The Journal of Research ANGRAU
Contents of 41(1) 2013 - acharya ng ranga agricultural university
Contents of 41(1) 2013 - acharya ng ranga agricultural university
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ABIRAMI et al<br />
Socio-economic Impact: A cursory look at<br />
the Table 1 indicates that 46.67 per cent <strong>of</strong> beneficiary<br />
farmers had medium level <strong>of</strong> socio-economic impact,<br />
followed by high (28.33%) and low level <strong>of</strong> socioeconomic<br />
impact (25.00%). <strong>The</strong> result was the<br />
cumulative effect <strong>of</strong> all the factors contributed to the<br />
socio-economic impact. <strong>The</strong> reason for high level <strong>of</strong><br />
socio-economic impact might be particularly due to<br />
majority <strong>of</strong> the farmers obtained fine knowledge about<br />
SRI and adopted SRI technique fairly in their field.<br />
As a result they received more income and asset<br />
acquisition. Medium level <strong>of</strong> socio-economic impact<br />
might be due to partial adoption <strong>of</strong> technology and<br />
inefficient management <strong>of</strong> labour. That results in more<br />
cost <strong>of</strong> cultivation. Low level <strong>of</strong> socio-economic<br />
impact might be due to poor adoption & SRI<br />
technology.<br />
b) Relationship between pr<strong>of</strong>ile <strong>of</strong> beneficiary<br />
farmers and the socio-economic impact<br />
An attempt has been made to find out the<br />
association between independent variables and<br />
dependent variables through correlation coefficient<br />
(r) values. <strong>The</strong> results are presented in Table 2.<br />
Table 2. Correlation coefficient between pr<strong>of</strong>ile <strong>of</strong> beneficiary farmers and the socio-economic impact<br />
N= 120<br />
S. No Independent Variables ‘r’ values<br />
1. Age<br />
2. Education<br />
3. Land Holding<br />
4. Farming Experience<br />
5. Information sources utilization<br />
6. Training Received<br />
7. Economic Motivation<br />
8. Scientific Orientation<br />
9. Innovativeness<br />
10. Risk Orientation<br />
-0.2119 NS<br />
0.4014**<br />
0.3870**<br />
0.3537**<br />
0.3793**<br />
0.4815**<br />
0.5241**<br />
0.6113**<br />
0.5927**<br />
0.6084**<br />
** Significant at 0.01 level <strong>of</strong> probability NS = Non Significant<br />
<strong>The</strong> results presented in the Table 2 clearly<br />
indicate that almost all computed ‘r’ values <strong>of</strong><br />
education, land holding, farming experience,<br />
information sources utilization, training received,<br />
economic motivation, scientific orientation,<br />
innovativeness and risk orientation with socioeconomic<br />
impact were found positively significant<br />
relationship at 0.01 level <strong>of</strong> probability. Whereas, age<br />
with socio-economic impact had non-significant and<br />
negative relationship.<br />
From this study it could be concluded that<br />
higher the education, higher the land holding, higher<br />
the experience in farming, higher the information<br />
sources utilization, higher the training received,<br />
higher the economic motivation, higher the scientific<br />
orientation, higher the innovativeness and higher the<br />
risk orientation, the higher would be the socioeconomic<br />
impact.<br />
<strong>The</strong> probable reason for age, not influencing<br />
the socio-economic impact can be explained that<br />
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