find out the extent of adoption of improved pig production technology and identify the factors that influences adoption of pig production technology in pig farmers
Mizoram is a mountainous region and it lies within the tropics. The slopes are steep on all sides and the average height is about 900 metres from sea level. Pig is the most important livestock in the state and plays a major role in the livelihood of the small farmers. The present study was undertaken to find out the extent of adoption of improved farm practices and to identify the factors that influences adoption of pig production technology in pig farmers. A total 100 numbers of the farmers were selected for the study and personal interview and self observation method were employed to collect data on five different aspects namely, housing, breeding, feeding, health care and general care and management practices. The study revealed that 81% of the farmers adopted improved technology on breeding and 63% of them adopted heath care practices at higher level in their farms. The percentage of respondents in adopting improved technology on housing and feeding practices were very low i.e. 62% and 63% respectively. Half of the respondents (50%) had adopted general care and management practices partially. The overall adoption was partial (Average score was 55.87). Majority of the respondents (51%) adopted the improved technology on pig rearing partially. The adoptions of improved technologies were associated with age, education, operational land holding, farm size, income from piggery, social participation, extension contact, farming experience, farm education exposure, scientific orientation, knowledge level, training and financial help received. These variables contributed 92.00% variation in the adoption gain in improved technologies in pig farming.
Animal agriculture has a specialized significance as it can play an important role in improving the socio-economic status of a sizable section of the weaker and tribal population. It gives safeguard to the crop failures in the event of natural calamities. Most cases livestock is the source of cash income for the subsistence farmers as well as endurance of family purchasing power in the event of unprofitable agriculture due to unforeseen reasons. This immense potential is limited by the traditional and tenure system and subsistence farming practices (traditional technologies) that unfortunately seldom assure , or generate adequate returns which can promote the development of more commercially oriented livestock production systems. If agricultural technologies developed for farmers in developing countries are not transferred in correct (appropriate) manner and adopted accordingly, all the efforts by the researchers who developed new technologies would have been in vain. This is probably why transfer and adoption of new technologies is perhaps one of the most popular written about and controversial topics in developing agriculture (Nell et al 1998). Technology transfer and development is not a new concept, it has been around since mankind discovered things that they did not know before (Finlayson 1995). A farmer is a rational decision maker who normally strives for a better standard of living and seeks ways of adopting new technologies to accomplish this goal (Nell et al 1998).
Among the commonly available meat producing animals of Mizoram state, pig occupies a unique place, as pig rearing is considered to be the most encouraging and appropriate livestock enterprise to narrow down the gap between the availability and requirement of animal meat in the state. Pigs are reared by each and every family as a backyard venture in Mizoram, India. The backyard production system of pigs in the state is characterized by low input; traditional management system suited to the local condition. There is a need to identify the factors that contribute positively to the adoption of new livestock technologies as well as those that represent main constraints for the diffusion /adoption process. (Nell et al 1998). Reimund et al (1981) reported that with respect to hog industry the adoption of technology has led to increase in farm size, specialization and associated risk, transaction cost and asset specificity. This type of research is essential for policy formulation to develop the livestock sector and alleviate poverty in rural areas of the state. This, as well as the fact that no research was previously done on adoption of technologies by the pig farmers in Aizawl District, the study was under taken with the following objectives:
The study was carried out in Aizawl district of the Mizoram state of India during March 2005 to September 2005. In Aizawl district, there were five blocks and from these five blocks two blocks namely Aibawk and Tlangnuam were randomly selected. From each selected block 5 villages were selected randomly i.e. 10 villages were selected for the study. From each selected villages, ten pig farmers were selected randomly to make a sample size of 100 respondents. The Interview Schedule was developed to obtain relevant information covering all the objectives of the study. Before going to final data collection, the interview Schedule was pre-tested on 20 non-respondents farmers of Aizawl and accordingly appropriate changes in the construction and sequence of interview schedule were made. Interviews were conducted by means of Interview Schedule with 100 pig farmers; the interview with farmers who were not fluent in English was done with the help of translator in order to preserve the accuracy of the information. In order to ascertain extent of adoption of improved technology, the responses of respondents were collected on five selected practices, namely Housing, Breeding, Feeding, Health Care, and General Care and Management. The score was assigned for the adoption of each of the practices in the following way:
The total score for a respondent is obtained by summing up the score obtained on each practices. The minimum score one could score was 0 and maximum score was 90.
The adoption level of the respondents was measured by making use of adoption index developed by Karthikeyan (1994).
Depending upon the extent of adoption of improved technologies the respondents were categorized as follows:
1) Low adopters (up to 33%),
2) Partial adopters (34-66%) and
3) High adopters (67-100%).
The study was carried out with 15 independent characteristics (Socio-personal, economic and communication characteristics) and one dependent variable (Y=Adoption of improved technologies on piggery practices) of the pig farmers. The following independent variables were selected for the study:
Statistical analysis was done with the help of SPSS 10.0 package. The following statistical analyses were performed in the study:
- Pearson Product Moment Correlation Test: Correlation coefficient was computed to know the relationship between selected Independent variables of pig farmers with dependent variable i.e. adoption of improved technology on piggery practices.
- Multiple Regression Analysis: It was employed to find out the effect and extent of influence of each Independent variable contributing significantly towards the dependent variable i.e. adoption of improved technologies on piggery practices.Results and discussion
The data in the Table 1 shows majority of the farmers i.e. 81% and 63% adopted improved technology on breeding and heath care practices at higher level in their farms and the average adoption score was found to be 79.85 and 73.83, respectively. It is observed that 62% and 63% of the respondents were low adopters in respect of housing and feeding practices respectively. Half of the respondents (50%) had adopted general care and management practices partially. The mean was calculated at 64.54, which indicated that though adoption was partial, there is drift towards high adoption level.
|Table 1. Practice-wise distribution of respondents according to extent of adoption|
|Sl.No.||Level of adoption||Score index||Frequency and percentage (N=100)||Mean|
|1||Low adopter||Up to 33%||62||31.83|
|1||Low adopter||Up to 33%||4||79.85|
|1||Low adopter||Up to 33%||63||29.67|
|1||Low adopter||Up to 33%||8||73.83|
|E||General care and Management|
|1||Low adopter||Up to 33%||7||64.54|
A perusal of the data in Table 2 reveals that the overall adoption was partial (Average score was 55.87). Majority of the respondents (51%) adopted the improved technology on pig rearing partially, whereas 34% and 15% adopted improved technology on pig rearing at higher and lower level, respectively.
|Table 2. Overall adoption level of pig farmers|
|Sl.No.||Level of adoption||Score index||Frequency and percentage (N=100)||Mean|
|1||Low adopter||Up to 33%||15||55.87|
Assuming that adoption is influenced by various socio-personal and economic characteristics of the farmers, correlation coefficient was computed to know the relationship between 15 selected variables of pig farmers with adoption behaviour. The results were shown in Table 3.
|Table 3. Correlations of adoption of improved pig rearing practices with fifteen selected independent variables|
|Sl.no.||Independent variables||Coefficient of correlation (r)|
|5||Operational land holding(X5)||0.472**|
|6||Farm Size (Herd Size)(X6)||0.694**|
|7||Income from Piggery(X7)||0.783**|
|11||Farm education exposure(X11)||0.892**|
|15||Financial Help received(X15)||0.237*|
It was observed that age had a negative and significant relationship with adoption level. It might be because the aged persons were less change prone and reluctant to adopt new technologies in their farms. It was also observed by Motamed and Singh (2003) on sericulture farmers of Dehradun.
Table 3 reveals that education was positively and significantly associated with adoption level. It indicates that as the education level increases the adoption level also increases. The finding was similar with the findings of Motamed and Singh (2003) and Haque and Ray (1983).
A positive and significant correlation was found between adoption of technologies by the farmers and their land holdings. More operational land holding leads to more application of modern technologies in the farms.
It exhibited a positive and significant relationship with adoption level. It indicates that farmers having large number of pigs in their farms adopted improved technologies in their farms.
Knowledge of the farmers was positively correlated with adoption of improved pig production technologies. It shows that farmers having better knowledge on pig farming influenced to adopt improved technologies in their farms.
It is found to be significantly and positively correlated with adoption. Farmers with high scientific orientation tended to adopt improved technologies in their farms for better productivity and profitability.
It exhibited a positive and significant relationship with adoption level of farmers. Social participation helped the farmers in gaining more information and adoption on improved technologies in their farms.
It is found to be positively and significantly associated with the adoption level of farmers. Contact with extension personnel/veterinarians influenced the farmers to adopt improved pig production practices in their farms.
Farming experience showed a positive and significant relationship with the adoption of improved technologies by the farmers. Experience helps an individual to think in a better way and makes a person more mature to take right decision.
It had shown a positive and significant relationship with adoption level of the farmers. A farmer with high farm education exposure became more change prone, look into the innovative practices to be adopted at the farm level.
It was found to have a positive and significant correlation with the adoption level of the respondents. Training might have inculcated technical competency, more exposure to the subject matter and convinced to adopt the improved technologies in the farms.
Financial help received was positively and significantly associated with adoption level. It indicated that those who received financial help either from government or financial institution adopted new technologies in their farms.
The multiple regression analysis was performed to find out the effect and extent of influence of 15 independent variables to levels of adoption of improved technologies in pig farming. The results of analysis involving 15 variables are presented in Table 4.
|Table 4. Multiple regression analysis of adoption of improved technologies with fifteen selected independent variables|
|Independent Variable||Unstandardized Coefficients B||Standard Error||Standardized Coefficients Beta||T Value||Sig.|
|Operational Land holding(X5)||-.217||.687||-.012||-.316||.753|
|Farm Size (Herd Size)(X6)||-7.161E-02||.166||-.022||-.431||.668|
|Income from Piggery(X7)||1.333E-04||.000||.145||2.533||.013*|
|Farm education exposure(X11)||.815||.401||.159||2.030||.045*|
|Financial help received(X15)||-1.581||.1.668||-.033||-.948||.346|
|** Significant at the 0.01 level * Significant at the 0.05 level R2 = 0.92|
A perusal of Table 4 shows that out of 15 variables taken for analysis of regression, 2 variables i.e. Knowledge and Scientific Orientation were found to have significant contribution at one percent level, 3 variables i.e. Extension contact, Income from piggery, and Farm Education Exposure had significant contribution at five percent level of significance.
The coefficient of determination (R2 value) was 0.92, which indicates that 92.00% variation in the adoption gain in improved technologies in pig farming was explained by these 15 independent variables selected for the study.
From the above findings it can be concluded that:
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Rahman S 2007: Adoption of improved technologies by the pig farmers of Aizawl district of Mizoram, India. Livestock Research for Rural Development. Volume 19, Article #5. Retrieved printDate()January 22, 2007, from http://www.cipav.org.co/lrrd/lrrd19/1/rahm19005.htm
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