5672

Relative importance of Farmers’ Characteristics in Predicting their 
Knowledge about Indigenous Agricultural Practices

A. Sakeer Husain1, M. Sundaramari2  and J. Sreekumar3

ABSTRACT

 This study was conducted to identify the farmers’ characteristics that act as 
factors in influencing their knowledge on indigenous agricultural practices. The study was 
conducted in the state of Kerala among 40 farmers each of ten selected horticultural crops. 
Step wise regression analysis and multiple linear regression analysis were employed 
to identify the influencing factors. The study revealed that age, farm power status, 
innovativeness, rational orientation, communication status, and social participation status 
positively influence knowledge of farmers on indigenous agricultural practices whereas 
material status, educational status, and family status were the important characteristics 
of farmers negatively influencing the knowledge of indigenous practices.

Keywords : Traditional agricultural practices, Indigenous Technical Knowledge, 
Knowledge determinants, Kerala

1.Associate Professor, Kerala Agricultural University, Thrissur, Kerala, India 2. Professor, Gandhigram Rural 
Institute, Gandhigram, Tamil Nadu, India and 3. Principal Scientist, Central Tuber Crops Research Institute (ICAR), 
Thiruvananthapuram, Kerala, India

Received : 19-05-2017; Accepted : 12-06-2017

INtRODUCtION

 Indigenous knowledge (IK) is the 
knowledge that the people in a given 
community have developed over time 
and continue to develop (IIRR, 1996). 
It is based on experience, often tested 
over centuries of use, adapted to local 
culture and environment, and it is 
dynamic and changing. Any community 
possesses IK- rural and urban, settled 
and nomadic, original inhabitants and 
migrants. According to IIRR (1996), 
indigenous knowledge in agriculture may 
be classified into different types such as 
information, practices and technologies, 

beliefs, tools, materials, experimentation, 
biological resources, human resources, 
education, and communication.

 Indigenous knowledge being the 
knowledge of local people is important 
in many ways, mainly due to the unique 
nature of such technologies/practices. 
IK is the social capital of the poor, their 
main asset to invest in the struggle for 
survival, to produce food, to provide for 
shelter, or to achieve control of their 
own lives. Prasad and Ramaprasad 
(2006) reiterated that the best traditional 
practices serve as a knowledge pool for 
the small and marginal farmers without 

Journal of Extension Education
Vol. 28  No. 3,  2016
DOI:https://doi.org/10.26725/JEE.2016.3.28.5672-5679



5673

high risk.  However, the lacuna is lack of 
effective communication to disseminate 
this knowledge to the resource poor 
farmers.

 Various studies have revealed 
that the awareness level of traditional 
knowledge is declining at an alarming 
rate. But this knowledge coupled with 
biological diversity is vital for the survival 
of mankind, especially for the future 
generations. Before making efforts to 
perk up the knowledge and adoption of 
various practices, attempts should be 
made not only to analyse the validity of the 
practices, but also to ascertain the present 
status of the target group with regard to 
their knowledge. Hence, it is worthwhile 
to analyse the knowledge level of people 
on indigenous practices in all spheres 
of life, including the agricultural sector, 
and also to analyse the factors that may 
determine knowledge. In this backdrop, 
the present study was undertaken with 
the objective of identifying the factors that 
may influence the knowledge of farmers 
about Indigenous Technical Knowledge 
in agriculture.

METHODOlOGY
 The study was conducted among 
the farmers of the state of Kerala. It 
was decided to have the analysis on the 
knowledge of farmers among horticultural 
crops, since they contribute more than 80 
percent of the cultivated crops in Kerala. 
After careful analysis of the available 
literature and keeping the objectives in 
view, more of qualitative and attitudinal 

variables were selected for the study. 
Most of the selected variables were of 
expost facto in nature and the researcher 
had very little chance to control them. 
Hence an expost facto research design 
was used for the present study.

 Among the five agro climatic zones 
of Kerala viz. Southern zone, Central 
zone, Northern zone, High altitude zone, 
and Problem area zone.,  excluding the 
problem area zone, which is scattered 
in many districts of Kerala, one district 
each, from the other four agro climatic 
zones was purposively selected based on 
the larger coverage of horticultural crops. 
Thus, four districts out of the fourteen 
districts of Kerala were selected. From 
each district, two blocks each having 
predominant area under horticultural 
crops were  selected purposively,  and  
from  each  block  two village panchayats 
were selected purposively. Thus, a total 
of 16 village panchayats spread over the 
state of Kerala were selected. 

 Based on the area under cultivation 
of various horticultural crops in the 
study area, the economic importance of 
the crops and the number & importance 
of indigenous practices collected, ten 
crops were selected for the study, which 
include coconut, banana, amaranth, 
vegetable cow pea, bitter gourd, elephant 
foot yam, pepper, ginger, arecanut and 
coffee. In addition, indigenous practices 
on general agriculture were also included. 
The knowledge of concerned farmers on 
indigenous practices of various crops 
was assessed. 

Journal of Extension Education



5674

 It was intended to approach 40 
farmers for the selected ten crops, and 
thus a total of 400 farmers formed the 
sample of the study. For each of the 10 
crops, ten farmers were required to be 
contacted from each district, except in 
the case of coffee. For the high elevation 
crop viz. coffee, it was decided to contact 
40 farmers exclusively from Wayanad 
district.  Within a district, five farmers 
each for each crop from each of the 
selected block were identified. When 
respondents were selected from the 
village panchayats, proportionate random 
sampling was used i.e. proportionate to 

the area under cultivation of each crop.

 Accordingly, after collecting 
the list of farmers from the concerned 
Agricultural offices (Krishibhavan) of the 
Department of Agriculture in each of the 
earlier selected 16 village panchayats, 
farmers were contacted at random.  When 
a total of 127 farmers were contacted, 
sufficient responses (40 set of responses 
in each crop) were obtained, since many 
of the selected farmer respondents had 
been cultivating one or more of the 
selected crops. The crop-wise and village-
wise distribution of the farmers selected 
for the study is given in Table 1.

table 1.  
Crop wise and Village wise Distribution of Farmer Respondents 

Sl. 

No. D
is

tr
ic

t

 V
il

la
ge

  
 

p
an

ch
ay

at

Number of farmer respondents contacted (Crop wise)
Actual 

Number 
contacted

C
o
co

n
u
t

B
an

an
a

A
m

ar
an

th

V
eg

. 
co

w
p
ea

B
it

te
r 

go
u
rd

E
le

p
h
an

t 
fo

o
t 

y
am

P
ep

p
er

G
in

ge
r

A
re

ca
 n

u
t

C
o
ff

ee
 

T
o
ta

l

1.

2.

3.

4.

I

II

III

IV

1
2
3
4

1
2
3
4

1
2
3
4

1
2
3
4

3
2
2
3

2
3
2
3

3
2
2
3

2
3
3
2

2
3
3
2

3
2
2
3

2
3
2
3

2
3
2
3

2
3
4
1

3
2
2
3

3
2
2
3

2
3
3
2

2
3
4
1

3
2
2
3

2
3
2
3

2
3
3
2

2
3
4
1

3
2
2
3

2
3
2
3

2
3
3
2

3
2
2
3

2
3
3
2

2
3
3
2

3
2
2
3

3
2
2
3

2
3
3
2

2
3
3
2

2
3
3
2

3
2
3
2

3
2
2
3

3
2
2
3

3
2
2
3

2
3
2
3

2
3
2
3

2
3
3
2

3
2
3
2

---
---
---
---

---
---
---
---

---
---
---
---

10
10
10
10

22
23
26
19

23
22
20
25

21
24
21
24

31
34
34
31

6
7
9
8

6
7
8
7

7
6
7
6

10
11
12
10

40 40 40 40 40 40 40 40 40 40 40 127

Relative importance of Farmers’ Characteristics in Predicting their Knowledge about Indigenous Agricultural Practices



5675

The objective of the study necessitated 
knowledge of farmers about indigenous 
horticultural practices as the dependent 
variable of the study. Based on extensive 
review of literature on the subject, 
and consultation with the agricultural 
extension scientists, followed by 
screening out variables by judges rating, 
13 variables with a relevancy score above 
the mean relevancy score (4.2) were 
identified, as followed by Nataraju (1991) 
and Sundaramari (2001). The identified 
variables were: age, farming experience, 
livestock possession, socio-economic 
status, extension agency contact, mass 
media exposure, fatalism, decision 
making ability, innovativeness, rational 
orientation, environmental orientation, 
belief in traditional agriculture, and 
attitude towards indigenous knowledge. 
To study the influence in detail, the 
subcomponents of socio economic status 
such as educational status, family status, 
occupational status, farm status, social 
participation status, communication 
status, farm power status, material status 
were also used in the analysis along with 
the independent variables, replacing the 
socio economic status 

 Step wise regression analysis was 
done to know the relative effect of the 
independent variables in the study in 
predicting the dependent variable and 
for elimination of unimportant ones. 
Thus it gave information regarding the 
best subset of components and the 
relative contribution of each of these 
components in the variation in dependent 

variables after eliminating unimportant 
components. Here, the step wise 
(forward) regression analysis was done 
using the criterion, Adjusted R-squared 
for selecting the best model among all 
possible models. This analysis was done 
at two stages. Accordingly models were 
suggested in each case.

 Multiple linear regression analysis 
was carried out to determine the combined 
contributions of the independent 
variables considered (contribution of 
each model) for the variations in the 
dependent variable. It was also meant 
to find out the variables which have 
contributed significantly for the changes 
in the dependent variable.

 To find out the extent of influence of 
independent variables on the dependent 
variable, knowledge of Indigenous 
Agricultural Practices (IAPs) step wise 
regression analysis and multiple linear 
regression analysis were performed. The 
step wise (forward) regression analysis 
was done here so as to find out the 
best model among different models 
predicting the dependent variable. It is 
an accumulated analysis of deviance 
resulting from stepwise regression 
starting with no candidate terms in the 
model. The criterion used in this analysis 
was adjusted R-squared. After identifying 
the best model, multiple linear regression 
analysis was subsequently done in the 
particular model to know the extent 
of influence of different independent 
variables. 

Journal of Extension Education



5676

FINDINGS AND DISCUSSION
 As mentioned, the relative 
importance of independent variables in 
predicting the knowledge of indigenous 
agricultural practices (IAPs) was analysed 
using regression analysis. The step wise 
(forward) regression analysis to identify 
the best knowledge model had suggested 
the final model as follows:

 Knowledge of IAPs = Constant 
+ age + livestock possession + belief in 

traditional agriculture + innovativeness 
+ socio-economic status + extension 
agency contact + decision making ability 
(Knowledge Model- I)

 To know the relative importance 
of these variables in predicting the 
knowledge on IAPs, multiple linear 
regression analysis was done on 
this model, and the results are given  
in Table 2.

table 2. 
Multiple Linear Regression Analysis of Knowledge Model – I          

(n = 127)
Sl. 
No.

Particulars 
Regression 
coefficients

Standard 
Error

t 
value*

t 
probability

1.

2.

3.

4.

5.

6.

7.

8.

Constant

Age

Livestock possession

Belief in traditional agriculture

Innovativeness

Socio-economic status

Extension agency contact

Decision making ability

18.59

 0.3360

 1.544

 3.98

 4.16

 0.0792

 0.233

-0.306

6.47

0.0709

0.422

1.05

1.26

0.0413

0.113

0.263

2.87

4.74

3.66

3.78

3.29

1.92

2.05

1.16

0.005

<.001

<.001

<.001

0.001

0.058

0.042

0.247

         F = 14.79     F pr. <.001        R2 = 0.434 SE = 7.90               * df =119

 Table 2 reveals that the variables 
such as age, livestock possession, 
belief in traditional agriculture, and 
innovativeness had the major role in 
developing the knowledge of IAPs at 1% 
level of significance, whereas extension 
agency contact had influence on 
knowledge level, which is significant at 
5% level. But this model explained only 

43.40% of the total variation. Hence, 
instead of socio-economic status, all the 
constituent variables of socio-economic 
status were included along with other 
independent variables, and a step wise 
regression analysis was done again, 
which has given the following final model.

 Knowledge of IAPs = Constant + 
age + farm power status+ material status+ 

Relative importance of Farmers’ Characteristics in Predicting their Knowledge about Indigenous Agricultural Practices



5677

innovativeness + belief in traditional 
agriculture + occupational status + 
rational orientation + educational status 
+ communication status + livestock 
possession + social participation status 

+ family status + mass media exposure + 
farm status (Knowledge Model- II)

 The result of multiple regression 
analysis done on this model is given in 
Table 3. 

table 3. 
Multiple Linear Regression Analysis of Knowledge Model – II 

(n = 127)

Sl. 
No.

Particulars
Regression 
coefficients

Standard 
Error

t 
value*

t 
probability

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

Constant

Age

Farm power status

Material status

Innovativeness

Belief in traditional agriculture

Occupational status

Rational orientation

Educational status

Communication status

Livestock possession

Social participation status

Family status

Mass media exposure

Farm status

  35.19

    0.3144

    0.380

    0.2721

    3.24

    1.64

   -1.112

    3.51

   -3.10

   1.610

   0.887

   1.443

   -1.339

   0.594

   1.000

9.29

0.0640

0.115

0.0663

1.07

1.03

0.623

1.26

1.06

0.773

0.458

0.695

0.550

0.363

0.693

 3.79

 4.91

 3.31

 4.11

 3.02

 1.59

 1.78

 2.78

 2.92

 2.08

 1.94

 2.08

 2.44

 1.64

 1.44

<.001

<.001

0.001

<.001

0.003

0.114

0.077

0.006

0.004

0.040

0.055

0.040

0.016

0.104

0.152

    F = 14.63   F pr. <.001      R2 = 0.602 SE = 6.80   * df =112
The results given in Table 3 reveal that 
the model explained 60.20 percent of 
the total variation. Among the variables, 
age, farm power status, innovativeness, 

and rational orientation had positive 
and significant influence while material 
status and educational status had 
negative and significant influence on 

Journal of Extension Education



5678

knowledge at 1 per cent level. At the same 
time, communication status, and social 
participation status had shown significant 
positive influence at 5 per cent level, 
and family status had shown significant 
negative influence at 5 percent level.  It 
is quite natural that the age of  farmers 
may  be expected  to have significant 
positive influence on the knowledge about 
indigenous practices, as the old farmers 
are the treasure house of information 
especially the indigenous knowledge. 
Hence the saying, ‘when an old man dies 
a library is lost’. Similarly farmers with 
high farm power status, innovativeness 
and rational orientation would also try 
to gain more knowledge whether it is 
about indigenous knowledge or not.  The 
increased communication status and 
social participation status would also 
definitely enable the farmers to gain 
more knowledge on indigenous practices 
by way of more contact, interaction and 
communication. On the other hand, 
when material status, educational status, 
and family status increase, people will 
go behind modern, sophisticated, so 
called advanced technologies, and try to 
get more information on it, ignoring the 
old techniques and practices with an 
intention to get quick results, more profit 
and to have comfort without considering 
the advantages of Indigenous Knowledge. 
Thus the influence of all the independent 
variables mentioned above has been 
justifiable and logical.The findings 
are partly in conformity with those of 
Jayawardana (2007)

CONCLUSION

 Knowledge is the precursor 
of adoption; without knowledge and 
adoption, a practice cannot be propagated. 
To propagate and promote a practice, 
careful understanding of the factors 
that influence the knowledge of farmers 
and adoption of indigenous technical 
practices in agriculture is vital. The 
present study concludes that age, farm 
power status, innovativeness, rational 
orientation, communication status, 
social participation status material 
status, educational status, and family 
status were the important characteristics 
of farmers in influencing the knowledge 
of indigenous agricultural practices, of 
which the latter three variables were 
negatively influencing knowledge. Thus, 
by improving the social participation 
status, communication status, 
innovativeness, rational orientation of 
farmers as well as operating through 
aged farmers, knowledge of farmers 
on indigenous technical knowledge in 
agriculture can be nurtured.

REFERENCES

IIRR. (1996). Recording and Using 
Indigenous Knowledge: A Manual. 
International Institute of Rural 
Reconstruction, Silang, Cavite, 
Philippines. 211p.

Jayawardana, J. K. J. P. (2007). Organic 
agricultural practices in coconut based 
homesteads in Thiruvananthapuram 
district. Unpublished M. Sc. (Ag.) 

Relative importance of Farmers’ Characteristics in Predicting their Knowledge about Indigenous Agricultural Practices



5679

thesis, Kerala Agricultural University, 
Thrissur, India, 124p.

Nataraju, M.S. (1991). Effectiveness 
of farm magazines- a component 
analysis. Unpublished  Ph.D. thesis, 
Tamil Nadu Agricultural University, 
Coimbatore, India.

Prasad, G. K. & Ramaprasad, V. (2006). 
Disseminating traditional seed 

storage practices through people’s 
participation.  LEISA INDIA, 8(3): 34-
35.

Sundaramari, M. (2001). Adoption and 
perceived effectiveness of indigenous 
agricultural practices in different 
farming systems. Unpublished Ph. D. 
thesis, Gandhigram Rural Institute, 
Gandhigram, India. 

Journal of Extension Education