chandrasekaran. D.C. and Manivannan. A. (2009), “Effect of Feeding Supplements of SNF content in Milk” Tamil Nadu Veterinary and Animal Sciences, Vol. 5, No. 1, Jan-Feb, Pp. 28-29. 28 Rhone A., Ward R., De Vries A. and Elzo. M.A. (2008), “Comparison of two milk pricing systems and their effect on milk price and milk revenue of dairy farms in the Central region of Thailand”, Tropical Animal health and production, Vol:40, No:5, Pp:341-348. 28
month and year affected farm milk price (FMP), farm milk revenue (FMR) and loss in FMR of dairy farms in the Central region of Thailand. A total of 58,575 milk price and 813,636 milk yield records from 1034 farms were collected from November of 2004 to June of 2006. Farms were located in the districts of Muaklek, Pak Chong, Wang Muang, and Kaeng Khoi. A fixed linear model was used to analyze milk price of farms. Two pricing systems were defined as 1 = base price plus additions / deductions for milk fat percentage, solids-non-fat, and bacterial score, and 2 = same as 1 plus bulk tank somatic cell count (BTSCC). Farm size (small, medium, and large) was based on the number of cows milked per day. Results showed that FMP were lower (P < 0.05) in pricing system 1 than in pricing system 2. Most small farms had higher (P < 0.05) milk prices than medium and large farms across in both pricing systems. Large farms lost more milk revenue due to deductions from bacterial score and BTSCC than small and medium farms. Doyon. M., Criner. G. and Bragg. L.A. (2008)29 viewed and opined that the New England dairy farmers are under intense price pressure resulting from important growth in milk production from lower cost of production in Southwest states as well as by retailers’ market power. Agricultural officials and legislative bodies in New England and in other Northeast US states are aware of these pressures and have been reacting with emergency dairy farm aid, following a very low 2006 milk price, and with state legislations in an attempt to address perceived excess retailing margins for fluid milk. In this paper, we suggest that a sigmoid demand relationship exists for fluid milk. This demand relationship would explain fluid milk asymmetric price transmission, high-low pricing, and the creation of a large retailing margin (chain surplus) often observed for fluid milk. It is also argued that a sigmoid demand relationship offers an opportunity for state legislators to help Northeast dairy farmers capturing a larger share of the dollar of the consumers through various policy options. Therefore, 5 milk market channel regulatory mechanisms (status quo, price gouging, supply control, fair share policy, and chain surplus return) are discussed and compared. The supply control mechanism was found the most effective at
29 Doyon. M., Criner. G. and Bragg. L.A. (2008), “Milk Marketing Policy Options for the Dairy Industry in New England” Journal of Dairy Science, Volume 91, Issue 3, March, Pp. 1229-1235. 29
redistributing the chain surplus, associated with the sigmoid demand relationship for fluid milk, to dairy farmers. However, this option is unlikely to be politically acceptable in the United States. Second-best options for increasing dairy farmers’ share of the consumers’ dollar are the fair price policy and the chain surplus return. The former mechanism would distribute the chain surplus between retailers, processors, and farmers, whereas the latter would distribute it between consumers, retailers, and farmers. Remaining mechanisms would either transfer the chain surplus to retailers (status quo) or to consumers (price gouging). Kedija Hussen1, Mohammed Yousuf1 and Berhanu Gebremedhin (2008)30 viewed that the Ethiopia holds the largest ruminant livestock population in Africa, productivity has remained low and its contribution to the national economy is limited compared to its potential. The overall milk production system in Ethiopia could be broadly classified as pastoral and agropastoral, crop-livestock mixed and peri-urban and urban dairy production systems. Cattle, camel and goats are the main livestock species that supply milk. Total annual milk production from about 10 million milk animals is estimated at about 3.2 billion litres, which translates to 1.54 litres per cow per day (CSA, 2008). The bulk of this milk production (81.2%) comes from cattle, while small ruminants and camels contribute 12.5% and 6.3%, respectively (CSA, 2008). The lowland covers 60% of total land area and is home for 12.2% of the total human population. Ecologically it has arid (64%), semi-arid (21%) and sub-humid (15%) areas dominated by semi nomadic transhumane population whose economy is entirely dependent on livestock production (GETACHEW, 2003). Milk is the major source of food and income. Cattle dominate the population (55.4% of the TLU) followed by camels (15.3%), goats (13.7%) and sheep (6.4%), (CSA, 2008), and produce 27% of the total annual milk production (Getachew, 2003). Information is very scantly on the milk production and marketing system in the lowland areas in general. This study was therefore undertaken in the lowlands of Mieso district to (1) characterize the milk production and marketing system, (2)
30 Kedija Hussen1, Mohammed Yousuf1 and Berhanu Gebremedhin (2008), Paper on “Cow and camel milk production and marketing in agro-pastoral and mixed crop-livestock systems in Ethiopia”, Presented at the Conference on International Research on Food Security, Natural Resource Management and Rural Development held at University of Hohenheim, on October 7-9. 30
identify major constraints for the development of market-oriented dairy production, and (3) formulate recommendations for further development interventions. Saravanakumar. V. and Jain. D.K. (2008)31 conducted a study ‘Technical Efficiency of Dairy Farms in Tamil Nadu” which was carried out to evaluate dairy farm households in terms of efficiency of milk production using stochastic frontier production methods. The data for the study comprised of fixed investments on dairy farms, quantity and price of feeds and fodders fed to individual animals, labour utilization pattern, veterinary and miscellaneous expenses, quantity of milk produced and price realized etc. collected from 160 sample households across flush and lean season for the year 2002-03. The coefficients for the value of green fodder and concentrate were found to be statistically significant with a relatively higher magnitude implying their greater and significant role in crossbred cow milk production. The technical efficiency of crossbred cow farms ranged from 72.30 to 97.90 percent with an average of 82.10 percent. The study indicated that there existed a scope to increase milk production of an average farm to 16.32 percent for crossbred cows and 14.04 percent for buffaloes without incurring any extra expenditure on these farms. Sharad Gupta (2007)32 viewed that the country’s milk production is estimated to have touched 100 million tonnes (mt) last year, which is higher than the estimated 92 mt for rice and 75 mt for wheat. In value terms, too, a kg of milk is worth more than what you and I pay for a kg of rice and wheat. But despite all this and the fact that India is today the world’s largest milk producer, the dairy industry is for some strange reason not considered ‘glamourous’. For policy makers, dairying is viewed as a ‘subsidiary’ activity. This, when milk is one product that generates cash income to farmers almost on a daily basis, unlike sugarcane or wheat. Besides being a source of liquidity and insurance against crop failure, milk is the only crop where the farmer realizes 60-70 per cent of consumer price - against 20 per cent or so in fruits and vegetables. Again, it is striking that there are no commodity futures in milk powder or ghee, whereas the daily turnover volumes in NCDEX and MCX of
31 Saravanakumar. V. and Jain. D.K. (2008), “Technical Efficiency of Dairy Farms in Tamil Nadu”, Journal of Indian Soc. Agriculture Statistics, Vol. 62, No. 1, Pp. 26-33. 32 Sharad Gupta (2007), “Indian Dairy Market to Double by 2011”, Dairy India, (Sixth Edition), P.840. 31
guarseed, mentha oil, jeera or pepper run to hundreds (even thousands) of crores! One reason for this ‘image problem’ suffered by milk has to do with the absence of proper databases with authentic information on the sector. This is a gap that Dairy India 2007 (Sixth Edition) seeks to fill. A treasure trove of information, this 864-page publication offers the most comprehensive and up-to-date picture about the world’s numero uno dairying nation. An invaluable Databank-cum-Management Guide-cum-Directory, it contains over 120 in-depth articles, 260 statistical tables and charts and reference details of 7,000 organizations including dairy plants and farms, equipment and consumable manufacturers, cattle feed and veterinary pharmaceutical manufacturers, chemicals and food additives, project consultants, breeding and fodder seed farms, analytical and disease-diagnostic laboratories, cooperative institutions and government agencies. The articles cover a range of topics including trends in consumption and market size of milk and milk products, WTO challenges and export potential, management of dairy plants and farms, breeding, feeding and nutrition, health care, clean milk production, food safety and quality standards as well as techno-economic feasibility of small and large scale dairy plants and farms, cattle feed units, and manufacture of cheese, ice-cream, etc. In addition, there is a special section devoted to technology innovations and organized production of indigenous milk products such as paneer, gulabjamun, rasogolla and shrikhand - a potentially lucrative segment ignored so far by the industry in its obsession with butter, cheese and other ‘foreign’ products.Dairy India 2007 has estimated the size of India’s dairy sector in 2005 at Rs.27,340 crore (valued at consumer prices). The largest contributor to this is liquid milk (at Rs.82,835 crore), followed by ghee (Rs.22,980 crore), khoa/chhana/paneer (Rs.24,100 crore), milk powder (Rs.4,680 crore), table butter (Rs.770 crore), cheese/edible casein (Rs.975 crore) and other products such as ethnic sweets, ice-cream, etc (Rs.9,100 crore). Out of the total milk production of 94.5 mt, 77 per cent or 73.1 mt is sold as liquid milk, with the balance 23 per cent or 21.4 mt converted into products. Further, the organized industry handles only 18 per cent or 17 mt of milk, with 36 per cent (34.5 mt) being handled by private dudhias and unorganized players and 46 per cent (43 mt) being retained in rural areas. Within the 18 per cent organized sector share, private and cooperative/government dairies handle an equal 8.5 mt each. By 2011, Dairy India projects the value of the industry to more 32
than double to Rs.520,780 crore, which includes Rs.159,600 crore from liquid milk, Rs.42,680 crore from ghee, Rs.50,500 crore from khoa / chhana / paneer, Rs.9,100 crore from milk powder, Rs.2,250 crore from table butter, Rs.6,150 crore from cheese/edible casein and Rs.25,050 crore from other products. Interestingly, out of the anticipated milk output of 120 mt, the share of liquid milk will rise to 81 per cent or 97.5 mt and only the rest 19 per cent (22.5 mt) would get converted into products. But the organized industry’s share of total milk handling will go up to 30 per cent (36 mt), while the small players will see their share dip to 22 per cent (26 mt). At the same time, higher rural incomes will marginally boost the share of milk retained in rural areas to 48 per cent or 58 mt. The other significant feature is that within the 30 per cent overall share of organized dairies, the major 20 per cent (24 mt) will be accounted for by the private sector. The cooperatives and government dairies will handle 10 per cent or 12 mt of milk, which will be lower than that of the organized private sector. Srikanth Reddy. M. and Vasudev. N. (2006)33 studied and an attempt has been made to quantify the level of consumption, production, and marketed surplus of milk in Karimnagar district of Andhra Pradesh. Better feeding followed by congenial weather conditions during the winter has positive effect on milk production. It was also interesting to note that in relative terms marketed surplus was more in summer (ranging from 58.5 percent to 60 percent) compared to that in rainy season (50 percent to 56 percent). On an average marketed surplus during the year ranged between 55 percent in the case of small farmers to 57.2 percent in the case of medium farmers. But in all the categories of farmers the consumption of milk was above recommended level. i.e. 250 gm / day/person. With the disposal of marketed surplus of milk through different agencies it was evident that the co-operatives and milk vendors emerge as major procurement agencies (more than 70 percent) in all categories of farmers. Majority of the small and medium farmers preferred milk vendors while large farmers preferred milk co-operatives to sell their surplus milk. The large family size, education level of family had influenced the consumption pattern of milk. These lead to consume more, resulting in shrinkage of marketed surplus.
33 Srikanth Reddy. M. and Vasudev. N. (2006), “An Economic Analysis of Production Consumption and Marketed Surplus of Milk in Karimnagar District of Andhra Pradesh - a Case Study”, Indian Journal of Agricultural Economics, Vol. 61, No. 3, July-Sept, P.421. 33
Pranajit Bhowmilk, Smita Sirohi and Dhaka. J.P. (2006)34 analysed that the net cost of milk production from crossbred cows is nearly half of the same from local cow, thus in the economic interest of the farmers, strategies aimed at crossing nondescript cattle with superior germplasm should be intensified by the concerned state department. The contribution of technological component in higher milk production for cross breed cows is about 68 percent, thus, propagation of crossbreeding in the region has the potential to ensure reasonable returns of investment. The annual value of inputs saved in one district alone, covers 87 percent of the expenditure on dairy development made by the state in four years. Therefore, from the planners’ perspective also, it is a winsome proposition. Bhowmilk (2006)35 opined that the Cost and returns from milk production were estimated separately for local and crossbred cattle. The gross cost of maintenance was worked out as the sum of fixed and variable costs items. The net cost was arrived at by deducing the value of dung from gross cost per milch cattle per day was divided by the average milk yield per day of the respective breed. The net return was calculated by deducting gross cost from gross return. Chauhan. A.K., Raj Vir Singh and Raina. B.B. (2006)36 examined the economics of manufacturing of different dairy products, viz. ghee, full-cream milk, standardized milk, toned milk, double-toned milk, skimmed milk and ice-cream (processing only) have been reported. The study has been conducted in an ISO-9002 dairy plant situated in the north-eastern part of Haryana. It has been observed that all the products, except the double-toned milk are being produced above the recommended breakeven level. A comparison of unit manufacturing cost with unit price received by the plant for different products has revealed that ice-cream manufacturing has been the most profitable proposition among different dairy products, and standardized milk has provided the maximum profit margin among the
34 Pranajit Bhowmilk, Smita Sirohi and Dhaka. J.P. (2006), “Gains from Crossbreeding of Dairy Cattle in the North East: Micro Evidence from Tripura”, Indian Journal of Agricultural economics, Vol. 61, No. 3, July-Sept., Pp. 306-307. 35 Bhowmilk (2006), “Economics of Milk Production and Analysis of Technological Change in Dairying in South Tripura”, Unpublished M.Sc. Thesis, National Dairy Research Institute, Karnal, Haryana. 36 Chauhan. A.K., Raj Vir Singh and Raina. B.B. (2006), “A study on the Economics of Milk Processing in a Dairy Plant in Haryana”, Agricultural Economics Research Review, Vol.19, Issue 2, P. 25. 34
milk pouches manufactured during the study period, 2000-01. The double-toned milk has revealed a loss. Therefore, the study has suggested that the quantity of double- toned milk production should be raised at least equal to the recommended break-even level to avoid losses, if there is a market demand for this product or the resources of this product could be shifted to some other profitable products. Ashok Shivagaje, Nanda Pandharikar, and Mayura Mathankar (2004)37 viewed that India’s estimated milk production in the year ending March 1999, 74 million tonnes, was 13% of the world’s milk production. This has been appreciated by the United Nation’s Food and Agriculture Organization (FAO), which has declared India as the world’s largest producer of milk. FAO-estimated milk production of 71 million tonnes by USA in the same year is placed second in the list. Data on estimates of milk production in the world and India during 1985–2000 reveal that a linear regression Y = a + bt, where t is the year and Y the estimate of milk production, is the best fit to the data. For India, the estimates of a and b are 41.14 and 2.28 respectively, and for the world they are 501.85 and 3.80 respectively. This implies that an annual increase in estimate of India’s milk production is found to be 2.28 million tonnes (P < 0.01), whereas it is 3.8 million tonnes (P < 0.01) for the world. Assuming that the rate of increase will remain the same for the year 2010, estimates of India’s milk production will be 100.52 million tonnes, whereas the world’s milk production is estimated to be 600.56 million tonnes. The demand for milk products would increase as a result of increase in national GDP. In order to meet the demand, it is essential to have consistent increase in milk production, which will be possible on successful implementation of ‘Operation Flood’ and evolution of new animal breed. Khem Chand and Gajja B.L. (2004)38 in their attempt to analyse the livestock composition, population pattern and factors affecting it in the arid zone of Rajasthan. For the purpose of study, secondary data of livestock population pertaining the animal census year 1961, 1966, 1972, 1977, 1983, 1988, 1992 and 1997 were collected. For the estimation of fodder availability, data on crop production, hallow land, culturable waste and policy area etc. were collected for the year
37 Ashok Shivagaje, Nanda Pandharikar, and Mayura Mathankar (2004), “Milk Production in India”, Current Science, Vol. 86, No. 10, 25 May, Pp. 1349-1350. 38 Khem Chand and Gajja B.L. (2004), “Livestock Population: Composition and Trends in Arid Rajasthan” Indian journal of Agricultural Economics, Vol. 59, No. 3, July-Sep., Pp.609. 35
1996-1997. The requirement of fodder and nutrient intake was also estimated for the region. The study revealed an increase in buffalo population in the region while a sharp decline was observed in per cent share of cattle in the total livestock population. The major deficiency of fodder was felt in the case of bovine in the array region. The factors responsible for increase in buffalo’s population are increasing cropping intensity and rural population density in the arid region while the same factors resulted in a decrease in cattle population. The arid region farmers also adopted buffalo as drought resistance strategy since unproductive buffalo can be sold during drought, which does not affect the religious sentiments as in the case of cattle. The study recommends storage of foliage produced in good monsoon year for use in the deficit period. The government of India is also implementing a scheme for this region for developing and rejuvenate the pasture land to be available on the large scale to improve the livestock situation in this region. Prashant Khare Sharma and Singh (2003)39 of their opinion, Milk collection was higher in healthy season (from September to February) and lower in unhealthy season (from March to August). In spite of more production in the month of July and August, the producer members of the society were not in position to transport their product due to lack of all weather roads. As the distance of the milk producer’s co-operative society increases form the dairy plant, the volume of milk collection decreases, the milk collection was higher in those societies, which are well connected to the dairy plant. The variable cost was the main component of cost of milk production and the maximum cost incurred in the purchase of feed and fodder and in labour management. Low price of milk was the most important problems in the collection of milk, followed by lack of cold storage, delay in payment, inadequate water for animals, lack of all weather roads, small quantity of marketable surplus of milk, improper treatment, lack of cross breed animals and uncertainty of electricity. Hence, efforts should be made to solve all there constraints.
39 Prashant Khare Sharma and Singh (2003), “Marketing Analysis of milk production in Bhopal District of Mathyapradesh”, Agricultural Marketing, Vol. XLVI, No. 2, Jul-Sep., Pp.9-14. 36
White S.L., Benson G.A. and Washburn S.P. (2002)40 in their 4-yr study examined total lactation performance of dairy cows in two feeding systems: pasture- based and confinement. Spring and fall calving herds were used and each seasonal herd had 36 cows on pasture and 36 cows in confinement with 282 Holstein and 222 Jersey cows included over seven seasonal replicates. Pasture-fed cows received variable amounts of grain and baled haylage depending upon pasture availability. Confinement cows received a total mixed ration with corn silage as the primary forage. Data were collected on milk production, feed costs, and other costs. Pasture- fed cows produced 11.1% less milk than confinement cows. Across treatments, Jerseys produced 23.3% less milk than Holsteins, but calving season and various interactions were not significant. Feed costs averaged $0.95/cow per day lower for pastured cows than confinement cows. Feed costs were lower for Jerseys than Holsteins and for cows calving in spring. Income over feed costs averaged $7.05 ± 0.34 for confinement Holsteins, $6.89 ± 0.34 for pastured Holsteins, $5.68 ± 0.34 for confinement Jerseys, and $5.36 ± 0.34 for pastured Jerseys; effects of breed were significant but treatment, season, and interactions were not. Economic factors such as labor for animal care, manure handling, forage management, and cow culling rates favored pastured cows. Higher fertility and lower mastitis among Jerseys partially offsets lower income over feed cost compared with Holsteins. Milk production was lower in this study for pasture-based systems but lower feed costs, lower culling costs, and other economic factors indicate that pasture-based systems can be competitive with confinement systems. Hemme. T., Garcia. O. and A.R. Khan (2002)41 in their opinion 130 million people in Bangladesh should consume at least 120 g of milk per day (as fluid or processed in any form), the annual milk demand would be about 5.70 million tons. This estimate of milk demand in Bangladesh demand is over two and half times
40 White S.L, Benson G.A. and Washburn S.P (2002), “Milk production and Economic measures in confinement or pasture system using seasonally calved Holstein and jersey cows” Journal of Dairy Science, Volume 85, Issue 1, January, Pp.95-104. 41 Hemme. T., Garcia. O. and Khan. A.R. (2002), “A Review of Milk Production in Bangladesh with Particular Emphasis on Small-scale Producers”, Pro-Poor Livestock Policy Initiative (PPLPI), Website:http://www.fao.org/ag/pplpi.html, Working Paper: http://www.fao.org/ag/againfo/projects/en/pplpi/docarc/wp7.pdf. 37
FAO’s recorded national milk production for the country (for 2002). Therefore, meeting Bangladesh’s potential milk demand is a huge national task and the question arises how well-positioned Bangladesh is to meet this milk demand. This study shows that the 2 cow farms (BD-2) not only cover full economic costs, but can produce milk at a cost almost as low as the larger farms included in the study. This should be very encouraging for more than 7.2 million Bangladeshi families involved in small scale cattle rearing, of which few make a profit and most consider it a highly risky activity. The small farm (BD-2) is competitive at the national level but not at the international level. The cost of milk production of all farms in comparison to larger farms in India, Pakistan and Oceania is around 50% higher. Assuming a liberal trade of dairy products in the future all farms analysed will have to improve the production systems significantly to gain from the growing demand of dairy products in the country. Further studies of small dairy farms in Bangladesh need to include a land-less milk production system, a typical goat milk production system and a more exhaustive evaluation of the non-cash benefits obtained from dairy cattle (like draught power). Moreover the cost reduction potential of the farms by improvements in farm management should be analysed. Khem Chand, Kulwant Singh and Raj Vir Singh (2000)42 revealed that milk production in commercial dairy herds is an economically viable and profitable enterprise in Bikaner city. It generated around 973 man-days of gainful employment per year in an average dairy herd. The contractual procurement and auctioning system of milk has helped a lot in increasing the number of diary herds in the city, the optimum herd size analysis has suggested the scope for further increases in the number of milch animals in the dairy herds. Though these dairy herds have helped in increasing the supply of milk, they have created many problems too. The herd owners many times set their animals free, which generally choked due to disposal of animal waste in it. These problems are created by around 40 percent of dairy herds which are maintained inside the city. The shifting of diary herds to the outskirts of the city can solve the problem. Another way to improve upon the situation is by developing a
42 Khem Chand, Kulwant Singh and Raj Vir Singh (2000), “Economic Analysis of Commercial Dairy Herds in Arid Region of Rajasthan” Indian Journal of Agricultural Economics, Vol. 57, No. 2, April-June, P.233. 38
modern dairy complex along the lines of Aarey milk colony, Mumbai with provision of good infrastructure facilities. Rougoor C.W., Sundaram. R. and Van Arendonk J.A.M. (2000)43 investigated the relation between breeding management and 305-day milk production. Second goal of the study was to investigate advantages and disadvantages of principal components regression (PCR) and partial least squares (PLS) for livestock management research. Multicollinearity was present in the data set and the number of variables was high compared to the number of observations. Out of 70 variables related to breeding management and technical results at dairy farms, 19 were selected for PLS and PCR, based on a correlation of ≥0.25 or ≤−0.25 with 305-day milk production. Five principal components (PCs) were selected for PC-regression with 305-day milk production being the goal variable. Related variables were combined into one so-called synthetic factor. All synthetic variables were used in a path- analysis. The same path-analysis was worked out with PLS. PLS forms synthetic factors capturing most of the information for the independent X-variables which are useful for predicting the dependent Y-variable(s) while reducing the dimensionality. Both methodologies showed that milk production per cow is related to critical success factors of the producer, farm size, breeding value for production and conformation. Milk production per cow was the result of the attitude of the farmer as well as the genetic capacity of the cow. It was found that at high producing farms the producer put relatively much emphasis on the quality of the udder and less on the kg of milk. Advantages of PLS are the optimization towards the Y-variable, resulting in a higher R2, and the possibility to include more than one Y-variable. Advantages of PCR are that hypothesis testing can be performed, and that complete optimisation is used in determining the PCs. It is concluded that PLS is a good alternative for PCR when relations are complex and the number of observations are small.
43 Rougoor C.W., Sundaram. R. and Van Arendonk J.A.M. (2000), “The relation between breeding management and 305-day milk production, determined via principal components regression and partial least squares” Livestock Production Science, Volume 66, Issue 1, September, Pp. 71-83. 39
Prasad. D.S (1999)44 observed that the concentrates contributed as an important input in the milk production having significant and positive regression coefficient for all the breeds of buffaloes. The dummy variables for the both the winter and rainy seasons had negative regression coefficients for the local and graded buffaloes but for murrah buffaloes the same were positive and significant for both the seasons. This shows that more yields are realized in the summer season for local and graded buffaloes while higher yields are realized in the winter and rainy seasons for murrah buffaloes. This clearly demonstrated that the summer season contributed significantly to the milk yield in the case of local and graded buffaloes, while the winter and rainy seasons significantly facilitated the murrah buffaloes in increasing the milk yield as compared to the other season. The higher milk yield among the local and graded buffaloes during the summer season might be due to the reason that a majority of these buffaloes might have calved during the summer season itself on the sample farms. Inter-seasonal fluctuations in milk production can be minimized by adjusting the calving dates of buffaloes. The milk yield of the animals can be stabilized through advance planning of calving dates of ensure continuous milk production on the farm through adjustment of mating dates of the buffaloes. This means that at a given time all the buffaloes would not go dry and at least one or two animals would be giving milk to the dairy farmers. Bennett, Charles D. Fullhage, and Donald L. (1999)45 conducted a comparative analysis of two nutrient management systems for Missouri dairies. Annual ownership and operating costs were computed for herd sizes of 100-1,000 cows. A break-even analysis was also provided for irrigation systems used with the lagoon system. Lagoon systems consistently handled dairy nutrient at a lower cost than liquid tank systems for all herd sizes. Even though nutrients from liquid tank systems are more concentrated and valuable than nutrients from lagoon systems, the liquid system's net cost was 1.5 to 2.4 times greater than the lagoon system's net cost, depending on herd size. The liquid tank system also required a 5 to 10 times larger
44 Prasad. D.S. (1999), “Seasonal Variations in Buffalo Milk Production in Rnaga Reddy District of Andhra Pradesh” Indian journal of Agricultural Economics, Vol. 57, No. 2, April- June, Pp. 238-239. 45 Bennett, Charles D. Fullhage and Donald L. (1999), “Economic Considerations for Dairy Waste Management Systems”, Downloaded from http://www.muextension.missouri. edu/xplor/waterq/wq0302.htm, 7 September. 40
plant filter area than the lagoon system. This can be an important consideration for operations with limited acreage. Dairies with more than 300 cows benefited from purchasing a travelling gun irrigator rather than relying on a custom operator to remove nutrients from lagoon systems. Rajendran. K. and Dr. Prabakaran. R., (1998)46 pointed out the present Scenario of milk Production in India. India’s agriculture has been dominated by the belief that its base is in crop production. Also, the focus should be shifted from quantity to quality in the daily diet by enhancing the intake of animal proteins, the major source of which are milk, eggs and meat. In recent years, one unfortunate trend has seen the decreasing per capita availability of pulses, the only major source of protein for the large majority of the population. The nutritional demand has to be bridged rapidly and the milk, egg and meat provide affordable alternative sources of protein. Recently, the annual rate of the growth in milk production has been encouraging which has gone up from 4.5 percent in the seventies to 5.7 percent in the eighties. Today, India ranks as the World’s second larges milk producer after USA. By then, India’s milk output is expected to range between 84 million tonnes at the minimum and 88 million tonnes at the maximum. India’s per capita consumption of milk does not commensurate with its ranking as world second largest milk producer. However, the present per capita availability of 214 grms / day (78 kgs / year) is much higher than the average of 26.27 kg / year for the developing countries in Asia / Pacific region. Today milk is India’s second most important agricultural commodity in terms of value of its output, ranking after paddy, but much above wheat. Verma, N.K., Singh, and Des Raj. (1997)47 conducted a study in Karnal town of Haryana to ascertain deterioration in milk quality during marketing and to estimate real margins in milk trade, it was reported that in the lean seasons milk supplied to consumers by producers directly was of better quality at an average price of Rs.5.68/- per litre than that was sold to Halwai and vendor at Rs.4.75/- and Rs.4.04/- per litre respectively. Raju (1992) on consumer’s perceptions about milk
46 Rajendran. K. and Dr. Prabakaran. R., (1998), “Present Scenario of milk Production in India”, Agricultural Situation in India, Vol. LV, November, No. 8, P-489. 47 Verma, N.K. Singh, and Des Raj (1997), “Variations in the quality of market milk and its impact on the efficiency of milk marketing system”, Indian Journal of Agricultural Marketing, 11(1 & 2), Pp: 93-94. 41
marketed by Vijaya cooperative Dairy in Hyderabad revealed that Vijaya dairy milk had powdery smell which used to easily get curdled compared to vendor milk and buffalo farm milk. Consumers judged the quality of milk fat content, color and taste, thickness, freshness, hygiene, curd formation and flavor of the raw milk. A majority of consumers, irrespective of all income groups, considered thickness, taste curd formation to be most important factors in judging the quality of milk. In Orissa, Omfed milk was perceived better than unbranded milk on thickness criterion whereas it lagged behind on taste and freshness. Pander. B.L. and Hill. W.G. (1993)48 argued that the genetic prediction of heifer’s 305-day lactation yield from complete test day records or from records in progress was investigated. The accuracies of genetic indices predict breeding value for total yield from all 10 test day records of milk, fat and protein yields were 0.71, 0.66 and 0.67, respectively. These accuracies were slightly higher than if indices were computed to predict phenotypes and from these breeding values of 305-day records. The accuracy for a repeatability model (giving equal weight to each record) was not far below that of an optimal index. Inclusion of records in progress in genetic evaluation was investigated using a repeatability model and a phenotypic index to predict the phenotype for complete lactation from test day records. Approximate expansion factors to equate the genetic variance of past records to that of complete records and weights to give to past records in genetic evaluation using an animal model were derived. For genetic prediction of heifer lactation yield from test day records, a repeatability model giving equal weight to each record could be used without increasing computational facilities and could be implemented directly in current genetic evaluation in the UK. Records in progress could easily be incorporated. Hansen and Brandon. D. (1993)49 viewed that the primary objective of his study was to develop a series of worksheets to analyze the economic, financial, risk, and environmental impacts of alternative nutrient management methods for a
48 Pander. B.L. and Hill. W.G. (1993), “Genetic evaluation of lactation yield from test day records on incomplete lactation” Livestock Production Science, Volume 37, Issues 1-2, December, Pp. 23-36. 49 Hansen, Brandon D (1993), “An Economic Model for Analyzing Alternative Dairy Waste Handling Systems,” M.A. thesis, Department of Agricultural Economics, Washington State University, Pullman, December. 42
representative western Washington dairy farmer. He considered total waste that must be handled, facilities and equipment associated with each alternative, transportation of manure to storage, storage procedure, transport to land, and soil incorporation. He examined capital investment required, annual costs, financing, cash flow, nutrient values of the waste, and financial and environmental risks. The dairy selected by Hansen needed a larger nutrient handling system to accommodate expansion for 69 additional mature cows and 42 additional heifers. He considered two alternatives: (1) add a second lagoon, use a solid separator, and purchase a big-gun pumping system for distribution of liquid nutrients on land, or (2) add a second lagoon without a solid separator, and hire a custom service to pump liquid nutrients from the lagoons. Alternative 2 had a lower capital investment, a net annual cost advantage, a lower net annual cash outflow and lower financial risk because of less debt. Alternative 1 had a lower risk of environmental damage because of excess lagoon capacity. Garsow, James D., and Sherrill B. Nott (1992)50 examined seven liquid handling systems and one solid manure handling system for three Michigan dairy herd sizes ranging from 60 to 250 cows. They found that investment costs for the least expensive system could be less than a fifth of the most expensive system. Yet, more stringent manure handling regulations could cause some producers to leave the industry because the additional costs of improved manure handling systems could force their break-even price above the expected milk price. The likelihood of a producer leaving the industry depended on the farm’s current financial position and performance. Oltenacu P.A., Smith T.R. and Kaiser H.M. (1989)51 elucidate the effect of a base-excess seasonal pricing plan on pattern of production and the role played by various factors related to management and to breeding practices on seasonality of production were investigated. A mail survey of a randomly selected group of farmers in New York State provided the data; 1061 farmers responded to the questionnaire. Seasonality coefficient (difference between spring and fall production as a proportion
50 Garsow, James D. and Sherrill B. Nott (1992), “Impact of Michigan Dairy Manure Handling Alternatives”, No. 561, Department of Agricultural Economics", Michigan State University, East Lansing. 51 Oltenacu P.A., Smith T.R., and Kaiser H.M. (1989), “Factors Associated with Seasonality of Milk Production in New York State” Journal of Dairy Science, Volume 72, Issue 4, April, Pp. 1072-1079. 43
of fall production) was used as a measure of seasonal production pattern. Three major conclusions were: 1) the use of a base-excess plan in addition to the Louisville plan reduced seasonality when compared with the Louisville plan alone; 2) seasonality was associated with region, type of housing, and herd production; and 3) farmers’ perceptions that spring milk production is more profitable than production in other seasons was an important cause of seasonality. Morgan, Russell M., and Luther H. Keller (1987)52 emphasized the need for reliable and complete cost and benefit data in their evaluation of nutrient management systems for Tennessee dairy farms. Considering alternative herd sizes, they computed direct construction and installment costs, annualized costs, and stability of cost/return relationships of different nutrient systems. They also conducted a sensitivity analysis of nutrient loss rates of different nutrient management systems during storage and varying nutrient values after application to land. They noted the substantial cost of all nutrient management systems and the fact it could be expected to increase significantly should more stringent environmental regulations be applied to the dairy farm sector (as they have now been applied in Washington). Young C.W., Hillers J.K. and Freeman A.E. (1986)53 in their comparative analysis, Production and consumption of milk fat, milk protein, and lactose were compared for 1970, 1975, 1979, and 1983 to determine whether production and consumption were balanced and, if not, to determine how balance might be achieved. Ratios of these components in milk produced remained virtually constant from 1970 to 1983. However, increased cheese consumption during this period resulted in increased per capita consumption of fat and protein despite reduced consumption of these components in other dairy products. Because lactose is not in cheese, lactose consumption declined. Because of these changes, imbalances of production and consumption of milk components now exist and are due almost entirely too much lactose being produced. Because of small variation of lactose percentage, this imbalance could be reduced by increased fat and protein percentages. Milk pricing
52 Morgan, Russell M., and Luther H. Keller (1987), “Economic Comparisons of Alternative Waste Management Systems on Tennessee Dairy Farms”, Bulletin 656, University of Tennessee Agricultural Experiment Station, Knoxville. 53 Young C.W., Hillers J.K. and Freeman A.E. (1986), “Production, Consumption, and Pricing of Milk and its Components” Journal of Dairy Science, Volume 69, Issue 1, January, Pp. 272-281. 44
should encourage this by emphasizing fat and protein (not solids-not-fat). Fat and protein differentials should differ from market to market and should be based on utilization. Milk pricing is reviewed, and a procedure for determining blend differentials is outlined. Emerson M. Babb (1981)54 analyzed the relationship between milk prices and production costs as sources of change in the level and geographic distribution of United States milk production. Milk prices and direct and total costs of production from 1974 to 1980 were estimated as a function of distance from the upper Midwest by ordinary least-squares regression. Milk prices and costs increased with distance of production areas from the upper Midwest, but the increases were less than transportation costs. The cost and price changes during 1974 to 1980 provided a strong incentive for increased milk production in all regions. Changes in milk prices and cost of production did not encourage production expansion in higher cost regions relative to expansion in the upper Midwest. Vijay Gorakh Patil (1981)55 conducted a random sample survey study on fifty dairy farmers from eight villages of Shirpur Tehsil of Dhule District of Maharashtra (India) was undertaken to know the cost of production of milk in the study area. The total cost of milk production per cow/buffalo was Rs.113.87 in which the variable cost was 83.76 percent (Rs.95.38) and remaining Rs.16.24 percent (Rs.18.49) was fixed cost. In variable cost, the cost of feed stuff was 73.39 percent (Rs.70). Labour cost was 15.73 percent (Rs.15.00), the cost of medical treatment was 2.62 percent (Rs.2.50) and interest on working capital was 8.26 percent (7.88). Finally it was found that the cost of milk was Rs.9.10 per litre in the study area. Dairy farming has been recognized as an important source of income and is more remunerative in comparison to crop production in India. Milk production in India is predominantly the domain of small farmers in mixed farming system. Scientific dairy management helps the farmer to channelize his limited resources to maximize returns from his dairy farm.
54 Emerson M. Babb (1981), “Analysis of Regional Milk Prices and Production Costs”, Journal of Dairy Science, Volume 64, Issue 10, October, Pp. 2043-2047. 55 Vijay Gorakh Patil (1981), “Marketing Analysis of Milk Production in Shirpur Tehsil of Dhule District of Maharashtra (India)” Ph.D. Research Fellow YCMOU, Nashika, Pp.(14-15). 45
The importance of dairying lies not only in products but also it brings about significant changes in socio-economic structure of rural economy. The National Commission on Agriculture (1976) observed dairying as an additional enterprise for improving the status of rural masses especially weaker sections consisting of small, medium & landless laborers. It therefore, becomes essential to examine the production cost of milk.
46
2.3. REVIEW OF LITERATURE RELATED TO CHANNELS OF MARKETING Daniel R. Block (2009)56 explored that the agricultural policy in the United States is often structured around conflicts and relationships within particular production regions. These regional solutions may evolve into national policies. This paper explores a historical example of this, the development of fluid milk policy and the fluid milk economy in the Chicago milkshed between 1900 and the New Deal. This example is particularly interesting because it was the part of the rise of the post- World War II modern food system. Both urban and rural groups were important in this development. Urban groups took a particular interest in milk production and regulation due to its importance as a nutritious but highly perishable staple. Rural groups responded to urban attempts to control production practices by organizing cooperatives. Negotiations and strikes resulted in an agreement in 1929 that was positive for farmers, the Chicago Department of Health, and other major entities in the milkshed. It attempted to place regulatory barriers around the milkshed. However, it soon failed due to improvements in transportation technology and new distribution systems that allowed for cheaper retail prices. The group then proposed a marketing plan to the USDA, which became the ancestor of the federal milk marketing order program. This story sheds light on the manner in which local interest groups and internal politics within the U.S. Department of Agriculture combined to shape New Deal agricultural legislation. India Post (2008)57 opined that the demand for value added milk products, such as cheese, dahi (Indian yoghurt) and probiotic drinks is increasing at a double digit rate. At present, India seems to be self-sufficient in meeting its requirement for milk and milk products. However, given that demand is growing faster than supply, there could be serious issues with respect to self-sufficiency in the near future. Any increase in milk production is dependent on the farm gate price received by the producer. Farm gate prices have increased by more than 50 percent in the last three years. Focused efforts would be required on two fronts increasing farm size (currently
56 Daniel R. Block (2009) “Public health, cooperatives, local regulation, and the development of modern milk policy: the Chicago milkshed 1900-1940” Journal of Historical Geography, Volume 35, Issue 1, January, Pp. 128-153. 57 India Post (2008), “Milk production reaches 111 million tonnes by 2010”, India Post, 17th September. 47
the average number of animals per producer is three to four), and increasing productivity of milk producing animals. Global milk production, approx.655 million tones in 2006/07, is estimated to be growing at 1.6 percent per annum. India ranks second in terms of milk production after the EU-27 and accounts for 15 percent of global production. Annual milk production in India was at 100.9 million tones in 2006-07 and was growing at 4 percent per annum. The market for liquid milk, as well as value-added dairy products, is still largely dominated by the unorganized sector. India has an insignificant share of the global dairy trade, less than 1 per cent, despite being a leading producer of milk. Rangasamy. N. and Dhaka. J.P. (2008)58 analysed the marketing of milk and milk products by dairy plants of co-operative and private sectors in Tamil Nadu and compared. The study is based on the data collected for toned milk, standardized milk, full cream milk, flavoured milk, butter and ghee from the selected co-operative and private dairy plants of the Coimbatore district for the financial year 2001-2002. It has been found that the marketing cost for toned milk is the same in both the dairy plants, whereas it is higher for standardized milk, full cream milk and flavoured milk in the co-operative dairy plant. The marketing cost has been found less in the cooperative plant for products like butter and ghee. All the dairy products earn more marketing margins in the private sector than in co-operative dairy plant, except for toned milk. The marketing efficiency of cooperative dairy plant for all dairy products has been observed relatively less than that of private dairy plant, except for toned milk. The study has suggested the development of co-operative dairy industry in a sustainable manner, and the co-operative dairy plants should formulate long-term vision and strategy. The study has observed that value addition in dairy products should be done without compromising the quality and consumer-oriented market research and development should be accorded greater attention. Kamat. G.S. (2008)59 has emphasised on the market-oriented dairy development. In his opinion it can alone ensure success of dairy units whether they
58 Rangasamy N. and Dhaka J.P (2008) Marketing Efficiency of Dairy Products for Co-operative and Private Dairy Plants in Tamil Nadu - A Comparative Analysis. Agricultural Economics Research Review Vol. 21 July-December, Pp: 235-242. 59 Kamat, G.S. (2008), “Dimensions of Dairy Marketing”, Kurukshetra, Vol. 26, No. 5, December, New Delhi. 48
are in public, private or co-operative sector. There is a great need to instutionalise milk trade from the stage of production to marketing. Sharma. M.L., Raka Saxena, and Dipan Das (2007)60 of their opinion that India is the leading milk producer in the world and the dairy cooperatives are the backbone of Indian dairy industry. This study has analyzed the inefficiencies existing in improving milk production, procurement pattern, marketing channels, and price spread of a dairy cooperative, Uttaranchal Cooperative Dairy Federation Ltd (UCDFL), also known as the Kumaun region of Uttarakhand and has proposed a model for eliminating these inefficiencies. It has been found that UCDFL is focused mainly on liquid milk marketing and has not adopted product diversification, which is the need of the day. Nainital and Almora districts of Kumaon region have been selected for the study; these cover almost 40 per cent of cattle population in the division, except Udham Singh Nagar. It has been found that due to insufficient margins, the number of agents working for other private dairies has increased. Different marketing channels for milk have been identified and price spread has been calculated for all the channels. Lack of business development services related to dairy industry has been found leading the farmers to disassociate from Anchal. The study has suggested that Anchal should evolve a definite policy with regard to procurement of milk in both lean and regular periods and to sustain its members, incentive package should be provided. Anchal should find ways to establish fodder banks at strategic locations for providing fodder during emergencies and periods of fodder scarcity. Local sale of milk at the society level should be encouraged to increase the popularity of Anchal brand Denford Chimboza and Edward Mutandwa (2007)61 viewed that branding is increasingly being used as a strategy for managing markets in developed countries while developing countries still lag behind. The objective of this study was to assess the level of brand awareness and factors underlying brand preference of dairy brands in Chitungwiza and Harare urban markets in Zimbabwe. A total of 90 respondents
60 Sharma. M.L., Raka Saxena and Dipan Das (2007), “Potential and prospects of Dairy Business in Uttarakhand: A Case study of Uttaranchal Co-operative Dairy Federation Limited”, Agricultural Economics Research Review, Vol. 20, Issue 2007, P. 23. 61 Denford Chimboza and Edward Mutandwa (2007), “Measuring the determinants of brand preference in a dairy product market” African Journal of Business Management Vol. 1, No. 9, December, Pp. 230-237. 49
who included individual and institutional consumers were selected using judgmental and simple random sampling respectively. Primary data was collected using structured interview schedules developed for each category of consumers. Consumer product awareness indices, cluster analysis and factor analysis were the main tools used in the analysis. The findings of the study showed that 52% of the respondent consumers were aware of ARDA dairy brands despite having come across few ARDA DDP advertisements. Four factors were identified as key determinants of dairy product choice namely promotion, price and availability of product, attractive packaging and product quality. There is need for agricultural marketers to incorporate these findings in the formulation of responsive marketing strategies. Edward V. Jesse, Norman F. Olson and Vijay P. Sharma (2006)62 opined that, in the third in depth country study, the Babcock Institute study team discusses India’s dairy sector. India is an interesting case study because it has the world’s second largest population making it the world’s largest milk-producing country. The country’s main system of dairy productions involves a smallholder production system in which most of the milk produced is consumed on the farm or distributed through informal channels. This system of production, combined with Indian policies that encourage self- sufficiency and restrict dairy imports, leaves much unused potential in the Indian dairy market. Fengxia Dong (2006)63 presented a 10-year outlook for major Asian dairy markets (China, India, Indonesia, Japan, South Korea, Malaysia, the Philippines, Thailand, and Vietnam) based on a world dairy model. Then, using Heien and Wessellsï¾’s technique, dairy product consumption growth is decomposed into contributions generated by income growth, population growth, price change, and urbanization and these contributions are quantified. Using the world dairy model, the paper also analyzes the impact of alternative assumptions of higher income levels and
62 Edward V. Jesse, Norman F. Olson and Vijay P. Sharma (2006), “The Dairy Sector of India: A Country Study” Discussion Papers from University of Wisconsin-Madison,Babcock Institute for International Dairy Research and Development. Downloaded by http://purl.umn.edu/37353 (application/pdf). 63 Fengxia Dong (2006), “Outlook for Asian Dairy Markets: The Role of Demographics, Income, and Prices” Staff General Research Papers from Iowa State University, Department of Economics, Food Policy, June, Vol. 31, No. 3, Pp. 260-271. 50
technology development in Asia on Asian dairy consumptions and world dairy prices. The outlook projects that Asian dairy consumption will continue to grow strongly in the next decade. The consumption decomposition suggests that the growth would be mostly driven by income and population growth and, as a result, would raise world dairy prices. The simulation results show that technology improvement in Asian countries would dampen world dairy prices and meanwhile boost domestic dairy consumption. Stukenberg. D., Blayney. D. and Miller. J. (2006)64 suggested that the Federal dairy programs have been instituted to assist dairy farmers in marketing their milk. Milk marketing licenses were issued for city markets in 1933 during the depression. Federal Milk Orders replaced licenses in 1937 with enactment of the Agricultural Marketing Agreement Act. Low prices returned in the late 1940s and Congress passed the Agricultural Act of 1949 creating the support program for milk. Congressional involvement in milk marketing was minimal until passage of the 1977 Farm Bill. A support price adjustment to seek favorable political responses from farmers resulted in higher prices and ultimately higher production. Large expenditures and burdensome supplies caused Congress to make major changes to both programs. Other milk marketing programs have evolved from Congressional actions, including export and promotion programs. The exciting and consolidation of the dairy processors and producers have lead to a reduction in the number of marketing orders. Rajendran. K. and Samarendu Mohanty (2004)65 explained that the operation Flood and dairy co-operatives emerged in India as the largest rural employment scheme, enabling the modernization of the dairy sector to a level from where it can take off to meet not only the country'’s demand for milk and milk products but can also exploit global market opportunities. This study reviews the existing status of milk marketing and dairy co-operatives in India and provides recommendations to meet future challenges. The results of the study indicate that 80
64 Stukenberg. D., Blayney. D. and Miller. J. (2006), “Major Advances in milk marketing Government and Industry Consolidation”, Journal of Dairy Science, Volume 89, Issue 4, April, Pp. 1195-1206. 65 Rajendran. K. and Samarendu Mohanty (2004), “Dairy Co-operatives and Milk Marketing in India Constraints and opportunities” Journal of Food Distribution Research, Vol. 35, Issue 02, P. 24. 51
percent of the milk produced by the rural producer is handled by an unorganized sector and the remaining 20 percent is handled by an organized sector. It is found that the dairy co-operatives play a vital role in alleviating rural poverty by augmenting rural milk production and marketing. Involvement of intermediaries; lack of bargaining power by the producers; and lack of infrastructure facilities for collection, storage, transportation, and processing are the major constraints which affect the prices received by producers in milk marketing. Milk quality, product development, infrastructure support development, and global marketing are found to be future challenges of India's milk marketing. Kurup (2003)66 viewed that the price realized by farmers from informal sector was Rs.9.5 to Rs.10 per litre, whereas cooperatives paid between Rs.8.00 and 8.50. Further, the middlemen who bought from them made instant cash payments whereas it took 12-15 days to realize payments from the cooperative system. Samajdar, Tanmay and Chander, Mahesh. (2003)67 in his study about the livestock husbandry of the Vangujjars of Uttaranchal also observed that even though they possess sound experience about various aspects of animal husbandry, they are vulnerable to and open for exploitation by the middlemen to whom they sell milk despite the existence of cooperatives in that area. They are often riddled with debt and stand marginalized. The study recommended that the cooperatives should come forward to find out the reasons for Vangujjars’ apathy towards cooperatives and involve them as society members. Ray and Sunil (2000)68 conducted a study in Jaipur city reported that local milkmen supply fresh raw milk at the doorsteps or to the vendor who in turn supplies it to households. The prices varied from Rs.13-20 per litre for cow’s milk depending on adulteration of milk with water and the category of customer. The price generally realized by small farmers from the local vendor was about Rs.10-12 per litre, whereas they got only about Rs.9-10 from the cooperatives. Some middlemen also deployed
66 Kurup (2003), “Livestock sector in Orissa”, Indian journal of agricultural economics, Vol. 48, P. 59. 67 Samajdar, Tanmay and Chander, Mahesh (2003), “Milk production by forest dwellers: A case of Vangujjars of Uttaranchal”, Indian Dairyman, 55(5), Pp: 49-51. 68 Ray, and Sunil (2000), “Dairy industry in Rajasthan: Problems and prospects”, Institute of Development Studies, Rajasthan, Research Note on “Economics of Milk Marketing and Price Spread in Chittor District of Andhra Pradesh”. 52
daily wage workers to collect milk by using bicycles, jeep or camel cart to collect milk from the doorstep and take it to different selling points in nearby major cities. Sharma (2000)69 conducted an opinion survey in Andhra Pradesh regarding the consumer perception and attitude towards the different sources of milk purchase. It revealed that a majority of the families purchase milk from private vendors due to non-availability of Dairy milk within the reasonable distance from the consumer’s residence. Several households reported that the housewives are unable to collect the milk in person from the milk booths as it involves time and energy and they are forced to employ servants for collection of milk from the booths, which involves additional cost and delay. Further, they also expressed dissatisfaction with the present arrangement of milk supply from the booths and suggested home delivery. Nearly, 60 percent of the families felt that the home delivery of milk in polythene sachets is advantageous and indicated willingness to pay additional costs/service charges for the same. So, the co-operatives may have to seriously think about the system of home delivery of milk in order to bring more consumer families under its fold. Other reason for household preference to private vendor was non-availability of milk in small packing of less than half litre with the Dairy as several small families and those belonging to lower income groups strongly felt that such facility is essential to enable them to purchase the Dairy milk. It is also true with small size families irrespective of their economic status. Similarly, it was also noticed that in Orissa, a majority of higher income group (85.6%) were not purchasing OMFED milk due to absence of home delivery, poor taste, less cream, bad smell and nonavailability of credit structure in co-ops. There was also strong correlation between income and proportion of home delivered milk. For example, in Orissa, the percent of milk that was home delivered increased from 40 percent for those with income less than Rs.4,000 to 63 percent for those with income more than Rs.10,000. Shah, D. (2000)70 in his opinion that the predominance of middlemen in this area was mainly due to the non-existence of co-operative infrastructure. Generally, the middlemen advanced money to needy milk producers and procured milk at a low
69 Sharma (2000), “Marketing of milk - An opinion survey of consumer perceptions, Rajahmundry, AP”, Indian Journal of Marketing, Vol. 2, No. 4, Pp. 10-13. 70 Shah, D. (2000), “An Enquiry into Producer Members’ Perception towards Working of Milk co-operatives in Maharashtra”, Indian Dairyman, Vol. 32, No. 6, Pp. 31-41. 53
price round the year. It was reported that 75 percent of marketed surplus of small producer’s production was cornered by them. Similar observations were reported in a study conducted in Jalgaon and Kolhapur districts of Maharashtra. Owango. M., Staal. S.J. and Lukuyu. B. (1998)71 in their opinion Liberalisation in the dairy industry in Kenya is currently under way in several forms. The urban milk market monopoly of the Kenya Co-operative Creameries has been lifted. Clinical veterinary and artificial insemination (AI) services are no longer publicly supported in many areas. Private sector response to these reforms was expected to be the greatest in the high-potential market-oriented dairy zones of Central Province, where the dairy farmers' co-operative societies play a central role in meeting the needs of dairy producers. A survey conducted by the authors measured the changes between 1990 and 1995 in milk marketing and service provision by the dairy co-operatives. Tabular and GIS analyses were used to evaluate the survey data. Dramatic changes in milk market patterns are apparent, in ways unintended by the policy reforms. Most notable has been a large increase in the role of the unregulated raw milk market. This helped increase real milk prices paid to producers by up to 50%, but also led to a steepening of the price gradient with distance from urban consumption centres. Large increases were observed in the provision of veterinary and AI services by the dairy farmers' co-operatives societies, whose producer client base and credit facilities may enable them to compete effectively with the independent private sector. Market liberalisation therefore expanded the role of the raw milk market and the participation of the dairy farmers' co-operative societies in milk marketing and the provision of input services. Deepak Shah (1997)72 viewed that though milk production in Maharashtra over last decade has increased by leaps and bounds, only 25 percent of the milk co-operatives are economically viable in the state. Differential price structure and mismanagement of co-operatives has led to poor procurement of milk resulting in vast regional imbalances in terms of milk production. For the smooth functioning of the
71 Owango. M., Staal. S.J. and Lukuyu. B. (1998), “Dairy co-operative and policy reform in Kenya: effects of livestock service and milk market liberalization” Food Policy, Volume 23, Issue 2, April, Pp. 240-247. 72 Deepak Shah (1997), “Co-operative Dairying in Maharashtra Lessons to be Learned”, Economic and Political Weekly, September 27, Vol. 32, No. 39, P. 12. 54
milk co-operatives, it is not enough to give remunerative prices to the producers, but the co-operatives themselves should take over the onerous task of ensuring necessary inputs so as to improve productivity and overall genetic stock of milch animals. Ntengua Mdoe, Steve Wiggins (1996)73 in their view a priority in developing African dairy industries is to build marketing systems which provide incentives for local farmers and supply consumers with the produce they demand. Studies were carried out in Kilimanjaro Region, northern Tanzania to investigate the regional demand for dairy produce and the marketing system. Demand proved to be buoyant, with an average LME consumption of 142 kg/person/year and an income elasticity of demand of 0.9 in the urban areas, and 45 kg/person/year and 1.1 for the rural areas. The main products taken were fresh and sour milk. More than half, the milk was consumed in the rural areas. Demand was forecast to grow from 1990 to 2000 at 5%/year. The marketing system consisted of competing multiple channels involving a parastatal, cooperatives and private traders. There was ample evidence that the system was efficient, with producers obtaining as much as 78% of the final milk price. The main policy concern was the adequate upkeeping of rural feeder roads during the rains. Public intervention in marketing was not necessary for successful development of a regional dairy industry in this case. Vijayalakshmi S., Sitaramaswamy J. and John De Boer (1995)74 in their remarks on developmental efforts for animal production systems in India started with organized milk procurement, processing and marketing. Most rural areas around Bangalore and Kolar districts of Karnataka state are covered by an organized dairy development program. Parallel to this organized sector, the unorganized (informal) dairy sector also functions with different strategies. This study compared the cost of procurement/distribution of the organized and informal sectors of the dairy industry in Bangalore and Kolar districts. The optimum quantity of milk to procure per collection route in the organized sector was calculated and a saving of Rs.0.09 kg−1 of milk marketed could be generated using this level, compared to a loss of Rs.0.13 kg−1 of
73 Ntengua Mdoe, Steve Wiggins (1996), “Dairy products demand and marketing in Kilimanjaro, Tanzania”, Food Policy, Volume 21, Issue 3, July, Pp. 319-336. 74 Vijayalakshmi S., Sitaramaswamy J. and John De Boer (1995), “Rationalisation of milk procurement, processing and marketing in southern India” Agricultural Systems, Volume 48, Issue 3, Pp. 297-314. 55
milk marketed under existing conditions. By contrast, the informal marketing sector, by using differential procurement price, diversified procurement channels and selective selling channels, earned Rs.0.42-0.77 kg−1 of milk marketed. To reduce losses in the organized sector and assist producers who are not able to participate in the formal sector, control points in the existing system were identified and analyzed. Pawar and Sawant (1995)75 examined the marketing efficiency of three channels - private, cooperative and government - in Western Maharashtra. Their results suggest that private dairies paid somewhat higher prices to the producers and still managed to supply milk to the consumer at competing prices. This was due to higher efficiency in procurement, processing, transportation and distribution. Kalsi, (1992)76 viewed that the unorganized sector usually scores over the organized sector on account of the consumers’ confidence, the richness of milk as indicated by “Malai” on milk, the freshness of their products, their ability to give credit and the low overheads. Raju, (1992)77 opined that the general practice of milk vendors in Hyderabad was that they finance the producers for purchasing milch animals and other personal needs and thereby bind the producer to sell milk to them round the year. Richard F. Fallert, et al. (1978)78 examined the major structural changes in marketing occurring with the integration of food chains into the processing and distribution of fluid milk. Thus, the objectives of this study were 1) to determine the extent of vertical integration by food chains and 2) to explore the implications of such for the dairy industry. The study was confined to the Southern Region. Response to a survey indicated that 60% of the food chains were involved in some type of vertical integration with 84% of these initiated during the past 15 yr. Lower cost and uniform merchandising were the most prominent reasons for having some type of central milk buying programs. Vertical integration leads to increased market power of food chains and can affect both price and market structure. The actual vertical integration of food
75 Pawar and Sawant (1995), “Comparative efficiency of Alternative milk marketing agencies in western Maharastra”, Indian Journal of Agricultural Economics, Pp. 160-167. 76 Kalsi (1992), “Let’s All Do It- Market More Milk”, Indian Dairyman, 44(8), Pp. 393- 400. 77 Raju (1992), “Market survey of liquid milk in Hyderabad”, MTS Report (Unpublished). Institute of Rural Management, Anand, Gujrat. 78 Richard F. Fallert, et al. (1978), “Food Chain Integration and Fluid Milk Marketing”, Journal of Dairy Science, Volume 61, Issue 7, July, Pp. 983-987. 56
chains into fluid milk processing through ownership of processing facilities tends to increase the barriers to entry into a market. For processors, the barrier is the non- availability of market outlets. For the food chain, the number of stores and ownership of processing facilities for fluid milk necessary to compete economically may be the barrier. A continuation of these structural trends can be expected.
57
2.4.REVIEW OF LITERATURE RELATED TO CONSTRAINTS IN MILK PRODUCTION AND MARKETING
Shisode. M.G., Dhumal. M.V. and Siddiqui. M.F. (2009)79 on their opinion that the constraints expressed by the dairy cattle owners of Rajarambapu Patil Sahakari Dudh Sangh Ltd. Islampur as regards the reproduction, nutrition, management, health, economic and milk distribution were studied. Some remedial measures like trainings, exhibitions, brain storming sessions, poster presentations, radio talks and programmes on Door-darshan can be taken up to create awareness in dairy farmers and to impart knowledge to them to undertake new animal managemental practices to increase the milk yield. Peter Enderwick (2009)80 analyses the problem of “quality failure” in China using as an illustration the recent case of melamine contaminated dairy products. This conceptual paper examines whether it is possible to anticipate the incidence of quality fade and, if so, what can be done to minimise the likelihood of such problems occurring. Drawing on theoretical frameworks of alternative transactions governance modes, the discussion highlights the interaction between environmental operating conditions and effective governance modes. The discussion suggests that it is possible to anticipate quality and safety problems and identifies the key environmental conditions in China that contribute to the problem of quality deterioration. Analysis of three primary transaction governance modes - contracts, hierarchy and trust - and local operating conditions reveal a dairy industry which, in contrast to many of the developed economies, is highly fragmented, politicised, ineffectively regulated and characterised by corrupt and opportunistic behaviour. The dairy industry case provides a concrete application of recent conceptual analysis of quality and safety concerns in emerging markets. This case allows the derivation of recommendations on appropriate management practices for maintaining quality in the challenging business environment of China.
79 Shisode. M.G., Dhumal. M.V. and Siddiqui. M.F. (2009), “Evaluation of constraints faced by farmers in adoption of dairy cattle managemental practices”, The Indian Journal of Field Veterinarians, Volume 5, Issue 1, P. 26. 80 Peter Enderwick (2009), “Managing Quality Failure in China: lessons from the Dairy Industry Case”, International Journal of Emerging Markets, Vol. 4, Issue 3, Pp. 220-234. 58
Albert Christopher Dhas (2008)81 in his opinion, from independence, size and composition of bovines in Tamil Nadu showed differential growth pattern. The total bovine population showed an increasing trend up to the early-Sixties and thereafter stagnant till the early Eighties. While the milch animal stock increased steadily, the work animals showed a declining trend from seventies. These trends not only indicate the growing importance of dairy animals but also the competitive linkage between work and milch animal population. The work animal stock is highly influenced by the agro-climatic, institutional and economic factors and an analysis of capturing them is attempted in this paper. Initially, the changes in the size and composition of bovines, work animal population and its density since independence are traced. Subsequently, the factors determining work animal population and its density are examined using regression models. Two regression analyses are made; one representing phase I (1956-1974) and the other for phase II (1977-1994). Phase I basically represents the period when mechanization in agriculture had been at the early stages and phase II represents the period when mechanization (both energisation of irrigation and tractorisation) was at a relatively higher level. The study revealed that while the agro-climatic and irrigation factors had played a major role in shaping the work animal density during the period prior to mid-Seventies, the technological, economic and institutional factors played a major role in recent years. Satbir Singh, Timothy James Coelli and Euan Fleming (2008)82 viewed that, Since the 1970s, the policy of Indian government has been to promote dairy development on the basis of the cooperative organizations. During the 1990s the dairy industry in India was liberalized. This study examines the impact of the liberalization policy on the cooperative dairy plants in India. Data envelopment analysis (DEA) and the Fisher index approach are applied to measure economic efficiency and total productivity changes, respectively. The data involves 65 observations from a complete panel of 13 cooperative dairy plants from 1992/93 to 1996/97. The
81 Albert Christopher Dhas (2008), “Determinants of Work Animal Density in Tamil Nadu: An Econometric Analysis”, MPRA Paper from University Library of Munich, Germany. 82 Satbir Singh, Timothy James Coelli and Euan Fleming (2008), “Efficiency and Productivity Analysis of Cooperative Dairy Plants in Haryana and Punjab States of India” Working Papers from University of New England, School of Economics. 59
empirical results show that the deregulation and liberalization of the dairy industry alone is not the answer. Shamsuddin. M., Alam. M.M. and Hossein. M.S. (2007)83 assessed resources, challenges and prospects of the dairy industries in four districts of Bangladesh (Mymensingh, Satkhira, Chittagong and Sirajganj) with the participation of 8 to 12 dairy farm families in each district. We used ten participatory rural appraisal (PRA) tools, namely social mapping, semistructured interview, activity profiles, seasonal calendar, pie charts, mobility diagram, matrix ranking, preference ranking and scoring, system analysis diagram and focus group discussion in 57 PRA sessions from September through October 2002. Dairying contributed more to family income (63 to 74%) and utilized a smaller portion of land than did crops. Twenty seven to 49% of cattle feed is rice straw. Only Sirajganj and Chittagong had limited, periodic grazing facilities. Fodder (Napier, Pennisetum purpureum) cultivation was practised in Sirajganj and Satkhira. Fodder availability increased milk production and decreased disease occurrence. Friesian crossbred cows were ranked best as dairy cattle. The present utilization of veterinary and AI services were ranked highly. Farmers outside the milk union desired milk purchasing centres as the most required service in the future. They identified veterinary and AI services as inadequate and desired significant improvements. The PRA tools effectively identified resources, constraints, opportunities and farmers’ perspectives related to the dairy industries in Bangladesh. Kathiravan. G., Thirunavukkarasu. M. and Selvakumar. K.N. (2007)84 opined that the Livestock has been an integral part of the Indian rural economy and an indispensable tool of income and employment generation to millions of poor households in India. A study was undertaken in Tamil Nadu (India) to ascertain the cost of livestock services availed by farmers. The districts of Tamil Nadu state were classified into two categories, viz., ‘livestock-developed’ (LD) and ‘livestock under developed’ (LUD), based on initial baseline. The cost of treatment of cattle was more
83 Shamsuddin. M., Alam. M.M. and Hossein. M.S. (2007), “Participatory rural appraisal to identify needs and prospects of market-oriented dairy industries in Bangladesh”, Trop Animal Health Prod, Vol. 39, Pp. 567-581. 84 Kathiravan. G., Thirunavukkarasu. M. and Selvakumar. K.N. (2007) “Cost of Livestock Services: The Case of Tamil Nadu (India)” Journal of Applied Sciences Research, Vol. 3, No. 10, Pp. 1195-1205. 60
compared to other species of animals with the similar disease condition. The mean cost of treatment of a chronic medical case in cattle at a public veterinary centre was INR 20.83, in which the labour cost alone accounted for INR 17.35, with the remaining amount for the drugs purchased outside. However, the mean costs of treating a chronic medical condition in buffalo and small ruminant at public veterinary centres were only INR 13.34 and INR 10.80, respectively. Cost of treating an acute surgical case in cattle at a public veterinary centre was INR 43.08 and treating a chronic surgical case was INR 41.85, while an acute medical case cost INR 35.69 and a gynaecological case INR 31.68. The major component of cost in all cases was the labour cost incurred to bring sick animal to the centre. The charge collected at public veterinary centres per insemination was uniform at INR 15.00. However, the average total cost, including labour cost for transport accrued to the farmers varied from INR 27.58 for cows to INR 29.17 for buffaloes. Overall average cost of insemination by engaging a veterinarian at farm gate was INR 57.83 for cows and INR 45.00 for buffaloes. Although no charges were made for animal health care services rendered at public veterinary centres, the charges in terms of imputed labour cost for bringing the animal to the centre was incurred. Service fee accounted for more than 60 per cent of cost of treatment for home service by a veterinarian or a para-veterinarian. Frank H. Fuller, Jikun Huang, and Scott Rozelle (2006)85 pointed out that with the rapid growth in China’s dairy industry, a number of recent papers have addressed either the supply or the demand trends for dairy products in China. None, however, presents a systematic explanation for the recent growth in both the supply and demand for dairy products. The goal of this paper is to sketch a more comprehensive picture of China’s dairy sector and to assess the nature of the sectorï’s development in the coming decades. Drawing upon several empirical studies, we examine the trends in dairy product consumption to create a composite picture of the factors underlining the recent growth. We also empirically investigate the sources of production gains in milk supply and assess the relative importance of expanding herd
85 Frank H. Fuller, Jikun Huang, and Scott Rozelle (2006), “Got Molk? The Rapid Rise of China's Dairy Sector and Its Future Prospects”, Food policy, June, Vol. 31, Pp. 201-215. 61
size, changes in the nature of production, technological change, and improvements in efficiency to the overall growth of milk production. Rajarajan. T.R. (2006)86 opined that the combined effects of both domestic reforms and WTO commitments in the last decade have changed the environment in which the Indian dairy industry will operate in future. A term of trade is a significant indicator of gains from trade and efficiency of domestic industry. In average terms, the terms of trade of Indian dairy products have declined in the post-liberalization period compared to pre-liberalization years. The year-wise trend is unstable with wide fluctuations in post-liberalization years. The real effects of trade liberalization will unfold only when the WTO provisions are properly implemented. Yue Yaguchi and Kei Kajisa (2006)87 pointed out that it was widely believed that not only a Green Revolution in a crop sector but also a White Revolution in a dairy sector has generated the great momentum of agricultural development in India since the late 1960s. However, owing to the dominance of sector-specific analyses, the importance of the interaction between these two sectors has been neglected in the existing literature. The interaction is important in that the dairy sector provides manure to crop production while the crop sector supplies fodder to the dairy. Using household data collected in Tamil Nadu, India for three decades from 1971, we show that the increase of fodder production as a byproduct of Green Revolution in 1970s enabled subsequent White Revolution in 1980s and the byproduct of the White Revolution, i.e., increased manure availability is enhancing the recent revival of organic farming system for sustainable agricultural development. Suzuki N. and Kaiser H.M. (2005)88 in their opinion, say that Dairy is highly regulated in many countries for several reasons. Perishability, seasonal imbalances, and inelastic supply and demand for milk can cause inherent market instability. Milk buyers typically had more market power than dairy farmers. Comparative production advantages in some countries have led to regulations and policies to
86 Rajarajan. T.R. (2006), “Trade Liberalization and Terms of Trade in Dairy Products in India”, The IUP Journal of Agricultural Economics, 2006, Vol. III, Issue 1, Pp. 22-26. 87 Yue Yaguchi and Kei Kajisa (2006), “Production Systems in South India from 1971 to 2002”, Annual Meeting, August 12-18, Queensland, Australia from International Association of Agricultural Economics. 88 Suzuki N. and Kaiser H.M. (2005), “Impacts of the Doha Round Framework Agreements on Dairy Policies”, Journal of Dairy Science, Volume 88, Issue 5, May, Pp. 1901-1908. 62
protect local dairy farmers by maintaining domestic prices higher than world prices. A worldwide consensus on reduction of border measures for protecting dairy products is unlikely, and dairy will probably be an exception in ongoing World Trade Organization (WTO) negotiations. Under the Doha Round framework agreements, countries may name some products such as dairy as “sensitive,” thereby excluding them from further reforms. However, new Doha Round framework agreements depart from the current WTO rule and call for product-specific spending caps. Such caps will greatly affect the dairy sector because dairy accounts for much of the aggregate measure of support (AMS) in several countries, including the United States and Canada. Also, the amount of dairy AMS in several countries may be recalculated relative to an international reference price. In addition, all export subsidies are targeted for elimination in the Doha Round, including export credit programs and state trading enterprises, which will limit options for disposing of surplus dairy products in foreign markets. Currently, with higher domestic prices, measures for cutting or disposing of surpluses have been used in many countries. Supply control, which is not regulated by WTO rules, remains as an option. Although explicit export subsidies are restricted by WTO rules, many countries use esoteric measures to promote dairy exports. If countries agree to eliminate “consumer financed” export subsidies using a theoretical definition and measurements proposed herein as Export Subsidy Equivalents (ESE), dairy exports in many countries may be affected. Although domestic supports and export subsidies will be reduced in the Doha Round, possible exclusion of “sensitive” products from tariff reduction will help some countries’ dairy sectors survive after those final agreements. A key concern for those countries will be the simultaneous restriction of surplus-disposing measures. With fewer marketing options for surpluses, countries that continue border protection and high internal prices will likely be forced to use domestic supply control programs in the future. Rajput A.M. and Sandeep Yadav (2004)89 in their study in indore district of Madhya Pradesh study the economics and identify the constraints relating to cross
89 Rajput A.M. and Sandeep Yadav (2004), “An Economic Analysis of Cross-bred Cow Milk Production and Identification of Constraints in Indore Districts of Madhya Pradesh” Indian Journal of Agricultural Economics, Vol. 59, No. 3, July-Sep., Pp. 614. 63
bred cow milk production. Specifically, it examines the cost and returns per year, the net return, cost of milk production per litre and benefit cost ratio on small, medium and large size groups of cross bred cow farms. Multi stage stratified random design was used for the selection of the ultimate unit of the sample. Indore block of the Indore district was selected for the study and five villages were selected randomly from Indore Block. In all 50 milk producer households were selected for one allocation period covering the agricultural year 2003-2004 and the data was collected by survey method. The results of the study revealed that, on an average, the total cost of maintenance of a cross bred cow per annum was worked out to Rs.21, 657.76. After deducting the income received from cross bred cow dung and sale of the young stock, the average net cost of maintenance came to Rs.19,942.15 per cross bed cow. The farmers of large size groups had incurred higher expenditure on the maintenance of a cross-bred cow as they had maintained cross-bred cows of relatively better breed and had made higher investment on fodder and concentrates for maintaining them. However, large number of cross bred cow dairy entrepreneurs complained that the weak financial status, cost factor and management difficulties were the main constraints in not maintaining good quality of animals on the farms. The respondent’s farm families strongly expressed the dire need for finance for the purchase of animals and also for feed, fodder and veterinary aid. A large number of commercial cross bred cow dairy entrepreneurs reported insufficient storage facilities on their farms. Milk and milk products fall under highly perishable group of commodities and have to be stored under controlled conditions of temperature and humidity in cold storage and deep freezers. Sukhpal Singh (2004)90 pointed out that Indian dairy industry has witnessed many policy and market changes in the last decade both in the domestic as well as the international markets. In this context, this paper examines the profile of organized private sector in liquid milk business, its growth, performance, business and marketing strategies and prospects, with special reference to the Gujarat state and the Ahmedabad milk market, besides assessing the impact of policy changes in the recent
90 Sukhpal Singh (2004), “Liquid Milk Business in India after Delicensing: A Case study of Ahmedabad Milk Market” Indian Journal of Agricultural Economics, Vol. 59, No. 3, July- Sep., Pp. 607. 64
years. It is primarily based on the secondary data and the interviews with the co- operative and private dairy unit owners and managers in Ahmedabad city mainly focused on liquid milk as Ahmedabad is one of the most competitive milk markets in the country with more than 25 brands of liquid milk being marketed in the city. The nature and dynamics of the Ahmedabad milk market are analysed and marketing strategies of various types of players are examined. The policy of delicensing and its impact on milk marketing in India is also addressed. The paper concludes by discussing important steps for achieving competitiveness in the domestic and international markets. Dhawal Mehta, Jatin Pancholi and Paurav Shukla (2004)91 in their action research have extensively used world-wide for decision making related to policy due to its nature of involving the researcher and decision maker in the process. Following independence in India, one of the major revolutions was brought about in the dairy sector with regard to complete management systems. Most innovations and changes occurred in the line function while the staff function was more often neglected in the overall change. The authors undertook an action research study focusing on staff function and re-laid improvements that can influence policy related to decision making. The authors have also developed the MPS model for staff function which can help a company or industry in appraising their own staff and functions which can thereby aid in utilizing their potential. Ashutosh Shrivastava (2003)92 conducted a study to find out the impact of milk processing on income and employment on small farms of Damoh district, Madhya Pradesh and to examine the problems faced by the small milk processing farms and suggest measures thereon. Twenty small milk processing farms mainly producing deshi ghee and 20 non-milk processing farms were selected. The study concludes that the processing of milk definitely increased income and employment of the small milk processing units compared to non-milk processing units which sold directly to other vendors. The major problems faced by the processing farms are non- availability of good quality of milch animals, inefficient management of feeding and
91 Dhawal Mehta, Jatin Pancholi and Paurav Shukla (2004), “Action research in policy making: a case in the dairy industry in Gujarat, India”, AI & Society, Vol.18, No.4, Pp.344-363. 92 Ashutosh Shrivastava (2003), “Impact of Milk Processing on Small Farms: Case Study”, Indian Journal of Agricultural Economics, Vol. 58, No. 3, July-Sept, Pp. 620. 65
breeding of animals, lack of proper organized market system (farmers did not receive remunerative prices every time), lack of storage facilities, technical and infrastructure support system and packaging facilities. To overcome these problems the study suggests that since the processing units are looked after by household workers, good training programmers for managing these units be developed for manufacturing low cost packaging material and dairy feed formulations at the village level. The collection centres must be established on co-operative basis. Sufficient financial assistance by the government credit agencies at cheaper rates of interest must be provided to encourage the small producers and infrastructure facilities and extension activities must be developed. Sarvesh Kumar and Sirohi Smita (2003)93 opined that the Indian dairy industry has undergone substantial changes during the 1990s due to opening of dairy products processing for the private players after industrial delicensing in 1991. At the same time concerns have emerged about the viability of increasing number of private processing units competing with each other and with existing plants for fixed supply of raw material, that is milk. The study attempts to address this concern using the data of financial statements of 30 dairy processing firms in the private sector (including 5 multinational corporations) for the period 1991-92 to 2000-2001. The economic performance of these firms is assessed on the basis of growth trends and ratio analysis. The growth trends indicate positive growth in scales (at current prices) and value of output (at constant prices) for 25 out of 30 firms and compound annual growth rate varied from 172 percent to 4.20 percent for sales and 147 percent to 1.43 percent for value of output. The newly established firms registered very high growth rates due to low base levels. The investments in terms of gross fixed assets (at current prices) also increased in all the firms excepting one. It was found that there existed in general large inter-firm variations in the economic performance of the dairy forms. On one hand, are the MNCs that have made heavy investments in dairy business, capturing a sizeable share of the market showing good economic performance. On the other extreme are the chronically sick units and some other poor performing ones
93 Sarvesh Kumar and Sirohi Smita (2003), “Performance of Dairy Industry in Post- Liberalisation Period”, Indian Journal of Agricultural Economics, Vol. 58, No. 3, July-Sept, Pp. 631. 66
that are basically facing teething problems. In between these two extremes are some Indian firms that have shown considerably good performance and have a foothold in the market. One common problem affects all the firms is the underutilization of installed capacity due to shortage of raw milk in relation to their processing capacities. The establishment of large number of private dairy plants after industrial delicensing has aggravated the shortages. The study concludes that the dairy industry has the potential of improving its performance provided that there is more milk flow through the organized sector. David A. Hennessy and Jutta Roosen (2003)94 of their opinion that the Milk production is seasonal in many European countries. While quantity seasonality poses capacity management problems for dairy processors, a European Union policy goal is to reduce price seasonality. After developing a model of endogenous seasonality, we study the effects of three E.U. policies on production decisions. These are private storage subsidies, production removals, and production quotas. When cost functions are seasonal in a specified way, then arbitrage opportunities interact with storage subsidies to reduce both price and consumption seasonality. But production seasonality increases because storage subsidies promote temporal market integration. Conditions are identified under which product market interventions increase quantity seasonality. Jan M. Sargeant, et al. (1998)95 studied the association between protein production and individual-cow reproductive performance, health, and culling were investigated in a 2-year observational study involving a convenience sample of 75 Ontario, 5 Alberta, and 3 Nova Scotia dairy farms. Protein production was defined by 305-day lactation protein yields and by estimated breeding values for protein yield. After controlling the level of milk production, herd, parity, breed, and season of calving, there were no significant associations between either measure of protein production and days open or days to first breeding. The only associations between protein production and disease were small positive associations between the estimated
94 David A. Hennessy and Jutta Roosen (2003), “Cost-Based Model of Seasonal Production, with Application to Milk Policy, A” Journal of Agricultural Economics, Vol. 54, July, Pp. 285-312. 95 Jan M. Sargeant, et al. (1998), “Association between milk protein production and reproduction, health and culling”, Preventive Veterinary Medicine, Volume 35, Issue 1, 16 April, Pp. 39-51. 67
breeding value for protein yield and cystic ovaries and mean lactation somatic cell count. The risk of culling, after controlling for the level of milk production, was negatively associated with previous-lactation 305-day protein yield for parity three animals only. The estimated breeding value for protein yield had a small negative association with the overall risk of culling, although the associations were not significant for individual lactations. Janakiraman.K. (1990)96 pointed out that the scientific management of a dairy herd is essential not only to exploit the genetic potential of the animals, but also for taking care of the animals and use the resources in an optimal manner. The management inputs have been decomposed into various aspects like breeding, feeding, housing, health management and general up keeping of animals. Almost all the stalls maintained their own bulls for breeding purposes. Though the State Government has set up stockmen / artificial insemination (AI) centers in the vicinity of the area where most of the stalls are located, the majority of stall owners preferred natural service to AI because of high success rate. The success rate in AI is reported to be low. Robert W. Blake (1979)97 in his study emergence of government action to define a national policy on food and nutrition implies increased emphasis on programs for food production and marketing. Optimal policy will rely upon information from targeted basic and applied research. Dairy cattle are discussed in the context of their comparative advantage among livestock species for providing high quality protein in the human diet Research needs are suggested to supply economical milk protein by improving biomass efficiency, economic efficiency, milk pricing, and aggregate analyses of systems of dairy production. Nagarcenkar. R. (1979)98 viewed that all the dairy herds in the Bikaner city were situated either inside the walled city or in the adjoining areas. A part of the residential house was converted into cattlesheds to house the animals. No additional
96 Janakiraman. K. (1990), “Hand Book of Animal Husbandry, Publication and Information Division, Indian Council of Agricultural Research”, Indian Journal of Agricultural Economics, Vol. 57, No. 2, April-June, New Delhi, Pp. 560-595. 97 Robert W. Blake (1979), “Research Needs to Supply Milk Protein in the Human Diet” Journal of Dairy Science, Volume 62, Issue 12, December, Pp. 1963-1977. 98 Nagarcenkar. R. (1979), “Dairy Hand Book (Production), National Dairy Research Institute, Karnal”, Indian Journal of Agricultural Economics, Vol. 57, No. 2, April-June. P. 227. 68
land was available with the dairy owners to grow fodder for the animals. On an average, 404, 623 and 1309 sq. meters (sq.m) area was available to maintain an average small, medium and large herd respectively. In other words, the area allocated to each animal varied from 17 to 18 sq.m. which included the area for feeding, milking and free movement. These areas were quite close to the recommended floor space (15. sq.m) per animal. Chapter - III
Profile of the study area and Methods and Materials 69
CHAPTER – III PROFILE OF THE STUDY AREA AND METHODS AND MATERIALS
This chapter outlines the research design of the present study including sampling technique and analytical procedures adopted for the analysis of data. The first section gives profile of the study area. The second section records concepts and definitions of the terms used, the data base and period of the study, sampling design and statistical tools used.
3.1. PROFILE OF THE STUDY AREA Thanjavur District The composite Thanjavur District comprising the present Thanjavur, Thiruvarur and Nagapattinam districts along with the composite Trichy district was known as Chola Nadu or Chola Mandalam in ancient days. Thanjavur was the capital of Chola kings for many years and later Maratha rulers had this place as their headquarters. Even now, the Maratha Royal Family has their heirs in Thanjavur. Thanjavur district is one of the 30 districts in Tamil Nadu. The district was carved out from the composite district of Thanjavur, which had been trifurcated into Thanjavur, Thiruvarur and Nagapattinam. This district is a part of Cauvery delta with rich and fertile soil. This district is contributing the major part of the food grains particularly paddy to the state pool and hence popularly known as “Rice Bowl” of Tamil Nadu and “Granary of South India”. A very old and efficient canal irrigation system has facilitated agriculture to be the main occupation of the population. The “Stanley Reservoir” constructed during pre-independence period across Cauvery River at a distance of about 200km northwest of Thanjavur is still serving as the chief source of surface water irrigation in Thanjavur delta. Water received from the dam through Cauvery River is well regulated at Grand Anicut located at a distance of 28 kms and distributed in a balanced way through three main systems like Cauvery, Vennar and Grand Anicut canal. However in the recent past, the storage capacity in the Stanley Reservoir has become low and people of the district are being forced to venture upon other sources for irrigation water particularly ground water. 70
The district has 14 blocks at present bound by Tiruchirapalli, Ariyalur and Cuddalore districts in the north, Pudukkottai district in the west, Bay of Bengal in the south and Thiruvarur and Nagapattinam districts in the east. The district lies between 90 50’ and 110 25’ northern latitude and 780 45’ and 790 25’ of eastern longitude. The soil is fertile because of the deltaic terrain and greater part of the district consists of an undulating plain bisected by the valley of Cauvery. The climate is tropical and the district falls under the category of medium and high rainfall region with average rainfall around 1020 mm. Majority of the rain is received through North East Monsoon (October to early December). The economy of the district is basically agrarian and about 75 per cent of the work force is depending on agriculture. Paddy is the main crop of the district and raised in nearly 60 per cent of the cropped area. Sugarcane, groundnut, pulses, gingelly and coconut are the other important crop s cultivated in the district. Surface irrigation is the main source of irrigation. Cauvery, Vennar, and Grand Anaicut Canal with their subsidiaries viz. Vettar, Kudamurutti, Thirumalairajan, Veerachozhan, Arasalar, Agniyar, Kalyana Odai and Poonaikuthi river constitute the irrigation system of the district. Being a land of temples, Thanjavur had always been the patron of fine arts and crafts. Bharathanatyam and Carnatic Music have their strong roots in Thanjavur. Thanjavur paintings and Thanjavur art plates are special items of the district. Thanjavur town is known for music instrument manufacturing especially, Veena and Harmonium. The areas near Kumbakonam are famous for icon making, bell metal wares, lead utensils and silk sarees. Pith work known as Netti work is also predominant in many places. The basic strategies advocated under agro-climatic Zonal Planning System is to include improvement of Cropping systems, development of land and water resources, animal husbandry and fisheries activities. The district has large tracts of land suitable for horticulture activities. Dairy rearing is popular allied activities. Poultry farming also is done in some places. The district is blessed with the presence of substantial network of various Govt, departments, banking network and specialized agencies like the Soil and Water Management Research Institute, Soil Survey and Land Use Organisation, Tamil Nadu Rice Research Institute, Paddy Processing Research Centre, Regional Coir Training and Development Centre, Marine Products 71
Export Development Authority, etc. The district is industrially backward with 5 blocks classified as Industrially Most Backward and six Blocks as Industrially Backward. Well-developed Hand loom and Handicrafts Sector include activities like icon making, lamp making, art-plates manufacture, musical instruments production etc. The dependability of ground water is further increased by the vagary of monsoon as well as poor intensity of rainfall in the delta. This situation had put people to lots of hardships affecting even the drinking water supply in addition to agricultural instability. When there is flow in Cauvery River, natural recharge is taking place in the delta area. With surface water availability not guaranteed, to the full extent, at a time when it is needed, people resorted to exploit the ground water in large proportions. This has caused lowering of water table in the area especially in summer months. In Thanjavur district, coastal habitations are facing severe drinking water supply problems especially in summer. The people depend on the land utilization pattern. It is influenced by many factors, one of which is environment pollution, which has been found to affect land productivity. The land utilization pattern of the study area is analyzed and the data are presented in Table 3.1. 72
TABLE NO: 3.1 LAND USE PATTERN
S. Area Percentage to Land Classification No. (in Hectares) total area
1. Geographical area 339657(Sq kmt) 100.0
2. Forest 3390 1.0
3. Barren & uncultivable Land 2149 0.6
4. Land put to non-agricultural Use 81676 24.1
5. Cultivable Waste 13800 4.1
6. Permanent pastures and Other Grazing lands 1385 0.4
7. Land under Miscellaneous tree crop and groves (not included in Net Area Sown) 5010 1.5
8. Current Fallow 9404 2.8
9. Other Fallow land 29913 8.8
10. Net area sown 197817
11. Area sown more than once 54263 27.43
12. Gross sown area 207505 70.43 Source: Statistical Department, Thanjavur 73
TABLE NO: 3.2 DEMOGRAPHIC DATA Features of Population
S. Details No. Percentage No. 1 Male 1096638 49.48 2 Female 1119500 50.52 Total 2216138 100 3 Sex Ratio 49.5 : 50.5 4 Rural/Urban population (i) Rural population 1467577 66.22 (ii) Urban population 748561 33.78 TOTAL 2216138 100 5 Literacy Rate (i) Male 814354 55.2 (ii) Female 661902 44.8 Total 1476256 100 (ii) Rural a. Male 515621 56.5
b. Female 396824 43.5 Total 912445 100 (iv) Urban a. Male 298733 53.0
b. Female 265078 47.0 Total 563811 100 Source: Statistical Department, Thanjavur
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TABLE NO: 3.3 SC / ST / OBCs and Minorities (2001 census)
1. Scheduled Caste 399653
2. Scheduled Tribes 3641
3. Other Backward Class & Minorities 1812844
Source: Statistical Department, Thanjavur
TABLE NO: 3.4 WORK FORCE
S. Description Numbers WPR (%) No.
1. Total Workers 897123 100
2. Main Workers 750032 85.22
3. Marginal Workers 147091 14.78
Total Workers 897123 100 Source: Statistical Department, Thanjavur
TABLE NO: 3.5 TOTAL WORKERS CLASSIFICATION
1. Cultivators 144942 18.35
2. Agricultural Laborers 410718 30.98
3. Workers in house hold industry 37986 5.38
4. Other workers 303477 45.29
Total 897123 100 Source: Statistical Department, Thanjavur
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EMPLOYMENT STATUS
(i) Employment in Agriculture
(1) Agriculture - 144942
(2) Agricultural Laborers - 410718
(ii) Employment in Animal Husbandary & Fisheries
(1) Animal Husbandry - 125220
(2) Fisheries - 15552
(iii) Employment in mines
(1) Mines 17(Gravels) - 5304
(2) Quarries 22 (Sand) - 9130
(iv) Employment in Rural Industry
(1) Employment in Factories - 14062
(2) Hand Loom - 19342
(3) Power Loom - NIL
(4) Handy Crafts - 4582
(v) Employment in Services and other Activities
(1) No of Xerox Centre - 1525
(2) No of Factories Registered - 2688
(3) No of Working Factories - 2531
(4) Employment in Factories. - Male: 123221 Female: 169110 (vi) The District economy is mainly agrarian in nature. Majority of the workforce depends on agriculture and allied activities. Dairy sector plays a major role and livelihood of people in this district. Details of Livestock: Livestock growth in the district has shown a marginal increase over the decade. Animal Husbandry with allied activity of Agriculture cannot grow as fast as agriculture since its breeding programme is a slow process the district has more indigenous cattle than any special breed of cattle. We depend on 76
cattle purchases outside the district. Thanjavur poled cattle are distinguished by dehorned and possession of clipped ears. The main stream of the District is fed by Cauvery River, when the river is dry flock owners of the sheep from Ramnad and Southern Districts come with their migratory stock for pasturing temporarily. The Cattle Breeding and Fodder Development have been replaced for Intensive Cattle Development Project which functions from Thanjavur. Under Cattle Breeding and Fodder Development a Semen Bank is established at Ammapettai about 19 Kms., from Thanjavur from which Liquid Nitrogen and Frozen Semen straws are being supplied to various institutions and Veterinary Sub-centres of the Animal Husbandry Department in this district. Livestock development plays an important role in Thanjavur next to agriculture. One Regional Joint Director of Animal Husbandry monitors the entire Animal Husbandry activities in Thanjavur district. The Joint Director of Animal Husbandry has jurisdiction over the district. In developing economies, particularly in India, the livestock support the farm incomes of the rural household and thereby help in reducing inequalities in income. Livestock also complemented the rural folk through additional income and employment opportunities. The animal husbandry units of the state, districts, taluks, blocks and villages are taking care of the livestock, poultry and domestic animals during their ailments. There are six Government veterinary hospitals, 55 dispensaries, two clinical centers and 67 sub centers in this district. And there is no private hospital in this district. Particulars of livestock in the district are furnished in the table 3.6.
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TABLE NO: 3.6 ANIMAL HUSBANDRY
Classification Numbers
1.Cattle 380989
2. Buffalos 22949
Total Bovine 403938
3. Sheep 35609
4. Goats 416543
5. Horses and Ponies 113
6. Pigs 3252
7. Mules 00
8. Camels 00
9. Donkeys 295
10. Dogs, Domestic Dogs 60549
Total livestock 999433
Poultry
1. Fowls 704664
2. Ducks 1542
3. Others 577
Total Poultry 706783 Source: Regional Joint Director, Animal Husbandry, Thanjavur. 78
BUDALUR BLOCK As a representative of the rain fed areas of the district, Budalur block was selected for the study. There are 51 revenue villages, 42 panchayat villages and one town panchayat in Budalur block. It is located at 22 km to the west of Thanjavur and around 45 km to the east of Thiruchirapalli district. There are three rivers passing through Budalur namely Vennaaru, Anandha Cauvery and Grand Anaicut Canal (also called Pudhaaru). Budalur stands as a witness for Tamilian Culture. Jallikattu is a very famous event conducted with the cooperation of people from the surrounding villages during Pongal festival. Also many specialists in Silambaatam (Tamilian Martial Art), Karakaatam (Rural Dance Method) are available in the nearby villages. Another special festival here is Aadi Perukku. People used to go to river on that day and spend the evening there with their families and friends. There are three Matriculation Schools (Our Lady of Health Matriculation School-A Christian Convent, Vidhya Matriculation School, Wesley Matriculation School), two Government Elementary Schools, a Government Girls Higher Secondary School and a Government Higher Secondary School. Budalur is the main educational center for lot of small villages around it. Following table explains the Budalur block at a glance. 79
TABLE NO: 3.7 BUDALUR BLOCK AT A GLANCE (Year 2008-09) S. No. Particulars Numbers 1 Area (Sq.km) 286.01 2 Population(2001) 97419 3 Density 326 4 Literates 61700 5 Cultivators 6523 6 Agricultural labourers 13056 7 House hold Industrial Workers 866 8 Other Workers 8139 9 Marginal Workers 12149 10 Total Workers 40.733 11 New Workers 36686 12 Rainfall (Normal) in mm NA 13 Rainfall (Natural) in mm 3103.1 14 Net Area Sown in Hect 11778 15 Gross Area sown in Hect 17356 16 Net Area irrigated in Hect 10912 17 Gross Area irrigated in Hect 15740 18 Cattle Population 39546 19 Buffaloes 3653 20 Sheeps 4696 21 Goats 28995 22 Veterinary Dispensaries 3 23 Reserve Forest Area (Hect) 147 24 Hospitals 1 25 Primary Health Centers 3 26 High Schools 9 27 Higher Secondary Schools 9 28 Nationalized Banks 4 29 Cinema Theatre 2 30 Police Station 4 Source: Statistical Department, Thanjavur 80
TABLE NO: 3.8 AREA AND POPULATION (YEAR 2008-09)
Revenue Area Village Population Rural Urban Year (Sq. Total km) To Person M F P M F P M F 1971 288.40 52 71159 35730 35429 71159 33730 35429 ------1981 288.40 52 86395 43464 42931 74396 37345 37051 11999 6119 5880 1991 286.01 51 93121 46863 46258 80510 40505 40505 12611 6358 6253 2001 286.01 51 97419 48493 48926 84852 42202 42650 12567 6291 6276 Source: Statistical department, Thanjavur. TABLE NO: 3.9 LITERACY RATE (YEAR 2008-09) Population Rural Urban Year Person M F P M F P M F 1961 19004 13891 5113 19004 13891 5116 ------1971 26724 18026 8698 26724 18026 8698 ------1981 43063 23775 19288 35644 19317 16327 7419 4458 2961 1991 51601 30372 21229 43028 25625 17403 8573 4747 3826 2001 61700 34225 27475 52374 29237 23137 9326 4988 4338 Source: Statistical department, Thanjavur. TABLE NO: 3.10 WORKERS DETAILS (YEAR 2008-09)
Total Rural Urban
Person M F P M F P M F Cultivators 6523 5511 1012 6234 5258 976 289 253 36 Agricultural Labourers 13056 7924 5132 12541 7479 5062 515 445 70 House hold Industry Manufacturing 866 508 358 782 448 334 84 60 24 processing servicing and repairs Other Workers 8139 6621 1518 5758 4559 1199 2381 2062 319 Marginal Workers 12149 6628 5521 11157 6083 5074 992 545 447 Total Workers 40733 27192 13541 36472 23827 12645 8261 3365 896 New Workers 56686 21301 35385 48380 18375 30005 8306 2926 5380 Population 97419 48493 48926 84852 42202 42650 12567 6291 6276 SC 24863 12382 14281 23368 11622 11746 1495 760 735 ST 100 48 52 100 42 52 ------Source: Statistical department, Thanjavur. 81
DETAILS OF BOVINE There are three veterinary dispensaries in this block viz., Budalur, Thirukkattuppalli and Sengipatti. This block has 39546 cattle population and 3653 Buffalo population. In thirukkattupalli veterinary dispensary control area, the cross breed cows are high. The milk production is also high in this area. The marketing of milk is functioning under the unorganised sector. The bovine details of the study area data presented in Table No. 3.10. TABLE NO: 3.11 BOVINE DETAILS OF THE STUDY AREA
Name of the Panchayat Buffaloes Total S. No. Cow in Nos Villages in Nos Bovines 1 Achampatti 956 - 956 2 Agarapettai 521 5 526 3 Alamelupuram 452 84 536 4 Arcadu 219 - 219 5 Avarampatti 863 59 922 6 Budalur 897 9 906 7 Deekshasamudram 423 2 425 8 Indalur 596 - 596 9 Kadambangudi 320 6 326 10 Kankeyanpatti 860 16 876 11 Katchamangalam 391 8 399 12 Koothur 263 2 265 13 Koviladi 502 15 517 14 Kovilpathu 434 5 439 15 Maickelpatti 623 6 629 16 Maniyeripatti 964 - 964 17 Maraneri 880 - 880 18 Megalathur 486 - 486 82
19 Muthuveerakandianpatti 323 - 323 20 Nandavanapatti 559 - 559 21 Nemam 649 - 649 22 Orathur 507 - 507 23 Palamaneri 381 15 396 24 Palayapatti (North) 1064 - 1064 25 Palayapatti (South) 797 9 806 26 Pathirakkudi 1532 - 1532 27 Pavanamangalam 212 73 285 28 Pudukkudi 1120 1 1121 29 Pudupatti 672 12 684 30 Rajagiri 86 21 107 31 Ranganathapuram 146 4 150 32 Sanoorapatti 835 8 843 33 Sellappanpettai 767 - 767 34 Sengipatti 1141 14 1155 35 Solagampatti 620 - 620 36 Thiruchinampoondi 749 - 749 37 Thogur 453 - 453 38 Thondarayanpadi 232 - 232 39 Veeramarasanpettai 277 - 277 40 Vendayampatti 1446 8 1454 41 Vishnampettai 428 99 527 42 Vittalapuram 327 - 327
Total 25973 481 26454 Source: Assistant Director of Animal Husbandry Thanjavur. 83
THANJAVUR DISTRICT BLOCKS
84
BUDALUR BLOCK PANCHAYAT VILLAGES
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3.2. DEFINITION AND CONCEPTS Milk Milk is solid white liquid produced by the mammary glands of mammals. It provides the primary source of nutrition for young mammals before they are able to digest other types of food. The early lactation milk is known as colostrums, and carries the mother's antibodies to the baby. It can reduce the risk of many diseases in the baby. The exact components of raw milk vary by species, but it contains significant amounts of saturated fat, protein and calcium as well as vitamin C. Cow’s milk has a pH ranging from 6.4 to 6.8, making it slightly acidic. Milk contains dozens of other types of proteins besides caseins. They are more water-soluble than the caseins and do not form larger structures. Because these proteins remain suspended in the whey left behind when the caseins coagulate into curds, they are collectively known as whey proteins. Whey proteins make up around twenty per cent of the protein in milk, by weight. Lacto globulin is the most common whey protein by a large margin. The carbohydrate lactose gives milk its sweet taste and contributes about 40 per cent of whole cow's milk's calories. Lactose is a composite of two simple sugars, glucose and galactose. In nature, lactose is found only in milk and a small number of plants.[5] Other components found in raw cow's milk are living white blood cells, Mammary-gland cells, various bacteria, and a large number of active enzymes. Animal milk is first known to have been used as human food during the Secondary Products Revolution, around 5000BC. It is assumed that when animals such as cattle were first domesticated, it was only for purposes of meat. Cow's milk was first used as human food in the Middle East. Goats and sheep are ruminants: mammals adapted to survive on a diet of dry grass, a food source otherwise useless to humans, and one that is easily stockpiled. The animals dairying proved to be a more efficient way of turning uncultivated grasslands into sustenance: the food value of an animal killed for meat can be matched by perhaps one year’s worth of milk from the same animal, which will keep producing milk - in convenient daily portions-for years. Milk is often homogenized, a treatment which prevents a cream layer from separating out of the milk. The milk is pumped at high pressures through very narrow tubes, breaking up the fat globules through turbulence and cavitations. A greater 86
number of smaller particles possess more total surface area than a smaller number of larger ones, and the original fat globule membranes cannot completely cover them. Casein micelles are attracted to the newly-exposed fat surfaces; nearly one-third of the micelles in the milk end up participating in this new membrane structure. The casein weighs down the globules and interferes with the clustering that accelerated separation. The exposed fat globules are briefly vulnerable to certain enzymes present in milk, which could break down the fats and produce rancid flavors. To prevent this, the enzymes are inactivated by pasteurizing the milk immediately before or during homogenization. Homogenized milk tastes blander but feels creamier in the mouth than unhomogenized; it is whiter and more resistant to developing off flavors. Cream line, or cream-top, milk is unhomogenized; it may or may not have been pasteurized. Milk which has undergone high-pressure homogenization, sometimes labeled as "ultra- homogenized," has a longer shelf life than milk which has undergone ordinary homogenization at lower pressures. Homogenized milk may be more digestible than unhomogenized milk.
Feed Efficiency Feed efficiency is simply defined as yield of milk per unit of dietary dry matter consumed. It is a measure of how efficient cows convert consumed nutrients into products (milk, muscle, fat, and calves).
Insurance of Dairy Animal Insurance is a contract by two parties, where by the insurer under takes in consideration of certain periodical fixed amount called premium to indemnity the other called insured against a certain amount of risk or loss to life or property insured. Cattle insurance has gained importance in recent years. The country is heading for white revolution with introduction of massive cross breeding programme to increase the productivity of the animals. The financial institutions are pressing for security for loans for the purchase of animals, the land less labourer does not possess the necessary property to offer as security. The insurance of animals which are hypothecated to the financial institution is the only security, which encourages live stock loans. 87
3.3. DEFINITIONS OF VARIOUS CATEGORIES OF INCOMES
There are enormous categories of incomes that are being practised by the respondents in the study area. They can be under as the income from milk production, income from sale of manure, income from gunny bags and at last the income from the sale of calves.
The significance of the concept of deriving income from milk production reveals that lot of income has been collected by the various respondents, through the way of milk production. Hence this activity namely selling of milk as it is being produced becomes one of the greatest givers of income to the respondents in the study area.
Next to the source of getting income from the milk production, there exists another essential source of grasping the income for the respondents in the study area respectively. That is nothing but the income which could be derived from the sale of manure that is being produced by the respondents in their own places respectively. Thus it becomes another important beneficially way of getting income.
Besides these two above mentioned ways of getting income, there is also an essential way through which the large amount of income is being derived by the respondents in the study area. That is through sale of gunny bags. This income appears when the respondents get into the activities like supply of hygienic food materials for their animals, the empty bags which have been used and made empty are being sold at various prices, bring an excessive income to the respondents. Therefore it is one of the ways to earn income by the respondents in the given study area.
Along with all the above mentioned ways of getting income in different ways, there exists an important source of getting income through selling of calves. This present situation refers to the way of selling out the calves and raising the income. Especially it becomes an advantage of selling out the cross breed calves which creates more income to the respondents in the study area. Hence the income that comes by selling of cross breed calves is more when compared to the other types of calves.
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3.4. DATA BASE AND PERIOD OF THE STUDY The study uses both primary and secondary data. The primary data were collected for the financial year 2008 - 2009. The data were collected from the respondents through interview method during October 2009 to December 2009. The secondary data were also collected.
3.5. SAMPLING DESIGN The study was conducted in Thanjavur District of Budalur Block. The study area was purposefully selected by the researcher due to the following reasons: Agricultural based area, Animal Intensity Rearing habit and livelihood pattern and Employment opportunity. The above facts are presented based on the pilot survey conducted by the researcher. The researcher felt that Budalur Block is viable and potential one to conduct so meaningful and systematic study for dairy Industry. There are three veterinary dispensaries of which three zones have been identified viz., Thirukkattupalli, Budalur and Sengipatti. In Thirukkattupalli dispensary controlled villages are 33, in Budalur dispensary controlled villages are 11 and in Sengipatti dispensary controlled villages are nine. The classification has been done on the basis of the bovine population at these villages (Refer Appendix - I) five villages from each group have been selected using random sampling method. The data relating to age, sex, community, occupation, family size, education and source wise income of the respondents have been obtained. Details on borrowings of the sample household for bovine rearing, bovine wise milk production and marketing, bovine wise milk production, net income of the respondent, Cost for bovine milk production, productivity for bovine milk production and problems faced by respondent, bovine population, and so on were collected for the present study. From each category of villages 100 respondents have been chosen using simple random method. In this way, a total of 300 respondents (milk producer) have been chosen by using stratified simple random sampling technique. Details are given in the following chart and table.
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Budalur Block 300 Samples
Budalur Sengipatti Thirukkattuppalli 100 Samples 100 Samples 100 Samples
Thirukkattuppalli 31 samples Budalur 26 samples Sengipatti 28 samples Pathiragudi 19 samples Avarampatti Pudugudi 25 samples Maraneri 18 samples 25 samples Vendayampatti 5 Villages 5 Villages 5 Villages Kankeyampatti Chellapanpettai 22 samples 17 samples 21 samples Palayapatti 13 samples Thiruchinamppondi Nandavanapatti Maniyeripatti 12 15 samples 16 samples samples Kovilpathu 12 samples
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SAMPLING DESIGN
Total Number of Number of Area Name Village Name Bovine Respondents Population Selected
Thirukkattuppalli 1532 31
Pathiragudi 942 19
Maraneri 880 18 Thirukkattuppalli Kankeyampatti 876 17
Thiruchinampoondi 749 15
Total 4979 100
Budalur 950 26
Avarampatti 922 25
Chellapanpettai 767 21 Budalur Nandavanapatti 559 16
Kovilpathu 439 12
Total 3637 100
Sengipatti 885 28
Pudugudi 805 25
Vendayampatti 705 22 Sengipatti Palayapatti 400 13
Maneripatti 398 12
Total 3193 100
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3.6. STATISTICAL TOOLS USED The following statistical tools were used to analyse the data collected. 1. Chi-square Analysis. 2. One way and Two way ANOVA. 3. Independent t-test. 4. Correlation Analysis. 5. Simple Regression Analysis. The above tools were used as statistical packages. Chapter – IV
Analysis of the characteristics of the milk producers in Budalur block 92
CHAPTER - IV ANALYSIS OF THE CHARACTERISTICS OF THE MILK PRODUCERS IN BUDALUR BLOCK
This chapter is devoted to the analysis of the characteristics of the milk producers in the study area. And it comprises of two sections. Section I furnishes the analysis of the characteristics of the milk producers in the study area. Section II exhibits the analysis of the standard of living of milk producers in the study area. Section III gives the analysis of the bovine population possessed by the respondents in the study area.
4.1 ANALYSIS OF CHARACTERISTICS OF THE RESPONDENTS
The analysis of characteristics of the respondents in Budalur Block can be understood with the help of the following eleven tables. Table.4.1.1 brings out the religion wise distribution of the respondents. Table4.1.2 deals with the community wise distribution of the respondents. Table 4.1.3 deals with the sex wise distribution of the respondents. Table 4.1.4 deals with the age wise distribution of the respondents. Table 4.1.5 deals with the education wise distribution of the respondents. Table 4.1.6 deals with the area wise house distribution of the respondents. Table 4.1.7 brings out area wise family expenditure distribution of the respondents. Table 4.1.8 deals with area wise saving pattern of the respondents. Table 4.1.9 brings out area wise investment pattern of the respondents. Table 4.1.9.1 ANOVA. Table 4.1.9.2 deals with area wise comparison investment in bovine population. Table 4.1.10 brings out borrowing status of the respondents. Table 4.1.11 brings out sources of borrowing.
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TABLE NO: 4.1.1 RELIGION WISE DISTRIBUTION OF THE RESPONDENTS
Religion No. of Respondents Percentage
Christian 98 32.7
Hindu 202 67.3
Total 300 100.0 Source: Primary data. The Table 4.1.1 reveals that the religion wise distribution of the respondents. The respondents belong to the following religions namely Hindus and Christians. Majority of 67.3 per cent of the respondents are Hindu and 32.7 per cent of the respondents are Christians. The table clearly indicates that the majority of the milk producers belong to Hindu religion.
TABLE NO: 4.1.2 COMMUNITY WISE DISTRIBUTION OF THE RESPONDENTS
Community No. of Respondents Percentage
S.C 75 25.0
B.C 203 67.7
M.B.C 22 7.3
Total 300 100.0 Source: Primary data.
Table 4.1.2 reveals the community wise distribution of the respondents. The respondents are belonging to the following communities namely Scheduled Caste, Backward Community and Most Backward Community. 67.7 per cent of the milk producers are Backward Community, 25.0 per cent of the respondents are Scheduled Caste, and 7.3 per cent of the respondents are Most Backward Caste. 94
Diagram No: 4.1.1
Community wise Distribution of the Respondents
7.3
25
67.7
S.C B.C M.B.C 95
TABLE NO: 4.1.3 SEX WISE DISTRIBUTION OF THE RESPONDENTS
Sex No. of Respondents Percentage
Male 275 91.7 Female 25 8.3 Total 300 100.0 Source: Primary data.
Sex ratio is one of the power full indicators of the social health conditions of the any society. It conveys a great deal about the state of gender relations. It gives the ratio of women and men in the population and reflects the relative chances of survival of women in relation to men. The table 4.1.3 gives the sex wise distribution of the respondents. Among the total number of the respondents, 91.7 per cent of the milk producers are male while, 8.3 per cent are female. As for sex wise distribution of the respondents, male respondents dominate the female respondents and the females are less in number.
TABLE NO: 4.1.4 AGE WISE DISTRIBUTION OF THE RESPONDENTS
Age No. of Respondent Percentage
Upto 30 37 12.3 31-50 216 72.0 Above 50 47 15.7 Total 300 100.0 Source: Primary data.
Table 4.1.4 reveals the classification of the age group of the respondents. There is low per cent with 12.3 of the milk producers who are up to the age of 30 and the milk production is lower when compared to the age group 31-50. 72.0 per cent of the respondents belonging to the age group 31-50 have higher percentage of their milk production. Majority of the respondents belong to the age group of 31-50 are involved in milk production. 96
TABLE NO: 4.1.5 EDUCATION WISE DISTRIBUTION OF THE RESPONDENTS Education No. of Respondents Percentage Illiterate 26 8.7 Primary School 59 19.7 Middle School 38 12.7 High School 127 42.3 Higher Secondary 37 12.3 Diploma 9 3.0 Graduate 4 1.3 Total 300 100.0 Source: Primary data. Human development basically comprises of income, health and education apart from various other factors like gender equality and political freedom. Among the various factors, the principal, institutional mechanism for human development is the development of educational systems. According to the census definition, a person is confirmed as literate if he or she can read and write with understanding in any language. A person who can merely read but cannot write is not literate. Any person, who is not literate according to the above definition of literacy, is an illiterate person. The level of literacy is an important part of the study of the socio-economic structure of households. It has great significance on the occupational structure and animal husbandry as one is no exception to this. The table 4.1.5 reveals the education wise distribution of the respondents. 8.7 per cent of the milk producers are illiterate and they are unable to read and write any language. 19.7 per cent of the respondents have completed the primary education that is upto-5th standard. 12.7 per cent of the milk producers have finished the middle school education that is 6-8 standard. 42.3 per cent of the milk producers have completed the High School education that is 9-10 standard. 12.3 per cent of the respondents have completed the higher secondary school education that is 11-12 standard. 3.0 per cent up the respondents have completed diploma education and only 1.3 per cent of the respondents have completed the under graduate level of education. The table reveals that majority of the respondents have not crossed high school education 97
Diagram No: 4.1.2
Education wise Distribution of the Respondents 3 1.3 8.7 12.3 19 .7 1 2.7 42.3
Illiterate Primary School Middle School High School Higher Secondary Diploma Graduate 98
TABLE NO: 4.1.6 AREA WISE HOUSE DISTRIBUTION OF THE RESPONDENTS House Type Area Total Pucca Semi Pucca Kachha 33 54 13 100 Thirukkattuppalli (33.0) (54.0) (13.0) (100.0) 28 48 24 100 Budalur (28.0) (48.0) (24.0) (100.0) 27 49 24 100 Sengipatti (27.0) (49.0) (24.0) (100.0) 88 151 61 300 Total (29.4) (50.3) (20.3) (100.0) Source: Primary data Note: (Figures in parentheses are percentage). The economic reforms which were initiated in this country in 1991 have certainly accelerated the pace of economic development which is anticipated to create an increased demand for better quality of housing and non-residential spaces. At this moment, the country needs “socially desirable and market- responsive policies” to enable the real estate sector to provide housing for all in a healthy social environment. Our country has succeeded in providing food and clothing to the people during the past 50 years. The table 4.1.6 gives the area wise house distribution of the respondents. 33 per cent of the respondents have pucca house, in Thirukkattuppalli area which is higher. 27 per cent of the respondents have pucca house in Sengipatti area which is lower. 54 per cent of the respondents have semi- pucca house in Thirukkattuppalli area which is higher. 48 per cent of the respondents have semi - pucca house in Budalur area which is lower. And 24 per cent of the respondents have kachha house in Budalur and Sengipatti area respectively, which is higher. 13 per cent of the respondents have in Thirukkattuppalli area which is lower. From this table it is observed that the Thirukkattuppalli area respondents have better house conditions compared to the remaining two areas.
99
Diagram No: 4.1.3
Area wise House Distribution of the Respondents
60
54
50 49 48
40
33
30 28 27 P e r ce nt a ge 24 24
20
13
10
0 Thirukkattuppalli Budalur Sengipatti Area
Pucca Semi Pucca Kachha
100
TABLE NO: 4.1.7 AREA WISE FAMILY EXPENDITURE DISTRIBUTION OF THE RESPONDENTS Area Thirukkattuppalli Budalur Sengipatti Total Particulars N =100 N =100 N =100 Std. Std. Std. Std. Mean Mean Mean Mean N Deviation Deviation Deviation Deviation Food 1643.00 905.946 1398.40 1695.7000 1401.90 1694.918 1481.10 300 1479.234 Cloth 359.20 128.414 339.00 119.041 340.00 117.422 346.07 300 121.671 Medical 161.00 87.207 153.50 111.974 155.50 110.986 156.67 300 103.721 Education 263.60 191.303 240.10 188.409 243.60 194.560 249.10 300 191.081 Transport 117.50 65.572 129.60 89.566 129.60 89.566 125.57 300 82.271 Compliments 45.00 49.492 54.00 70.596 55.00 70.532 51.33 300 64.255 Cell Phone 178.90 138.512 167.20 70.268 181.45 75.720 175.85 300 99.621 Entertainment 122.20 160.810 95.40 96.016 95.60 96.046 104.40 300 121.771 Common festival 271.00 167.148 271.10 152.805 270.10 151.614 270.73 300 156.821 Religious festival 387.00 295.045 349.75 179.874 351.75 177.036 362.83 300 224.069 Others 242.50 126.006 242.50 136.584 242.50 136.584 242.50 300 132.706 Source: Primary data 101
The table 4.1.7 explains the area wise family expenditure distribution of the respondents. Rs.1643.00 is the average food expenditure of the respondents in Thirukkattuppalli area which is higher. Rs.1398 is the average food expenditure of the respondents in Budalur area which is lower. Rs.359.20 is the average cloth expenditure of respondents in Thirukkattuppalli area which is higher, Rs.339.00 is the average cloth expenditure of the respondents in Budalur area which is lower. Rs.161.00 is the average medical expenditure of the respondents in Thirukkattuppalli area which is higher. Rs.153.50 is the average medical expenditure of the respondents in Budalur area which is lower.
Rs.263.60 is the average educational expenditure of the respondents in Thirukkattuppalli area which is higher while Rs.240.10 is the average educational expenditure in Budalur area becomes lower.
Rs.117.50 is the average Transport expenditure of the respondents in Thirukkattuppalli area which is higher. And Rs.129.60 is the average Transport expenditure of the respondents in both Budalur and Sengipatti area respectively.
Compliment expenditure means that the respondents have given cash and gift to the people in marriage functions, birthday functions and other functions. Rs.55.00 is the average compliment expenditure of the respondents in Sengipatti area which is higher and Rs.45.00 is the average compliment expenditure of the respondents in Thirukkattuppalli area which is lower.
Rs.181.45 is the average cell phone expenditure of the respondents in Sengipatti area which is higher. And Rs.167.20 is the average cell phone expenditure of the respondents in Budalur and which is lower.
Rs.122.20 is the average entertainment expenditure of the respondents in Thirukkattuppalli area which is higher. And Rs.95.40 is Budalur area which is lower.
Rs.270.10 is the average common festival expenditure of the respondents in Budalur area which is higher. And Rs.270.10 is in Sengipatti area which is lower. 102
Rs.387.00 is the average religious festival expenditure of the respondents in Thirukkattuppalli area which is higher. And Rs.349.75 is in Budalur area which is lower.
Rs.242.50 is the average expenditure for others, of the respondents in three chosen areas. From this analysis Thirukkattuppalli area respondents have more expenditure than the other two areas.
103
TABLE NO: 4.1.8 AREA WISE SAVING PATTERN OF THE RESPONDENTS (Per month in Rs.) Area Thirukkattuppalli Budalur Sengipatti Total Particulars N = 100 N = 100 N = 100 N = 300 Std. Std. Std. Std. Mean Mean Mean Mean Deviation Deviation Deviation Deviation Cash in hand 1745.00 3719.343 745.50 1489.307 740.50 1489.307 1077.00 2504.922 Chit funds 63.50 508.208 105.00 999.937 105.00 999.937 91.17 864.884 Post office 1496.50 4353.834 634.00 2941.353 634.00 2941.353 921.50 3488.746 Co-operative societies 14.50 109.243 792.70 5278.314 792.70 5278.314 533.30 4311.435 Bank 60.50 229.327 215.00 2004.106 215.00 2004.106 163.50 1637.819 Insurance 192.50 236.491 100.00 162.680 95.50 162.680 129.33 194.720 Others 30.00 84.087 5.00 50.000 5.00 50.000 13.33 64.312 Source: Primary data 104
The table 4.1.8 explains the area wise average saving pattern of the respondents. The respondents have saved their money in different categories viz., cash in hand, chit funds, post office, co-operative societies, bank, insurance and others. The table gives Rs.1745.00 as the average saving of cash in their hands in Thirukkattuppalli area which is higher and Rs.740.50 is in Sengipatti area which is lower. Rs.1496.50 is the average post office saving of the respondents in Thirukkattuppalli area which is higher, and Rs.634.00 in both Budalur and Sengipatti area respectively is lower. Rs.192.50 is the average insurance saving of the respondents in Thirukkattuppalli area which is higher and Rs.95.50 is in Sengipatti area which is lower. The table reveals that the respondents have saved their money in cash in hand post office, and insurance, which is in the maximum level. 105
Diagram No: 4.1.4
Area wise Saving Pattern of the Respondents
2000
1800 1745
1600
1496.5
1400
1200
1000 Mean
792.7792.7 800 745.5740.5
634 634
600
400
215 215 192.5 200
105 105 10095.5 63.5 60.5 30 14.5 5 5 0 Cash in hand Chit funds Post office Co-operative Bank Insurance Others societies Particulars
Thirukkattupalli Budalur Sengipatti
106
TABLE NO: 4.1.9 AREA WISE INVESTMENT PATTERN OF THE RESPONDENTS (Per year) 95% Confidence Interval Std. for Mean Area N Mean Std. Error Deviation Lower Upper Bound Bound Thirukkattuppalli 100 6845.00 12055.992 1205.599 4452.83 9237.17 Budalur 100 5160.00 6538.495 653.850 3862.62 6457.38 Agricultural Land Sengipatti 100 5000.00 6465.917 646.592 3717.02 6282.98 Total 300 5668.33 8764.811 506.037 4672.49 6664.18 Thirukkattuppalli 100 65.00 298.608 29.861 5.75 124.25 Budalur 100 1597.00 15000.959 1500.096 -1379.52 4573.52 Business Sengipatti 100 1614.00 15000.094 1500.009 -1362.34 4590.34 Total 300 1092.00 12229.711 706.083 -297.52 2481.52 Thirukkattuppalli 100 7275.00 6233.360 623.336 6038.67 8512.33 Budalur 100 3564.50 4945.538 494.554 2583.20 4545.80 Bovine Sengipatti 100 3559.50 4943.814 494.381 2578.54 4540.46 Total 300 4799.83 5668.380 327.264 4155.80 5443.87 Source: Primary data
107
The table 4.1.9 reveals the area wise investment pattern of the respondents. The respondents have invested in different ways in agriculture land, business and bovine.
Among the three study areas, Thirukkattuppalli area respondents have invested in agricultural land Rs.6845.00 which is higher, and the Sengipatti study area respondents have invested Rs.5000.00 in agricultural land which is low.
The table shows that the respondents have mostly invested in business. The average investment is Rs.1614.00 in Sengipatti study area which is higher. The average investment with Rs.65.00 in Thirukkattuppalli study area is higher.
The table indicates that the respondents have invested in bovine. It means that the respondents have invested in cow or buffalo. The average investment is Rs.7275.50 in Thirukkattuppalli study area, which is higher. And Sengipatti area has the investment of Rs.3559.50 which is lower.
108
TABLE NO: 4.1.9.1 ANOVA
Sum of Mean Df F Sig. Squares Square Agricultural Between Groups 2E + 008 2 104480833.3 1.363 .257 Land With in Groups 2E + 010 297 76635648.15
Total 2E + 010 299 Business Between Groups 2E + 008 2 79111900.00 .527 .591 With in Groups 4E + 010 297 150040259.3
Total 4E + 010 299 Bovine Between Groups 9E + 008 2 459670033.3 15.714 .000 With in Groups 9E + 009 297 29251472.81
Total 1E + 010 299
The table 4.1.9.1 reveals the respondents who have invested in agricultural land in three averages, viz., Thirukkattuppalli, Budalur and Sengipatti. From the ANOVA table, the significance value is 0.257 which is higher than 0.05 which means there is no significant difference between the investments on agricultural land between the three areas of study viz., Thirukkattupalli, Budalur and Sengipatti.
The table explains the area wise investment in business of the respondents. The significance value of 0.591 which is greater than 0.05 means, there is no significant difference between investments in business in area wise.
The table also explains that the respondents have invested on bovine. As the significance value is 0.00 is less than 0.05 it means there is significant difference between the investments on bovine in three chosen areas.
109
TABLE NO: 4.1.9.2 AREA WISE COMPARISON OF INVESTMENT IN BOVINE POPULATION DUNCAN POST HOC TEST
Subset for alpha = .05 Area Number 1 2
Sengipatti 100 3559.50
Budalur 100 3564.50
Thirukkattuppalli 100 7275.50
Sig. .995 1.000
The DUNCAN Post Hoc analysis clearly explains the area wise comparison of investment in bovine population. The table 4.1.9.2 shows Rs.7275.50 is investment in bovine population in Thirukkattuppalli area which is higher compared to the other two areas.
TABLE NO: 4.1.10 BORROWING STATUS OF THE RESPONDENTS
Sources Number of Respondents Percentage
Borrowed 175 58.3
Not borrowed 125 41.7
Total 300 100.0 Source: Primary data.
The table 4.1.10 describes the borrowing status of the respondents in the study area. From this table we observe that, out of three hundred respondents, 58.3 per cent of the respondents have borrowed money while 41.7 per cent of the respondents have not borrowed money. From this analysis the researcher observes that the majority of the respondents have borrowed money. 110
TABLE NO: 4.1.11 SOURCES OF BORROWING
Number of Sources Percentage Mean Respondents Money lender 92 52.6 11994.57 Bank 28 16.0 815.22 Relatives 25 14.3 7027.17 Chit funds 14 8.0 217.39 Co-operative Societies 16 9.1 154.35 Total 175 100.0 20208.70 Source: Primary data Broadly a money lender is one whose primary business is lending of money or giving loans. Money lenders in rural areas generally give short-term loans. These loans are given for various purposes to meet some urgent needs of milk producers, to buy and maintain bovine population. Money lenders in rural areas generally grant loans on the basis of milk income. Money lenders in rural areas occupy a dominant position in practically all spheres of rural activities and exercise the informal powers over the entire rural economy. Chit funds are voluntary and it is comparatively loose organization comprising of a number of members, both to promote savings and to give loans to members. The table 4.1.11 shows the sources of borrowing by the respondents from which out of hundred and seventy five respondents, 52.6 per cent of the respondents have borrowed money from money lenders which is higher because it is so easy to get the money from them when compared to others. 16 per cent of the respondents have borrowed money from banks. 14.3 per cent of the respondents have borrowed money from relatives. 8 per cent of the respondents have borrowed money from chit funds which is lower and 9.1 per cent of the respondents have borrowed money from co-operative banks. The respondents have borrowed money for the various purposes like agriculture, buying bovine population, buying fodder, veterinary and other purposes like maintenance of bovine and its shelters. From this analysis the researcher observes that the majority of the respondents have borrowed money from money lenders. 111
Diagram No: 4.1.5
Sources of Borrowing
9.1 8
14.3
52.6
16
Money lender Bank Relatives Chit funds Co-operative Societies
112
4.2 ANALYSIS OF THE STANDARD OF LIVING OF MILK PRODUCERS IN THE STUDY AREA The stand of living index (SLI) is calculated as given in National Family Health Survey (NFHS-2) by giving score for each items of house and household articles which is given as follows. House type: 4 for pucca, 2 for semi pucca, 0 for Kachha Toilet facilities: 4 for own flush toilet, 2 for public or shared flush toilet or own pit toilet, one for share or public pit toilet, 0 for no facility Source of lighting: 2 for electricity, 1 for Kerosene, Gas or Oil, 0 for other source of lighting: Main fuel for cooking: 2 for electricity, liquid petroleum Gas, or biogas, 1 for coal, charcoal, or Kerosene, 0 for other fuel Source of Drinking water: 2 for pipe, hand pump or well in residence / yard / plot, one for public tap, hand pump or well, 0 for other water source Separate room for cooking: 1 for yes, 0 for no Ownership of house: 2 for yes, 0 for No Ownership of agricultural land: 4 for 5acres or more , 3 for 2.0 to 4.9 acres, 2 for less than 2 acres or acreage not known, 0 for no agricultural land Ownership of Irrigated land: 2 if household owns at least some irrigated land, 0 for no irrigated land Ownership of livestock: 2 if he owns livestock, 0 if he does not own livestock Ownership of durable goods: 4 each for a car or Tractor, 3 each for a Moped / Scooter / Motorcycle, Telephone, Refrigerator, or colours Television, 2 each for a Bicycle, Electric fan, Radio / Transistor, Sewing machine, Black and white Television, Water pump, Bullock cart, or Thresher, 1 each for a Mattress, Pressure Cooker, Chair, cot/bed, Table or Clock / Watch. Index scores range from 0 to 14 for a low SLI to 15-24 for a Medium SLI and 26-67 for a high SLI. The analysis of the standard of living of milk producers in the study area can be understood with the help of the following ten tables. Table.4.2.1 brings out the standard of the living of the respondents. Table 4.2.2 deals with the area wise standard of the living of the respondents. Table 4.2.3 deals with the correlation between type of land and standard of living. Table 4.2.4 deals with the bovine population wise standard of living of the respondents. Table 4.2.5 deals with the sex wise standard of living of the respondents. Table 4.2.6 deals with the Age wise standard of the living of the respondents. Table 4.2.7 brings out marital status wise standard of living of the respondents. Table 4.2.8 deals with religion wise standard of living of the respondents. 4.2.9 brings out community wise standard of living of the respondents. 4.2.10 deals with educational wise standard of living of the respondents. 113
TABLE NO: 4.2.1 STANDARD OF LIVING OF THE RESPONDENTS Category No. of Respondent Percentage Low 17 5.7 Medium 243 81.10 High 40 13.3 Total 300 100.0 Source: Primary data The table 4.2.1 Indicates the standard of living of the respondents in the study area. The standard of living of the respondents is classified into low, medium and high category. Among the 300 respondents, 81.0 per cent of the respondents were in medium standard of living, which is higher. 5.7 per cent of the respondents were in low standard of living which is lower in the study area.
TABLE NO: 4.2.2 AREA WISE STANDARD OF LIVING OF THE RESPONDENTS Area Standard of living Total Thirukkattuppalli Budalur Sengipatti 3 7 7 17 Low (17.6 ) (41.2 ) (41.2) (100.0) 81 81 81 243 Medium (33.3 ) (33.3) (33.3 ) (100.0) 16 12 12 40 High (40.0 ) (30.0 ) (30.0) (100.0 ) 100 100 100 300 Total (33.3) (33.3 ) (33.3 ) (100.0) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.2.2 designates the area wise standard of living of the respondents in the study area. It is classified into three categories, viz., low, medium and high. 40 per cent of the respondents were in high standard of living in Thirukkattuppalli area which is higher, In Budalur and Sengipatti area, the standard of living of the respondents were 30 per cent respectively. The table points out the standard of living of the respondents was very low in Thirukkattuppalli area, but in Budalur and Sengipatti area, the standard of the living of the respondents was the same which is 41.2 per cent respectively. 114
Diagram No: 4.2.1
Area wise Standard of Living of the Respondents
45
41.2 41.2 40 40
35 33.3 33.3 33.3
30 30 30
25
P e r ce nt a ge 20 17.6
15
10
5
0 Low Medium High Standard of Living
Thirukkattupalli Budalur Sengipatti 115
CHI - SQUARE TESTS
Asymp. Sig. Value df (2-sided)
Pearson Chi - Square 2.682 4 .612
Likelihood Ratio 2.878 4 .578
Association 1.732 1 .188
N of Valid Cases 300
From the Chi-Square test the significance value is 0.612 which is greater than 0.05, the Chi-Square test is not significant, which means that the standard of living is not significantly associated with the three areas of study.
TABLE NO: 4.2.3 CORRELATION BETWEEN TYPE OF LAND AND STANDARD OF LIVING
Standard of Land Type living Pearson Correlation 0.073 Dry Land Sig.(2-tailed) 0.210 Number 300 Pearson correlation 602 ** Wetland Sig.(2-tailed) 0.000 Number 300 Pearson correlation -0.058 Thoppu Sig.(2-tailed) 0.317 Number 300 ** Correlation is significant at the 0.01 level (2-tailed).
The table 4.2.3 reveals that there is highly significant correlation of 0.602 between standard of living and the amount of wet land owned. Thus more the wet land higher the standard of living. 116
TABLE NO: 4.2.4 BOVINE POPULATION WISE STANDARD OF LIVING OF THE RESPONDENTS
Standard of Type of Animal Total living Indigenous Cross Breed Buffalo 9 6 2 17 Low (52.9) (35.3) (11.8 ) (100.0 ) 92 102 49 243 Medium (37.9) (42.0) (20.2 ) (100.0) 19 17 4 40 High (47.5 ) (42.5 ) (10.0 ) (100.0 ) 120 125 55 300 Total (40.0) (41.7) (18.3 ) (100.0 ) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.2.4 represents the animal wise standard of living of the respondents in the study area. Majority (52.9 per cent) of the indigenous cow rearers are living in low standard of living. 11.8 per cent of the Buffalo rearers are living in low standard of living. The table 4.2.4 explicates the animal wise high standard of living. 47.5 per cent cow rearers who had cross breed, were living in high standard of living. Among Buffalo rearers 10 per cent only living in high standard of living.
CHI-SQUARE TEST Asymp. Sig. Value df (2-sided) Pearson Chi_Square 4.090a 4 .394 Likelihood Ratio 4.353 4 .360 Linear-by-Linear Association .437 1 .509 N of Valid Cases 300
From the Chi-square test the significance value is 0.394 which is greater than 0.05, the chi-square test is not significant which means based on the animal type, the standard of living is not influenced. 117
TABLE NO: 4.2.5 SEX WISE STANDARD OF LIVING OF THE RESPONDENTS
Standard of Sex Total living Male Female 16 1 17 Low (94.1 ) (5.9) (100.0) 221 22 243 Medium (90.9 ) (9.1) (100.0 ) 38 2 40 High (95.0 ) (5.0 ) (100.0 ) 275 25 300 Total (91.7 ) (8.3 ) (100.0 ) Source: Primary data Note: (Figures in parentheses are percentage).
Table 4.2.5 gives the sex wise standard of living of the respondents. 95.0 per cent of the male respondents were in high standard of living. 5.0 per cent of the female respondents were in high standard of living. 94.1 per cent of the male respondents were in low standard of living. 5.9 per cent of the female respondents wherein low standard of living. From the analysis the table reveals that the male respondents are having higher standard of living than the female.
CHI - SQUARE TESTS
Asymp. Sig. Value df (2-sided)
Pearson Chi - Square .880a 2 .644
Likelihood Ratio .980 2 .613
Linear-by-Linear Association .198 1 .656
N of Valid Cases 300
From the chi-square test the significance value is 0.644. It is greater than 0.05. The chi-square test is not significant which means that sex not influence the standard of living. 118
TABLE NO: 4.2.6 AGE WISE STANDARD OF THE LIVING OF THE RESPONDENTS Standard of Age Group Total living Up to 30 31-50 Above 50 0 13 4 17 Low ( 0 ) (76.5 ) (23.5 ) (100.0 ) 33 178 32 243 Medium (13.6) (73.3 ) (13.2) (100.0 ) 4 25 11 40 High (10.0 ) (62.5) (27.5 ) (100.0 ) 37 216 47 300 Total (12.3 ) (72.0 ) (15.7 ) (100.0 ) Source: Primary data Note: (Figures in parentheses are percentage). Table 4.2.6 Indicates the age wise standard of living of the respondents. 13.6 per cent of the respondents who are up to 30 years of age is in medium of standard of living. From this table, the respondents who are in the age group of 31-50, 76.5 per cent of the respondents have low standard of living, 62.5 per cent of the respondents have high standard living in the same age group. In the age group of above 50, 27.5 per cent of the respondents have high standard of living, 13.2 per cent of the respondents have medium standard of living.
CHI - SQUARE TESTS Asymp. Sig. Value df (2-sided) Pearson Chi - Square 8.395a 4 .078 Likelihood Ratio 9.818 4 .044 Linear-by-Linear Association .323 1 .570 N of Valid Cases 300
From the Chi-Square test, as the significance value is 0.07 which is greater than 0.05, the Chi-Square test is not significant, which means age did not influence the standard of living.
119
TABLE NO: 4.2.7 MARITAL STATUS WISE STANDARD OF LIVING OF THE RESPONDENTS
Standard Marital Status Total of living Married Unmarried Widow Widower 16 0 1 0 17 Low (94.1 ) ( 0.0 ) (5.9 ) (.0 ) (100.0 ) 222 1 18 2 243 Medium (91.4 ) (0. 4 ) (7.4 ) (0.8 ) (100.0 ) 40 0 0 0 40 High (100.0 ) (0.0 ) (0.0 ) (0.0) (100.0 ) 278 1 19 2 300 Total (92.7 ) (0.3 ) (6.3 ) (0.7 ) (100.0 ) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.2.7 illustrates the marital status wise standard of living of the respondents. 100 per cent of the married respondents have high standard of living. 91.4 per cent of the respondents have medium of standard of living. Among widows 7.4 per cent of the respondents have medium standard of living and 5.9 per cent respondents have low standard of living.
CHI - SQUARE TESTS
Asymp. Sig. Value df (2-sided)
Pearson Chi - Square 3.966a 6 .681
Likelihood Ratio 7.031 6 .318
Linear-by-Linear Association 1.822 1 .177
N of Valid Cases 300
From the Chi-Square test, as the significance value is 0.681 which is greater than 0.05, the chi-square test is not significant which means that marital status is associated with the standard of living. 120
TABLE NO: 4.2.8 RELIGION WISE STANDARD OF LIVING OF THE RESPONDENTS
Standard of Religion Total living Christian Hindu 8 9 17 Low (47.1) (52.9 ) (100.0 ) 77 166 243 Medium (31.7 ) (68.3 ) (100.0 ) 13 27 40 High (32.5 ) (67.5 ) (100.0 ) 98 202 300 Total (32.7 ) (67.3) (100.0 ) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.2.8 indicates the religion wise standard of living of the respondents. Among the Christian respondents 47.1 per cent have low standard of living. 31.7 per cent of the respondents have medium of standard of living. The table also indicates that 68.3 per cent of Hindu respondents have medium of standard of living and 52.9 per cent of the respondents have low standard of living. From this analysis religion is not influenced the standard of living.
CHI - SQUARE TESTS
Asymp. Sig. Value df (2-sided)
Pearson Chi – Square 1.707 2 .426
Likelihood Ratio 1.619 2 .445
Linear-by-Linear Association .518 1 .472
N of Valid Cases 300
From the Chi-Square test, as the value is 0.426 which is greater than 0.05, the Chi-square test is not significant which means that religion did not influence the standard of living.
121
TABLE NO: 4.2.9 COMMUNITY WISE STANDARD OF LIVING OF THE RESPONDENTS
Standard of Community Total living SC BC MBC 7 8 2 17 Low (41.2) (47.1 ) (11.8) (100.0 ) 60 165 18 243 Medium (24.7 ) (67.9 ) (7.4 ) (100.0 )
8 30 2 40 High (20.0 ) (75.0) (5.0 ) (100.0 )
75 203 22 300 Total (25.0 ) (67.7 ) (7.3 ) (100.0 ) Source: Primary data Note: (Figures in parentheses are percentage).
Table 4.2.9 Shows the community wise standard of living of the respondents. From the SC community 41.2 per cent of the respondents have low standard of living and 20.0 per cent of the respondents have high standard of living. From the BC community 75.0 per cent respondents have high standard of living and 47.1 per cent respondents have low standard of living. From the MBC community 11.8 per cent respondents have low standard of living and 5.0 per cent respondents have low standard of living. CHI - SQUARE TESTS
Asymp. Sig. Value df (2-sided) Pearson Chi - Square 4.329 4 .363 Likelihood Ratio 4.150 4 .386 Linear-by-Linear Association .580 1 .446 N of Valid Cases 300
From the Chi-Square test as the significance value is 0.363 which is greater than 0.05, the chi-square test is not significant which means that community is not associated with the standard of living. 122
TABLE NO: 4.2.10 EDUCATION WISE STANDARD OF LIVING OF THE RESPONDENTS
Education Standard Higher Primary Middle High Total of living Illiterate Secondary Diploma Graduate School School School School 0 3 4 8 0 0 2 17 Low (0.0) (17.6 ) (23.5 ) (47.1 ) (0.0) (0.0 ) (11.8) (100.0) 21 50 31 97 34 8 2 243 Medium (8.6 ) (20.6 ) (12.8 ) (39.9) (14.0) (3.3 ) (0.8 ) (100.0) 5 6 3 22 3 1 0 40 High (12.5) (15.0 ) (7.5 ) (55.0 ) (7.5) (2.5) (0.0 ) (100.0) 26 59 38 127 37 9 4 300 Total (8.7 ) (19.7 ) (12.7 ) (42.3) (12.3) (3.0 ) (1.3 ) (100.0) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.2.10 explains the educational status wise standard of living of the respondents. They are classified as Illiterate, Primary School, Middle School, High School, Higher Secondary School, Diploma and Graduate level. 47.1 per cent of the respondents have low standard of living who have finished High School level of education. 11.8 per cent of the respondents have low standard of living and they have completed Graduate level.
The table discloses the medium of standard of living of the respondents. 39.9 per cent of the respondents have medium of standard of living and the respondents have completed High School level of education. 3.3 per cent of respondents have medium of standard of living which is lower and the respondents have finished Diploma level of education.
The table reveals that 55.0 per cent of the respondents have high level of standard of living and the respondents have completed High School level of education and 2.5 per cent respondents have high standard of living and the respondents have completed Diploma education.
123
CORRELATION ANALYSIS
Asymp. Approx. Approx. Value Std. Error T Sig.
Interval by Interval Pearson’s R -.048 .057 -.833 .406
Ordinal by Ordinal Spearman -.019 .054 -334 .738 Correlation
N of Valid Cases 300
The correlation value between education level and standard of living is -0.048 and the significant value is 0.406 which is greater than 0.05. There is no significant correlation between educational level and standard of living. From the correlation analysis the hypothesis - 1 is proved.
4.3 ANALYSIS OF THE BOVINE POPULATION POSSESSED BY THE RESPONDENTS IN THE STUDY AREA
The analysis of the bovine population possessed by the respondents in the study area can be understood with the help of the following seven tables. Table 4.3.1 brings out the bovine population possessed by the respondents. Table 4.3.2 deals with the area and bovine population wise distribution of the respondents. Table 4.3.3 deals with the bovine number wise distribution of the respondents in Thirukkattuppalli area. Table 4.3.4 deals with the Bovine number wise distribution of the respondents in Budalur area. Table 4.3.5 deals with the Bovine number wise distribution of the respondents in Sengipatti area. Table 4.3.6 deals with the Bovine number wise distribution of the respondents. Table 4.3.7 brings out the area wise bovine shelter distribution of the respondents. 124
TABLE NO: 4.3.1
BOVINE POPULATION POSSESED BY THE RESPONDENTS
Type of Bovine No. of Respondents Percentage
Indigenous 125 41.7 Cow Cross Breed 120 40.0
Buffalo 55 18.3
Total 300 100.0 Source: Primary data
The table 4.3.1 reveals the type of the bovine population owned by the milk producers. The milk producers were asked to indicate their preference for Cross Breed Cows and local cows in relation to feed, animal care susceptibility to disease, milk yield and milk quality. The table shows the 41.7 per cent of the respondents have Indigenous Cow, 40.0 per cent of the respondents have Cross Breed cow and only 18.3 per cent of the respondents have Buffalo.
125
TABLE NO: 4.3.2 AREA AND BOVINE POPULATION WISE DISTRIBUTION OF THE RESPONDENTS
Type of bovine Area Indigenous Cross Total Buffalo cow Breed cow 25 60 15 100 Thirukkattuppalli (25.0) (60.0) (15.0) (100.0) 60 20 20 100 Budalur (60.0) (20.0) (20.0) (100.0) 40 40 20 100 Sengipatti (40.0) (40.0) (20.0) (100.0)
125 120 55 300 Total (41.7) (40.0) (18.3) (100.0) Source: Primary data Note: (Figures in parentheses are percentage). The table 4.3.2 describes the area wise type of bovine population of the respondents. The bovine type is different from area wise. 60 per cent of the respondents have reared cross breed cow in Thirukkattuppalli area which is high while the rearing 15 per cent of the respondents of buffaloes in this area is lower. Thirukkattuppalli area people have preferred and gave priority for rearing cross breed cow, because they want to more milk yield. Therefore they have concentrated over the indigenous cow to cross breed through insemination. 60 per cent of the respondents have indigenous cow in Budalur area while 20 per cent of the respondents have both cross breed and buffalo respectively. The indigenous cow population is high in Budalur area, because they don’t want to convert the indigenous breed to cross breed by using insemination. And also the respondents thought that the indigenous breed is not affected by disease. From this analysis we observe that the indigenous breed is maintained in large number. This table also explains that 40 per cent of the respondents have both indigenous and cross breed cow in Sengipatti area respectively. 20 per cent of the respondents have buffalo. The table 4.3.2 shows that the area wise bovine size differs. 126
Diagram No: 4.3.1
Area and Bovine Population wise distribution of the Respondents
120
100
15 20 20
80
20
60 40 60 P e r ce nt a ge
40
60
20 40
25
0 Thirukkattuppalli Budalur Sengipatti Area
Indigenous Cross Breed Buffalo 127
CHI - SQUARE TESTS Asymp. Sig. Value Df (2-sided) Pearson Chi-Square 35.709 4 .000 Likelihood Ratio 36.821 4 .000 Linear - by - Linear .913 .339 Association 1 N of Valid Cases 300
From the above table Chi-square is carried out and chi square value is 0.000 which is less than 0.05. The Chi-square test is significant which means there is significant association between area and the type of bovine population.
TABLE NO: 4.3.3 BOVINE POPULATION NUMBER WISE DISTRIBUTION OF THE RESPONDENTS IN THIRUKKATTUPPALLI AREA
Type of Number bovine 1 2 3 4 5 6 7 Total ↓ → 6 6 4 5 2 2 25 Indigenous cow _ (24.0) (24.0) (16.0) (20.0) (8.0) (8.0) (100) 10 20 12 7 5 3 3 60 Cross breed cow (16.6) (33.4) (20.0) (11.6) (8.4) (5.0) (5.0) (100) 3 5 2 3 2 15 Buffalo _ _ (20.0) (33.4) (13.3) (20.0) (13.3) (100) 13 31 20 14 12 5 5 100 Total (13.0) (31.0) (20.0) (14.0) (12.0) (5.0) (5.0) (100) Source: Primary data Note: (Figures in parentheses are percentage). The table 4.3.3 gives that 24 per cent of the respondents have maintained two and three indigenous cows respectively. It becomes higher in Thirukkattuppalli area while eight per cent of the respondents have six and seven respectively. This indicates that the respondents have maintained cross breed cow. 33.4 per cent of the respondents have maintained two cows while five per cent of the respondents have maintained six and seven respectively. The table describes that the respondents have maintained buffalo. 33.4 per cent of the respondents have maintained two buffaloes while 13.3 per cent have the same number of three and five respectively. 128
TABLE NO: 4.3.4 BOVINE POPULATION NUMBER WISE DISTRIBUTION OF THE RESPONDENTS IN BUDALUR AREA
Type of Number 1 2 3 4 5 6 7 Total bovine → ↓
15 13 9 12 6 5 60 Indigenous cow _ (25.0) (21.7) (15.0) (20.0) (10.0) (8.3) (100)
4 6 4 3 1 1 1 20 Cross breed cow (20.0) (30.0) (20.0) (15.0) (5.0) (5.0) (5.0) (100)
5 6 3 3 3 20 Buffalo _ _ (25.0) (30.0) (15.0) (15.0) (15.0) (100)
9 27 20 15 16 7 6 100 Total (9.0) (27.0) (20.0) (15.0) (16.0) (7.0) (6.0) (100) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.3.4 shows the animal numbers maintained by the respondents in Budalur area. 25.0 per cent of the respondents have maintained two indigenous cows.
The table describes that 30.0 per cent of the respondents have maintained two cross breeds while 5.0 per cent of the respondents have maintained five, six and seven respectively.
The table indicates that the 30.0 per cent of the respondents have maintained two buffaloes while 15.0 per cent of the respondents have maintained three, four and five respectively. From this analysis we observe that the respondents have maintained less number of animals in this area. And the small dairy farms are more in this area. The table clearly analyzed that the respondents have not maintained more number of buffaloes that is to say they have maintained five, six and seven respectively, because the maintenance of the buffalo becomes more risky.
129
TABLE NO: 4.3.5 BOVINE POPULATION NUMBERSWISE DISTRIBUTION OF THE RESPONDENTS IN SENGIPATTI AREA
Type of Number 1 2 3 4 5 6 7 Total bovine → ↓
9 9 7 8 3 4 40 Indigenous cow _ (22.5) (22.5) 17.5) (20.0) (7.5) (10.0) (100)
8 13 8 6 3 1 1 40 Cross breed cow (20.0) (32.5) (20.0) (15.0) (7.5) (2.5) (2.5) (100)
6 5 3 3 3 20 Buffalo _ _ (30.0) (25.0) (15.0) (15.0) (15.0) (100)
14 27 20 16 14 4 5 100 Total (14.0) (27.0) (20.0) (16.0) (14.0) (4.0) (5.0) (100) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.3.5 shows the bovine population number wise distribution of the respondents in Sengipatti area. The type of bovine population possessed are classified into indigenous cow, cross breed cow and buffalo. 22.5 per cent of the respondents possess two and three number of indigenous cow. And 32.5 per cent of the respondents possess two number of cross breed cow. Most the buffalo rearers possess one or two numbers. 30.0 per cent of the respondents possess one buffalo and 25 per cent with two buffalo. Very limited number of respondents possess more then three bovine population.
130
TABLE NO: 4.3.6 BOVINE POPULATION NUMBERSWISE DISTRIBUTION OF THE RESPONDENTS
Type of Number 1 2 3 4 5 6 7 Total bovine → ↓
_ 30 28 20 25 11 11 125 Indigenous cow (24.0) (22.4) (16.0) (20.0) (8.8) (8.8) (100)
22 39 24 16 9 5 5 120 Cross breed cow (18.3) (32.5) (20.0) (13.3) (7.5) (4.2) (4.2) (100)
14 16 8 9 8 55 Buffalo _ _ (25.5) (29.1) (14.5) (16.4) (14.5) (100)
36 85 60 45 42 16 16 300 Total (12.0) (28.4) (20.0) (15.0) (14.0) (5.3) (5.3) (100) Source: Primary data Note: (Figures in parentheses are percentage).
The table 4.3.6 explains bovine population number wise distribution of the respondents 24.0 per cent of the respondents have two indigenous cows while the 8.8 per cent of the respondents have six and seven indigenous cow respectively. This table also explains that 32.5 per cent of the respondents have maintained two cross breed cows while 4.2 per cent of the respondents have six and seven cross breed cows respectively. This table clearly describes that 29.1 per cent of the respondents have two buffaloes while 14.5 per cent of the respondents have three and five buffaloes respectively. From this table it is observed that most of the milk producers possess less than three numbers.
131
TABLE NO: 4.3.7 AREA WISE BOVINE SHELTER DISTRIBUTION OF THE RESPONDENTS
House Type Area Total Pucca Semi Pucca Katcha
42 58 100 Thirukkattuppalli - (42) (58) (100)
33 67 100 Budalur - (33) (67) (100)
21 79 100 Sengipatti - (21) (79) (100)
96 204 300 Total - (32) (68) (100) Source: Primary data Note: (Figures in parentheses are percentage).
Infrastructure is the basic structure which facilitates an organization to function efficiently. It is instrument in enhancing the productivity of the animals, increasing the quantum of milk production, facilitating easy marketability of milk produced and stabilizing the price of the milk. The table 4.3.7 reveals the area wise animal shelter distribution of the respondents. 42 per cent of the respondents have semi pucca shelters in Thirukkattuppalli area and 21 per cent o the respondents have semi pucca shelter in Sengipatti area. The table also explains that 79 per cent of the respondents have katcha shelter in Sengipatti area and 58 per cent of the respondents have katcha shelter in Thirukkattuppalli area. The foregoing analysis shows that the maintenance and space for shelters are very poor which would affect the caring of the animals. Chapter – V
Analysis of factors determining milk production income 132
CHAPTER - V ANALYSIS OF FACTORS DETERMINING MILK PRODUCTION INCOME
The analysis of factors determining milk production income in the study area can be understood with the help of the following eleven tables. Table 5.1 deals with the income received from bovine population. Table 5.2 brings out income comparison of the respondents Table 5.3 deals with sex wise income distribution of the respondents. Table 5.4 deals with area wise income distribution of the respondents, Table 5.5 carries out the area wise income comparison of the respondents. Table 5.6 conveys the area and bovine population wise income distribution of the respondents, Table 5.7 express the area and education wise income status of the respondents. Table 5.8 deals with the area wise average total income of the respondents, Table 5.9 brings out the education wise average total income of the respondents, Table 5.10 states the bovine population wise total income from milk production, Table 5.11 deals with the area wise total income from milk production. TABLE NO: 5.1 INCOME RECEIVED FROM BOVINE POPULATION (Per month In Rs) No. of Mean Std. Type of bovine Percentage Respondents Income Deviation Cow Indigenous 125 41.7 8573.60 2618.171 Cross Breed 120 40.0 19562.50 9741.491 Buffalo 55 18.3 15065.27 9774.981 Total 300 100.0 14159.30 9098.295 Source: Primary data.
The table 5.1 reveals the distribution of the income of the respondent based on the bovine type. Among the 300 respondents, 41.7 per cent of the respondents are indigenous cow milk producers and their average income is Rs.8573.60, which is lower, because the milk yield of the indigenous cow is lower. 40.0 per cent of the respondents are cross breed cow milk producers and their average income is Rs.19562.50, which is higher compared to the other type of bovine population. 133
Because the cross breed animal gives more milk. And 18.3 per cent of the respondents are buffalo milk producers and their average income is Rs.15065.27.
ONE-WAY ANOVA Sum of Mean Df F Sig. Squares Square Between Groups 7E+009 2 3724248626 63.928 .000 Within Groups 2E+ 010 297 58257283.17 Total 2E+010 299
The ANOVA table represents the income of the respondents based on the animal type. From the ANOVA table, as the significance value is 0.000 which is < 0.05, there is significant difference in income between type of animal. The following Duncan table represents the comparison of the average income of the respondents in different animal type group.
TABLE NO: 5.2 INCOME COMPARISON OF THE RESPONDENTS (in Rs.) Type of Bovine No. of Subset for alpha = .05 Population Respondents 1 2 3 Indigenous cow 125 8573.60 Buffalo 55 15065.27 Cross Breed cow 120 19562.50 Sig. 1.000 1.000 1.000
The table 5.2 represents the comparison of the average income of the respondents in different bovine type groups. The Cross breed cow milk producers’ average income is Rs.19562.50, which is higher because it gives high yield. The buffalo milk producers’ average income is Rs.15065.27, which is medium. And the indigenous cow milk producers’ average income is Rs.8573.60 which is low when compared to other groups. The table 5.2 represents the cross breed cow gives the highest income compared to the other type of bovine population. 134
Diagram No: 5.1
Income Comparison of the Respondents
120 125
55
Indigenous Buffalo Cross Breed
135
TABLE NO: 5.3 SEX WISE INCOME DISTRIBUTION OF THE RESPONDENTS
No. of Mean Sex Std. Deviation Std. Error Mean Respondent Income
Male 275 14105.78 8969.249 540.866
Female 25 14748.00 10604.367 2120.873
Total 300 Source: Primary data.
The table 5.3 gives the sex wise income distribution of the respondents. Rs.14105.78 is the average income of the male respondents and Rs.14748.00 is the average income of the female respondents.
INDEPENDENT SAMPLES TEST Levene’s Test for t-test for Equality of Means Equality of Variances
95% Confidence Sig. Mean Std. Error Interval of the F Sig. t df (2-tailed) Difference Difference Difference Lower Upper Equal variances .188 .665 -.337 298 .736 -642.218 1903.394 -4388.016 3103.579 assumed Equal variances -.293 27.213 .771 -642.218 2188.753 -5131.523 3847.087 not assumed
From the above table the significant value is 0.736 which is greater than the 0.05, there is no significance difference in income between male and female respondents.
136
TABLE NO: 5.4 AREA WISE INCOME DISTRIBUTION OF THE RESPONDENTS
95% Confidence Interval for Mean No. of Mean Std. Std. Area Minimum Maximum Respondent Income Deviation Error Lower Upper Bound Bound
Thirukattupalli 100 16235.70 9854.093 985.409 14280.43 18190.97 4200 44000
Budalur 100 12123.50 7964.091 796.409 10543.25 13703.75 4200 44000
Sengipatti 100 14118.70 8996.461 899.646 12333.61 15903.79 4200 44000
Total 300 14159.30 9098.295 525.290 13125.57 15193.03 4200 44000 Source: Primary data
137
The table 5.4 reveals the area wise income distribution of the respondents. The average income of the respondents in Thirukkattuppalli area is Rs.16235.70, Rs.12123.50 is the average income of the respondents in Budalur area and Rs.14118.70 is the mean income of the respondents in Sengipatti area. The table shows that the mean income of the respondents in Thirukkattuppalli area is higher, and the mean income of the respondents in Budalur area is lower. The total average income in three areas of the respondents is Rs.14159.30.
ONE WAY ANOVA
Sum of df Mean Square F Sig. Squares
Between Groups 8E + 008 2 422878348.0 5.254 .006
Within Groups 2E + 010 297 80488732.85
Total 2E + 010 299
From the above ANOVA table gives, the average income of the respondents in different areas. As the significant value is less than 0.05 there is significant difference in income between the study areas.
138
Diagram No: 5.2
Area wise Income Distribution of the Respondents
18000
16235.7 16000
14118.7 14000
12123.5 12000
10000
8000
6000
4000
2000
0 Thirukattupalli Budalur Sengipatti
Thirukattupalli Budalur Sengipatti
139
TABLE NO: 5.5 AREA WISE INCOME COMPARISON OF THE RESPONDENTS
Subset for alpha = .05 No. of Area Respondents 1 2
Budalur 100 12123.50
Sengipatti 100 14118.70
Thirukattupalli 100 16235.70
Sig. .117
Source: Primary data
The Duncan table 5.5 analysis explains the income of the respondents in different areas. Rs.16235.70 is the income of the Thirukkattuppalli area respondents. Rs.12123.50 is the income of the Budalur respondents and Rs.14118.70 is the income of the respondents in Sengipatti. Among the three study areas, the income of respondents in Thirukkattuppalli area is higher.
140
TABLE NO: 5.6
AREA AND BOVINE POPULATION WISE INCOME DISTRIBUTION OF THE RESPONDENTS
No. of Std. Type of bovine Area Mean Respondents Deviation
Thirukattupalli 25 8362.00 2702.672
Budalur 60 8614.17 2691.891 Indigenous Sengipatti 40 8645.00 2510.179
Total 125 8573.60 2618.171 Cow Thirukattupalli 60 19891.67 9899.397
Budalur 20 19780.00 10245.492 Cross Breed Sengipatti 40 18960.00 9465.749
Total 120 19562.50 9741.491
Thirukattupalli 15 14734.67 9525.827
Budalur 20 14995.00 9681.805 Buffalo Sengipatti 20 15383.50 10524.561
Total 55 15065.27 9774.981
Thirukattupalli 100 16235.70 9854.093
Budalur 100 12123.50 7964.091 Total Sengipatti 100 14118.70 8996.461
Total 300 14159.30 9098.295 Source: Primary data
141
The table 5.6 reveals the distribution of the milk producers’ income based on the type of animals in different study areas. The average income of the indigenous cow respondents in three areas is as follows. Rs.8645.00 is the average income of the indigenous cow respondent in Sengipatti area. Rs.8362.00 is average income in Thirukkattuppalli area. And the total average income of the indigenous cow respondent in the study area is Rs.8573.60.
The study indicated that the average income of cross breed of the respondents in three areas Rs.19891.67. It is the average income of the respondent in Thirukkattuppalli area which is higher. Rs.18960.00 is the average income of the respondent in Sengipatti area which is lower. The total average income for the cross breed cow respondent is Rs.19562.50.
From the analysis, the table gives the average income of respondents from buffalo of the different study areas. Rs.15383.50 is the average income of the respondent in Sengipatti area which is higher. Rs.14995.00 is the average income in Budalur area.
From the analysis, the table clearly indicates the total average income of the respondents in three types of animals in different study area. The total average income of the respondents in Thirukkattuppalli area is Rs.16235.70 which is higher, because the cross breed cow number is high. And Rs.12123.00 is the average income of the respondent in Budalur area, because the indigenous cow number is high. And the average income of the respondents in Sengipatti area is Rs.14118.70.
142
TABLE NO: 5.7 AREA AND EDUCATION WISE INCOME STATUS OF THE RESPONDENTS No. of Mean Std. Area Education Respondents Income Deviation Illiterate 12 13783.33 9449.948 Primary School 14 12100.00 5027.004 Middle School 14 18787.14 12907.067 High School 38 16719.74 10461.445 Thirukattupalli Higher Secondary 17 18005.88 9831.167 Diploma 3 17133.33 4416.258 Graduate 2 16450.00 5868.986 Total 100 16235.70 9854.093 Illiterate 7 8785.71 3698.391 Primary School 22 10736.36 6065.087 Middle School 13 12638.46 6022.256 High School 44 12786.36 9394.743 Budalur Higher Secondary 10 13610.00 9139.226 Diploma 3 14266.67 11243.368 Graduate 1 8850.00 Total 100 12123.50 7964.091 Illiterate 7 21014.29 14282.790 Primary School 23 14039.13 7882.935 Middle School 11 2627.27 3701.105 High School 45 14237.11 9946.142 Sengipatti Higher Secondary 10 13980.00 5832.057 Diploma 3 11633.33 2182.506 Graduate 1 20600.00 Total 100 14118.70 8996.461 Illiterate 26 14384.62 10620.384 Primary School 59 12347.46 6684.887 Middle School 38 14032.11 9434.148 High School 127 14477.32 9966.929 Total Higher Secondary 37 15729.73 8768.468 Diploma 9 14344.44 6583.713 Graduate 4 15587.50 5956.841 Total 300 14159.30 9098.295 Source: Primary data. 143
The table 5.7 shows the Area and Education wise income of the respondents. Rs.18787.14 is the average income of respondents in Thirukkattuppalli area, who have completed middle school level education. Rs.13783.33 is the average income of respondents, who are illiterate.
The above table indicated that the average income of the respondent in Budalur area Rs.14266.67 is the average income of the three respondents, and they have completed diploma level of education. Rs.8850.00 is the average income of the one respondent with graduate level of education.
The table reveals the average income of the respondent in Sengipatti area. Rs.21014.29 is the average income of the seven respondents and the respondents are illiterate.Rs.2627.27 is the average income of the eleven respondents, and they have completed middle school level of education.
The mean income of the respondents in the study area. 37 respondents who have completed the Higher Secondary School level of education and their average income is Rs.15729.73, which is higher. 59 respondents’ mean income is Rs.12347.46, and they have finished primary school level of education. From the analysis, Education does not influence the income of the respondents. It is not proportional.
144
TWO WAY ANOVA FOR THE TOTAL INCOME BETWEEN AREA AND EDUCATION
By using two way ANOVA, the total income is compared between area and education wise, the results are given below:
Type III Sum Mean Source df F Sig. of Squares Square
Area 75696138 2 378458069.2 4.650 .010
Education 219341115 6 36556852.44 .449 .845
Error 2.369+010 291 81394544.82
Total 2.475E+010 299
The above table reveals total income which is compared between area and education, the income is significant (P < 0.05) but based on the education level, the income is not significant (P > 0.05).
TABLE NO: 5.8 AREA WISE AVERAGE TOTAL INCOME OF THE RESPONDENT
95% Confidence Interval for Mean Area Mean Std. Error Lower Upper Bound Bound
Thirukattuppalli 16233.927 1129.859 14010.196 18457.658
Budalur 12305.158 1173.844 9994.857 14615.459
Sengipatti 14308.191 1177.410 11990.871 16625.510 Source: Primary data
The table 5.8 reveals the area wise total income of the respondents in different study areas. Among the three areas, Thirukkattuppalli area respondents’ income is Rs.16233.927 and the Budalur area respondents’ income is Rs.12305.158 which is low when compared to the other. 145
TABLE NO: 5.9 EDUCATION WISE AVERAGE TOTAL INCOME OF THE RESPONDENTS
95 % Confidence Interval Std. Educational Mean Error Lower Upper Bound Bound
Illiterate 14009.327 1775.163 10515.540 17503.114
Primary School 12611.631 1179.524 10290.152 14933.111
Middle School 13982.106 1464.459 11099.831 16864.381
High School 14569.317 801.492 12991.860 16146.774
Higher Secondary 15360.527 1489.911 12428.160 18292.894
Diploma 14344.444 3007.298 8425.633 20263.256
Graduate 15099.625 4514.812 6213.799 23985.450
Source: Primary data
The table 5.9 reveals the education wise average total income of the respondents, Rs.15360.527 is the average total income of the respondents, who have completed the higher secondary school level of education and Rs.12611.631 is the average total income of the respondents, who have completed the primary school level of education.
146
TABLE NO: 5.10 BOVINE POPULATION WISE TOTAL INCOME FROM MILK PRODUCTION (In Rupees) Type of Bovine Indigenous Cross Breed Buffalo Sources of Income N = 125 N = 120 N = 55 Std. Std. Std. Mean Mean Mean Deviation Deviation Deviation Milk 24673.44 5816.207 82475.83 17705.613 63753.82 15370.410 Manure 668.63 230.630 470.00 127.826 623.64 99.468 Gunny Bags 390.40 162.105 263.33 107.245 312.73 82.898 Calves 1749.20 255.818 3260.00 729.297 1968.18 380.346 Total 27481.67 6142.615 86478.50 17674.373 66658.36 15253.083 Source: Primary data The table 5.10 indicates the animal wise income from the milk production of the respondents. These incomes are mainly derived from various sources viz., milk, manure Gunny bags and calves. The table gives income from different sources. The indigenous cow average milk income is Rs.24673.44 which is lower than the income from the cross breed and buffalo, because the milk yield is very low. The cross breed cow mean milk income is Rs.82475.83. The average milk income of the buffalo is Rs.63753.82. From this table we know the manure income of the different bovine population. The average manure income of indigenous cow is Rs.668.63 which is high, manure of cross breed cow average income is Rs.470.00. And the buffalo average manure income is Rs.623.64. The table explains the gunny bag income of the respondents from different animals. The average gunny bag income of indigenous cow is Rs.390.40, cross breed cow average income is Rs.263.33 and the buffalo average income is Rs.312.73. The table also explains the calves’ income from different animals of the respondents. The calves’ average income of the indigenous cow is Rs.1749.20. The cross breed calves income is Rs.3260.00. And the buffalo calves average income is Rs.1968.18. From this analysis it is concluded that the milk income is higher in cross breed animals. 147
Diagram No: 5.4
Bovine Population wise total income from milk production
90000 82475 . 83
80000
70000 63753 . 82
60000
50000 M ean 40000
30000 246 7 3 . 44
20000
10000 3260 1968 . 18 1749 .2 470 390 .4 668 . 63 623 . 64 263 . 33 312 . 73 0 Milk Manure Gunny Bags Calves Sources of Income
Indigenous Cross Breed Buffalo 148
TABLE NO: 5.11 AREA WISE TOTAL INCOME FROM MILK PRODUCTION Area Sources Thirkattuppalli Budalur Sengipatti Total Bovine Type of N = 100 N = 100 N=100 N = 300 Income Std. Std. Std. Std. Mean Mean Mean Mean Deviation Deviation Deviation Deviation Milk 6084.00 11012.763 14887.20 13002.367 9870.60 12689.324 10280.60 12747.196 Manure 168.56 313.256 395.18 370.040 272.05 367.207 278.60 362.056 Indigenous Gunny Cow 100.00 192.538 234.00 228.619 154.00 215.987 162.67 219.241 Bags
Calves 433.00 765.784 1054.00 886.905 699.50 875.465 728.83 879.377 Total 6785.56 12233.750 16570.38 14386.868 10996.15 14078.547 11450.70 14136.043 Milk 49008.40 42502.387 16599.20 34296.105 33363.40 42550.566 32990.33 41985.349 Manure 273.30 247.027 98.30 203.421 192.40 249.792 188.00 244.328 Cross Breed Gunny 152.00 148.378 53.50 118.759 110.50 152.305 105.33 145.862 cow Bags Calves 1942.50 1704.175 636.50 1309.249 1333.00 1699.246 1304.00 1664.583 Total 51385.00 44355.236 17386.50 35834.906 35002.70 44484.291 34591.40 43876.837 Milk 9103.50 22701.290 12730.50 26356.739 13230.60 27435.189 11688.20 25558.869 Manure 97.00 236.218 124.00 252.511 122.00 248.665 114.33 245.381 Gunny Buffalo 48.00 120.168 62.00 129.513 62.00 129.513 57.33 126.225 Bags Calves 295.00 722.492 389.50 800.703 398.00 816.525 360.83 779.776 Total 9543.50 23703.838 13306.00 27467.646 13812.60 28557.476 12220.70 26636.621 Source: Primary data 149
The table 5.11 explains the area wise income of the respondents. The income from different sources viz., milk, manure, gunny bags and calves. This table shows the milk income of the respondents of indigenous cow area wise. The milk income is Rs.14887.20 in Budalur area. The income of indigenous cows are more in Budalur area while it is Rs.6084 in Thirukkattuppalli area. The milk income of the Cross breed cow in different area as the milk income Rs.49008.40 in Thirukkattuppalli area because the cross breed cow number is high while in Budalur it is Rs.16599.20. The milk income of the buffalo in different areas of Rs.13230.60 is in Sengipatti area because the population of the buffalo is high, while it is Rs.9103.50 in Thirukkattuppalli area. From this analysis among the three types of animals’ milk income, the cross breed cow milk income is high in Thirukkattuppalli area and also the total milk income is higher at Rs.64195.9 in Budalur Rs.44216.9 and in Sengipatti Rs.26464.6. This table also explains manure income of the respondents in different areas. The manure income is Rs.617.48 in Budalur area because the respondents have collected the cow dung (cow waste) properly and sold it, while the manure income is Rs.538.86 in Thirukkattuppalli area. The table indicates the gunny bag income from different areas. The total gunny bag income in three areas is Thirukkattuppalli Rs.300, Budalur Rs.349.5 and Sengipatti Rs.326.5. The gunny bag income is high in Budalur area and Rs.300 in Thirukkattuppalli area. This table shows the calves income from different areas. Thirukkattuppalli Rs.2670.5, Budalur Rs.2080 and Sengipatti Rs.2430.5. From this analysis we observe that the income from calves is Rs.2670.5 in Thirukkattuppalli area. It is high because the cross breed calves are more in this area and money value of these calves is high. This table describes the total income from milk, manure, gunny bags and calves in three areas. Rs.67714.06 is total income in Thirukkattuppalli area, Rs.47262.88 in Budalur area and Rs.59811.45 in Sengipatti area. From this analysis we observe that Thirukkattuppalli respondents have earned more income than others. Chapter – VI
Analysis of the cost and productivity of milk production in the study area 150
CHAPTER - VI ANALYSIS OF THE COST AND PRODUCTIVITY OF MILK PRODUCTION IN THE STUDY AREA
This chapter is devoted to the analysis of the cost and productivity of milk production in the study area. And it comprises of two sections. Section I analyses the cost of milk production in the study area. Section II delivers the analysis of the productivity of the bovine population in the study area.
6.1. ANALYSIS OF THE COST OF MILK PRODUCTION IN THE STUDY AREA
The analysis of factors determining milk production income in the study area can be understood with the help of the following eleven tables. Table 6.1.1 deals with feed cost of indigenous cow in the study area. Table 6.1.2 brings out feed cost of cross breed cow in the study area. Table 6.1.3 deals with feed cost of buffalo in the study area. Table 6.1.4 deals with labour cost of indigenous cow in the study area. Table 6.1.5 carries out the labour cost of cross breed cow in the study area. Table 6.1.6 conveys the labour cost of buffalo in the study area. Table 6.1.7 expresses the health cost of indigenous cow in the study area. Table 6.1.8 deals with the health cost of cross breed cow in the study area. Table 6.1.9 brings out the health cost of buffalo in the study area Table 6.1.10 states the area wise employment details of men. Table 6.1.11 deals with the area wise wage and employment status. TABLE NO: 6.1.1 FEED COST OF INDIGENOUS COW IN THE STUDY AREA Thirukkattuppalli Budalur Sengipatti No. of Respondents 25 60 40 Mean 12960.00 13050.00 13260.00 Std. Deviation 2893.095 3097.642 2982.048
The table 6.1.1 explains the feed cost of indigenous cow in different area. The average cost is Rs.13260 in Sengipatti area and Rs.12960 is lower in Thirukkattuppalli area because the availability of fodder is high. Therefore the feed cost is lower in Thirukkattuppalli area compared to other areas. 151
TABLE NO: 6.1.2 FEED COST OF CROSS BREED COW IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 60 20 40
Mean 30510.00 31275.00 31830.00
Std. Deviation 10760.06 10881.90 10297.59
The table 6.1.2 explains the feed cost of cross breed cow in different areas. The average cost is Rs.31830 in Sengipatti area and Rs.30510 is Thirukkattuppalli area because the availability of fodder is high. Therefore the feed cost is lower in Thirukkattuppalli area compared to other areas.
TABLE NO: 6.1.3 FEED COST OF BUFFALO IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 15 20 20
Mean 28200.00 29610.00 30510.00
Std. Deviation 9827.658 8411.890 10680.52
The table 6.1.3 explains the feed cost of buffalo in different area. The average cost is Rs.30510 in Sengipatti area and it is Rs.28200 in Thirukkattuppalli area because the availability of fodder is high. Therefore the feed cost is lower in Thirukkattuppalli area compared to other areas.
152
TABLE NO: 6.1.4 LABOUR COST OF INDIGENOUS COW IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 25 60 40
Mean 21456.00 21900.00 21780.00
Std.Deviation 7008.452 6736.342 6866.911
The table 6.1.4 explains the labour cost of indigenous cow in different areas. The average cost is Rs.21,900 in Budalur area and it is Rs.21456 in Thirukkattuppalli area.
TABLE NO: 6.1.5 LABOUR COST OF CROSS BREED COW IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 60 20 40
Mean 31545.76 31590.00 32490.00
Std. Deviation 12237.24 12367.44 12503.70
The table 6.1.5 explains the labour cost of cross breed cow in different areas. The average cost is Rs.32490 in Sengipatti area and it is Rs.315456 in Thirukkattuppalli area.
153
TABLE NO: 6.1.6 LABOUR COST OF BUFFALO IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 15 20 20
Mean 26520.00 27094.74 25650.00
Std.Deviation 9822.947 10807.89 10542.32
The table 6.1.6 explains the labour cost of indigenous cow in different areas. The average cost is Rs.27094 in Budalur area and it is Rs.25650 in Sengipatti area.
TABLE NO: 6.1.7 HEALTH COST OF INDIGENOUS COW IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 25 60 40
Mean 458.4000 465.4167 466.0000
Std.Deviation 72.89719 65.49868 6834303
The table 6.1.7 explains the Health cost of indigenous cow in different areas. The average cost is Rs.466 in Sengipatti area and it is Rs.458 is lower in Thirukkattuppalli area. The health cost includes Insemination artificial and natural, Doctor fees, medicine, and so on. In the study area the health cost is calculated per annum. Government veterinary hospitals charged lower charge to the animal’s rearers. Therefore the bovine rearers thought the health cost is not a big cost.
154
TABLE NO: 6.1.8 HEALTH COST OF CROSS BREED COW IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 60 20 40
Mean 668.1667 650.7500 672.6250
Std.Deviation 279.87734 277.81229 290.85415
The table 6.1.8 explains the Health cost of indigenous cow in different areas. The average cost is Rs.672 in Sengipatti area and it is Rs.458 is Budalur area. The health cost is Insemination, artificial and natural, Doctor fees, medicine, and so on. In the study area the health cost is calculated per annum. Government veterinary hospitals charged low to the animal’s rearers therefore the bovine rearers thought the health cost is not a big cost. TABLE NO: 6.1.9 HEALTH COST OF BUFFALO IN THE STUDY AREA
Thirukkattuppalli Budalur Sengipatti
No. of Respondents 15 20 20
Mean 630.7500 640.2500 630.7500
Std. Deviation 84.39062 83.54758 84.39062
Source: Primary data
The table 6.1.9 explains the Health cost of indigenous cow in different areas. The average cost is Rs.640 in Budalur area and it is Rs.630 is lower in both Thirukkattuppalli and Sengipatti area. The health cost is Insemination, artificial and natural, Doctor fees, medicine, and so on. In the study area the health cost is calculated per annum. Government veterinary hospitals charged low to the animal’s rearers. Therefore the bovine rearers thought the health cost is not a big cost.
155
TABLE NO: 6.1.10
AREA WISE EMPLOYMENT DETAILS OF MEN
95% Confidence Interval for No. of Std. Std. Area Mean Mean Minimum Maximum Respondent Deviation Error Lower Upper Bound Bound
Thirukattupalli 100 .57 .498 .050 .47 .67 0 1
Budalur 100 .54 .501 .050 .44 .64 0 1
Sengipatti 100 .56 .499 .050 .46 .66 0 1
Total 300 .56 .498 .029 .50 .61 0 1 Source: Primary data
The table 6.1.10 illustrates the area wise employment details of the respondents per animal. Among the 300 respondents, 0.57 is the average labour in Thirukkattuppalli area. 0.54 is the average labour in Budalur area i.e., nearly half-a- day of men labour is put into take a care of animals. 156
Diagram No: 6.1.1
Area wise Employment Details of Men
0.575
0.57 0.57
0.565
0.56 0.56
0.555
0.55
0.545
0.54 0.54
0.535
0.53
0.525 Thirukattupalli Budalur Sengipatti
Thirukattupalli Budalur Sengipatti 157
ONE WAY ANOVA
One way ANOVA is used for comparing three or more averages. Here, it is used for comparing number of family men labourers engaged per day per animal, which is given below in the following table.
ANOVA TABLE FOR COMPARING MEN LABOURERS IN THREE AREAS
Sum of df Mean Square F Sig. Squares
Between Groups .047 2 .023 .094 .911
Within Groups 73.990 297 .249
Total 74.037 299
In the above ANOVA table given the significance value is 0.911 which is greater than 0.05, there is no significant difference in the men’s family labour among the three chosen areas of the study. 158
TABLE NO: 6.1.11 AREA WISE WAGE AND EMPLOYMENT STATUS (Per animal) Area Thirukkattuppalli Budalur Sengipatti Total N = 100 N = 100 N = 100 N = 300 Std. Std. Std. Std. Mean Mean Mean Mean Deviation Deviation Deviation Deviation Men Family .57 .498 .54 .501 .56 .499 .56 .498 Labour Men Hours 2.33 2.279 2.04 2.108 2.30 2.272 2.22 2.217 Employed Men’s 31.30 34.124 23.75 28.073 28.30 32.092 27.78 31.578 Wage Men 4.40 16.350 5.50 18.930 4.80 17.780 4.90 17.664 Total Wage Women .95 .219 .98 .141 .96 .197 .96 .188 Family Labour Women Hours 5.41 1.485 5.64 1.133 5.46 1.374 5.50 1.338 Employed Women’s 36.20 21.071 30.30 18.934 32.00 20.986 32.83 20.438 Wage Women 6.65 16.300 9.30 19.070 9.45 19.331 8.47 18.269 Total Wage Source: Primary data Labour is the major item of expenditure but it is highly variable. The table 6.1.11 reveals the employment status of the respondents in different areas. In the study area family labour has major role in milk production. The table gives the average employment status of milk production in the study area.
The table reveals the total wage of men labour in the study area. It is Rs.4.40 in Thirukkattuppalli area, Rs.6.65 is the average wage of women labour. The labour wage in Budalur area is for men Rs.5.50 and for women Rs.9.30. The labour wage for Sengipatti study area is Rs.4.80 for men and Rs.9.45 for women.
From this analysis we observed that the family labour is a vital part for producing milk and we can take the labour wage also the part of the profit and the milk rearer do not take into account the wage as part of the cost.
159
Diagram No: 6.1.2
Area wise Wage and Employment Status
40
36.2
35
32 31.3 30.3 30 28.3
25 23.75
20 Mean
15
10
5.41 5.64 5.46 5
2.33 2.04 2.3 0.95 0.98 0.96 0.57 0.54 0.56 0 Men Family Men Hours Men’s wage Women Family Women Hours Women's wage Labour Employed Labour Employed Particulars
Thirukkattupalli Budalur Sengipatti
160
6.2 ANALYSIS OF THE PRODUCTIVITY OF THE BOVINE POPULATION IN THE STUDY AREA
The analysis of the productivity of the bovine population in the study area can be understood with the help of the following thirteen tables. Table 6.2.1 deals with the area wise indigenous cow feed intake. Table 6.2.2 brings out Area wise cross breed cow feed intake. Table 6.2.3 deals sex Area wise buffalo feed intake. Table 6.2.4 deals with Area wise milk yield per day by type of bovine population Table 6.2.5 carry out the Regression analysis for indigenous cow milk yield on feed intake Table 6.2.6 convey the Regression analysis for cross breed cow milk yield on feed intake Table 6.2.7 expresses the Regression analysis for buffalo milk yield on feed intake. Table 6.2.8 deals with the Milk lactation period of the indigenous cow. Table 6.2.9 brings out the calving interval period of the indigenous cow. Table 6.2.10 states the Milk lactation period of crossbreed cow. Table 6.2.11 deals with the Calving interval period of cross breed cow. Table 6.2.12 states the Milk lactation length of buffalo. Table 6.2.13 brings out the Calving interval period of the buffalo.
Milk yield is influenced by a variety of factors such as breed of the animals, level of diurnal nutrition intake, status of animal health care, hygienic conditions, etc. It is axiomatic to say that the average yield rate of milk of crossbred animals is higher than that of the indigenous breeds. 161
TABLE NO: 6.2.1 AREA WISE INDIGENOUS COW FEED INTAKE
95% Confidence Interval for Std. Std. Mini Maxi Area N Mean Mean Deviation Error mum mum Lower Upper Bound bound
Thirukkattuppalli 25 .8521 .15512 .03102 .7881 .9161 .67 1.13
Budalur 60 .8527 .15805 .02040 .8119 .8936 .67 1.13
Sengipatti 40 .8391 .15086 .02385 .7909 .8874 .67 1.13
Total 125 .8483 .15408 .01378 .8210 .8755 .67 1.13 Source: Primary data
The table 6.2.1 reveals the area wise indigenous cow feed intake. The average feed intake of 0.8527 kg in Budalur area and 0.8391 kg in Sengipatti area.
ANOVA
Sum of Mean Df F Sig. squares Square
Between Groups .005 2 .002 .102 .903
Within Groups 2.939 122 .024
Total 2.944 124
The above ANOVA table reveals the area wise indigenous cow feed intake. The significance value is 0.903 which is greater than 0.05, which means there is no significant difference in feed intake between area.
162
Diagram No: 6.2.1
Area wise Indigenous cow feed intake
0.855
0.8527 0.8521
0.85
0.845
0.84 0.8391
0.835
0.83 Thirukkattuppalli Budalur Sengipatti
Thirukkattuppalli Budalur Sengipatti 163
TABLE NO: 6.2.2 AREA WISE CROSS BREED COW FEED INTAKE
95% Confidence Interval for Std. Std. N Mean Mean Minimum Maximum Deviation Error Lower Upper Bound bound
Thirukkattuppalli 60 2.4722 1.83208 .28968 1.8863 3.0581 .40 9.00
Budalur 20 2.4095 1.63636 .21125 1.9867 2.8322 .40 9.00
Sengipatti 40 2.3889 1.81305 .40541 1.5403 3.2374 .40 9.00
Total 120 2.4269 1.71859 .15688 2.1163 2.7376 .40 9.00 Source: Primary data
The table 6.2.2 explains the area wise cross breed cow feed intake. The average feed intake of 2.4722 kg in Thirukkattuppalli area and 2.3889 kg in Sengipatti area.
ANOVA
Sum of Mean Df F Sig. squares Square
Between Groups .129 2 .065 .022 .979
Within Groups 351.342 117 3.003
Total 351.472 119
The above ANOVA table reveals the area wise cross breed cow average milk yield by feed intake. The significance value is 0.979 which is greater than 0.05, which means there is no significant difference between area wise milk yields by feed intake. 164
Diagram No: 6.2.2
Area wise cross breed cow feed intake
2.48 2.4722
2.46
2.44
2.42
2.4095
2.4
2.3889
2.38
2.36
2.34 Thirukkattuppalli Budalur Sengipatti
Thirukkattuppalli Budalur Sengipatti
165
TABLE NO: 6.2.3 AREA WISE BUFFALO FEED INTAKE
95% Confidence Interval for Mean Std. Std. N Mean Minimum Maximum Deviation Error Lower Upper Bound bound
Thirukkattuppalli 15 1.2712 .46940 .12120 1.0113 1.5312 .56 2.25
Budalur 20 1.2514 .46045 .10296 1.0359 1.4669 .56 2.25
Sengipatti 20 1.3043 .45144 .10094 1.0930 1.5156 .56 2.25
Total 55 1.2761 .45161 .06090 1.1540 1.3981 .56 2.25 Source: Primary data
The table 6.2.3 reveals the area wise buffalo average feed intake of 1.3043 kg in Sengipatti area and 1.2712 kg in Thirukkattuppalli area.
ANOVA
Sum of Mean Df F Sig. squares Square
Between Groups .028 2 .014 .067 .935
Within Groups 10.985 52 .211
Total 11.014 54
The above ANOVA table reveals the area wise buffalo average milk yield by feed intake. The significance value is 0.935 which is greater than 0.05 which means there is no significant difference in buffalo feed intake between three areas.
166
Diagram No: 6.2.3
Area wise buffalo feed intake
1.3043 1.31
1.3
1.29
1.28 1.2712
1.27 Mean 1.26 1.2514
1.25
1.24
1.23
1.22 Thirukkattuppalli Budalur Sengipatti Areas
Thirukkattuppalli Budalur Sengipatti 167
TABLE NO: 6.2.4 AREA WISE MILK YIELD PER DAY BY TYPE OF BOVINE POPULATION
Thirukkattuppalli Budalur Sengipatti Type of animal Mean Mean Mean
Indigenous 4.48 4.53 4.46
Cross Breed 15.80 15.78 15.75
Buffalo 7.87 8.15 8.30
Source: Primary data
The table 6.2.4 indicates area wise average milk yield by difference types of animal. The average milk yield of indigenous cow in Budalur area is 4.53 litre per animal per day, 4.46 litre per animal in Sengipatti area which is lower. And the average milk yield of cross breed cow in Thirukkattuppalli area is 15.80 litre per animal, 15.75 litre per animal in Sengipatti area which is lower. The table also indicates the average milk yield of buffalo in Sengipatti area is 8.30 litre per animal and 7.87 litre per animal in Thirukkattuppalli area.
From this analysis the average of milk yield of different area is not much different where as the different types of animal milk yield is different.
168
REGRESSION ANALYSIS FOR INDIGENOUS COW MILK YIELD ON FEED INTAKE
Regression analysis is used for giving a mathematical equation between a response variable Y and a independent variable X. Here milk yield per day is taken as the response variable Y and feed given per day is taken as the independent variable X. The results are given below. TABLE NO: 6.2.5 MODEL SUMMARY
Adjusted Std. Error of Model R R Square R Square the Estimate 1 .977 .955 .955 .47678 Source: Primary data
From the above model summary table we observe that the R2 value is 0.955 which means that 95.5 per cent of variability in milk yield per day is determined by the feed given per day.
Coefficients
Unstandardized Standardized Model Coefficients Coefficients t Sig. B Std.Error Beta (Constant) .086 .035 2.434 .016 Feed intake .784 .010 .977 79.662 .000 Source: Primary data
From the above table we obtain the regression equation of milk yield on feed intake given by Y=0.086 + 0.784X Further, The correlation value between milk yield and feed given is 0.977 which is highly significant. It means that higher the feed intake higher the milk yield.
169
REGRESSION ANALYSIS FOR CROSS BREED COW MILK YIELD ON FEED INTAKE
Here the milk yield per day is taken as the response variable Y and feed given per day is taken as the independent variable X, the results are given below. TABLE NO: 6.2.6 MODEL SUMMARY
Adjusted Std. Error of Model R R Square R Square the Estimate 1 .955 .912 .845 5.95377 Source: Primary data From the above model summary table we observe that the R2 value is 0.912 which means that 91.2 per cent of variability in milk yield per day is determined by the feed given per day. Coefficients Unstandardized Standardized Model Coefficients Coefficients t Sig. B Std. Error Beta (Constant) 3.715 .387 9.598 .000 Feed intake 1.520 .040 1.33 38.000 .000 Source: Primary data From the above table we obtain the regression equation of milk yield on feed intake given by Y = 3.715 + 1.520 X.
REGRESSION ANALYSIS FOR BUFFALO MILK YIELD ON FEED INTAKE Here milk yield per day is taken as the responsive variable Y and feed given per day is taken as the independent variable, the results are given below. TABLE NO: 6.2.7 MODEL SUMMARY Adjusted Std. Error of Model R R Square R Square the Estimate 1 .933a .871 .870 1.15921 Source: Primary data From the above model summary table we observe that the R2 value is 0.871 which means that 95.5 per cent of variability in milk yield per day is determined by the feed given per day. 170
Coefficients
Unstandardized Standardized Model Coefficients Coefficients t Sig. B Std. Error Beta (Constant) .150 .073 2.053 .041 Feed intake 1.044 .023 .933 44.813 .000 Source: Primary data
From the above table we obtain the regression equation of milk yield on feed intake given by Y = 0.150 + 1.044 X.
From the above three regression analysis, the regression coefficient for cross breed cow is higher (i.e.) 1.52 compared to the other animals, which means that cross breed cow gives higher returns compared to the other animals.
From this regression analysis the hypothesis - 2 is proved.
TABLE NO: 6.2.8 MILK LACTATION PERIOD OF THE INDIGENOUS COW
Lactation Period(In days) No. of Respondents Percentage
240 61 48.8
270 45 36.0
300 19 15.2
Total 125 100.0 Source: Primary data
The table 6.2.8 reveals the milk lactation length for the Indigenous cow of the respondents. Among the 125 indigenous cow respondents, 48.8 per cent of the respondents had the lactation period of 240 days, which is higher. 36 per cent of the respondents had 270 days as lactation period for their cows and only 15.2 per cent of the respondents had 300 days as lactation period for their cows. 171
TABLE NO: 6.2.9 CALVING INTERVAL PERIOD OF THE INDIGENOUS COW
Calving Interval No. of Respondents Percentage (in moths)
12-13 19 48.8
14-15 45 36.0
16-above 61 15.2
Total 125 100.0 Source: Primary data
Calving Interval is a good measure of breeding efficiency in which the period between successive parturition is calculated. In cattle, calving interval of 12 to 13 months is ideal. The calving interval includes gestation period and days open. The days open are of course most flexible and are determined by such factors as how soon heat occurs after calving, when service is allowed, how many services are required for conception and how much time is lost because of missed heat period or losses of early pregnancies. The table 6.2.9 reveals the indigenous cow inter calving period among the 125 indigenous cow respondents. The Calving Interval period of 12-13 months was found 48.8 per cent of the cow rearers. Periods of 14-15 months and 16 and above were recorded for 36.0 per cent and 15.2 per cent of cow rearers respectively.
172
Diagram No: 6.2.4
Calving Interval Period of the Indigenous Cow
48.8
50
45
40 36
35
30
25 P e r c entage
20 15.2
15
10
5
0 12-13 14-15 16-above Calving Interval (in months)
12-13 14-15 16-above 173
TABLE NO: 6.2.10 MILK LACTATION PERIOD OF CROSSBREED COW
Lactation Period(In days) No. of Respondents Percentage
240 5 4.2 260 10 8.3 270 2 1.7 280 10 8.3 300 93 77.5 Total 120 100.0 Source: Primary data The table 6.2.10 reveals the milk lactation length of cross breed cows. 77.5 per cent of the respondents have 300 days for lactation length in cross breed cows which is high and 1.7 per cent of the respondents have 270 days for lactation length of cross breed, which is. From this analysis lactation length of Cross Breed cow differs from cow to cow.
TABLE NO: 6.2.11 CALVING INTERVAL PERIOD OF CROSS BREED COW Calving Interval No. of Respondents Percentage (in moths) 12-13 60 50.0 14-15 33 27.5 16-above 27 22.5 Total 120 100.0 Source: Primary data
Calving interval period changes from cow to cow. The table 6.2.11 reveals the different calving interval period of the cross breed cow. 50.0 per cent of the respondents have 12-13 months of calving interval period, which is high and 27.5 per cent of the respondents have 14-15 months of calving interval period for their cow and 22.5 per cent of the respondents have 16 and above months of calving interval period for their cow which is low.
174
TABLE NO: 6.2.12 MILK LACTATION LENGTH OF BUFFALO
Lactation Period No. of Respondent Percentage (in days) 210 5 9.1 240 5 9.1 270 9 16.4 300 36 65.5 Total 55 100.0 Source: Primary data Lactation length is an important trait influencing the lactation milk yield in buffaloes. The overall lactation in buffaloes ranged from 240 days to 355 days The table 6.2.12 reveals the milk lactation length of Buffalo. The lactation length differs from buffalo to buffalo. 65.5 per cent of the respondents have the milk lactation length of buffalo is 300 days, which is higher. 9.1 per cent of the respondents have 210 days and 240 days as the milk lactation length, which is lower.
TABLE NO: 6.2.13 CALVING INTERVAL PERIOD OF THE BUFFALO
Calving Interval No. of Respondents Percentage (in moths) 12-13 5 9.0 14-15 12 22.0 16-above 38 69.0 Total 55 100.0 Source: Primary data
The table 6.2.13 indicates the calving interval period of buffalo. 69.0 per cent of the respondents have 16 and above months are calving interval period for buffalo which is high. 9.0 per cent of the respondents have 12-13 months are calving interval period for buffalo which is low. Chapter – VII
Analysis of the various channels of marketing and problems of milk production in the study area 175
CHAPTER – VII ANALYSIS OF THE VARIOUS CHANNELS OF MARKETING AND PROBLEMS OF MILK PRODUCTION IN THE STUDY AREA
This chapter is devoted to the analysis of the various channels of marketing and problems of milk production in the study area. And it comprises of two sections. Section I furnishes the analysis of the various channels of marketing of milk production in the study area. Section II delivers the analysis of the problems faced by the milk producers in the study area.
7.1 ANALYSIS OF THE VARIOUS CHANNELS OF MARKETING OF MILK PRODUCTION IN THE STUDY AREA
The analysis of the various channels of marketing of milk production in the study area can be understood with the help of the following two tables. Table 7.1.1deals with the marketing channels. Table 7.1.2 brings out average milk price.
TABLE NO: 7.1.1 MARKETING CHANNELS
Marketing Number Number Percentage Percentage Channels (Cow) (Buffalo) Tea stall 61 24.90 29 52.73 Household 99 40.40 11 20.00 Milk Vendor 85 34.70 15 27.27 Total 245 100.00 55 100.00 Source: Primary data
The table 7.1.1 explains the marketing of the milk in different channels in the study area. The Bovine milk is distributed to Tea stall, Household and Milk vendor. 40.40 per cent of the cow milk rearers sold their milk to Household which is higher because the price of milk is higher and 24.90 per cent of the milk rearers sold their milk to Tea stall. 176
The table indicates the 52.73 per cent of the buffalo milk rearers sold their milk to Tea stall because the fat content is higher in buffalo milk therefore, the price of milk is higher in tea stall and 20.00 per cent of the milk rearers sold their milk to household which is lower because most of the people do not purchase buffalo milk. From this explanation we observed that the Cow rearers sold their milk to Household in higher level and Buffalo rearers sold their milk to tea stall. And there is no Milk co-operative society (AAVIN) in the study area.
177
Diagram No: 7.1.1
Marketing Channels
60
52.73
50
40.4 40
34.7
30 27.27
P e r c n t a ge 24.9
20 20
10
0 Tea stall Household Milk Vendor Channels
Cow Buffalo 178
TABLE NO: 7.1.2 AVERAGE MILK PRICE
Price of cow Milk Price of Buffalo Milk Marketing Number Number (Average in Rs. (Average in Rs. per (Cow) (Buffalo) Channels per lit) lit)
61 29 Tea stall 20.36 27.68 (24.90) (52.73)
99 11 Household 20.84 22.45 (40.40) (20.00)
85 15 Milk Vendor 15.62 20.33 (34.70) (27.27) Source: Primary Data Note: Figures in the parentheses are percentage
The table7.1.2represents the milk price in different marketing channels viz., Tea stall, household and milk vendor. The bovine rearers sold their milk in different prices according to the marketing channels. 40.40 per cent of the cow milk rearers got the average milk price is Rs.20.84 from household which is higher and 34.70 per cent got the average milk price of Rs.15.62 from milk vendor which is low.
The buffalo milk rearers got higher milk price. 52.73 per cent got the average milk price is Rs.27.68 from Tea stall which is higher and 27.27 per cent got the average milk price is Rs.20.33 which is lower.
The price of cow milk is low compared to the buffalo milk because the buffalo milk fat is higher than the cow milk. Therefore the tea stall persons bought the buffalo milk with higher price.
179
7.2.ANALYSIS OF THE PROBLEMS FACED BY THE MILK PRODUCERS IN THE STUDY AREA
The analysis of the various channels of marketing of milk production in the study area can be understood with the help of the following six tables. Table 7.2.1 deals with Common land using for bovine population. Table 7.2.2 brings out Doctors attended the respondents place. Table 7.2.3 deals with Distance between respondents’ house and the veterinary dispensary. Table 7.2.4 deals with expectation of milk price by the respondents. Table 7.2.5 carries out the Problems faced by the respondents. Table 7.2.6 conveys the Cattle insurance taken by the respondents. The following table explains that the respondents used the common land for grazing purpose in their area.
TABLE NO: 7.2.1 COMMON LAND USING FOR BOVINE POPULATION
Frequency Percentage
Not used 226 75.3
Used 74 24.7
Total 300 100.0 Source: Primary data
The table 7.2.1 reveals that 75.3 per cent of the respondents have not used the common land in their area and 24.7 per cent of the respondents have used the common land. The researcher observed that the common land size decreases due to the government free land distribution scheme in Tamil Nadu state. Therefore the respondents faced the problems of common land for grazing purposes as the means of food for their animals.
180
TABLE NO: 7.2.2 DOCTORS ATTENDED THE RESPONDENTS PLACE
Frequency Percentage
Yes 175 58.3
No 125 41.7
Total 300 100.0 Source: Primary data
The table 7.2.2 represents the veterinary doctors’ treatment given to the animals on time. 58.3 per cent of the respondents have expressed that the doctors have come and gave treatment to the animal on time. And 41.7 per cent of the respondents revealed that the doctors did not give treatment for the animals in emergency situation. From this analysis it is concluded that the respondents faced doctor’s treatment problem on time. 181
Diagram No: 7.2.1
Doctors Attended the Respondents' Place
41.7
58.3
Yes No 182
TABLE NO: 7.2.3 DISTANCE BETWEEN RESPONDENTS’ HOUSE AND THE VETERINARY DISPENSARY
Distance Frequency Percentage (in Kilo Meters)
1-2 16 5.3
3-4 110 36.7
5-6 143 47.7
7 and above 31 10.3
Total 300 100.0 Source: Primary data
The following table 7.2.3 explains the distance between the respondents’ house and veterinary dispensary. 47.7 per cent of the respondents have the distance between respondents place and veterinary dispensary as 5-6 kilo meters which is higher and 5.3 per cent of the respondents have the distance between respondents place and dispensary as 1-2 kilo meters which is lower. From this analysis the researcher observes that the veterinary dispensary is located in the long distance. And there is no private hospital and dispensary in the study area. 183
Diagram No: 7.2.2
Distance between Respondents' House and the Veterinary Dispensary
5.3 10.3
36.7
47.7
1-2 1-4 5-6 7 and above 184
TABLE NO: 7.2.4 EXPECTATION OF MILK PRICE BY THE RESPONDENTS
Valid Cumulative Price Frequency Percentage Percentage Percentage
20 19 6.3 6.3 6.3
22 11 3.7 3.7 10.0
24 12 4.0 4.0 14.0
25 34 11.3 11.3 25.3
26 22 7.3 7.3 32.7
27 29 9.7 9.7 42.3
28 92 30.7 30.7 73.0
30 37 12.3 12.3 85.3
32 7 2.3 2.3 87.7
33 5 1.7 1.7 89.3
34 22 7.3 7.3 96.7
36 10 3.3 3.3 100.0
Total 300 100.0 100.0 Source: Primary data The table 7.2.4 reveals the expectations of the milk price by the respondents. 30.7 per cent of the respondents expected the milk price to be Rs.28 per litre which is higher. 1.7 per cent of the respondents expected the milk price to be Rs.33 litre which is lower. From this analysis it is concluded that 85.3 per cent of the respondents expected the milk price from Rs.20 to Rs.30 per litre and 14.7 per cent of the respondents have expected the milk price from Rs.32 to Rs.35. 185
Diagram No: 7.2.3
Expectation of milk price by the Respondents
35
30.7
30
25
20 P e r ce nt a ge 15
12.3 11.3 9.7 10 7.3 7.3 6.3
4 5 3.7 3.3 2.3 1.7
0 20 22 24 25 26 27 28 30 32 33 34 36 Price
20 22 24 25 26 27 28 30 32 33 34 36 186
TABLE NO: 7.2.5 PROBLEMS FACED BY THE RESPONDENTS
Valid Cumulative Problems Frequency Percentage Percentage Percentage Loan 34 11.3 11.3 11.3 Grazing Land 18 6.0 6.0 17.3 Dispensary 28 9.3 9.3 26.7 Marketing 82 27.3 27.3 54.0 Storage 40 13.3 13.3 67.3 Fodder 98 32.7 32.7 100.0 Total 300 100.0 100.0 Source: Primary data
The table 7.2.5 reveals that the respondents faced the problems viz. to get loan from the bank, problem of grazing land, problem of long distance dispensary, marketing problems, storage problems and fodder problems. The table gives that 32.7 per cent of the respondents faced the fodder problem of green fodder, dry fodder and particularly paddy straw. 6.0 per cent of the respondents faced the grassing land problems for their animals. The table also gives that 27.3 per cent of the respondents have the marketing problem and 13.3 per cent have storage problem due to lack of milk cooperative society(AAVIN) and common storage facilities in this study area. The study shows the veterinary dispensary and hospital problems. It focuses that there is no private hospital and dispensary in this study area. The study explains that the respondents faced the credit (loan) problem and could not get from the bank. The foregoing analysis shows that the respondents faced the fodder problem which is higher due to the mechanization of agriculture so the respondents could not get the paddy straw. The grazing land is decreasing due to the government free land distribution scheme
187
Diagram No: 7.2.4
Problems faced by the Respondents
35
32.7
30
27.3
25
20 P e r ce nt a ge 15 13.3
11.3
10 9.3
6
5
0 Loan Grazing DispensaryMarketing Storage Fodder Land Problems
Loan Grazing Land Dispensary Marketing Storage Fodder
188
TABLE NO: 7.2.6 CATTLE INSURANCE TAKEN BY THE RESPONDENTS
Valid Cumulative Insurance Frequency Percentage Percentage Percentage
Taken 33 11.0 11.0 11.0
Not taken 267 89.0 89.0 100.0
Total 300 100.0 100.0 Source: Primary data
The table 7.2.6 gives that 89.0 per cent of the respondents have not taken cattle insurance and 11.0 per cent of the respondents have taken cattle insurance for their cattle. From this analysis the researcher observes that the respondents have not given priority to take insurance for their cattle. Chapter - VIII
Findings, Suggestions and Conclusion 189
CHAPTER – VIII FINDINGS, SUGGESTIONS AND CONCLUSION
8.1. MAJOR FINDINGS OF THE STUDY The study on the milk production at Budalur block, Thanjavur district has led to the following findings.
Ø The study found out that in study area of Budalur block, there is an identical structure and systematic pattern of religion and caste system. In the study we found that the majority of the respondents 67.3 per cent belong to the Hindu religion.
Ø This study refers to the caste systems in the study area. The major portion of milk production is undertaken by the backward community milk producers and they are in large number with 67.7 per cent.
Ø The present study shows the male and female milk producers in the study area. It is found that the male milk producers with 91.7 per cent are more than the female milk producers.
Ø Majority of the respondents, (72.0 per cent) belong to the age group of 31-50.
Ø Education of the milk producers depend upon the income they receive from milk production. This study reveals that the literacy rate in the study areas. Milk producers have majority of high school level of education.
Ø 33 per cent of the respondents in Thirukkattuppalli study area have Pucca house which is higher compared to other area.
Ø The expenditure is higher for Thirukkattuppalli area respondents.
Ø The study shows that the habit of saving of the respondents in Thirukkattuppalli area is higher.
Ø The investment pattern of the respondents is higher in Thirukkattuppalli study area. 190
Ø The respondents have invested on bovine population. There is significant difference in the investment on bovine population in three chosen areas.
Ø 52.6 per cent of the respondents have borrowed money from money lenders.
Ø Among the 300 respondents, 81.0 per cent of the respondents were in medium standard of living.
Ø 40 per cent of the respondents were in high standard of living in Thirukkattuppalli area.
Ø 60 per cent of the respondents have reared cross breed cow in Thirukkattuppalli area. They preferred and gave priority for rearing cross breed cow, because they want more milk yield.
Ø 60 per cent of the respondents have indigenous cow in Budalur area. The indigenous cow population is high in Budalur area, because they don’t want to convert the indigenous breed into cross breed by using insemination. The traditional cow is maintained in this area.
Ø 40 per cent of the respondents have both indigenous and cross breed cow in Sengipatti area. There is significant association between areas and the type of bovine population.
Ø 40.0 per cent of the respondents are cross breed cow milk producers and their average income is Rs.19562.50, which is higher compared to the other type of bovine population, because the cross breed animal gives more milk.
Ø The respondents who have reared cross breed cow get higher income.
Ø Among the three study areas, the income of respondents in Thirukkattuppalli area is higher.
Ø Feed cost is low in Thirukkattuppalli area because of the availability of green fodder.
Ø Feed cost is high for buffalo and cross breed cow.
Ø Labour cost is high in Budalur area because of industrialization.
Ø Labour cost is high for cross breed cow and buffalo. 191
Ø Health cost is high for cross breed cow and buffalo but for indigenous cow it is very low because of immunity.
Ø The area wise indigenous cow average feed intake of 0.8527 kg in Budalur area and 0.8391 kg in Sengipatti area.
Ø The area wise cross breed cow average feed intake of 2.4722 kg in Thirukkattuppalli area and 2.3889 kg in Sengipatti area.
Ø The area wise buffalo average feed intake of 1.3043 kg in Sengipatti area and 1.2712 kg in Thirukkattuppalli area.
Ø From this study the average of milk yield of different area is not much different whereas the milk yield is different between type of animals.
Ø The correlation value between milk yield and feed given is highly significant. It means that higher the feed intake higher the milk yield.
Ø The respondent sold their milk to household.
Ø The price is high for buffalo milk.
Ø There is difference in the milk price of different channels of marketing.
Ø The study observed that the common land size decreases due to the government free land distribution scheme in Tamil Nadu state. Therefore the respondents faced the problems of common land for grazing purposes as the means of food for their bovine population.
Ø From this study 41.7 per cent of the respondents have faced doctor’s treatment problem on time.
Ø From this study we observe that the veterinary dispensary is located in the long distance. There is no private veterinary dispensary and hospital in the study area.
Ø This study focuses that milk price is not the up to the expected level.
Ø 38.7 per cent of the respondent faced fodder and grassing land problems due to mechanization of agriculture and government free land scheme.
Ø The study focuses that 89 per cent the respondents have not taken cattle insurance. 192
Ø The majority of the animal shelters (68 per cent) in the study area belong to katcha shelter.
Ø From the study we found that the milk producers in the study area are saving their income in chit funds, post office, banks and co- operative banks.
Ø This study also shows that most of the milk producers are possessing indigenous cow in the study area.
Ø This study shows that 60 per cent of the respondents have reared cross breed cow in Thirukkattuppalli area, 60 per cent of the respondents have reared indigenous cow in Budalur area and in Sengipatti area there is equal number of indigenous cow and cross breed cow with 40 per cent each.
Ø Present study reveals that most of the (75.3 per cent) common land is not used for grazing of animals in the study area.
Ø The milk producers in study the area face the problem of reaching veterinary dispensaries at long distance covering 5-6 kms.
Ø The milk producers in great number face the problem of fodder facilities.
Ø 89 per cent of the milk producers in the study area have not taken insurance for their animals.
Ø 81.10 per cent of the milk producers in the study area are leading medium standard of life.
Ø The number of married milk producers in the study area is higher than the unmarried milk producers.
Ø In the study it shows that the backward community milk producers are having good standard of living better than the other caste community milk producers.
Ø Religion wise the Hindu community has low standard of living in the study area but religion does not influence the standard of the living of the milk producers in the study area.
Ø Cost of green fodder in Thirukkattuppalli is low because there is more of availability of green fodder compared to other area. 193
Ø The total monthly income of the milk production in Thirukkattuppalli is higher and the income is Rs.16233.927.
Ø 85.3 per cent of the milk rearers in the study area expect the milk price to be Rs.20-30 and 14.7 per cent of the milk rearers expect Rs.32-36 in the study area.
Ø The income received from cross breed cow is higher than from the indigenous cow and buffaloes in the study area.
General findings
Ø The number of milch animals per households got reduced, especially buffaloes and local cows. A tremendous increase in adoption of crossbreed cows yielded an increase in milk output.
Ø The consumption of concentrate feed per milk animals had significantly increased in spite of shift in cropping pattern and other reasons.
Ø For dairy development, feed aspect is of utmost importance. Due consideration should be given to developing food and fodder resources.
Ø The government should make arrangements for feed and fodder by removing useless plants like “kablee-keelpar” etc. and in its place green fodder of improved variety should be grown. It can be made possible by improving the quality of land and providing water-resources.
Ø Land for green fodder must be made available to landless milk producers either free of cost or on lease basis. Green fodder (like Jowar, Bajra, Barsem, Motha, Ragi, Gawar etc.) production societies may be set up on no profit-no loss basis.
194
8.2. SUGGESTIONS Dairy sector in the study area depends upon the natural resource such as grazing land, forest, pastures and other uncultivated land. In a nutshell to develop bovine population resources into an income and employment generating enterprise, the productivity of milch cattle can be improved by adopting appropriate breeding policies. Necessary steps should also be taken for supply of balance feed to enable the off spring to protect their genetic potential. For improvement of milk production the innovative technique has to be adopted by the dairy farmers. The following suggestions are to be provided for the development of the Dairy Sector in the study area: (1) Adequate Veterinary Services: The veterinary facilities available in the study area are not adequate and sufficient. Steps should be taken to provide adequate and proper veterinary facilities in the study area. (2) Proper Training Facilities: There is good potentials for developing small scale industries for manufacturing indigenous milk products in the study area. There is need to educate and assist the dairy farmers in respect of breeding, feeding, animal management technique and marketing of milk and milk products. (3) Infrastructure Development: Some infrastructural development like road communication is needed for transportation of fodder, feed concentrates, veterinary services and medicines and transportation of milk to the consuming centres. (4) Credit Facilities: The financial institutions can also play a significant role in improving the processing infrastructure by extending credit to good working SHGs and milk producing units. (5) Marketing Infrastructure: Establishment of organized marketing networks of market is necessary so that the dairy farmers get the remunerative return for their produce. (6) Artificial Insemination: The State Veterinary Department should create facility for Artificial Insemination and pregnancy test at the door step of the dairy farmers.
195
8.3. CONCLUSION In conclusion, two differing points of view emerge about the status of dairy development in the study area. While on one hand, the area showed remarkable progress in terms of overall growth rate in milk production over the period, on the other hand, there were also wide inter-and intra-area variations in growth rates. The factors underlying area imbalance in the growth of milk production could be many. Imbalances might be associated with (a) differences in the distribution of breedable bovine population in different study area of the block; (b) differences in resource base with respect to feeds and fodder and bovine health cover; (c) differences in terms of number of insemination in the field areas for breed improvement and thereby causing differences in genetic architecture of milch animlas, and (d) differences in the productivity of animals. Further, a substantial number, among the weaker sections entered dairying. The decline in grazing lands and the decrease in the availability of green fodder required more human labour for fodder collection. The landless and the marginal farmers with available labour time could make use of this opportunity, whereas the large farmers found the activity more expensive. Though the activity became attractive to the weaker sections, the backward castes and scheduled castes still lag behind the forward castes. The findings of the study revealed that the composition of milch animals with adequate number of cross breed animals could boost milk production significantly. The potential of indigenous livestock needs to be tapped by improving nutrient availability from locally available feed and fodder resources. The comparative performance of cross-breed cows and indigenous cows revealed that the income from cross breed cows is higher than from the indigenous cows. This has sufficiently established that the cross breeding programme through Artificial Insemination may make a real break - through in genetic improvement of breedable milch animals for improvement of milk production and productivity. The dairy enterprise in the study area has been able to improve the economic conditions and standard of living of the dairy farmers. This has created a positive impact in creating of gainful employment opportunity and income to the people living in the rural areas of Tamil Nadu.
196
8.4. AREA OF FURTHER RESEARCH This research particularly concentrates on production and marketing of milk in research area but there is also shadow area which has to be concentrated apart from these aspects of production and marketing. That is to say the research which is going to be conducted next to this research must concentrate the changes in animal management and animal feeding practices, especially by small dairy farmers who could be the instrumental in increasing milk yields in the short run. It is also an important area which must be highly concentrated so that, the co-operative societies which act as the channels of pumping milk and participate in increasing the level of milk production will help the milk producers. In addition to this the research can be conducted area wise which also would enhance the significance of pertinent areas of milk production. Hence these aspects are highly expected from further research that is going to be made in future.
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BOOKS Ø Dhingra I.C. (2010), The Indian Economy, Sultan Chand & Sons, New Delhi, p.287. Ø Edward V. Jesse, William D. Dobson, Norman F. Olson and Vijay P. Sharma (2006) “The Dairy Sector of India: A Country Study” Discussion Papers from University of Wisconsin-Madison, Babcock Institute for International Dairy Research and Development. Downloaded by http://purl.umn.edu/37353 (application/pdf). Ø Gopal Lal Jain (1997), Rural Development, Mangal Deep Publications, Jaipur, Pp.134 – 139. Ø Hemme.T., Garcia.O. and Khan.A.R. (2002) “A Review of Milk Production in Bangladesh with Particular Emphasis on Small-scale Producers”, Pro-Poor Livestock Policy Initiative (PPLPI), Ø Kedija Hussen1, Azage Tegegne, Mohammed Yousuf1 and Berhanu Gebremedhin (2008) Paper on “Cow and camel milk production and marketing in agro-pastoral and mixed crop-livestock systems in Ethiopia” presented at the Conference on International Research on Food Security, Natural Resource Management and Rural Development held at University of Hohenheim, on October 7-9. Ø Leonard A.G. (2006), Tamil Nadu Economy, Macmillan India, Delhi, Pp.157 – 160. Ø Raju, S.S. 1992. “Market survey of liquid milk in Hyderabad”. MTS Report (Unpublished). Institute of Rural Management, Anand, Gujrat. Ø Ray, and Sunil (2000) “Dairy industry in Rajasthan: Problems and prospects”. Institute of Development Studies, Rajasthan. Research Note on “Economics of Milk Marketing and Price Spread in Chittor District of Andhra Pradesh”. Ø Sankaran S. (2009), Indian Economy, Margham Publications, Chennai, p.335. B 12
Ø Satbir Singh, Timothy James Coelli and Euan Fleming (2008) “Efficiency and Productivity Analysis of Cooperative Dairy Plants in Haryana and Punjab States of India” Working Papers from University of New England, School of Economics. Ø Sintayehu Yigrem,* Fekadu Beyene, Azage Tegegne and Berhanu Gebremedhin (2008) “Dairy production, processing and marketing systems of Shashemene - Dilla area, South Ethiopia” - abstract of the project on Improving Productivity and Market Success (IPMS) of Ethiopian farmers project, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia. Ø Vijay Gorakh Patil “Marketing Analysis of Milk Production in Shirpur Tehsil of Dhule District of Maharashtra (India)” Ph.D. Research Fellow YCMOU, Nashika, Pp. 14-15. Ø Website:http://www.fao.org/ag/pplpi.html,WorkingPaper: http://www.fao.org/ag/againfo/projects/en/pplpi/docarc/wp7.pdf. Ø Yue Yaguchi and Kei Kajisa (2006) “Production Systems in South India from 1971 to 2002”, 2006 Annual Meeting, August 12-18, Queensland, Australia from International Association of Agricultural Economists.
SURVEY Ø National Family Health Survey (NFHS-2), 1998 – 99, India, ORC Macro Calverton, Maryland, USA, Pp. 39 - 41. Ø Statistical Handbook of Tamil Nadu (2008), Principal, Secretary and Director, Department of Economics and Statistics, Chennai, Pp.139 – 147. Ø Economic Survey (2009 – 10).
Appendices A 1
APPENDIX - I
Trends in Milk Production in Tamil Nadu TABLE 1 – MILK PRODUCTION IN TAMIL NADU
Production Per capita availability of milk production Year (Lakh tonnes) (grams per day)
1985-86 31.18 165
1990-91 33.75 166
1995-96 37.91 185
2000-01 48.99 216
2001-02 49.88 219
2002-03 46.22 204
2003-04 47.53 209
2004-05 47.84 210
2005-06 54.74 231
2006-07 55.61 232
2007-08 55.86 233
Source: Directorate of Animal Husbandry and veterinary sciences.
A 2
District wise milk production in Tamil Nadu in 2007-08 (in ‘000 Tonnes) S. District Total Milk Production No. 1 Chennai 3.932 2 Kancheepuram 156.023 3 Thiruvallur 154.873 4 Cuddalore 190.675 5 Villupuram 334.215 6 Vellore 312.367 7 Thiruvannamalai 256.178 8 Salem 450.613 9 Namakkal 237.724 10 Dharmapuri 208.823 11 Krishnagiri 171.965 12 Erode 314.711 13 Coimbatore 333.225 14 The nilgiris 89.769 15 Tiruchirappalli 224.558 16 Karur 110.200 17 Perambalur 163.250 18 Pudukottai 114.036 19 Thanjavur 196.748 20 Nagapattinam 150.340 21 Thiruvarur 160.492 22 Madurai 169.428 23 Theni 70.822 24 Dindigul 148.296 25 Ramanathapuram 67.047 26 Virudhunagar 194.808 27 Sivagangai 72.751 28 Tirunelveli 296.309 29 Thoothukudi 105.861 30 Kanyakumari 126.118 Source: Department of Animal Husbandry and Veterinary services. A 3
Bovine Population in Tamil Nadu –Census wise (nos in lakhs)
Year Cattle Buffalo
1951 102.16 22.97
1956 96.98 20.40
1961 108.28 25.94
1966 108.59 27.94
1974 105.72 28.53
1977 108.01 30.78
1982 103.66 32.12
1989 93.53 31.28
1994 92.71 32.00
1998 90.47 27.41 Source: Directorate of Animal Husbandry and veterinary sciences.
A 4
SAMPLING SELECTION
Thirukkattuppalli Area– Bovine Population S. Area Name Total population Percentage No. 1 Thirukkattuppalli 1532 31 2 Pathiragidi 942 19 3 Maraneri 880 18 4 Kangayampatti 876 17 5 Thiruchinampoondi 749 15 Total 4979 100
BudalurArea – Bovine Population S. Area Name Total population Percentage No. 1 Budalur 950 26 2 Avarampatti 922 25 3 Chellapanpatti 767 21 4 Nandavanapatti 559 16 5 Kovilpathu 439 12 Total 3637 100
Sengipatti Area -Bovine Population S. Area Name Total population Percentage No. 1 Sengipatti 885 28 2 Puthugudi 805 25 3 Vendayampatti 705 22 4 Palayapatti 400 13 5 Maneripatti 398 12 Total 3193 100
A 5
BUDALUR BLOCK POPULATION
S. Area Population SC Population ST Population Literates Name HHs No. (Hec) Total Male Female Male Female Male Female Male Female 1 Achampatti 671.52.5 322 1545 777 768 375 370 0 0 395 264 2 Avarmpatti 338.55.0 275 1268 635 633 176 188 20 19 447 355 3 Budalur 828.00.5 1592 6986 3489 3497 890 890 0 0 2649 2237 4 Indalure 782.68.0 392 1623 815 808 218 221 0 0 474 295 5 Kadamngudi 288.47.0 264 1149 567 582 14 14 0 0 382 293 6 Kangayampatti 825.29.0 314 1384 694 690 230 263 8 7 504 369 7 Kotrapatti 380.52.5 188 741 379 362 99 86 0 0 282 191 8 Kovilpathu 423.520 542 2348 1165 1183 420 424 0 0 906 764 9 Maneripatti 578.69.0 460 2088 1057 1031 526 531 0 0 652 476 10 Maraneri 422.49.5 423 1753 873 880 201 182 0 0 697 550 11 Muthuveera Kandiyanpatti 385.98.5 234 1014 511 503 106 102 0 0 356 255 12 Nandavanpatti 784.83.5 421 1895 962 933 270 244 0 0 632 486 13 Paliyapatti (South) 1308.39.0 485 2072 1015 1057 261 271 0 0 611 490 14 Paliyapatti(North) 1160.80.0 505 2184 1129 1055 345 311 0 0 411 264 15 Pudugudi (South) 1109.21.5 79 357 175 182 46 40 0 0 105 79 16 Pudugudi(North) 1203.23.5 727 3308 1677 1631 470 474 0 0 1075 758 17 Pudupatti 856.89.5 363 1714 869 845 68 59 0 0 568 467 18 Rayamundanpatti 928.08.5 332 1413 711 702 99 91 0 0 392 257 19 Sanoorapatti 934.59.0 590 2943 1458 1485 409 377 0 0 996 811 20 Sellappanpettai 496.98.0 365 1540 762 778 38 37 0 0 474 342 21 Sengipatti 1721.14.0 868 3865 1937 1928 850 850 2 6 1221 849 22 Sologampatti 874.21.0 335 1494 730 764 202 219 1 0 496 411 23 Suragudipatti 589.22.5 186 823 395 428 141 142 0 0 242 174 24 Thondrayampadi 361.93.5 261 1164 586 578 153 151 0 0 400 307 A 6
25 Veeramarasanpettai 608.88.5 183 750 366 384 181 195 11 11 208 172 26 Vendayanpatti 978.44.0 301 1294 671 623 287 253 0 0 397 256 27 Agarpetti 263.69.5 347 1410 701 709 267 266 0 0 510 415 28 Alamelupuram 402.00.0 576 2617 1223 1394 136 176 0 0 973 920 29 Arcadu 273.06.0 164 664 330 334 92 105 0 0 224 168 30 Dekshasmudram 294.77.0 385 1648 821 827 371 380 0 0 583 485 31 Katchmangalm 245.53.5 360 1491 735 756 190 197 0 0 565 453 32 Koothur 340.20.5 288 1239 615 624 339 351 0 0 387 277 33 Koviladi 970.47.0 876 3703 1826 1877 289 291 6 9 1296 1073 34 Mahadevapuram 195.04.5 78 365 171 194 88 94 0 0 130 108 35 Maikelpatti 276.86.0 505 2202 1093 1109 7 13 0 0 866 836 36 Megalathur 227.37.5 225 969 490 479 228 228 0 0 401 327 37 Natthamangalam 259.13.0 139 601 293 308 234 255 0 0 191 152 38 Nemam 206.39.0 417 1740 847 893 112 94 0 0 646 526 39 Orathur 165.11.5 332 1326 670 656 199 183 0 0 538 434 40 Pathiragudi 479.18.5 334 1518 755 763 458 461 0 0 512 404 41 Palmaneri 471.12.5 524 2325 1310 1195 60 58 0 0 879 709 42 Pavanamangalam 112.84.0 294 1231 612 619 0 0 0 0 502 396 43 Rajagiri 162.44.0 512 2155 4045 1110 407 488 0 0 797 651 44 Ranganathapuram 73.09.0 127 528 279 249 98 93 0 0 219 167 45 Thogur 729.94.5 548 2317 1127 1190 184 215 0 0 887 714 46 Thiruchinampoondi 768.88.0 535 2083 1033 1050 389 420 0 0 710 571 47 Unjini 224.45.5 49 191 100 91 0 0 0 0 76 54 48 Vishnampettai 607.52.5 594 2559 1285 1274 339 329 0 0 870 668 49 Vittalapuram 413.40.0 284 1255 616 639 60 64 0 0 503 457 50 Thirukkatupaali 275.68.0 2889 12567 6291 6276 760 735 0 0 4988 4338 Total 22389 97419 48493 48926 12382 12481 48 52 34225 27475 Source: Statistical Department, Thanjavur. A 7
Thirukkattuppalli Dispensary control area population and Bovine population
Bovine S. Area Name HHs Population Populati No. (Hec) on 1 Agarpetti 263.69.5 347 1410 526 2 Alamelupuram 402.00.0 576 2617 536 3 Indalure 782.68.0 392 1623 596 4 Kadamngudi 288.47.0 264 1149 326 5 Kangayampatti 825.29.0 314 1384 876 6 Katchmangalm 245.53.5 360 1491 399 7 Koothur 340.20.5 288 1239 265 8 Koviladi 970.47.0 876 3703 517 9 Maikelpatti 276.86.0 505 2202 629 10 Maraneri 422.49.5 423 1753 880 11 Megalathur 227.37.5 225 969 486 12 Nemam 206.39.0 417 1740 649 13 Orathur 165.11.5 332 1326 507 14 Palmaneri 471.12.5 524 2325 396 15 Pathiragudi 479.18.5 334 1518 942 16 Pavanamangalam 112.84.0 294 1231 285 17 Rajagiri 162.44.0 512 2155 107 18 Ranganathapuram 73.09.0 127 528 150 19 Sologampatti 874.21.0 335 1494 620 20 Thiruchinampoondi 768.88.0 535 2083 749 21 Thirukkatupaali 275.68.0 2889 12567 1532 22 Thogur 729.94.5 548 2317 453 23 Thondrayampadi 361.93.5 261 1164 232 24 Vishnampettai 607.52.5 594 2559 527 25 Vittalapuram 413.40.0 284 1255 327 Total 12961 55509 14596
Source: Regional Joint Director, Animal Husbandry, Thanjavur. A 8
Budalur Dispensary control area population and Bovine population
S. Bovine Village Name Area(Hec) HHs Population No. Population 1 Budalur 828.00.5 1592 6986 950 2 Kovilpathu 423.520 542 2348 439 3 Chellapanpettai 496.98.0 365 1540 767 4 Avarampatti 338.55.0 275 1268 922 5 Veeramarasan pettai 608.88.5 183 750 277 6 Muthuveera 385.98.5 234 1014 323 Kandiyan patti 7 Nandavanappatti 784.83.5 421 1895 559 8 Arcadu 273.06.0 164 664 219
Total 3776 16465 4456
Source: Regional Joint Director, Animal Husbandry, Thanjavur.
Sengipatti dispensary control area population and Bovine population
Bovine S. No. Village Name Area(Hec) HHs Population Population 1 Sengipatti 1221.14.0 868 3865 885 2 Sanoorapatti 934.59.0 590 2943 388 3 Puthupatti 856.89.5 363 1714 372 4 Archampatti 671.52.5 322 1545 392 5 Puthugudi (South) 1109.21.5 79 357 120 6 Puthugudi (North) 1203.23.5 727 3308 805 7 Vedayampatti 978.44.0 301 1294 705 8 Maneripatti 578.69.0 460 2088 398 9 Palayapatti (north) 1160.80.0 505 2184 400 10 Palayapatti(south) 1308.39.0 485 2072 359
Total 5218 23606 5810
Source: Regional Joint Director, Animal Husbandry, Thanjavur. A 9
.
Veterinary Institutions and animals treated block wise
Veterinary Institutions Other Units d
S. Name of the Block No. E O AH Uni ts Sub Cen t e rs Ho s pi tal Anim a l T re at ed P o l y Clinic Di s pe n a ries in v e s t i gat o n M o bile U n i ts Anim a l D i s e C a s t r at i o n P er fo rme Clinici a n C e t ers
1 2 3 4 5 6 7 8 9 10 11 12
1 Thanjavur 5 1 9 1 1
2 Budalur 3 5
3 Orathanadu 2 6 4
4 Thiruvonam 3 7
5 Thiruvaiyaru 1 3 4
6 Kumbakonam 5 1 4 1
7 Thiruvidaimaruthur 4 7 719474 38056
8 Thirupanandal 3 3 Nil
9 Papanasam 3 4
10 Ammapet 1 4 6
11 Pattukottai 1 5 4 1
12 Madukkur 4 5
13 Peravurani 3 2
14 Sethubavachathiram 1 4 3
Total 6 55 2 67 1 3 719474 3805
Source: Regional Joint Director of Animal Husbandry, Thanjavur. A 10
Number of Veterinary Hospitals:
Number of S. No. Name of Block Government Private Hospitals Hospitals
(1) (2) (3) (4)
1 Thanjavur
2 Budalur
3 Orathanadu 2
4 Thiruvonam
5 Thiruvaiyaru 1
6 Kumbakonam
7 Thiruvidaimaruthur
8 Thirupanandal Nil
9 Papanasam
10 Ammapet 1
11 Pattukottai 1
12 Madukkur
13 Peravurani
14 Sethubavachathiram 1
6
Source: Regional Joint Director of Animal Husbantry, Thanjavur. A 11
APPENDIX - II
PRODUCTION AND MARKETING OF MILK IN BUDALUR BLOCK OF THANJAVUR DISTRICT OF TAMIL NADU
INTERVIEW SCHEDULE
I. Personal Details
1. Name of the Respondent :
2. Sex : 1) Male 2) Female
3. Age :
4. Marital status : 1) Married 2) Unmarried
3) widow 4) widower
5. Religion : 1) Christian 2) Hindu
3) Muslim 4) Others ______
6. Community : 1) SC 2) BC
3) MBC 4) General
7. Caste :
8. Educational Status : 1) Illiterate
2) Primary School
3) Middle School
4) High School
5) Higher Secondary
6) Diploma
7) Graduate
8) Post Graduate
9) Others ______A 12
9. Family details of the Respondent
Relationship Educational Income Per month S. No. Sex Age Occupation to the Head Qualification (in Rs)
1
2
3
4
5
Total
II. Income and Expenditure Details
10. Occupation and income
S. No. Nature Occupation Income Per Month
1 Primary:
III. Asset details
11. Whether you are living in
1) Own house 2) Rented house 3) leased
12. Movable and Immovable Asset details.
Present value Total S. No. Particulars Number (in Rs) (in Rs) Movable assets 1 Refrigerator 2 Cell Phone/Telephone 3 Tractor 4 Cycle 5 Scooter/ Bike 6 Car 7 TV 8 Transistor/Radio 9 Jewell 10 Mattress A 13
11 Chairs 12 Cot/Bed 13 Clock /Watch 14 Electric Fan 15 Pressure Cooker 16 Sewing Machine 17 Bullock Cart 18 Poultry 19 Livestock Immovable assets Land 20 Dry Land 21 Wet land 22 Thoppu Nature of House 23 Pucca 24 Tiled 26 Thatched Bovine shelter 27 Pucca 28 Tiled 29 Thatched Total
13. Toilet facility : Flush Toilet
Public Flush Toilet
No facility
14. Source of lighting : Electricity
Kerosene
Others
15. Main fuel for Cooking : Electricity
Liquid Petroleum Gas
Others A 14
16. Source of drinking water : Hand Pump
Public taps
Others
17. Separate Room for Cooking : Yes No
18. Family Expenditure Pattern (per month):
Amount S. No. Particulars Rs. 1 Food 2 Cloth 3 Medical 4 Education 5 Transport(vehicle petrol) 6 Compliments 7 Cell Phone 8 Entertainment 9 Common festival 10 Religious festival 11 Others (gas, EB, Tax, house maintenance etc…. 12 Total
19. Sources of saving (per month):
S. Amount Sources of saving No. Rs. 1 Cash in hand 2 Chit funds 3 Post office 4 Co-operative societies 5 Bank 6 Insurance 7 Others(compliments Moi) Total
A 15
20. Investment pattern (per year):
S. Amount Sources of Investment No. Rs. 1 Agriculture Land 2 Business 3 Bovine 4 Real Estate 5 Government securities 6 Kisan vikas Patra 7 Share 8 Others Total
21. Sources of Borrowing:
S. Sources Amount Rs. No. 1 Money Lender 2 Bank 3 Relatives/Friends 4 Chit fund 5 Co-Operative societies 6 Government scheme 7 Others Total
22. For what purpose you have borrowed
1) Agriculture 2) Buying Bovine 3) Buying fodder
4) Veterinary 5) Others
23. Is your bovine bought by borrowing? Yes No
If yes where you have borrowed
24. Animals maintained : 1) Cow 2) Buffalo 3) Both A 16
Bovine details
S. No. Bovine Numbers Present value Total Cow 1 Milch cows a) Indigenous b) Cross Breed c) Dry Cow d) Male calves e) Female calves Buffalo 2 a) Milch Buffalos b) Dry Buffalo c) Male calves d)Female calves Total
25. Which season Bovine is giving more milk per day Summer / Winter / Rainy / Spring?
Why?
Reasons ------
S. Summer Milk Rainy Bovine Winter Milk lit Per day No. lit Per day Milk lit Per day 1 Cow a) Indigenous b) Cross Breed 2 Buffalo
26. Which time bovine is giving more milk? 1) Morning 2) Evening Why?
Reasons ------
S. Bovine Morning Evening No. 1 Cow a) Indigenous b)Cross Breed 2 Buffalo A 17
IV The cost, returns and profitability of the milk production
27. Total quantity of milk attained (Returns /years) (Per animal)
Inter Income by sale of (Rs) Total S. Lactation Pric/lit income Bovine calving Gunny No. Length of milk Milk Manure Calves period bags (Rs) 1 Cow a) Indigenous b) Cross Breed 2 Buffalo
28. Have you got storing facilities for milk before sales yes/No If yes what type?
29. Sale of Milk (Per Animal)
Price of Milk Qty of Milk Income S. No. Particulars Cow Buffalo Cow Buffalo Cow Buffalo
1 To Tea stall
2 To Household
3 To Milk vendor
4 Own Consumption
5 Co-Operative societies
6 Total
30. Feed consumed (per animal) per day
Green Dry Price/Kg.(Rs) S. Concentrate Total cost Particulars fodder fodder No. (Kg) (Rs) ( Kg) (Kg) GF DF CT
1 Milch Cow a) Indigenous b) Cross Breed
2 Milch Buffalos
3 Cow Calves
4 Buffalo Calves
Total
A 18
31. Employment Prospects of Milk production (Per Animal)
Wage/day Family Hired Total S. Hours Particulars labour labour (Rs.) wage No. Employed (Rs.) (Nos) (Nos Cow Buffalo
1 Men
2 Women
3 Children Under18
Total
32. Cost on Health care per Month (Per animal)
Cow Buffalo S. Buffalo Cow Total Particulars Calves Calves No. in Rs. in Rs. Cost in Rs. in Rs.
1 Veterinary care
2 Vaccination
3 Deworming
4 Reproduction a)Artificial b) Natural
5 Insurance
6 Miscellaneous Maintenance(shelter)
7 Other cost Transport EB Storage (Cooling)
Total Medical
A 19
33. Fixed cost
S. Particulars Number Amount in Rs No.
1 Animals
2 Animal Shed
3 Dairy Implements
Total
34. How much distance from your house to bovine shelter?
1) Nearby your house 2) 1-2 kms 3) 3-4 kms
4) 5-6 kms 5) 7-8 kms 6) 9-10 kms
35. Do you have any grazing/Pasture land? How much acres you have?
1) Nil 2) 1-2 acres 3) 2 -3 acres
4) 3-4 acres 5) 5-6 acres
36. a) whether you are using common land for grazing purpose yes/no
37. What types of fodder you are cultivating?
S. No. Name of the fodder Area in Acres 1 Azola 2 CO-3 3 CO-4 4 Lucerne 5 Hedge Lucerne 6 Stylo 7 Soobabul 8 Sorghum 9 Maiz 10 Others Total
A 20
38. For what purpose Cow dung is used 1) Manure 2) Firework
39. Have you ever sold your cattle? Yes /No .Give details
V Problems
40. In emergency situation whether doctor comes or not: Yes No
41. How many kilometers from your house to the veterinary hospital
1) Nearby your house 2) 1-2 kms 3) 3-4 kms
4) 5-6 kms 5) 7-8 kms 6) 9-10 above
42. Whether you have common storage facilities or not Yes No
43. Is there any intermediaries when you are selling the milk? Yes No
44. How much you are expecting for milk price?
45. Whether the milk co-operative society is functioning or not Yes No
46. Have you got immediate payment when you are selling the milk? Yes No
47. Whether you have milk producer association or not. Yes No
48. Is your bovine affected by some disease Yes No if yes give the details
S. Cow Name of the disease Cow Buffalo Buffalo calves No. calves 1 Foot and Mouth 2 Anthrax 3 Black quarter(BQ) 4 Haemoragic Septiceia (HS) 5 Others
49. What are the problems you are facing?
1) Bovine health 2) Loan/Credit 3) Procurement price
4) Pasture Land/grassing land 5) Veterinary hospital 6) Marketing the milk
7) Storage and chilling unit 8) Middle man 9) Fodder
10) Others specify ------
50. Have taken insurance for your cattle? Yes No
51. Details of Insurance Government Scheme Private Scheme A 21
52. Which system urgent for effective milk production?
53. Is there any milk price fluctuation Yes No
54. Do you feel the bovine population is decreasing? If yes state the reasons
55. Give your suggestions and policy measures
56. Whether you have training undergone or not, where------
57. Technical consultation from------A 22
APPENDIX - III
PHOTO PLATES
Photo Plates - 1
A WOMAN IS MILKING FROM COW
Photo Plates - 2
COW FEEDS THE CALF A 23
Photo Plates - 3
COW AND CALF DRINK WATER FROM THE RIVER
Photo Plates – 4
GRAZING COW A 24
Photo Plates – 5
ROW OF CATTLE
Photo Plates - 6
A WOMAN IS FEEDING THE COWS
A 25
Photo Plates - 7
A MAN WASHES BUFFALO IN THE CAUVERY RIVER
Photo Plates - 8
COW EATS CONCENTRATE FROM BUCKET
A 26
Photo Plates – 9
COW EATS DRY FODDER
Photo Plates – 10
DRY FODDER
A 27
Photo Plates - 11
COWS IN THE SHELTER
Photo Plates – 12
COW SHELTER A 28
Photo Plates – 13
COW IS CHEWING
Photo Plates - 14
A MAN IS FEEDING THE COW A 29
Photo Plates - 15
A MAN IS GIVING DRY FODDER TO THE COW
Photo Plates - 16
COWS ARE IN THE KATCHA SHELTER
A 30
APPENDIX - IV
PAPER PUBLISHED
A 31
A 32
A 33
A 34
A 35
A 36
DAIRY SECTOR IN BUDALUR BLOCK OF THANJAVUR DISTRICT
P. Jayakumar*
Introduction
Dairying is the production and marketing of milk, usually cow’s milk and its products, it includes the care of cows, their breeding, feeding, management, and milking. The milk must be collected, processed into dairy products, and marketed. All of these operations have been studied and improved by physiological, economic, and marketing research and development. (Encyclopedia of Britanica) Dairying is playing a significant role in strengthening rural economy. It provides definite and regular income and employment to 11 million people in principle status and 9 million in subsidiary status. Women constitute 71 percent of the labour force in this sector.(Economic survey 03-04).The livestock sector provides an important role in the national economy and contributed over 5.26 per cent to the total GDP during 2006-07 and contributes about 31.7 per cent GDP from agriculture and allied activities. India ranks first in the world in milk production, which increased from 17 million tonnes in 1950-51 to about 104.84 million tonnes by 2007-2008. This success story of Indian milk production is the “Operation Flood” one of the world’s largest dairy development programs, which helped to create strong network and linkages among millions of smallholder producers, processors and urban consumers, was an important instrument in achieving this success. The per capita availability of milk has also increased from 112 grams per day in 1968-69 to 252 grams during 2007-2008.But still low compared to the world average of 265 grams/day (Economic survey 08-09).This deficit which is of a very serious nature may affect the health and vitality of the nation as milk is the only source of animal protein for a large number of people in this country. In addition to that there is also the problem with regard to the availability of milk. It has been
* Department of Economics, St.Joseph’s College (Autonomous) Tiruchirappalli-2. A 37
largely varied across the regions or states. The main constraint to less availability and large variation across the regions is not only limited to the production of milk but also purchasing power of the people as well as inadequate handling and processing facilities and marketing infrastructure. Though per capita availability of milk in India has increased, demand for milk is increasing day by day owing to increase in population and individual income.
Problem faced by the dairy Farmers Although there is remarkable improvement of dairy enterprises in recent years, the dairy farmers faced some problems in developing their dairy enterprise the study area. The major constraints hindering the development of dairy sector in the study area are.
a) Shortage of feed Shortage of green fodder and feed concentrate is the root cause of poor performance of dairy sector in general as the genetic milk production potential of cross breed animals could not be exploited fully in the absence of proper nutrition.
b) Lack of marketing facilities Due to lack of marketing facilities and extension services, there is poor perception of the farmers towards commercial dairy enterprise as an alternative to other occupations.
c) Insufficient veterinary services Due to lack of proper veterinary extension system there is poor perception to the farmers towards dairy enterprise as viable alternative to crop husbandry. d) Deprived of getting remunerative price Lack of access to urban markets for remunerative prices of milk and milk products is one of the major constraints affecting the development of dairy farming. e) Lack of proper livestock planning Lack of specific state policy on animal breeding and strategies for livestock development in the state plan with proper perspective. A 38
f) Prevalence of middleman Unorganised fragmented market for milk involved a chain of middleman who reap the actual benefit depriving the producers from their due share.
Suggestions The following suggestions are provide for the development of the dairy sector in the study area 1) Adequate veterinary services: The veterinary facilities available in the study area are not adequate and sufficient. Steps should be taken to provide adequate and proper veterinary facilities in the study area. 2) Credit facilities: The financial institutions can also play a significant role in improving the processing infrastructure by extending credits to good working SHGs and milk producing units. 3) Artificial insemination: The state veterinary department should create facility for artificial insemination and pregnancy test in the door step of the dairy farmers.
Conclusion The findings of the study revealed that the composition of milch animals with adequate number of cross breed animals could boost up milk production significantly. The farmers in the study area found to have used their wisdom to exploit the resource substantially in a sustainable manner. The sustainable development of dairy farming in the state through optimum utlisation of natural resources followed by health-care of livestock, improvement of breeding through Artificial Insemination, timely vaccination can go a long way in the field of animal husbandry in general and dairy sector development in particular. The potential of indigenous livestock needs to be tapped by improving nutrient fodder resources. The dairy enterprise in the study area has been able to improve the economic condition and standard of living of the dairy farmers. This created a positive impact in creating of gainful employment opportunity and income to the people living in the rural areas. A 39
INCOME AND EMPLOYMENT OPPORTUNITY IN ROSE CULTIVATION P. Jayakumar*
INTRODUCTION Floriculture is a fast emerging industry in India, as it has increased 12.5 times in area and 33 times in trade from 1962-1991.The increase in both area and trade is because of socio-economic factors such as changes in social values of people, environment, increase in population and living in the flats in cities, standard of living, development of hotels and shopping centers and making beautiful flower items presented on different auspicious occasions. Floriculture crops are very important for exports. “India can become a major exporter in floriculture and horticulture but not in other commodities”, said Dr. Manmohan Singh, Now floriculture has become one of the extreme focus segments for development of export by the government of India. The growth of floriculture industry from 1962 to1990 was very slow but thereafter there has been a significant rise in floriculture export from Rs.14.55 crores in 1991-92 to Rs.30.60 crores in 1994 –95, and Rs.57.80 crores 1995-96.Developing countries have only 6 per cent share in the world market. This helps in increasing the export from India, which is otherwise negligible. The liberalization of the country’s economy has given a boost to agri-business particularly floriculture. The prospect of better returns on value-added floriculture items has attracted private investors. Floriculture –defined as all activities related to production and use of flowers, ornamental plant seeds and bulbs, is eco-friendly and can be an important source for earning foreign exchange. An important requirement of floriculture is the production of good quality of plants which can give world class quality flowers. It is now felt that in order to achieve this goal, it is necessary to have nurseries in rural areas and that would help in increasing employment in rural areas. In fact, as we proceed towards globalization, our economy has attracted big investors in various sectors.
* Lecturer in Economics St. Joseph’s College (Autonomous) Trichirappalli-2. A 40
Also, some consultancy services have been set up to provide guidance and help to prospective floriculturists and the organizations involved. They also prepare market survey reports, project reports and provide training to farmers.
DETERMINANTS OF INCOME FROM ROSE FLOWER CULTIVATION PER ACRE
Multiple regression analysis is carried out taking income per acre as the dependent variable and considered as independent variables labour cost per acre, pesticide cost per acre, fertilizer cost per acre and other cost per acre and includes plant and transportation cost. The result of multiple regression analysis is given below. TABLE Adjusted Std. Error of R R Square R Square the Estimate
0.873 0.762 0.705 275.30
From the above model summary table the R square value is 0.762 which means that the variability in the income per acre is explained to the extent of 76.2 per cent by the above said independent variables.
Unstandardized Standardized Model coefficients coefficients B Std. Error Beta t Sig. (Constant) -706 284.3 2.48 0.13 Labour cost per acre 10.51 0.853 .045 12.3 0.000 Fertilizer cost per acre 12.31 2.35 .308 2 0.009 Pesticide cost per acre 8.44 1.57 .145 0.008 Total cost per acre .615 .485 .025 5.23 0.115 (plant-transport) 1.26
From the above table we observed that fertilizer cost per acre, labour cost per acre and pesticide cost per acre are the significant variables. Thus, the multiple
regression becomes as y = -706+10.51x1 +12.31x2 +8.44x3. In the above model x1 is labour cost per acre, x2 is fertilizer cost per acre and x3 pesticide cost per acre, Further A 41
the partial regression coefficient for labour cost per acre is 10.51 which means that for every one rupee invested in labour cost, the income increases at the rate of 10.51 rupees. Similarly the partial regression coefficient for pesticide cost is 8.44 which means that for every one rupee invested in pesticide cost the income increases at 8.44. The partial regression coefficient for fertilizer cost per acre is 12.31, which means that for every one rupee spent on fertilizer cost, the income increased at Rs.12.31.
Conclusion The floriculture has the scope of providing employment to the rural folks throughout the year thus it will eliminate unemployment and poverty if it is done on professional lines. Education of flower cultivators depends upon the income. Rose flower cultivators are getting more profit. So their standard of education is comparatively high. The study also found out that flower crops require huge amount of labour. Hence it is highly a labour intensive. Therefore it provides more employment opportunities to rural population men, and women are also employed. Floriculture is fast developing into an important economic activity. The world wide demand for flowers and flower products is also increasing due to the GDP increase in many countries. Though, India’s participation in the world trade is very successful. Unlimited opportunities created by the global trade deficit and the liberal policies of the country. The producer and the country should stand to gain in the process of developing this economic pursuit as also the consumer.