Adoption behaviour of the dairy farmers in relation to artificial insemination in co-operative farming system

R K Ghosh, A Goswami and A K Mazumdar

Department of Veterinary and Animal Husbandry Extension Education
West Bengal University of Animal and Fishery Sciences
68, K. B. Sarani, Belgachia, Kolkata- 37
arunasisvet@yahoo.co.in
* Part of the MVSc. Thesis of the First Author

Abstract

The present study was carried out in selected Gaighata and Bagdah blocks of North-24 Pgs district, West Bengal. From each block, 25 percent (approximately) of the Village Level Milk Co-operative Societies were selected randomly. From each of the selected milk co-operative societies four dairy farmers were selected randomly out of which both Member Co-operative Society (MCS) and Non-member Co-operative Society (NMCS) were two in number.  Direct face-to-face interview method with structured schedule was followed for the purpose of data collection.

The study revealed that adoption of AI is highly correlated with all the socio-psychological variables in both MCS and NMCS. It also revealed that all the communication variables were having significant correlation with adoption of AI both in MCS and NMCS except the urban contact in MCS. Among socio-economic variables age was having significant negative correlation with adoption of AI. On path analysis, innovation proneness and knowledge about de-worming were shown to be the key variables that directly and indirectly influenced the adoption of AI in MCS and NMCS respectively.

Key Words: Adoption, artificial Insemination, co-operative society, dairy farmers.

Introduction

Adoption of any improved technology involves a process in which awareness is created, attitudes are changed and favourable conditions for adoption are provided. Wilkening (1953) described the process of adoption, deciding and acting over a period of time. How latent is the knowledge of a dairy producer about various husbandry practices such as breeding, feeding and management of milk animals, determines largely the success or failure of a dairy enterprise. In this context, milk co-operatives have quite ambitious objectives. They not only want to increase the productivity of milk animals but also wish to raise the economic status of rural people at large through increased milk production. To enhance the production potential of our milk animals distributed through out the length and breadth of our country, introduction of superior germ-plasm into our indigenous breeds of cattle through artificial insemination (AI), may be the key factor. For this purpose mass adoption of AI by the dairy farmers is a crucial fvactor. At the same time, adoption behaviour of the dairy farmers depends on education, knowledge, attitude, risk orientation and innovation proneness (Bhople and Thakare 1994; Kunzru and Tripathi 1994). Kaura (1967) found that unfavourable attitude of the farmers towards AI was the major cause for its non-adoption in Haryana villages. Singh (1976) found that 68 percent and 32 percent of the adopter farmers had high and medium level of knowledge about AI respectively, while majority of non-adopters had either lower or medium and only 10 percent had high level of knowledge. Sreeja (1993) reported that AI is increasingly being adopted as the breeding technique and its success rate should be improved. Considering this theoretical back up, the study was carried out to find the correlation with socio-economic, socio-psychological and communication characteristics of the dairy farmers in relation to adoption of AI and also to find out the key variables that influence the adoption of AI.

Materials and Methods

The Gaighata and Bagdah blocks of North-24-Parganas in West Bengal were selected for the present study. From each of the selected two blocks, 25 percent (approximately) of the Village Level Milk Co-operative Societies were selected randomly, thus 30 Village Level Milk Co-operative Societies were selected.  From each of the selected milk co-operative societies, four dairy farmers were selected randomly out of which both Member of Co-operative Society (MCS) and Non-member of Co-operative Society (NMCS) were equally represented. In this way, 60 Member Co-operative Society and 60 Non-member Co-operative Society (total 120 respondents) were selected, which constituted the sample of the present study. Before going to final data collection, a pilot study was carried out and accordingly appropriate changes in the construction and sequence of interview schedule were made.  The schedule was administered to the respondents and the responses were recorded. Data were collected through face-to-face interview by the researcher himself.

Statistical analysis was done with the help of SPSS 10.0 package. In the present study, the adoption was measured by the adoption index method developed by Dasgupta (1968). According to him, adoption index is referred to as "Years of use of adopted applicable practices". The study was carried out with 24 independent characteristics (socio-economic, socio-psychological and communication characteristics) and one dependent variable of the dairy farmers (Table 1):

Personal localized sources include friends, neighbours and relatives. Personal cosmopolitan sources include Extension personnel and bank personnel.

Results and Discussion

Goswami et al (2000) reported similar findings for the relationship between the dependent variable (adoption of artificial insemination) and occupation, caste, family size, land and house type, knowledge about AI, deworming, feeding of concentrates and mass media communication (Table 2). A similar attitude towards dairy farming was shown by Kaura (1967)..

In the case of non-members of milk co-operatives, the relationships are similar to those reported by Chander (1970) for education of the respondent, with Kulkarni (1973) for family type, with Goswami et al (2000) for education of the respondent, occupation, caste, family size, land, house type, knowledge about AI, deworming, feeding of concentrates and mass media communication, and with Kaura (1967) for attitude towards dairy farming.

Path analysis ( http://www2.chass.ncsu.edu/garson/pa765/path.htm ) on the basis of relationship between adoption of AI and the exogenous variables:

Innovation proneness had the largest direct effect on adoption of AI in case of dairy farmers of Member Co-operative Societies (Path Diagram 1).

The residual effect was 0.388, that is 38.8 percent of the total variation was left unexplained.

Further processing of the data reveal that out of 24 exogenous variables, 13 had their largest indirect effects through innovation proneness. These were education of the respondent, house type, attitude towards dairy farming, risk orientation, knowledge about AI, deworming, green fodder feeding, concentrate feeding, mass media communication, personal cosmopolitan and localized sources and urban contact. On the other hand, three variables viz economic status, family educational status and occupation exerted their largest indirect effect through attitude towards dairy farming. Similarly, economic status steers two variables viz. material possession and land. Family type also steers two variables viz. family size and farm power. Innovation proneness, age, caste and family type had their largest indirect effect through knowledge about AI, green fodder feeding, concentrate feeding and communication source respectively.

The findings suggest that innovation proneness not only exerted the largest direct effect on adoption of AI by the dairy farmers of Member Co-operative Society but a number of factors also exert their largest indirect effect through it. So innovation proneness has come out to be the key element which directly and indirectly promotes the adoption of AI in case of dairy farmer of Member Co-operative Society.

Path analysis for Non-member Co-operative Society (Path Diagram 2) revealed that Economic Status had the largest direct effect on adoption of AI. The residual effect was 0.196.

Further processing of the data reveal that out of 24 exogenous variables, 7 had their largest indirect effect through knowledge about de-worming (innovation proneness, attitude towards dairy farming, risk orientation, knowledge about AI, knowledge about green fodder feeding, knowledge about concentrate feeding and communication source). Similarly, seven variables had their largest indirect effect through economic status (ccupation, family educational status, family size, land, house type, farm power and material possessions). Communication source influenced six variables (education of the respondent, economic status, mass media communication, personal cosmopolitan and localized sources, and urban contact). On the other hand, age and caste exerted their largest indirect effect through land. Similarly, family type and knowledge about de-worming exerted their largest indirect effect on adoption of AI through family size and innovation proneness, respectively.

It is clear that the extent of the indirect effect through knowledge about deworming was significantly higher than that through economic status. So knowledge about deworming appears to be the key element, which directly and indirectly promotes the adoption of AI in case of dairy farmers of Non-member Co-operative Societies. Economic status is the second most important variable that influences the adoption of AI by the dairy farmers of Non-member Co-operative Society.

Conclusions

• Innovation proneness is the key variable that directly and indirectly influence the adoption of AI in Member Co-operative Society

• Knowledge about deworming and economic status are the two main factors that influence the adoption of AI both directly and indirectly in Non-member Co-operative Society.

References

Bandyopadhyay A K 1986 A study on adoption of Rabi programme and investment pattern of additional income by farmers of Sundarban; Ph.D. thesis submitted to BCKV, West Bengal.

Bhople R S and Thakare S M 1994 Farm information source utilization, adoption and transfer behaviour of farmers; Rural India. 57(7): 153-154.

Chander Satish 1970 A study of socio-economic factors affecting the adoption of AI and attitude of farmers towards the same; A dissertation submitted to the Punjab University for M.Sc, (Dairy Extension) National Dairy Research Institute, Karnal.

Dasgupta S 1968 Relative predictability of five indices of adoption of recommended farm practices; Sociologia Ruralis. 8: 1-21.

Goswami A, Roy N, Mazumdar A K and Duttagupta R 2000 Factors related with adoption behaviour of the livestock owners about Artificial Insemination; Journal of Interacademcia. 4(2): 304-309.

Goswami A and Sagar R L 1987 A study of the knowledge level of the livestock owners about selected animal husbandry practices; M. V. Sc Thesis submitted to Indian Veterinary Research Institute, Izatnagar, U.P.

Gupta C L and Sohal T S 1976 A scale to measure dairy farmer's attitude towards dairy farming; Indian Journal of Extension Education. 13(3 and 4): 76.

Kaura M S 1967 A scale to measures farmer's attitude towards Artificial Insemination; M.Sc. Thesis submitted to Punjab Agriculture University, Hissar.

Kulkarni P S 1973 A study of socio-economic factors affecting adoption of AI in cattle in the selected villages of key village center, Nagpur; M.Sc. Thesis submitted to JNKVV, Jabbalpur.

Kunzru O N and Tripathi H 1994 A comparative study of adoption of dairy farm technologies between non-members and members of dairy co-operative villages; Indian Journal of Animal Sciences. 64(5): 501-507.

Moulik T K 1965 A study of the predictive values of some factors of adoption of Nitrogenous fertilizers and the influence of source of information on adoption behaviour; Ph.D. Thesis submitted to Indian Agricultural Research Institute, New Delhi.

Pareek U and Trivedi G 1964 Manual of Socio-Economic Status Scale (Rural), Mansayan, Delhi.

Ray G L 1967 A study of some Agricultural and sociological factors related to high and low levels of urbanization of farmers; Ph.D. Thesis submitted to Indian Agricultural Research Institute, New Delhi.

Singh J N 1976 An analysis of the adoption of AI for cross breeding in cows by dairy farmers of ICDP, Karnal; M.Sc. Thesis submitted to JNKVV, Jabbalpur.

Sreeja S 1993 Impact of technology on milk production in Kerala State; Journal of Veterinary Animal Science. 24(1): 68-71.

Supe S V 1969 Factors related to different degrees of rationality in decision-making among farmers; Ph.D. Thesis submitted to Div. of Agricultural Extension, Indian Agricultural Research Institute, New Delhi.

Wilkening E A 1953 Adoption of improved farm practices as related to family factors; Wisconsin Experiment Station Research Bulletin. 183 Wisconsin, USA.