Dr Arvind Kumar

1. Technology Assessment and
Refinement for Its Adoption
Dr Arvind Kumar
Principal Scientist (Agril Ext)
ICAR-Agricultural Technology Application Research Institute, Ludhiana

2. Mandate of KVK
• Technology Assessment and Demonstration for its
Application and Capacity Development
• On-farm testing to assess the location specificity of agricultural technologies
under various farming systems;
• Organize Frontline Demonstrations to establish production potential of
Activities
• Organize Frontline Demonstrations to establish production potential of
technologies on the farmers’ fields;
• Capacity development of farmers and extension personnel to update their
knowledge and skills on modern agricultural technologies;
• To work as knowledge and resource centre of agricultural technologies for
supporting initiatives of public, private and voluntary sector in improving the
agricultural economy of the district; and
• Provide farm advisories using ICT and other media means on varied subjects of
interest of farmers

4. Why TAR?
• Crops, animals and their environments are highly complex systems with
a multitude of variables that change from location to location in any
district of India.
• Due to this complexity, practices optimised for a research station might
not be so successful when transferred to farmer field.
• Though the new location anywhere in KVK district may appear similar to
that of research station, there may be an undefined key limitation or
that of research station, there may be an undefined key limitation or
combination of minor but different limitations that constrain potential
production.
• When practices recommended by the research system and extension
system are not being followed in the district;
• When practices recommended by the research system and extension
system are being followed, but yields/results remain low in the district;
• This necessitates for assessment and refinement of technology in
microclimatic conditions of the KVK district.

5. What is it?
• TAR refers to a set of procedures whose purpose
is to develop recommendations for a particular
agro-climatic situation/ location through
assessment and refinement of recently released
assessment and refinement of recently released
technology through participatory approach.
• It is the process or a set of activities before
taking up new scientific information for its
dissemination in a new production system.

6. Technology assessment
• Identified problems and related available
technological options may be discussed at different
platforms; i.e., District, SAU and Zonal level before its
testing.
• Technology assessment is conceptualized as finding
• Technology assessment is conceptualized as finding
out a more profitable and sustainable option than the
existing one in a given environment.
• To find out such an option, one or two new
technological options or practices are tested against
the farmers practice and the recommended practice.

7. Technology refinement
• If assessed technologies are not performing
satisfactorily in solving the problem, then the
technology refinement can be taken up with
necessary modification to suit the local
necessary modification to suit the local
conditions of the farmers taking into
consideration of socio-economic and bio-
physical conditions.

8. OFT &FLD: Points to ponder
• OFT is not identical to FLD, which aims at showing
farmers a technology of which researchers and
extension agents are sure that it works in the area.
• Both OFTs & FLDs are strictly to be conducted in
collaborating farmer fields and not in KVK land.

9. • In many cases, the technology after assessment may
be found totally unsuitable for the district.
• Or the KVK will find that by little refinement the
technology can be made suitable for the micro-
location.
• In such cases, the technology after assessment will go
again for refinement in farmer field in the next
season.
season.
• After successful refinement the technology can be
taken up for frontline demonstrations.
• If a technology fails in refinement stage, then it is not
to be recommended for the extension system or for
FLDs by KVK itself. But the results have to be
communicated to research system without fail.

10. • When convinced and satisfied with the
results/outcome of OFTs, formulate recommendations
for demonstrations (FLDs) on a larger area in the
farmers’ fields so as to popularize the technology
amongst farming communities and to provide feed-
forward to extension system.
The KVKs ensure that :
• Extension agents participate in the OFT and
demonstration process (to transfer recommendations
to farmers with skills and confidence); and
• Farmers involvement in the demonstration process (to
participate effectively in the diffusion of new
technologies).

11. The following technological attributes are
considered while assessing the results in OFTs
compared to the existing local ones.
1. Profitability;
2. Risks;
3. Relative costs;
3. Relative costs;
4. Simplicity;
5. Sustainability;
6. Farmers safety; and
7. Farming system compatibility.

12. When & Why OFT/FLD
Problem
Solution available Solution NOT available
Does not
work
Technological
problem
Management
problem
Work
satisfactorily
FLD if farmers
agree
FLD to
convince
Integrate ITK
Look for farmers
innovations

13. What to do with FLD data?
Situation 1
The average state yield of Mustard is 14.7 q/ha. The average yield
of 15 FLDs on Mustard conducted by KVK is 16.3 q/ha with a
standard deviation of 1.86. If the KVK scientist is interested in
standard deviation of 1.86. If the KVK scientist is interested in
comparing the yields of FLDs with state average yields, then which
statistical method he should use?
a) Independent t-test
b) Paired t-test
c) One-sample t-test

14. Answer
One-sample t-test
The one-sample t-test compares the mean score of a
sample to a known value, usually the population mean.
Null hypothesis
The difference between the state average yield and the yields of
FLDs is zero.
Alternative hypothesis
The difference between the state average yield and the yields of
FLDs is NOT zero.

16. 1. Population mean (μ) = 14.75
2. Sample mean (x
̄ ) = 16.30
3. Sample size (n) = 15
S.
No.
Yield of
Mustard
FLDs (q/ha)
1 17.5
2 13.9
3 20.2
4 16.4
5 17.8
6 13.9
7 17.6
4. Standard deviation (s) = 1.86
5. Standard error (SE) = 0.48001
6. Degree of freedom (df) = 15-1=14
7. P-value = 0.00538
7 17.6
8 16.6
9 13.8
10 15.9
11 17.3
12 17.5
13 13.8
14 15.8
15 17.2
7. P-value = 0.00538
t= 3.29
Decision
The p-value is less than 0.05 so this is the
strong evidence to reject null hypothesis.

17. Situation 2
KVK scientist conducted FLDs on feed supplement to cow. He has
divides 20 cows randomly into two groups. One group receives a
feed supplement and the other does not. Body weight is measured
for both groups after 6 months. Since KVK scientist is comparing
the means of these two sample groups, then which statistical
method he should use?
method he should use?
a) Independent t-test
b) Paired t-test
c) One-sample t-test

18. Independent (two sample) t-test
Use an independent t-test when you want to compare the mean of
one sample with the mean of another sample to see if there is a
statistically significant difference between the two. As the name
suggests, you use an independent t-test when your samples are
independent
Paired t-test
A paired sample t-test is used to determine whether there is a
significant difference between the average values of the same
measurement made under two different conditions. Both
measurements are made on each unit in a sample, and the test is
based on the paired differences between these two values.

19. Summary
• Conduct KVK activities systematically;
• Use combination of suitable extension
methods & tools, test, etc for execution
• Collect data systematically
• Collect data systematically
• Analyse data with suitable statistical
methods
• Publish the results

21. Thanks
Thanks