a study on production, consumption and...
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A STUDY ON PRODUCTION, CONSUMPTION AND
MARKETING PATTERN OF MAIZE AMONG THE
TRIBAL FARMERS OF SURGUJA DISTRICT OF
CHHATTISGARH
M.Sc. (Ag.) Thesis
by
Ganesh Kumar
DEPARTMENT OF AGRICULTURAL EXTENSION
COLLEGE OF AGRICULTURE
FACULTY OF AGRICULTURE
INDIRA GANDHI KRISHI VISHWAVIDYALAYA
RAIPUR (Chhattisgarh)
2017
A STUDY ON PRODUCTION, CONSUMPTION AND
MARKETING PATTERN OF MAIZE AMONG THE
TRIBAL FARMERS OF SURGUJA DISTRICT OF
CHHATTISGARH
Thesis
Submitted to the
Indira Gandhi Krishi Vishwavidyalaya, Raipur
by
Ganesh Kumar
IN PARTIAL FULFILMENT OF THE REQUIREMENT
FOR THE DEGREE OF
Master of Science
in
Agriculture
(Agricultural Extension)
VVID No. 20151622437 ID No. 120115023
SEPTEMBER, 2017
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i
ACKNOWLEDGEMENT
First of all, my humble and devoted prostration to almighty God with
soulful respect, I bow down my head to him, who enlightens and leads me in right
way, with his blessings I reached at this stage.
I feel it to be a privilege to express my deepest sense of gratitude to the
Chairman of my Advisor, Shri P.K. Sangode (Assistant Professor), Department of
Agricultural Extension, who is a blend of austerity and fortitude reflecting in his
integrity and simplicity. I feel proud to have a guide of such a stature and I shall
ever remain grateful to him for his competent and affectionate guidance, continued
inspiration, research insights, unique supervision, knowledge and enthusiastic
interest, which he provided me throughout my post graduation and research
investigation despite his heavy schedule of work.
I am extremely grateful to my Advisory Committee members Dr. M.A. Khan
(Associate Professor), Deptt. Of Agricultural Extension, Dr.(Major) G.K.
Shrivastava (Professor), Deptt. of Agronomy and Dr. (Smt.) S. Shukla (Scientist),
Department of Agril. Statistics and Social Science (Language) for their timely
advice and critical suggestions as and when needed. Without their kind co-
operation it would not have been easy to complete this Thesis.
I express my sincere thanks to my faculty members Dr. M.L. Sharma
(Professor and Head), Dr. R.S. Senger (Professor), Dr. H.K. Awasthi (Professor),
Dr. D.K. Suryawanshi (Senior Scientist), Dr. M.A. Khan (Associate Professor),
Shri M.K. Chaturvedi (Assistant Professor), Shri P.K. Pandey (Assistant
Professor) Deptt. of Agricultural Extension, for their valuable suggestions and co-
operation during this investigation.
I am highly obliged to Hon’ble Vice Chancellor Dr. S.K. Patil, Dr. S.S. Rao
Director Research Services, Dr M.P. Thakur Director Extension Services, Dr.
(Major) G.K. Shrivastava, Dean Student Welfare, Dr. O.P. Kasyap, Dean College
of Agriculture, Raipur and Dr. S.S. Shaw Director of Instructions, IGKV, Raipur
for providing necessary facilities to conduct the present investigation.
I have immense pleasure in expressing my whole hearted sense of
appreciation to Dr. Sunil Narbaria (SRF), Dr. Subodh Pradhan for his timely help
and advice during the of my research work.
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TABLE OF CONTENTS
Chapter Title Page
ACKNOWLEDGEMENT i
TABLE OF CONTENTS iii
LIST OF TABLES vii
LIST OF FIGURES ix
LIST OF NOTATIONS / SYMBOLS x
LIST OF ABBREVIATION xi
ABSTRACT xii
I INTRODUCTION 1
II REVIEW OF LITERATURE 5
2.1 Socio personal characteristics 6
2.1.1 Age 6
2.1.2 Education 6
2.1.3 Family size 7
2.1.4 Social participation 7
2.1.5 Farming experience 8
2.2 Socio economic characteristics 9
2.2.1 Land holding 9
2.2.2 Irrigation facility 10
2.2.3 Occupation 11
2.2.4 Annual family income 13
2.2.5 Credit acquisition 13
2.2.6 Benefit-cost ratio 14
2.2.7 Domestic consumption 15
2.3 Socio psychological characteristics 15
2.3.1 Scientific orientation 15
2.3.2 Level of knowledge 16
2.4 Communicational characteristics 17
2.4.1 Sources of information 17
2.5 Marketing practices 18
2.5.1 Marketing channel 18
2.5.2 Mode of marketing 19
2.6 Extent of adoption of maize production technology
and productivity of maize crop
19
2.6.1 Adoption 19
2.6.2 Productivity 21
iv
2.7 Constraints faced by the tribal farmers and obtain their
suggestions to overcome the constraint in cultivation of
maize crop
22
2.7.1 Constraints 22
2.7.2 Suggestions 23
III MATERIALS AND METHODS 25
3.1 Location of study area 26
3.2 Sample and sampling procedure 26
3.2.1 Selection of district 26
3.2.2 Selection of blocks 26
3.2.3 Selection of villages 26
3.2.4 Selection of respondents 26
3.2.5 Collection of data 26
3.2.6 Statistical methods 26
3.3 Variables of the study 28
3.3.1 Independent variables 28
3.3.2 Dependent variables 29
3.4 Operationalization of independent variables and their
measurement
29
3.4.1 Socio personal Characteristics of the respondents 29
3.4.1.1 Age 29
3.4.1.2 Education 29
3.4.1.3 Family size 29
3.4.1.4 Social participation 30
3.4.1.5 Farming experience 30
3.4.2 Socio economic characteristics of the respondents 30
3.4.2.1 Land holding 30
3.4.2.2 Irrigation facility 31
3.4.2.3 Occupation 31
3.4.2.4 Annual family income 31
3.4.2.5 Credit acquisition 32
3.4.2.6 Variety 32
3.4.2.7 Benefit-cost ratio 32
3.4.2.8 Domestic consumption 33
3.4.3 Socio psychological characteristics of the
respondents
33
3.4.3.1 Scientific orientation 33
3.4.3.2 Level of knowledge 34
3.4.4 Communicational characteristics of the
respondents
35
3.4.4.1 Sources of information 35
3.4.5 Marketing practices of the respondents 35
v
3.4.5.1 Marketing channel 35
3.4.5.2 Mode of marketing 36
3.5 Operationalization of dependent variables and their
measurement
36
3.5.1 Extent of adoption of recommended maize
production technology
36
3.5.2 Productivity 37
3.6 Constraints faced by the maize growers in adoption of
recommended maize production and marketing
37
3.7 Suggestions suggested by the maize growers to
overcome these constraints
37
3.8 Type of data 38
3.9 Developing the interview schedule 38
3.9.1 Validity 38
3.9.2 Reliability 39
3.10 Method of data collection 39
3.11 Statistical analysis 39
3.11.1 Frequency and percentage 39
3.11.2 Mean and standard deviation 39
3.11.3 Pearson’s Coefficient of correlation 40
3.11.4 Multiple regressions 40
IV RESULTS AND DISCUSSION 41
4.1 Independent variables 41
4.1.1 Socio personal characteristics 41
4.1.1.1 Age 42
4.1.1.2 Education 42
4.1.1.3 Family size 42
4.1.1.4 Social participation 42
4.1.1.5 Farming experience 43
4.1.2 Socio economic characteristics 44
4.1.2.1 Land holding 44
4.1.2.2 Irrigation facility 44
4.1.2.3 Occupation 46
4.1.2.4 Annual family income 48
4.1.2.5 Credit acquisition 48
4.1.2.6 Variety 50
4.1.2.7 Benefit-cost ratio 51
4.1.2.8 Domestic consumption 51
4.1.3 Socio psychological characteristics 53
4.1.3.1 Scientific orientation 53
4.1.3.2 Level of knowledge 53
vi
4.1.4 Communicational characteristics 57
4.1.4.1 Sources of information 57
4.1.5 Marketing practices 59
4.1.5.1 Marketing channel 59
4.1.5.2 Mode of marketing 61
4.2 Dependent variables 61
4.2.1 Extent of adoption of recommended maize
production technology by the maize growers 61
4.2.2 Productivity 65
4.3 Correlation analysis of independent variables with
adoption of recommended maize production
technology by the maize growers
66
4.4 Multiple regression analysis of independent variables
with adoption of recommended maize production
technology by the maize growers
67
4.5 Constraints faced by the maize growers in adoption of
recommended maize production technology
69
4.6 Suggestions from the maize growers for increasing the
adoption of recommended maize production
technology
70
V SUMMARY AND CONCLUSIONS 72
REFERENCES 78
APPENDICES Appendix A- Interview schedule 89 Appendix B- Photographs 100 RESUME 104
vii
LIST OF TABLES
Table Title Page
3.1 Selected area and number of respondents for the study 28
4.1 Distribution of the respondents according to the their socio
personal characteristics
43
4.2 Distribution of the respondents according to their size of land
holding
44
4.3 Distribution of the respondents according to availability of
irrigation and its sources
46
4.4 Distribution of respondents according to their involvement in
various occupations
46
4.5 Distribution of respondents according to their annual income of
family
48
4.6 Distribution of the respondents according to their credit
acquisition
50
4.7 Distribution of respondents according to their variety wise
cultivation of maize crop
51
4.8 Benefit-cost analysis of maize crop 51
4.9 Distribution of respondents according to their domestic
consumption of maize
53
4.10 Distribution of respondents according to their scientific
orientation
53
4.11 Distribution of respondents according to their practices wise
level of knowledge regarding maize production technology
54
4.12 Distribution of respondents according to overall level of
knowledge regarding maize production technology
55
4.13 Distribution of respondents according to their sources of
information
57
4.14 Distribution of respondents according to utilization of number of
information sources
59
4.15 Distribution of respondents according to their marketing channel
of maize
59
4.16 Distribution of respondents according to their mode of
marketing of maize
61
4.17 Distribution of respondents according to their practices wise
extent of adoption regarding maize production technology
63
4.18 Distribution of respondents according to their overall extent of
adoption regarding maize production technology
64
4.19 Distribution of respondents according to their production and
productivity of maize crop in study area
64
4.20 Correlation analysis of independent variables with extent of
adoption regarding maize production technology
66
4.21 Multiple regression of independent variables with extent of
adoption of maize production technology
68
viii
4.22 Constraints faced by the maize growers in adoption of
recommended maize production and marketing
69
4.23 Suggestions given by maize growers for solving the constraints
faced by them during the adoption of recommended maize
production and marketing
70
ix
LIST OF FIGURES
Figure Title Page
3.1 Location map of the study area 27
4.1 Distribution of the respondents according to their size of land
holding
45
4.2 Distribution of the respondents according to their availability of
irrigation sources
47
4.3 Distribution of respondents according to their involvement in
various occupations
47
4.4 Distribution of respondents according to their annual family
income
49
4.5 Distribution of respondents according to their domestic
consumption of maize
52
4.6 Distribution of respondents according to their practices wise
level of knowledge regarding maize production technology
56
4.7 Distribution of respondents according to their sources of
information
58
4.8 Distribution of respondents according to their marketing
channel of maize
60
4.9 Distribution of respondents according to their mode of
marketing of maize
62
4.10 Distribution of respondents according to their practices wise
extent of adoption regarding maize production technology
64
x
LIST OF NOTATIONS/SYMBOLS
% Percentage
F Frequency
@ At the rate
et al. and others/ and co-workers
ha Hectare
q Quintal
i.e. That is
Fig. Figure
Govt. Government
Deptt. Department
mm Mile meter
Rs. Rupees
viz. Namely
Sl. Serial
No. Number
* Significant of 0.05 level of probability
** Significant of 0.01 level of probability
X Mean
mha Million hectare
mt Million tones
Kg/ha Kilogram per hectare
q/ha Quintal per hectare
xi
LIST OF ABBREVIATION
ATIC Agricultural Technology Information Centre
ATMA Agricultural Technology Management Agency
BCR Benefit- Cost Ratio
C.G. Chhattisgarh
GDP Gross Domestic Product
KCC Kishan Call Centers
KVK Krishi Vigyan Kendra
NS Non – Significant
RAEO Rural Agricultural Extension Officer
RAWEP Rural Agricultural Work Experience Programme
SADO Senior Agricultural Development Officer
S.D. Standard Deviation
SMS Subject Matter Specialist
T.V. Television
IFPRI International Food Policy Research of institute
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The study reveals that the majority of respondents (52.50%) belongs to
middle age group (36 –55 years), educated up to middle school level (27.50%) and
62.50 per cent had medium size of family (6 to 10 members). The majority of
respondents (63.12%) had participated in one social organization. About 54 per
cent respondents had 11-20 years of experience in maize cultivation.
Maximum respondents (35.62%) were marginal farmers having land
holding up to 1 ha, while 25.63 per cent were small farmers having land holding
1.1 to 2 ha. Maximum respondents (60.44%) were having tube-wells for irrigation.
Agriculture was found to be their main occupation. Majority of respondents
(69.38%) belongs to the income category of Rs. 50,001 to Rs. 2,00,000. In case of
source of credit, majority of respondents (68.03%) acquired credit from
cooperative societies. Most of the respondents (70.75%) acquired credit for 6 – 12
months and 56.46 per cent respondents acquired Rs. 10,001 to Rs. 20,000 amount
of credit. In case of maize cultivation, improved variety (kanchan) was grown by
maximum respondents (34.37%) and hybrid variety (DMH-8255) were grown by
46.87 per cent respondents. Cent per cent respondents used green cob for domestic
consumption. The average benefit- cost ratio for maze cultivation was found 1.70.
Majority of the respondents (79.38%) were having medium level of
scientific orientation. In case of practice wise level of knowledge, majority of the
respondents (60.62%) had low level of knowledge about disease management.
Maximum respondents (51.88%) were having medium knowledge about selection
of improved varieties. Similarly, 48.75 and 45.63 per cent of the respondents were
having high knowledge about land preparation and irrigation & drainage practices,
respectively. In case of overall level of knowledge about maize production
technology, 38.12, 32.50 and 29.38 per cent respondents were found under
medium, low and high category, respectively.
Majority of the respondents (71.87%) obtained the information about
maize production technology from RAEOs/SADOs and also most of them were
using 4-6 information sources. Most of the respondents (71.87%) were sold their
maize product (grain) through shopkeeper.
In case of practice wise adoption of maize production technology,
maximum respondents (68.12%) had low level of adoption of storage. Maximum
xiv
respondents (51.88%) were found in medium level of adoption toward selection of
improved varieties. Similarly, high level of adoption were found about land
preparation (41.25%). About 51 per cent respondents were having medium level of
overall adoption of maize production technology. The average productivity of
maize was found 22.53 q/ha.
In correlation analysis, the finding reveals that out of 17 independent
variables, 13 variables i.e. education, family size, social participation, farming
experience, land holding, occupation, annual income, credit acquisition, mode of
marketing, domestic consumption, benefit- cost ratio, scientific orientation, level of
knowledge were found to be positive and significantly correlated with extent of
adoption of recommended maize production technology, at 0.01 and 0.05 level of
probability. Other variables viz. age, source of information, irrigation facility and
marketing channel were having non-significant correlation with the extent of
adoption of recommended maize production technology. In multiple regression
analysis, out of 17 independent variables, 8 variables viz. education, social
participation, farming experience, land holding, mode of marketing, domestic
consumption, benefit-cost ratio, knowledge level had positive and significant
contribution to the adoption of recommended maize production technology and
remaining 9 variables viz. age, family size, sources of information, irrigation
facility, occupation, annual income, credit acquisition, marketing channel,
scientific orientation did not indicate any significant contribution to the adoption of
recommended maize production technology.
Lack of knowledge about insecticide and herbicides and its accurate
quantity for application, followed by lack of irrigation facility and non- availability
of hybrid variety at appropriate time were found to be important constraints as
reported by most of the respondents of maize production technology.
Majority of the respondents (56.25%) suggested that the protection method
and materials during cob formation against birds and animals should be available,
followed by 51.25 per cent respondents suggested that the irrigation facility should
be available, while 50.62 per cent respondents suggested knowledge about accurate
quantity & time of fertilizer application.
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75½ }kjk _.k 6&12 ekg fy;s fy;k tkrk gS ,oa 56-46 izfr“kr d`’kdksa }kjk 10]001 :i;s ls 20]000
:i;s rd _.k fy;k tkrk gSA vf/kdka”k 34-37 izfr“kr d`’kdksa }kjk eDdk dh [ksrh es mUurf”ky
iztkfr ¼dapu½ dh [ksrh djrs Fks ,oa ladj iztkfr es DMH-8255 dks 46-87 izfr“kr d`’kd [ksrh
djrs djrs ik;s x;sA ’kr~ izfr’kr d`’kdksa }kjk eDdk dks HkwVVk ds :i esa ?kjsyw miHkksx djrs gSA eDdk
[ksrh dh vkSlr Ykkxr ykHk vuqikr 1-70 gSA
oSKkfud mUeq[khdj.k es vf/kdka”k d`’kd ¼79-38 izfr’kr½ e/;e Lrj ds ik;s x;sA eDdk
mRiknu ds ekeys es 60-62 izfr“kr d`’kdksa }kjk jksx izcU/ku ds ckjs es Kku dk fuEu LRkj FkkA mUUkr
fdLeks dh p;u ds ckjs es 51-88 izfr“kr d’kdksa dk Kku e/;e Lrj Fkk rFkk 48-75 o 45-63 izfr“kr
d`’kdksa es Hkwfe dh rS;kjh djus o flapkbZ RkFkk fudklh djus es Kku dk mPp Lrj FkkA eDdk mRiknu
es lEi~~~Zq.k Kku dk LRkj 38-12 o 32-50 RkFkk 29-38 izfr“kr d`’kdksa es Kku dk LRkj e/;e] fuEu] mPp
ik;k x;kA
eDdk mRiknu ds ckjs es 71-87 izfr“kr d’kdksa }kjk xzk-d-fo-v-@o-d-fo-v- ls lwpuk izkIr
dh tkrh gS ,oa lwpuk izkIr ds fy, 4&6 L=ksrks dk mi;ksx djrs gSA 71-87 izfr“kr d’kdksa }kjk eDds
dh mit ¼nkus½ dks fuft nwdkunkj dks csprs gS
eDdk mRiknu rdfud ds vxhadj.k es 68-12 izfr“kr d’kd vukt HkaMkj.k es fuEu Lrj]
bZlds ckn e/;e Lrj ds rgr mUurf”ky iztkfr dks p;u djus es 47-50 izfr“kr Fks] blh izdkj mPp
Lrj dh vxhadj.k Js.kh es 41-25 izfr“kr d`’kdksa dks Hkwfe dh rS;kjh ds vUrZxr ik;k x;kA eDdk
mRiknu es lEi~~~Zq.k vxhadj.k ds LRkj es yxHkx 51-25 izfr“kr d`’kd e/;e Lrj ds ik;s x;sA eDdk dh
vkSlr mRikndrk 22-53 fDoVy izfr gsDVs;j FkkA
lglac/ka fOk”ys’k.k ls ;g irk pyk fd 17 Lora= pj esa ls 13 pj tSls f”k{kk] ifjokfjd
vkdkj] lekftd Hkkfxnkjh] [ksrh dk vuqHko] tksr dk vkdkj] O;olk;] okf’kZd vk;] _.k vf/kxzg.k]
foi.ku lk/ku] ?kjsyw miHkksx] ykxr ykHk vuqikr] oSKkfud mUeq[khdj.k] Kku dk Lrj /kukRed
lkFkZdrk o vafxdj.k es eDdk mRiknu rduhd 0-01 o 0-05 Lrj dh lkFkZdrk ij vk/kkfjr gSA vU;
pj mez] lwpuk dk L=ksr] flapkbZ lqfo/kk ,oa foi.ku i)fr esa eDdk mRiknu rduhd dks viukus ds
izfr egRoiw.kZ lglac/ka iznf”kZr ugh djrkA izfrxeu fo”ys’k.k ls irk pyk fd 17 Lora= pj esa ls 8
pj tSls f”k{kk] lekftd Hkkfxnkjh] [ksrh dk vuqHko] tksr dk vkdkj] foi.ku lk/ku] ?kjsyq miHkksx]
ykxr ykHk vuqikr] Kku dk Lrj es eDdk mRiknu rduhd esa ldkjkRed o egRoiw.kZ ;ksxnku gS rFkk
“ks’k 9 pj mez] ifjokfjd vkdkj] lwpuk dk L=ksr] flapkbZ lqfo/kk] O;olk;] okf’kZd vk;] _.k
vf/kxzg.k] foi.ku i)fr] oSKkfud mUeq[khdj.k eDdk mRiknu rduhd ds vxhadj.k esa dksbZ egRoiw.kZ
;ksxnku ugh n”kkZ;kA
eDdk mRiknu rduhd es dbZ izeq[k ck/kk,sa gS] tSls dhVuk“kd o fuankuk“kd dh mfpr ek=k
o mi;qDr le; esa Mkyus ij Kku dh deh] blds ckn faalapkbZ lqfo/kk es deh vkSj ladj iztkfr ds
ckjs es Kku dh deh o mi;qDr le; esa miyC/k ugh gksuk ik;k x;kA
xvii
lq>ko ds vuqlkj 56-25 izfr“kr d`’kdksa }kjk crk;k x;k fd eDdk dh Qly es HkwVVk cuus
ds nkSjku i”kqvksa o if{k;ksa ls cpko ds fy, lqj{kk i)fr o lkexzh miyC/k gksuk pkfg,] bZlds ckn 51-
25 izfr“kr d`’kdksa }kjk lq>ko fn,s fd flapkbZ dh lwfo/kk miyC/k gksuk pkfg,] blh izdkj 50-62
izfr“kr d`’kdksa }kjk crk;k x;k moZjd dh mfpr ek=k o mi;qDr le; es mi;ksx djus dk Kku dh
vko“;drk izeq[k #i ls lq>ko ds #i es fn;s x;ssA
CHAPTER - I
INTRODUCTION
Maize is the most important cereal crop in the world. Major shift in global
cereal demand is underway: by 2020, demand for maize in developing countries
will surpass the demand for both wheat and rice. Maize requirements in the
developing world alone will increase from 282 million tones in 1995 to 504
million tones in 2020 (IFPRI, 2000). The challenge of meeting this unprecedented
demand for maize is daunting, especially for the developing world and its poor and
subsistence farmers.
Raising income in most of the developing world and the consequent growth
in meat and poultry consumption have resulted in a rapid increase in the demand
for maize as livestock feed (especially for poultry and pigs). Meanwhile, in the
least developed parts of the world, unabated population growth and the persistence
of poverty have maintained upward pressure on the demand for food maize; this is
the case in Sub-Saharan Africa, Central America, and parts of south Asia. Relative
to its 1995 level, annual maize demand in Sub-Saharan Africa is expected to
double to 52 million tones by 2020. In many maize consuming countries viz. Latin
America, where the culture and diet have been bound to maize for centuries, food
maize demand has remained high even as income have risen.
The exploding demand for maize presents an urgent challenge for most
developing countries. Although increased maize import is anticipated, especially in
the higher income in the developing countries, it should be remembered that the
international trade traditionally has supplied less than 10 per cent of the developing
world‟s maize requirements. At the global level, the proportion of maize demand
met through import is not expected to change, even as the absolute quantity of
maize traded is projected to grow 90 million tones in 2020, (IFPRI, 2000). For
developing countries, particularly those with large population, the accelerating
demand for maize must be met through dramatic increase in domestic supply. Even
the limited opportunities for augmenting maize area in most countries is dwindling,
thus future output growth must come from intensifying production on current
growing land.
Agriculture plays an important role in India‟s economy. Since the
independence, India has made great achievements in agriculture i.e. from import
food grains to self sufficiency and export of major agricultural commodities with a
contribution of 17.6 per cent to nations GDP (2015-16). Maize is one of the most
important cereal crops. In India, maize is cultivated in about 6 million ha with
production ranging between 7-10 million tones. National average yield of maize is
quite low about 1.6 tones per ha as compared to world‟s total of 4.3 tones per ha.
Punjab, Himachal Pradesh, Rajasthan, Uttar Pradesh, Madhya Pradesh, Bihar,
Gujarat, Andhra Pradesh and Karnataka are major maize growing states. The
highest average productivity of maize is 3 tones per ha which has been achieved by
the Karnataka state, (Mukherjee, 2012).
As it has yield potential far higher than any other cereal, it is sometimes
referred to as the miracle crop or the „Queen of Cereals‟. Maize grain contains (8-
10%) protein and (4-5%) oil. The consumption pattern for maize produced in India
at present includes poultry feed (52%), human food (24%), animal feed (11%),
starch (11%), brewery (1%) and seed 1 per cent. In our country with the growth in
demand of poultry feed the demand for maize is also going up. It is the crop with
the highest per day productivity. Some estimates indicate that India may have to
produce 55 million tones of maize to meet its requirement for human consumption,
poultry, piggery, farm industry and fodder, (Anonymous, 2011).
In Chhattisgarh state, maize is the second important crop next to paddy of
food grain production. Maize crop is cultivated in Chhattisgarh in 71.75 mha area
& production 134.16 mt and its productivity is 1886 kg/ha. Annual rainfall of CG
in average 1200-1400 mm. Coupled with 137 per cent cropping intensity (Krishi
Darshika, IGKV, Raipur, 2016).
Surguja district of Chhattisgarh state is the most maize growing areas.
Surguja district in total maize cultivated areas 0.40 mha & production 0.72 mt and
it‟s a productivity is 1806 kg/ha (Department of agriculture, Raipur, C.G., 2015-
16). Keeping the view all these facts, an investigation entitled “A study on
production, consumption and marketing pattern of maize among the tribal
farmers of Surguja district of Chhattisgarh” was planned during the year 2016-
17, with the following specific objectives:
1. To study the socio-economic profile of tribal maize growing farm
family.
2. To study the extent of adoption of maize cultivation practices by the
tribal farmers.
3. To analyses the consumption and marketing pattern of maize among
tribal families.
4. To identify the constraints faced by tribal farmers in production and
marketing of maize and obtain their suggestions to overcome the
constraints.
The need for the study
Taking into consideration for the magnitude of low production and
productivity of maize at farm level, it is evident that there is a need to adopt
improved production technology of maize so that we can maximize the low
production and productivity. Thus, there is a need to collect information about the
existing production technology of maize used by the maize growers and problems
faced by them in adoption of recommended maize production technology.
Hence, it was felt that the knowledge and adoption of recommended maize
production technology in Surguja district should be measured. The investigator
was motivated by this situation to undertake a small scale study about this aspect.
An effort has been made by planning a special study titled “A study on production,
consumption and marketing pattern of maize among the tribal farmers of Surguja
district of Chhattisgarh”.
Scope of the study
The present study would be helpful to understand the extent of adoption of
maize growers regarding recommended maize production technology in Surguja
district of Chhattisgarh state.
The present study will provide useful guidelines for knowing and
understanding production practices of maize used by the maize growers. The
findings of this study would also be helpful to understand the problem faced by the
farmers in adoption of recommended maize production technology and obtain the
suggestion to overcome the problems faced by them.
3
Limitation of the study
This study may help to administrators, planners and policy makers for
formulation of planning and policy for better adoption of maize production
technology among the maize growers. The finding of the study is based on
information expressed by the respondents regarding adoption of maize production
technology.
Since the study has been confined to only in four blocks of Surguja district of
Chhattisgarh state, the generalization based of findings may be applicable to the
aforesaid area and other adjoining areas with similar conditions. The study is
limited to recommended to maize production technology.
4
CHAPTER- II
REVIEW OF LITERATURE
In research, a body of literature is a collection of published information and
data relevant to a research question. A review of the literature is an essential part of
academic research project. The review is a careful examination of a body of
literature pointing toward the answer to our research question. Literature reviewed
typically includes scholarly journals, scholarly book, authoritative databases and
primary sources. Sometimes it includes news papers, magazines, other books, film,
audio, video tapes and other secondary sources. The main propose of the review
literature is to present some of the findings of research studies.
One of the important aspects of research is the review of past literature.
The researcher has to review the concerning literature at every stage. It is not a one
shot exercise but a continuous process, while going through the literature, the
researcher get acquainted with the subject matter, techniques, materials and guide
his efforts in desirable direction. Through review, researcher comes to know about
the methods, procedures and techniques as well as results of past studies. It
provides clues and guidance throughout the research process. Steady efforts were
made to compile research findings of the research studies possessing more or less
similar characteristics. The present chapter incorporates all the relevant literature
developed in India and abroad related to adoption of agricultural production
technology.
A brief account of related studies has been furnished under the following
heads:
2.1 Socio personal characteristics
2.2 Socio economic characteristics
2.3 Socio psychological characteristics
2.4 Communicational characteristics
2.5 Marketing practices
2.6 Extent of adoption of maize production technology and productivity of maize
crop
5
2.7 Constraints faced by tribal farmers and obtain their suggestions to overcome
the constraints in cultivation of maize crop.
2.1 Socio personal characteristics
2.1.1 Age
Singh and Rajendra (1990) stated that there is a positive and significant
association between age and adoption of COs-767 variety of sugarcane.
Gedageri (1991) stated significant relationship between the age and
adoption behaviour of groundnut cultivation.
Karthikeyan et al. (1995) reported that age of the respondents had a
significant and close relationship with the level of adoption of sugarcane
production technology.
Reddy and Reddy (1994) found that a positive but non significant
correlation between age and adoption level of castor crop of marginal and small
farmers under lab to land programme.
Tiwari and Lall (1998) found that age of farmers had positively and
significantly related with scientific attitude of sugarcane growers.
Nagaraj et al. (2000) found that age of big farmers had significant and
positively related with their adoption level.
Choudhary et al. (2001) stated that there is a non-significant relationship
between age and adoption of improved rice technology.
Shrivastava et al. (2002) reported that age was positively and significantly
related with the adoption level of chilli growers.
Sahu et al. (2003) observed that the age had a positive and significant
association with the extent of adoption of modern technologies.
2.1.2 Education
Patil (1991) found that there was a positive and significant relationship
between adoption behavior and education.
Dubey and Sawarnkar (1992) investigated that the adoption behaviour of
marginal and small farmers had a significant relationship with education in relation
to paddy technology.
Lianbeka and Nikhade (1993) reported that education was negatively
associated with the adoption behaviour of pineapple growers in Mizoram.
6
Krishnamurthy et al. (1997) revealed that the education was found to have
a highly significant relationship with adoption level of sugarcane cultivation.
Singh and Singh (1999) found that education shows significantly positive
and linear relationships with adoption of mustard technology.
Padmaiah et al. (2000) observed that the education was found to have
associated and contributed significantly in gaining knowledge on various aspects
of production technologies in cropping system.
Badal and Singh (2001) reported that the educational level of farmers,
existence of extension service and access to credit facilities were the significant
factors influencing behavior of farmers for adoption of improved technology in
maize. Non-availability of variety seed was also one of the reasons for non-
adoption of improved varieties. 45 per cent of respondents problem of
unavailability of quality inputs like seed, fertilizer and pesticides (insecticides and
fungicides) during peak season.
Tarde et al. (2006) revealed that education had highly significant
relationship with knowledge level of pomegranate growers.
2.1.3 Family size
Ingle (1974) observed that size of family was significantly related with use
of communication channels in adoption of recommended agricultural technology
by the farmers.
Saxena et al. (1990) observed that family size of the farmers had no
association with the adoption of innovations of rainfed wheat technology.
Arne (1994) reported that a positive and significant relationship between
family size and adoption.
Choudhary et al. (2001) observed that the size of family had nonsignificant
but positive relation with adoption of improved rice technology.
Mukim (2004) indicated that the majority of the farmers had medium size
of family (75%) and found that the size of family was significantly related with
adoption of sunflower production technology.
2.1.4 Social participation
Patil (1991) showed the positive significant relationship between social
participation and adoption behaviour.
7
Panwar et al. (1998) reported that social participation of farmers had
positive and significant correlation with the adoption of recommended soyabean
practices.
Tiwari and Lall (1998) investigated that social participation had positive
and significant relationship with scientific attitude of sugarcane growers.
Pal et al. (2001) observed that organization participation had significant
relationship with the adoption of recommended practices of sugarcane cultivation
Choudhary (2003) stated that the maximum numbers of the respondents
(34.54%) were found to be no membership in any organization regarding scientific
storage practices of food grains.
2.1.5 Farming experience
Saxena (2003) observed that majority of the respondents (51.38%) were
having 11 to 20 years of tomato farming experience, whereas 41.66 per cent of the
respondents were having up to 10 years of tomato farming experience and only
6.94 per cent of the respondents were having more than 20 years of tomato farming
experience as low and high category of experience. were found positively and
significantly correlated at 0.01 level of probability with the extent of knowledge
about tomato production technology.
Rahman et al. (2007) noticed 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
Tiwari et al. (2007) reported that the socio personal attributes like
education size of land holding experience of pea growing, income, knowledge
level, scientific orientation, source of information, extension participation and
marketing orientation play a significant role in adoption behaviour of farmers.
Kiran and Shenoy (2010) reported that majority of respondents having
medium farming (44%) experience as well as medium level of SRI cultivation
experience (64%).
Kumar and Rathod (2013) revealed that about 62 per cent respondents
found to have medium farm experience (8-13 year), followed by the respondents
(25.33%) of high experience where found farm experience was significantly
correlated with knowledge and adoption at 0.01 level of probability.
8
2.2 Socio economic characteristics
2.2.1 Land holding
Borkar et al. (2000) observed that land holding of the farmers was found
significantly associated with knowledge level of bio fertilizers.
Gogoi et al. (2000) revealed that a high degree association was found
between size of land holding and extent of adoption in improved rice cultivation.
Saxena and Singh (2000) observed that the land holding had positive
relationship with their adoption of organic farming practices.
Dongardive (2002) stated that nearly one third (30%) of the respondents
were in the marginal group, followed by 26.67 per cent, 23.33 per cent and 20 per
cent of them who had large, small and medium size of land holding respectively.
Jana and Verma (2004) concluded that paddy growers who were having
larger size of land holding and better socio-economic status were found to have
higher level of adoption in the recommended plant protection practices for paddy
cultivation.
Shrivastava (2005) observed that majority of the rice growers (41.25%) had
medium size of land holding (4.1 to 10 ha), followed by 35.00 per cent of the
respondents who had semi-medium size of land holding (2.1 to 4 ha). About 13.75
per cent of the respondents had small size of land holding (1.1 to 2 ha), as 9.37 per
cent of the respondents had large size of land holding (above 10 ha).
Vathsala (2005) revealed that about 38.9 per cent of the respondents had a
land holding of 2.5 to 5 acres (small farmers), followed by 43.3 per cent of the
respondents who had land holding of more than 5 acres (big farmers) and only 17.8
per cent of the respondents had land holding up to 2.5 acres (marginal farmers).
Maraddi et al. (2007) found the size of land holding to be non significantly
associated with adoption level of sustainable sugarcane cultivation practice.
Nagadev and Venkataramaiah (2007) reported that 39.33 per cent of
respondents belonged to semi medium category, 20 per cent belonged to medium
land holding, while 26.67 per cent possessed small land holding, 12 per cent
possessed marginal land holding and only (2%) had large land holding.
Rama (2007) observed that the farm size and proportion of area under
cotton influenced the adoption decision negatively.
9
Dhruw (2008) found that maximum number of the maize growers (37.50%)
had small size of land holding (1 to 2 ha), followed by 35.00 per cent respondents
who belonged under marginal category (up to 1 ha), whereas 20.83 per cent of the
respondents were having medium size of land holding (2 to 4 ha) however only
6.67 per cent respondents had large size of land holding (above 4 ha).
Patel (2008) revealed that maximum number of the soybean growers
(30.66%) had small size of land holding (1 to 2 ha), followed by 29.34 per cent
who had marginal land holding (up to 1 ha), whereas 26.66 per cent of the
respondents had medium size of land holding (2 to 4 ha), however 13.34 per cent
of the respondents had large size of land holding (above 4 ha).
Singh (2008) revealed that majority of (50.00%) the respondents belonged
to small category, followed by 48.00 per cent marginal farmers and only 2 per cent
were big farmers.
Ofuoku (2009) observed that (63.73%) of farm a household had (6-10
members) and also shows that (64.04%) of the farmers had less than six household
members assisting in pesticides and other agro-chemical application. Household
size had positive influence.
Banjo (2010) observed that the size of the land owned by the farmers range
from as little as a plot to as much as 10 ha. in different farmstead and many of the
had small holdings.
Kaushal and Singh (2010) concluded that political legal empowerment had
significant relationship with land holding.
Sathish (2010) concluded that majority (50.84%) of the respondents were
medium land holders followed by big and small landholders. In the study area
farmers had very good access for irrigation facilities in the form of tube wells, river
and canal on of one acre of irrigated land.
2.2.2 Irrigation facility
Pandey (2000) revealed that the 54.16 per cent respondents had no
irrigation facilities, whereas 36.66 per cent respondents had irrigation availability
up to partial level and only 9.16 per cent respondents had irrigation availability
up to significant level for rice cultivation in Chhattisgarh.
10
Mukim (2004) found that highest coverage of area under irrigation was
through tube well (42.19%), followed by Canal & well (32.81%). Canal & tube-
well and pond contributed 23.44 per cent and 1.56 per cent area under irrigation
respectively.
Thanh and Singh (2006) reported that the advantage of natural condition
(100%) farmers used the canals for the main sources of irrigation; whereas, for
respondent, it is one of the main constraints in their production when more than
half of them used tube-wells (66.00%), followed by canal (22.00%), rainfall
(10.00%) and wells (2.00%).
Singh et al. (2009) revealed that majority of (80%) respondents showed full
adoption, followed by 13 per cent respondents who had partial adoption, 5 per cent
respondents had adoption and only 2 per cent respondents had no adoption of
nursery management practices of hybrid rice.
Karki (2010) revealed that 62 per cent of the farmers were found to have
sufficient irrigation facilities into their farm.
2.2.3 Occupation
Raghuwanshi (2005) found that the occupation had positive and highly
significant correlation with adoption behaviour of rice growers regarding control
measures of various insect pests of rice crop.
Shrivastava (2005) found that most of the rice growers (26.87%) had
involved in farming + business, followed by (25.00%) respondents who involved
in farming + services, whereas 22.50 per cent of the respondents were involved in
farming. About 12.50 per cent of the respondents were employed in farming +
Animal husbandry. A few respondents (7.50%) had their farming + labour,
whereas only 5.63 per cent of the respondents were employed in farming + Animal
husbandry + services.
Sudheendra et al. (2004) reported that the majority of respondents 32.50
per cent were big farmers, then 29.70 per cent were marginal farmers, 20.30 per
cent were small farmers, 17.50 per cent were landless labours.
Prajapati (2006) revealed that the majority of the wheat growers (61.67%)
practiced only farming as the source of income, whereas (38.33%) farmers had
other sources of income along with farming.
11
Odeyinka et al. (2007) observed that the major occupation of the
respondents, 76.98 per cent indicated crop production, 35.97 per cent indicated
rearing of animals and few (23.02%) others engaged in non-farming business as
their major occupation.
Tiwari and Solanki (2007) found that agriculture was the main occupation
of the SHG members (64.37%) and link workers (59.37%) however majority of
them were involved in some subsidiary occupation like agricultural labour, animal
husbandry, business etc.
Yadav (2007) reported that education, occupation, source of information
and extension contacts of trained and untrained farmers were found positively and
it’s a significantly correlated with knowledge and adoption level of the
respondents.
Mao et al. (2008) noticed that all the respondents did their on farm work
during the wet season, while some of them had extra cultivation in the dry season
and most of families head did their off-farm employment in addition to on-farm
work. In terms of off-farm employment, some of them were lecturer, carpenter,
house constructor, masonry, sugar palm making, nurse, commune agricultural
extensionist, worker, motor taxi, find firewood and labor hired.
Patel (2008) observed that the majority of the soybean growers (52.00%)
were involved in farming, followed by farming + labor (14.00%), farming +
service (12.66%), farming + animal husbandry + service (7.34%), farming + others
(8.00%) and farming + occupation + service (6.00%) as their main occupation.
Singh et al. (2009) observed that all the farmers (100%) have agriculture as
their main occupation. Only 25 per cent farmers were having business (19%) or
service (6%) as their subsidiary occupation. It indicates that 75 per cent of farmers
did not associate with any subsidiary occupation.
Ogola et al. (2010) found that the 88.90 per cent respondents had doing
farming and only 11 per cent engaged in activities other than farming (e.g.
teaching, petty trading and pottery making).
Kaushal and Singh (2010) concluded that economic empowerment was
found positively correlated with family occupation.
2.2.4 Annual family income
12
Chandra (2001) concluded that 58.00 per cent of the respondents were in
the low income category (less than Rs. 20000), followed by 24.7 per cent and 17.3
per cent under medium and high income categories respectively (medium Rs.
20000 to Rs. 40000 and high above Rs. 40000).
Chaudhary et al. (2001) found that annual income had highly significant
and positive correlation with extent of adoption regarding improved rice
technology.
Shashidhara (2003) revealed that 42.44 per cent of the respondents
belonged to medium level of income (Rs. 1-2 lakh) and in low income category
30.00 per cent of respondents were noticed, whereas 27.70 per cent of the farmers
belonged to high income group.
Reddy et al. (2006) observed that the economic position of the respondents
indicated that high income (more than Rs. 59000) was noticed and a majority of
the respondents (72.50%) were medium landholders.
Ramesh and Santha (2008) the respondents with high annual income would
have spent more money on farm development through the adoption of organic
farming practice.
Kaushal and Singh (2010) concluded that economic empowerment was
found positively correlated with annual income.
Sathish (2010) concluded that in total 36.66 per cent of respondents
belonged to high income group, followed by medium (31.66%), semi medium
(27.5%) income groups and 4.16 per cent of them were in low income group.
Bolarinwa and Fakoya (2011) revealed that 35 per cent of the beneficiaries
of the farm credit scheme have income level of Rs. 21000 to Rs. 50000 compared
to 10.4 per cent of non beneficiaries in the same income level. Discrepancy in
income level of beneficiaries and non beneficiaries are reflected in farmer’s
productivity. That is the availability of credit is required for the purchase of needed
innovations and agricultural inputs which are utilized to increase income.
2.2.5 Credit acquisition
Kepley (1979) reported that significant and positive correlation between the
credit facility with level of knowledge and adoption for all categories of farmers.
13
Limje (2000) observed that significant and positive correlation between the
credit facilities with the adoption of soybean production technology.
Mukim (2004) indicated that the majority of respondents (96.09%)
acquired the credit and credit acquisition had positive and significant association
with the adoption of sunflower production technology.
Verma (2009) revealed that majority of the respondents (95.83%) acquired
is a credit from various agencies, whereas only 4.17 per cent respondents had not
acquired the credit facilities from the agencies providing the credit. Out of those
respondents who had acquired credit, the majority of the respondents (93.50%) had
taken short term credit, followed by mid term credit (6.50%) and none of the
respondents had taken long term credit.
Lakra et al. (2012) found that majority of the respondents (65.63%) had
acquired credit for agriculture. Out of total credit acquired farmers (105), it is
further noted that 61.90 per cent respondent had preferred to take the short term
loan credit (6 months), followed by 24.77 per cent of respondents had taken
medium term loan credit (6-18 months) and only 13.33 per cent of the respondents
had taken long term credit (18 month to 5 years).
2.2.6 Benefit-cost ratio
Moniriho and Bioza (2013) reported that data collection was conducted
through well structured questionnaire administered on 107 farmer respondents
selected purposively. The method of data presentation used was descriptive
statistics. The benefit-cost ratio was used to analyze the agricultural profitability in
the study area. The results revealed that, in the short run, agricultural investment is
a profitable business in the study area. This is reflected by the benefit-cost ratio of
1.47. The analysis also shows that all individual crops (potato, wheat, corn, tomato,
onion and cabbage) are profitable except for bean.
Alvardo (2013) observed that financial analysis determined that the annual
net benefit in the status quo did not cover the farmer’s investment. On the other
hand, the alternative project showed positive total and incremental net benefits,
implying that investment and operating costs would be covered. The government
cash flow statements for the current and the proposed projects showed cumulative
deficits. The economic analysis determined that the alternative project’s
14
incremental net benefit was positive. The net present value of the alternative
project at the individual level was positive, representing a 41% increment with
respect to the status quo. At the aggregate level, the net present value of the
project’s incremental net benefit was is a positive, which signifies an addition to
the national economy.
2.2.7 Domestic consumption
Mihic et al. (2006) determine which of the two analyzed concepts social
class or income has more influence over the buying behavior i.e. consumption of
certain products/services. The research was conducted on a sample of 270
respondents. Keeping in mind the research goals, three hypotheses were set. The
results confirmed two of them entirely and one partly, showing that both social
class and income significantly influence buying behavior. Among 19 analyzed
cases, social class proved to be more significant in eight of them and income in
four. The research showed that income better explains purchasing habits and
behavior with less visible products associated with significant expenditures, while
social class matters more with products reflecting life-style values, i.e. more visible
and expensive products associated with class symbols. Since members of different
social classes and income categories differ significantly in buying preferences with
all analyzed products/services, it can be concluded that both variables, depending
on specific situations and types of products/services, constitute important market
segmentation criteria.
2.3 Socio psychological characteristics
2.3.1 Scientific orientation
Khan et al. (2007) revealed that majority of the respondents (60%) showed
low level of scientific orientation while 24 per cent showed medium and only 16
per cent showed high scientific orientation.
Shakhya et al. (2008) revealed that scientific orientation was the important
factors which have direct and indirect effect on knowledge of chickpea growers.
Coefficient of correlation and regression coefficient “b” analysis show positive
significant with knowledge level of chickpea growers about chickpea production
technology.
Singh (2011) observed that non-significant correlation of scientific the
15
motivation with adoption of mung bean production technology in arid zone of
Rajasthan.
Deshmukh and Deshmukh (2013) revealed that scientific orientation was
found non-significantly associated with constraint level.
Thatchinamoorthy and Selvin (2014) found that more than 85 per cent of
SRI farmers possessed medium level of scientific orientation, followed by (10%)
and around (6%) who had high and low level of scientific orientation respectively.
The farmer’s better contact with extension agency, their inclination towards
scientific technologies and high education would have contributed to the present
trend in their scientific orientation.
2.3.2 Level of knowledge
Narayan et al. (1995) revealed that majority of the farmers having high
knowledge level regarding weedicide application in paddy production technology.
Resmy (1998) reported that above 40 per cent of small and half of the big
farmers had medium level of knowledge. Remaining 33.33 per cent of small
farmers had high knowledge level. In case of big farmer (25%) had high and low
level of knowledge.
Tailor et al. (1998) reported that the knowledge of selected dryland farming
practices of the small and big farmers was positively related with their adoption.
Nayak et al. (1998) indicated that the knowledge of sugarcane cultivation
practices had the greatest impact on productivity.
Desai et al. (2000) reported that majority (69.17%) of the farmers
possessed knowledge about recommended cotton production technology of NHH-
44 cotton variety.
Chapke (2000) reported that most of the farmers possessed average
(56.21%) knowledge about bio-control practices.
Satyavarthy (2001) found that the majority of the sugarcane farmers had is
a medium level of knowledge regarding sustainable cultivation practices of
sugarcane.
Vedpathak (2001) revealed that the highest per cent of marginal (42.64%)
and small (63.46%) farmers had medium and high knowledge respectively about
high yielding varieties. Whereas, majority of marginal (73.33%) and small 61.53
16
per cent farmers had no knowledge about seed treatment in rice.
Bala et al. (2005) reported that findings revealed that (47%) of the farmers
had medium level of knowledge about the recommended maize practices. Among
the various recommended technologies, the maximum gap was observed in micro-
nutrient application (99.30%), followed by herbicidal application (90.75%), plant
protection measures (84.35%) and balanced fertilizer use (78.33%). Limited
knowledge about micro-nutrients, pesticides and fertilizer application and their
advantages was the major reason for the chasm in the adoption of latest
recommended practices. Lack of technical know how, non availability of desired
variety seed, sub-standard, costly chemical fertilizers and plant nutrients, lack of
purchasing power etc. limited the adoption of recommended practices and hence
the maize productivity on farmer’s fields.
Dhruw et al. (2012) observed that the level of knowledge and adoption of
maize growers about recommended maize production technology. 120 farmers
were considered as respondents for this study. Respondents were interviewed
through personal interview. Collected data were analyzed with the help of suitable
statistical methods. The analysis of the results showed that maximum (62.50%)
respondents had medium level of knowledge regarding recommended maize
production technology and 61.66 per cent of the respondents had medium level of
adoption regarding recommended maize production technology.
2.4 Communicational characteristics
2.4.1 Sources of information
Singh and Singh (1999) revealed that mass media exposure have a great
role to play in the dissemination and adoption of improved technologies. These
factors were showed a positive and significant relationship with the adoption of a
package of showea positive and significant relationship with the adoption of a
package of practices for mustard cultivation.
Hedau (2000) revealed that variable, source of information was positively
and significantly associated with the adoption of paddy production technology.
Choudhary et al. (2001) found that information sources utilization pattern
had highly significant and positively correlated with adoption of rice production
technology in Faizabad district of U.P.
17
Lalitha et al. (2002) observed that the Agricultural Assistant were the most
consulted source of information in their study related to information consultancy
pattern among sugarcane farmers.
Mazher et al. (2003) revealed that a significant proportion of small farmers
(70.00%) gathered information through their fellow farmers and progressive
farmers. Large farmers (20.00%) got information about sugarcane production
technologies through the Agriculture Department (extension wing) and the
Research Institutes. While 10 to 20 per cent large farmers gathered information.
Patel et al. (2012) studied that the printed literatures, news papers and
television displays had played major role in mass media exposure. In case of
commercial agencies, the maize growers always used fertilizer and chemical
dealers and cooperative society as the source of agricultural information. It was
important to note that family members, neighbours and friends were perceived best
by tribal maize growers to get agricultural information. 140 maize growers
belonging to Panchmahals and Dahod district were interviewed.
2.5 Marketing practices
2.5.1 Marketing channel
Shiyani et al. (2000) observed that distance to the product market is
measured in kilometers. This is an important variable particularly in the study area
where the tribal farmers do not have easy access to markets. Therefore, market
distance is hypothesized to be negatively related to the adoption of improved
varieties i.e. nearer the output market, higher the adoption.
Kankanamge (2000) studied of familiarity with Market Maker was strongly
associated with strongly associated with share of total sales from vegetable crops,
farmer occupation, Internet speed as a barrier, Internet use in farming and finding
markets through Market in 5 per cent significant level.
Verma (2007) reported that the economics of production of maize on the
farms of different size-groups; examines the input output relationship and resource
use efficiency in maize enterprise on different sizes of farms; analyzes the price
spread in maize marketing in different channels studies the marketing efficiency of
various channels in maize marketing identifies various constraints in maize
production and marketing and suggests measures for improvement. A survey was
18
conducted on 40 small, 25 medium and 15 large farmers from the Dhar district of
Madhya Pradesh. The results of the study indicate that to reduce the price spread,
the maize growers should be encouraged to sell their produce through co-operative
marketing societies. Therefore, suggested that maize growers in the district should
be provided adequate marketing finance and facilities to access the regular market.
2.5.2 Mode of marketing
Ranade et al. (1981) worked on strategy for stabilizing the parity between
prices of groundnut and finished manufactured goods from groundnut. Minimum is
a support price of farm produce is to ensure that too in the years of fluctuation
output.
Teka (2009) study was initiated with the objectives of analyzing fruit and
vegetable marketing chains in Alamata District, southern zone of Tigray.
Specifically the study attempts to assess structure-conduct-performance of fruit and
vegetable marketing, analyze market supply determinants and analyze the
institutional support services of extension, input supply and credit. The study also
analyzes profitability of fruit, vegetable production, marketing and identifies
problems and opportunities in fruit and vegetable production and marketing. Data
came from 140 horticulture producing households, 9 horticulture wholesale and 30
retailers.
Espegren et al. (2015) study highly competitive environment businesses
invest big amounts of money into the new product development. New product
success potentially depends on different factors among which salespeople play an
important role. The aim of this paper is to explore the potential link between
salespeople’s personality, motivation to sell new products and performance in
selling new products.
2.6 Extent of adoption of maize production technology and
productivity of maize crop
2.6.1 Adoption
Kher (1991) observed that nearly two-third (63%) of the respondents had
medium adoption level, while (15%) possessed high adoption level towards maize
production technology.
19
Arya et al. (1996) were assessed to determine the technological gap in
adoption of wheat and sugarcane production technology. Component of technology
studied included high yielding cultivars, seed rate, date and method of sowing,
irrigation, fertilizers application, weed control and plant protection measures.
Adoption of fertilizer application and plant protection measures was the lowest of
the entire component studied in both crops and size of farms.
Krishnamurthy et al. (1997) revealed that many farmers (79.35%) adopted
is recommended varieties, seed rate and earthing up regarding adoption level of
sugarcane practices. Partial adoption was observed in case of NPK application. A
majority of the farmers did not adopt the practice of seed treatment, chemical weed
control and trush mulching. A high significant association was observed between
adoption levels and yield. The majority of the farmers belonged to the medium
level of adoption category.
Bhatkar et al. (1998) revealed that majority of the farmers were adopting
practices including improved seed, varieties, earthing up, spacing, control of
diseases and irrigation schedule. However, none of the respondents undertook
chemical weed control.
Chauhan et al. (1998) showed that 62.50 per cent of farmers had adopted
sugarcane quality seed production techniques that have been demonstrated to them,
with resulting increase in cane yield varying between 8.50 per cent and 36.50 per
cent.
Soni and Kurmvanshi (1999) reported that finding related to overall
adoption of modern agricultural technology, indicated that only 13.33 per cent
respondents adopted the overall recommended technology.
Manjunatha et al. (1999) found that knowledge of sustainable sugarcane
farming technologies contributing to differences in sustainable practice in adoption
level among sugarcane growers.
Shinde et al. (1999) indicated that the majority of farmers did not adopt the
practices like improved variety, application of fertilizers, spacing, thinning
operation, use of weedicide and plant protection measures regarding adoption of
rabi jowar cultivation practices.
20
Pandey (2000) reported that education annual income, land holding,
irrigation, knowledge level were significantly correlated with extent of adoption of
rice production technology.
Verma et al. (2000) found that the extent of knowledge and awareness
about improved production technology of soybean were positively and
significantly related with adoption level.
Ranganatha et al. (2001) found that education, use of mass media,extension
participation, innovation proneness, scientific orientation and risk orientations
were having significant relationship with the adoption level of small farmers about
organic farming practices.
Khan et al. (2002) found that majority of rice growers had medium level of
adoption of eco-friendly technologies.
Jaiswal et al. (2002) revealed that the partial adoption was a result of
various factors namely economic constraints, situational factors communication
gap with respect to plant protection, seed treatment and fertilizer doses regarding
soybean production technology.
Ajrawat and Singh (2004) concluded from their study that majority of the
farmers in both categories (large and small) had high level of adoption of seed and
irrigation facility while in reverse weeding technology and plant protection
technology had adopted to low extent regarding wheat production.
Anupama et al. (2005) observed that (97%) of the farmers fell under the
category of low adoption and only (3%) belonged to the medium adoption
category.
Meena et al. (2005) found that majority of the respondents (51.33%)
belonged to medium level of adoption group regarding improve practice of
cabbage cultivation.
Poswal et al. (2005) found the overall extent of adoption was 46.45 per
cent regarding recommended practices of sugarcane production technology.
Suchan et al. (2005) reveals that overall 50 per cent of the total respondents
were found to be in the medium adoption group, where as 28 per cent and 22 per
cent respondents were in the low and high adoption group respectively.
2.6.2 Productivity
21
Rao et al. (2013) suggested that the grain yield straw yield and Harvest
Index were higher in RNR 2465, followed by RNR 18833.
Naik (2015) observed that the during kharif season of 2014. The maximum
seed yield 2074 kg/ha. At the research instructional farm IGKV, Raipur, C.G.
Paikra (2016) studied that experiment was conducted kharif season of 2015
at the research cum instructional farm, Indira Gandhi Krishi Vishwavidyalaya,
Raipur to evaluate the effect of foliar nutrition on productivity and profitability of
soybean. In the higher grain yield 2157 kg/ha.
2.7 Constraints faced by the tribal farmers and obtain their
suggestions to overcome the constraints in cultivation of maize
crop
2.7.1 Constraints
Krishnamurthy et al. (1997) reported the major constraints identified for the
non-adoption or partial adoption of recommended practices of sugarcane were lack
of knowledge about number of setts, fertilizer doses and chemical weed control.
Soni and Kurmvanshi (1999) stated regarding the constraints in adoption of
technology, lack of awareness was the prominent constraint (expressed by 19.25%
if total) followed by high cost of inputs (18.50%).
Nayak (2000) reveals that the major constraints faced by ber growers in
adoption of improved cultivation practices were lack of knowledge about budding
and grafting (81.66%), followed by use of improved seedlings (77.66%).
Gogoi et al. (2000) observed that low level of adoption of the respondents
regarding improved rice cultivation practices due to less contact of village level
extension workers and lack of skill oriented agricultural training programmed and
is demonstrations.
Nirmala et al. (2002) found that inability to remember the quantity, method
of application reinforcement on the technology, inadequacy of irrigation water at
the time of application and inability to plan in advance were the major constraints
of bio fertilizers adoption.
Ayanwuyi (2005) studied that the adoption of improved farm technologies
on maize production in Shaki Agricultural Zone of Oyo State. A total of ninety
(90) respondents were interviewed through the administration of pre-tested
22
structured interview schedule. Data collected were analyzed with inferential
statistics like frequency counts and per cent, while chi-square and Kendall
coefficient of concordance was use to test the stated hypothesis. Various improved
technologies adopted by maize farmers were evaluated and ranked based on the
null hypothesis that there is no significant difference in farmers ranking of the
importance of the different improved technologies in relation to profitability.
Poswal et al. (2005) reported that more than 60 per cent sugarcane growers
do not adopt the scientific crop production technology properly due to non-
availability of resources.
Tarde et al. (2006) reported the major problems faced by pomegranate
growers were difficulty in taking bahar in rainy season (77.10%), limitation of
irrigation availability (74.30%), long distance of market (88%) and excessive price
fluctuation of fruits (84.50%).
Jaisridhar et al. (2011) studied that of extent of adoption indicated that the
most favourable season for sowing was adoption by most of the farmers (54.44 %).
Majority of the farmers, followed all the maize field practices like basal urea
application (61.11%), top dressing (60.00%), micronutrient application (46.70%),
seed treatment (34.50%), weed crop protection (78.90%) and water management
(74.40%). Most of the farmers in the study area (53.33%) harvested the produce
only when the seeds became dry and hard.
Raghu et al. (2015) in this paper analysed the case of hybrid maize
adoption using data from a survey of 340 maize-growing households from three
stress-prone regions in India. Hybrid maize adoption varies from (33%) to (99%)
in these locations. A profit model is used to assess the factors determining
adoption. The outcomes of hybrid maize adoption are examined in terms of yield
and profitability, employing mean-variance analysis. We find a clear superiority of
the hybrid technology with respect to yield enhancement, per-unit cost reduction
and risk reduction only in one of the study locations. Our findings indicate
significant economic potentials for developing abiotic stress tolerant maize.
2.7.2 Suggestions
Patel (2008) revealed that that majority of respondents (80%) suggested
that knowledge should be increased in various aspects of soybean production
23
technology i.e. Seed treatment, Rhizobium culture, Improved variety, use of proper
dose of Fungicide, Insecticide, Weedicide through systematic training programme,
followed by 78.66 per cent who suggested that the extension agents or agency
should convey right information at right time (74.66%) facility should be increased
regarding continuous supply of electricity, improved seed should be available
timely and sufficient quantity (68.00%), soybean processing unit should be
established in Kabirdham district (66.66%), skill oriented training should be
organized on seed treatment at village level (65.33%), proper and regular training
should be provided on soybean production technology (58.00%), market facility
should be increased as well as procurement rate of soybean crop (54%), subsidies
should be increased on fertilizers seed (53.33%), irrigation facility should be
increased (50.66%), credit should be provided at proper time (47.33%),
demonstration and farmer training should be organized at village level (46.66%)
increases infrastructure facility like road and transportation (26.66%) are the main
suggestions given by the respondents.
Lanjewar (2009) revealed that the adoption of recommended cabbage
production technology with reference to use of drip irrigation system it was
observed that subsidies should be increased on inputs i.e. fertilizers and seeds
emerged as the main suggestions as reported by (78.57%) of the respondents. The
other suggestions were subsidies increased on drip irrigation system (77.19%),
market as well as cold storage facility should be increased (74.28%).
Sahu (2013) revealed that the majority of the respondents (93.75%) were
of the opinion that appropriate subsidy should be provided to farmers to purchase
the drip irrigation system.
24
CHAPTER – IIIMATERIALS AND METHODS
The present investigation “A study on production, consumption and
marketing pattern of maize among the tribal farmers of Surguja district of
Chhattisgarh” was carried out during the year 2016-17. This chapter deals with the
methods and procedures used for the study during the course of investigation. The
different steps that were undertaken are listed below in following heads:
3.1 Location of study area
3.2 Sample and sampling procedure
3.2.1 Selection of districts
3.2.2 Selection of blocks
3.2.3 Selection of villages
3.2.4 Selection of respondents
3.2.5 Collection of data
3.2.6 Statistical methods
3.3 Variables of the study
3.3.1 Independent variables
3.3.2 Dependent variables
3.4 Operationalization of independent variables and their measurement
3.5 Operationalization of dependent variables and their measurement
3.6 Constraints faced by the maize growers in adoption of recommended
maize production and marketing
3.7 Suggestions suggested by the maize growers to overcome these
constraints
3.8 Type of data
3.9 Developing the interview schedule
3.9.1 Validity
3.9.2 Reliability
3.10 Method of data collection
3.11 Statistical analysis
25
3.1 Location of study area
Chhattisgarh state is divided in three agro climatic zones viz. Northern Hills,
Baster plateau and Chhattisgarh plain. The study was conducted during the year
2016-2017 in Northern Hills Agro-Climatic Zone of Chhattisgarh state. This Zone
is consists of five districts i.e. Surguja, Surajpur, Koria, Balrampur and Jashpur.
Out of that, only Surguja districts were selected purposively for this study. (Fig.
3.1)
3.2 Sample and sampling procedure
3.2.1 Selection of districts
This study was conducted in one selected district, namely Surguja in
Northern Hills of Chhattisgarh state. Surguja district was purposively selected for
the study, because more cultivated area of maize crop among the five district of
Northern Hills of Chhattisgarh state.
3.2.2 Selection of blocks
Surguja district consists of total seven blocks namely, Ambikapur, Lundra,
Lakhanpur, Batouli, Udaypur, Sitapur, Mainpat. Out of which four blocks namely
Ambikapur, Lundra, Lakhanpur, Batouli were selected randomly for the research
work.
3.2.3 Selection of villages
From each selected block, 4 villages were selected randomly, therefore total
16 (4×4=16) villages (viz. Rukhpur, Karmha, Labji, Kanchanpur, Nagam, Jamdih,
Gujarwar, Urdara, Nimha, Potaka, Rampur, Latori, Batouli, Khadhdhonwa,
Kunkuri, Bilashpur) were considered for the study.
3.2.4 Selection of respondents
From each selected village, 10 maize growing tribal farmers (Kharif season)
were selected randomly for the collection of data. Thus, total 160 (16×10=160)
tribal farmers were selected as a respondent for the present study.
3.2.5 Collection of data
The data were collected personally through pre-tested interview schedule.
3.2.6 Statistical methods
Collected data were tabulated and analysed by using appropriate statistical
tools and methods.
26
Fig. 3.1 Location map of the study area
27
Table 3.1: Selected area and number of respondents for the study
Selecteddistrict
Selected blocks
Selectedvillages
No. of selectedrespondents
Surguja Ambikapur Rukhpur 10Karmha 10 Karmha 10Kanchanpur 10
Lundra Nagam 10Jamdih 10Gujarwar 10Urdara 10
Lakhanpur Nimha 10Potaka 10Rampur 10Latori 10
Batouli Batouli 10Khadhdhonwa 10Kunkuri 10Bilashpur 10
3.3 Variables of the study
3.3.1 Independent variable
Socio personal characteristics : Age, Education, Family size, Social Participation, Farming Experience
Socio economic characteristics : Land holding, Irrigation facility, Occupation, Annual family income, Credit acquisition, Benefit-cost ratio, Domestic consumption
Socio psychological characteristics : Scientific orientation, Level of knowledge about maize production technology
Communicational characteristics : Sources of information
Marketing practices : Marketing channel, Mode of marketing
28
3.3.2 Dependent variables
Extent of adoption of maize production technology
Productivity
3.4 Operationalization of independent variables and theirmeasurement
3.4.1 Socio personal Characteristics of the respondents
3.4.1.1 Age
Age of the respondents was considered as informed by them during
personal interview was recorded. The chronological orders for age of the
respondents were applied for analysis. The age was categorized as follows:
Categories Score
Young (up to 35 years) 1
Middle (36 – 55 years) 2
Old (above 55 years) 3
3.4.1.2 Education
The reading and writing capability acquired by the respondents were
considered as their education status and it was categorized as under:
Categories ScoreIlliterate 0Primary school 1Middle school 2High school 3Higher Secondary school 4Graduation and above 5
3.4.1.3 Family Size
On the basis of number of members in the family of the respondents the
following categories were made:
Categories ScoreSmall (up to 5 members) 1Medium (6 to 10 members) 2Large (above 10 members) 3
29
3.4.1.4 Social Participation
The term social participation in this study refers to the degree of
involvement of the respondents in formal/ informal organization as a member of
executive/office bearer or both. A social participation score was computed for each
respondent on the basis of his membership and position in various formal/ informal
organizations. The scoring was done in following manner:
Categories ScoreNo membership in any organization 0Membership in one organization 1Membership in more than one organization 2
3.4.1.5 Farming Experience
The experience of respondents were categorized on the basis of years spent
in the farming (maize cultivation). The respondents were categorized as follows:
Categories ScoreUp to 10 years 111-20 years 2Above 20 years 3
3.4.2 Socio economic characteristics of the respondents
3.4.2.1 Land holding
Land holding of the respondent’s family was considered as an important
factor influencing process of the adoption. The number of hectares used for
cultivation by the respondents at the time of interview was considered depending
on the size of land holding of respondents and they were grouped into categories:
Categories ScoreMarginal farmers (up to 1 ha.) 1Small farmers (1.1 to 2 ha.) 2Medium farmers (2.1 to 4 ha.) 3Large farmers (above 4 ha.) 4
3.4.2.2 Irrigation facility
Information regarding the type of the source used by the respondents for
providing irrigation to the crops was collected. Different sources of irrigation such
30
as well, tube-well, dam/nahar, river, canal and pond were identified. On the basis
of availability of irrigation facility, the farmers were categorized in the following
manner for analysis of data.
Categories ScoreAvailable 1Not available 0
3.4.2.3 Occupation
The occupation held by the respondents such as Agriculture, Animal
Husbandry, Business, and Service etc. was included in the study. The kinds of the
occupation practiced by the farmer were categorized for analysis in following
manner:
Categories ScoreAgriculture 1Labour 2Animal Husbandry 3Business 4Service 5
3.4.2.4 Annual family income
Annual family income is defined as the total income a respondents derives
from agricultural, allied and other occupation in years. In the study, total annual
family income from all the available sources of respondents, family were
calculated and then the respondents were categorized in the following manner:
Categories ScoreUp to Rs. 50,000 1Rs. 50,001 to Rs. 1,00,000 2Rs. 1,00,001 to Rs. 2,00,000 3Above Rs. 2,00,000 4
3.4.2.5 Credit acquisition
The availability of credit is needed to purchase the required inputs may
influence the extent of adoption among farmers. The adoption of improved
agricultural technology requires more capital investment in farming to purchase the
inputs like fertilizer, pesticides, improved seed, implements etc. Sources of credit
were identified which included cooperative society, regional rural bank,
moneylenders, friends, neighbour, relatives etc and each source was given equal
31
weight age. Availability of credit identified by the farmers and then measured as
follows:
Categories ScoreAcquired 1Not acquired 0
3.4.2.6 Variety
The availability of variety of categories were in Local varieties, Improved
varieties and Hybrid varieties are cultivation of farmers as a follow:
Categories ScoreLocal varieties 1Improved varieties 2 Hybrid varieties 3
3.4.2.7 Benefit-cost ratio
Marshall (1900) that benefit-cost ratio is the value of benefits divided by
the value of cost.
The benefit-cost ratio is given by the following formula:
BCR =
If the benefit-cost ratio is greater than 1, because the benefits, measured by
the value of the total revenues are greater than the costs.
3.4.2.8 Domestic consumption
Domestic consumption in a family is very importents maize product.
Consumption such as a Corn, Popcorn, Roti, Grain feeding to animals etc.
Consumption identified by the family and then measure:
Categories ScoreCorn (cob) 1Popcorn 2Roti/ chappati 3Grain feeding of animals 4
3.4.3 Socio psychological characteristics of the respondents
3.4.3.1 Scientific orientation
It refers to the degree to which an individual is inclined to use scientific
method in farming and decision-making. The scientific orientation scale developed
by Supe (1975) was used for the measurement of scientific orientation of
32
respondents. The statements of the original scale were suitably modified to
measure the scientific orientation of respondents. The scale has six items. Out of
these five items, number 1, 3, 4, 5, 6 were positive items and number 2 was a
negative item. The score for positive item were 5, 4, 3, 2 and 1 and for negative
item scores were 1, 2, 3, 4, 5 for the response categories strongly agree, agree,
undecided, disagree and strongly disagree respectively. The sums of scores of all
the six statement were worked out. The respondents were categorized into
following groups:
Categories ScoreLow level of scientific orientation (up to 22 score) 1Medium level of scientific orientation (23 to 25 score) 2High level of scientific orientation (above 25 score) 3
Further, the respondents were classified into three categories by using
follows:
S.O. = Mean (XX ) S.D. (Standard Deviation)
Categories ScoreLow level of scientific orientation (< XX - S.D.) Up to 22
Medium level of scientific orientation (in between XX S.D.) 23 to 25High level of scientific orientation (>XX +S.D.) Above 25
3.4.3.2 Level of knowledge about recommended maize production technology
Knowledge is defined as a body of understands information possessed by
an individual or by culture.
Rogers (1983) stated that knowledge is of three types namely awareness
knowledge; how to knowledge and principle knowledge. In the present study
awareness and knowledge was studied and study is confined, as the technical
information possessed by the respondents about recommended maize production
technology.
The Knowledge test was composed of items called questions for
constructing the knowledge tests of all the package of practices of maize
production technology. A set of questions was developed and discussed with the in
33
the disciplines of advisory committee and then finalized. Total no. of questions was
15.
A device was developed to measure the level of knowledge for farmers
regarding selected technologies those recommended for maize crop, a teacher
made scale was used with some modifications. The responses of respondents
regarding knowledge were obtained into three point continuum as under:
Categories ScoreIncomplete knowledge 0Partial knowledge 1Complete knowledge 2
Further, the respondents were classified into three categories by using
follows:
K. I. = Mean (XX ) S.D. (Standard Deviation)
Categories ScoreLow level of knowledge (< XX - S.D.) Up to 13Medium level of knowledge (in between XX S.D.) 14 to 20High level of knowledge (>XX +S.D.) Above 20
3.4.4 Communicational characteristics of the respondents
3.4.4.1 Sources of information
Source of information are supposed to directly associate with the adoption
of new technology. These information sources provide various information to the
respondents regarding maize cultivation practices. For assessing this variable,
different 14 sources of information were identified. To determine the extent of
utilization of each information source, the responses of the farmers were recorded
and presented in frequency and percentage. Afterward the respondents were
categorized for analysis on the basis of using number of information sources as
follows:
S.I. = Mean (XX ) S.D. (Standard Deviation)
Categories ScoreLow level of use of information (< XX - S.D.) Up to 3Medium level of use of information (in between XX S.D.) 4 to 7High level of use of information (>XX +S.D.) Above 7
Their use of information sources:
34
Categories ScoreLow level of use of information (up to 3 sources) 1Medium level of use of information (4-7 sources) 2High level of use of information (above 7 sources) 3
3.4.5 Marketing practices of the respondents
3.4.5.1 Marketing channel
A marketing channel is the people, organizations and activities necessary to
transfer the ownership of goods from the point of production to the point of
consumption. It is the way products, services get to the end-user and consumer are
also known as a distribution channel. A distribution channel is a chain of
businesses or intermediaries through which a good or service passes until it reaches
the end consumer. It can include wholesalers, retailers, distributors and even
the internet itself. A channel is an institution through which goods and services are
marketed. Channels give place and time utilities to consumers. Channels give place
and time utilities to consumers. It was categorized as follow:
Categories ScoreProducer to whole sale market (cob) 1Producer to market (cob) 2Producer to krishi upaj mandi (grain) 3Producer to shopkeeper (grain) 4Producer to dairy farm (green leafs fodder) 5
3.4.5.2 Mode of marketing
It refers to the mode of marketing as a corn (cob), grain, green leaf fodder
of maize product by the respondents. It was categorized as follow:
Categories ScoreCorn(cob) 1Grain 2Green leafs fodder 3
3.5 Operationalization of dependent variables and theirmeasurement
3.5.1 Extent of adoption of recommended maize production technology
It is mental process through which an individual passes from hearing about
an innovation to final adoption (Rogers, 1995). It is operationalzed as the degree
of use of recommended practices.
35
To measure the extent of adoption, the list of recommended important
practices was prepared and responses for the each practice wise obtained into three
point continue as under:
Categories ScoreNot adopted 0Partially Adopted 1Fully Adopted 2
The researcher ascertained the extent of adoption in terms of selected
practices of maize production technologies adopted. The respondents were
classified into three categories by using following formula:
A.I. = Mean (XX ) S.D. (Standard Deviation)
Categories ScoreLow level of adoption (< XX - S.D.) Up to 10Medium level of adoption (in between XX S.D.) 11-19High level of adoption (> XX + S.D.) Above 19
3.5.2 Productivity
Productivity is a per unit area (kg or q). As reported by respondents of the
study area was recorded and presented in range and average. For analysis, actual
yield of the crop were utilized. For overall analysis of productivity of all maize
varieties were calculated and utilized.
3.6 Constraints faced by the maize growers in adoption ofrecommended maize production and marketing
To measure the constraints faced by the maize growers in adoption of
recommended maize production technology, the simple ranking technique was
applied, each farmers were asked to mention his constraints in adoption of
recommended maize production technology in order of degree of difficulties.
3.7 Suggestions given by the maize growers to overcome theseconstraints
Considering the constraints faced by the maize growers regarding adoption
of maize production technology. To overcome the same in adoption of maize
production technology successfully, the farmers were asked to give their valuable
suggestions for better adaptation among the maize growers. The suggestions
36
offered were ranked on the basis of number and per cent of farmers reported for the
respective suggestion.
3.8 Type of data
The data pertaining to selected characteristics about socio personal, socio
economic, socio psychological, communicational, marketing, adoption, problems
as perceived in terms of adoption and suggestions of respondents were collected as
per objectives of the study in the form of primary data. The official information’s
and records were also collected by the investigator from the concerning
departments as secondary data.
3.9 Developing the interview schedule
The interview schedule was designed on the basis of objectives and
independent and dependent variables for the present investigation. To facilitate the
respondents, the interview schedule was framed in “Hindi”. Each question was
thoroughly examined and discussed with the experts before using the interview
schedule. Adequate precautions and care were taken into consideration to
formulate the questions in a proper manner so that the respondents could be
understood the questions easily and can easier to respond properly.
The prepared interview schedule was used in the study area for collecting
the data. On the basis of experience gained in pre-testing, the necessary
modifications and suggestions were incorporated before giving a final touch to the
interview schedule.
3.9.1 Validity
Validity refers to “the degree to which the data collection instrument
measures what it is supposed to measure rather than something else”. It may be
defined as “validity is the extent to which difference found which a measuring
instruments reflects true different among those being tested”. Taking the following
steps to maximize validity of interview schedule used for this study:
1. The interview schedule was thoroughly discussed with the scientists and
their suggestions were incorporated.
2. Pre-testing of interview schedule was provided an additional check for
improving the instrument.
37
3. The relevancy of each question in terms of objectives of study, their
logical order and wording of each question was checked carefully.
3.9.2 Reliability
Reliability of an interview schedule refers to “its consistency or stability in
obtaining information from respondents”. The test-retest method of estimating
reliability of an interview schedule was followed in this study. 5-10 respondents of
the study area were randomly selected and were re-interviewed after 2 to 3 weeks
using the same interview schedule followed at the time of first interview. Since
same responses were observed, the reliability of the interview schedule was
ensured.
3.10 Method of data collection
Respondents were interviewed through personal interview. Prior to
interview, respondents were taken into confidence by revealing the actual purpose
of the study and full care was taken in to consideration and developed good rapport
with them. They were assured that the information given by them would be kept
confidential. The interview was conducted in the most formal and friendly
atmosphere without any complications.
3.11 Statistical analysis
The data collected during the course of investigation was tabulated into the
coding sheet and then appropriate analysis of data was made according to
objectives as suggested by Cochran and Cox (1957). The statistics techniques were
applied in the form of frequency, percentage, mean, standard deviation, coefficient
of correlation, multiple regression etc. the analysis was carried out with help of
Computer Section of IGKV, Raipur.
3.11.1 Frequency and percentage
Frequency and percentage were used for making simple comparison.
3.11.2 Mean and standard deviation
(i) Mean
Mean of sample was calculated by using the following formula:
XX =
Where, XX = Mean of the respondents
38
x = Sum of total number of respondents
n = Total number of respondents
(ii) Standard deviation
Standard deviation was calculated by using following formula:
S.D. =
Where, S.D. = Standard deviation
x = Deviation obtained from mean
n = Number of observation
3.11.3 Pearson’s Coefficient of correlation
The technique used to find out the relationship between two variables. The
formula was used as follows:
n xy – xy r =
nx2 – (x)2. ny2 – (y)2
where,
r = Corrélation coefficient
x = Score of independent variable
y = Score of dependent variable
n = Number of observation
3.11.4 Multiple regressions
This technique was used to know the partial and complete influence of
independent variables. For the present study linear model of regression equation
was used which is as follows:
Y1 = a + b1x1 + b2x2 + ………. + bnxn
Where,
Y1 = Dependent variable
x1…xn = Independent variables
a = Constant value
b1…bn = the regression coefficient for respective independent
variables
39
CHAPTER-IV
RESULTS AND DISCUSSION
This chapter deals with the results obtained on various aspects of the study
and supported with suitable discussion on each findings. The data were collected
from 160 respondents through the interview schedule on the basis of objectives of
the study. The collected data were classified, tabulated, analyzed, presented,
interpreted and discussed systematically.
The findings of the study are presented and discussed under the following
heads:
4.1 Independent variables
4.1.1 Socio personal characteristics of the respondents
4.1.2 Socio economic characteristics of the respondents
4.1.3 Socio psychological characteristics of the respondents
4.1.4 Communicational characteristics of the respondents
4.1.5 Marketing practices
4.2 Dependent variables
4.2.1 Extent of adoption of maize production technology
4.2.2 Productivity
4.3 Correlation analysis of independent variables with adoption of
recommended maize production technology by the maize growers
4.4 Multiple regression analysis of independent variables with adoption of
recommended maize production technology by the maize growers
4.5 Constraints faced by the maize growers in adoption of recommended
maize production technology
4.6 Suggestions from the maize growers for increasing the adoption of
recommended maize production technology
4.1 Independent variables
4.1.1 Socio personal characteristics of the respondents
Age, education, size of family, social participation and farming experience
were considered as socio personal characteristics of the respondents. Table 4.1.
40
4.1.1.1 Age
The data regarding age of the respondents are presented in Table 4.1, it is
observed from the table that majority of the respondents (52.50%) were belonged
to middle age group (36 to 55 years), followed by 40 per cent respondents were
under young age group (up to 35 years) and 7.50 per cent respondents were old age
group (more than 55 years).
4.1.1.2 Education
The data on education of respondents presented in Table 4.1, it was found
that 27.50 per cent of the respondents were educated middle school level and 23.75
per cent respondents were found under the category of primary school level and
22.50 per cent respondents were high school level. 15 per cent of the respondent’s
higher secondary level, where’s 8.75 per cent of illiterate and only 2.50 per cent
respondent’s graduation level and above.
The maximum number of maize growers had primary to high school level
of education. It may be because of the fact that primary and middle school are
found in most of the villages and the maize growers would have acquired, primary
to middle level education attending the schools in their village itself without any
need to go outside. Finally result clearly indicates that the majority of respondents
were having education up to primary to middle level.
4.1.1.3 Family size
The data regarding family size is presented in Table 4.1, maximum
(62.50%) respondents had medium size of the family (6 to 10 members), followed
by small size of family (1- 5 members) with 35 per cent. However, rest of 2.50 per
cent respondents had big size of family (more than 10 members). This indicates
that the majority of respondents had medium size of family.
4.1.1.4 Social participation
The data regarding social participation is presented in Table 4.1. As regard
to social participation, maximum number of respondents (63.12%) had
membership in one organization, followed by 18.75 per cent of respondents had
membership in more than one organization. There were 18.13 per cent respondents
who were having no membership in any organizations.
41
Table 4.1: Distribution of the respondents according to the their socio personal
characteristics
Sl. No. Particulars Frequency Percentage
1 Age
Young (up to 35 years) 64 40.00
Middle (36 to 55 years) 84 52.50
Old (above 55 years) 12 7.50
2 Education
Illiterate 14 8.75
Primary school 38 23.75
Middle school 44 27.50
High school 36 22.50
Higher secondary 24 15.00
Graduation and above 04 2.50
3 Family size
Small (1-5 members) 56 35.00
Medium (6-10 members) 100 62.50
Large (above 10 members) 04 2.50
4 Social participation
No membership in any organization 29 18.13
Membership in one organization 101 63.12
Membership in more than one
organization
30 18.75
5 Farming experience
Up to 10 years 66 41.25
11-20 years 86 53.75
Above 20 years 08 5.00
4.1.1.5 Farming experience
The data regarding farming experience (maize cultivation) are presented in
Table 4.1. It shows that most of the respondents (53.75%) where having 11 to 20
42
years of farming experience, followed by 41.25 per cent were having up to 10
years of farming experience and only 5 per cent of respondents having above 20
years of farming experience.
4.1.2 Socio economic characteristics of the respondents
The independent variables i.e. land holding, irrigation facility, occupation,
annual family income, credit acquisition, benefit-cost ratio and domestic
consumption were considered as socio economic characteristics of the respondents.
4.1.2.1 Land holding
The distribution of respondents according to their land holding is presented
in the Table 4.2 and Fig. 4.1. The data regarding land holdings indicates that most
of the respondents (35.62%) had less than 1 ha of land (marginal farmers),
followed by 25.63 per cent had 1.1 to 2 ha land holding (small farmers) and 24.37
per cent were medium farmers (2.1 to 4 ha). About 14.38 per cent respondents
were found under large farmer’s categories with land holding above 4 ha.
Table 4.2: Distribution of the respondents according to their size of land holding
Sl. No. Size of land holding Frequency Percentage
1 Marginal farmers (up to 1 ha) 57 35.62
2 Small farmers (1.1 to 2 ha) 41 25.63
3 Medium farmers (2.1 to 4 ha) 39 24.37
4 Large farmers (above 4 ha) 23 14.38
4.1.2.2 Irrigation facility
Irrigation is the most important critical input in agriculture. In case of crop
production, productivity, cropping intensity and profitability is directly related
with availability of irrigation facility and the total 83.75 per cent were having
irrigation facility. (Table 4.3) and (Fig. 4.2) Well, tube-well, dam/nahar, river,
canal, pond etc. were the sources of irrigation in the study area. Out of total
irrigated area, nearly 60 per cent area was irrigated by tube-wells. Dam/nahar were
also utilized as sources of irrigation by more than 17 per cent respondents. Same
respondents were also using canal, pond and other sources of irrigation.
43
Fig. 4.1 Distribution of the respondents according to their size of land holding
35.62%
25.63%
24.37%
14.38%
Land holding
Marginal farmers (up to 1 ha) Small farmers (1.1 to 2 ha)
Medium farmers (2.1 to 4 ha) Large farmers (above 4 ha)
44
Table 4.3: Distribution of respondents according to availability of irrigation and its
sources
Sl. No. Particulars Frequency Percentage
1 Availability of irrigation facilities
Available 134 83.75
Not available 26 16.25
2 Sources of irrigation
Well 10 7.46
Tube-well 81 60.44
Dam/nahar 24 17.91
River 09 6.72
Canal 06 4.48
Pond 04 2.98
4.1.2.3 Occupation
The data regarding respondent’s involvement in different occupations are
given in the Table 4.4 and Fig. 4.3.
Table 4.4: Distribution of respondents according to their involvement in various
occupations
Sl. No. Occupations Frequency* Percentage
1 Agriculture 160 100.0
2 Labour 125 78.12
3 Animals husbandry 64 40.00
4 Business 03 1.87
5 Service 02 1.25
*Data are based on multiple responses
The data reveals that cent per cent of the respondents were involved in
agriculture, followed by 78.12 per cent involved in labour work, about 40 per cent
were involved in animals husbandry, while, 1.87 and 1.25 per cent were involved
in business and service, respectively.
45
Fig. 4.2 Distribution of respondents according to their availability of irrigation
sources
Fig. 4.3 Distribution of respondents according to their involvement in various
occupations
7.46%
60.44%
17.91%
6.72%
4.48%2.98%
Sources of irrigation
Well Tube-well Dam/nahar River Canal Pond
100%
78.12%
40%
1.87% 1.25%
Occupations
Agriculture Labour Animals husbandry Business Service
46
4.1.2.4 Annual family income
As regard to annual income, the data given in Table 4.5 and Fig. 4.4,
reveals that the maximum respondents (46.88%) had obtained income Rs. 50,001
to Rs. 1,00,000, followed by 22.50 per cent of respondents had their annual income
in the Rs. 1,00,001 to Rs. 2,00,000, while 16.87 per cent of the respondents up to
Rs. 50,000 and only 13.75 per cent of respondents had income above Rs.
2,00,000.
Table 4.5: Distribution of respondents according to their annual income of family
Sl. No. Annual Income (Rs.) Frequency Percentage
1 Up to Rs. 50,000 27 16.87
2 Rs. 50,001 to Rs. 1,00,000 75 46.88
3 Rs. 1,00,001 to Rs. 2,00,000 36 22.50
4 Above Rs. 2,00,000 22 13.75
4.1.2.5 Credit Acquisition
The findings regarding credit acquisition are presented in Table 4.6. The
data reveals that the maximum respondents (91.87%) had acquired credit and 8.13
per cent of respondents had not acquired credit.
Out of total credit acquired respondents, 68.03 per cent respondents had
taken credit from cooperative society, 14.29 per cent from regional rural bank,
9.52 per cent from money lender and 8.16 per cent of respondents had taken credit
from friends, neighbours and relatives.
As regards to duration of credit, the most (70.75%) of the respondents had
taken loan 6-12 month, 20.41 per cent of respondents had taken loan up to 6
month and 8.84 per cent of respondents has taken credit for above 12 month.
Regarding amount of credit it was found that most of the respondents
(56.46%) had obtained credit Rs.10,001 – 20,000, while 40.82 per cent of the
respondents had taken credit up to Rs. 10,000 and 2.72 per cent respondents had
taken above Rs. 20,000, respectively.
47
Fig. 4.4 Distribution of respondents according to their annual family income
16.87
46.88
22.5
13.75
0
5
10
15
20
25
30
35
40
45
50
Up to Rs. 50,000 Rs. 50,001 to Rs. 1,00,000 Rs. 1,00,001 to Rs. 2,00,000 Above Rs. 2,00,000
Per
cen
tage
of
resp
on
den
ts
Categories
Annual income
48
Table 4.6: Distribution of the respondents according to their credit acquisition
Sl. No. Particulars Frequency Percentage
1 Credit acquired
Acquired 147 91.87
Not acquired 13 08.13
2 Source of credit (n=147)
Cooperative society 100 68.03
Regional rural bank 21 14.29
Money lender 14 9.52
Friends & Neighbours and Relatives 12 8.16
3 Duration of credit (n=147)
Up to 6 months 30 20.41
6-12 months 104 70.75
Above 12 months 13 8.84
4 Amount of credit (n=147)
Up to Rs. 10000 60 40.82
Rs. 10,001 – Rs. 20,000 83 56.46
Above Rs. 20,000 04 2.72
4.1.2.6 Variety
The data are presented in Table 4.7. That local variety of maize were grown
by only 6.25 per cent of the respondents in the study area. About improved
varieties, kanchan was most popular variety grown by 34.37 per cent of the
respondents. Similarly, about 47 per cent of the respondents were growing DMH-
8255 (hybrid variety). N.K.-30, Vikram, Saktiman and Ganga saphed etc. hybrid
varieties were also cultivated by same of the respondents in the study area.
49
Table 4.7: Distribution of respondents according to their variety wise cultivation of
maize crop
Sl. No. Varieties Frequency* Percentage
1 Local varieties 10 6.25
2 Improved varieties
Kanchan 55 34.37
Amber 19 11.87
3 Hybrid varieties
DMH-8255 75 46.87
N.K.-30 46 28.75
Vikram 20 12.50
Saktiman 16 10
Ganga saphed 14 8.75
*Data are based on multiple responses
4.1.2.7 Benefit-cost ratio
The benefit- cost ratio (BCR) is 1.70 of maize crop.
Table 4.8: Benefit-cost analysis of maize crop
Income from maize production
Average yield of maize (grain) per ha = 22.53 q
Value of maize @ Rs. 1365 per q. (According
to MSP in year 2016)
= Rs. 30753.45
Income of by product (green fodder) in maize = Rs. 800
Gross income (Rs./ha) = Rs.31553.45
Average cost of cultivation (Rs./ha) = Rs. 18500.40
BCR = 1.70
4.1.2.8 Domestic Consumption
Domestic consumptions of maize by tribal families is very important, Table
4.9 shows that cent per cent respondents were maize used as corn (cob), followed
by 32.50 per cent, 22.50 per cent and 21.87 per cent were used as popcorn, grain
feeding to animals and roti/chapatti, respectively. (Fig. 4.5)
50
Fig. 4.5 Distribution of respondents according to their domestic consumption of maize
100
32.5
21.87 22.5
0
20
40
60
80
100
120
Corn(cob) Popcorn Rotti/ chapatti Grain feeding to animals
Per
cen
tage
Categories
Domestic consumption
51
Table 4.9: Distribution of respondents according to their domestic consumption of
maize
Sl. No. Product Frequency* Percentage
1 Corn(cob) 160 100
2 Popcorn 52 32.50
3 Rotti/ chapatti 35 21.87
4 Grain feeding to animals 36 22.50
*Data are based on multiple responses
4.1.3 Socio psychological characteristics of the respondents
4.1.3.1 Scientific orientation
Regarding scientific orientation among the respondents data compiled in
Table 4.10, depicts that 79.38 per cent respondents were medium level (23 to 25
score) of scientific orientation, followed by 11.25 per cent respondents had high
level (above 25 score) of scientific orientation and only about 9.37 per cent
respondents were low level (less than 22 score) of scientific orientation.
Table 4.10: Distribution of respondents according to their scientific orientation
Sl. No. Level of scientific orientation Frequency Percentage
1 Low level (up to 22 Score) 15 9.37
2 Medium level ( 23 to 25 Score) 127 79.38
3 High level (above 25 Score ) 18 11.25
X=23.39, S.D.=1.78
4.1.3.2 Level of knowledge about recommended Maize production technology
The finding of Table 4.11 and Fig, 4.6, reveals the respondents were having
level of knowledge regarding selected practices of maize production technology.
About, 60.62 per cent respondents had low level of knowledge about
disease management, followed by storage (59.38%), insect management (53.75%),
seed treatment (51.25%), manure (45%), weed control (40%), spacing (20%),
fertilizer (18.75%), seed rate (15.62%), time of sowing (14.38%), irrigation &
drainage (12.50%), method of sowing and time of harvesting & cutting both
(10%), preparation of land (9.38%), selection of improved varieties (6.25%).
With respect to medium level of knowledge selection of improved varieties
(51.88%), followed by time of harvesting & cutting (50%), method of sowing
52
(48.13%), spacing (46.25%), seed rate, fertilizer and weed management (45%),
preparation of land and irrigation & drainage (41.87%), time of sowing (40.62%),
seed treatment (40%), insect management (37.50%), manure (35%) and disease
management and storage both (30%), respectively.
Maximum respondents (48.75%) had high level of knowledge regarding
preparation of land, followed by irrigation & drainage (45.63%), time of sowing
(45%), selection of improved varieties and method of sowing (41.87%), time of
harvesting & cutting (40%), seed rate (39.38), fertilizer (36.25%), spacing
(33.75%), manure (20%), weed management (15%), storage (10.62%), disease
management (9.38%), seed treatment and insect management both 8.75 per cent
respondent had high level of knowledge.
Table 4.11: Distribution of respondents according to their practices wise level of
knowledge regarding maize production technology
Sl.
No.
Practices Level of knowledge
Low Medium High
F (%) F (%) F (%)
1 Preparation of land 15 (9.38) 67 (41.87) 78 (48.75)
2 Time of sowing 23 (14.38) 65 (40.62) 72 (45.00)
3 Selection of improved
varieties
10 (6.25) 83 (51.88) 67 (41.87)
4 Seed rate(kg/ha) 25 (15.62) 72 (45.00) 63 (39.38)
5 Method of sowing 16 (10.00) 77 (48.13) 67 (41.87)
6 Seed treatment 82 (51.25) 64 (40.00) 14 (8.75)
7 Spacing 32 (20.00) 74 (46.25) 54 (33.75)
8 Manure (tonne/ha) 72 (45.00) 56 (35.00) 32 (20.00)
9 Fertilizer (kg/ha) 30 (18.75) 72 (45.00) 58 (36.25)
10 Irrigation & Drainage 20 (12.50) 67 (41.87) 73 (45.63)
11 Weed management 64 (40.00) 72 (45.00) 24 (15.00)
12 Insect management 86 (53.75) 60 (37.50) 14 (8.75)
13 Disease management 97 (60.62) 48 (30.00) 15 (9.38)
14 Time of harvesting &
cutting
16 (10.00) 80 (50.00) 64 (40.00)
15 Storage 95 (59.38) 48 (30.00) 17 (10.62)
F=Frequency, %=Percentage
53
The data presented in Table 4.12 indicates that the majority of the
respondents (38.12%) had medium level of knowledge regarding recommended
maize production technology, whereas 29.38 per cent and 32.50 per cent
respondents were having high and low level of knowledge respectively.
Table 4.12: Distribution of respondents according to their overall level of
knowledge regarding maize production technology
Sl. No. Level of knowledge Frequency Percentage
1 Low (up to 13 score) 52 32.50
2 Medium (14 – 18 score) 61 38.12
3 High (above 18 score) 47 29.38
X= 15.52, S.D. = 3.08
54
Fig. 4.6 Distribution of respondents according to their practices wise level of knowledge regarding maize production technology
0
10
20
30
40
50
60
70
Per
cen
tage
Practices
Knowledge level
55
4.1.4 Communicational characteristics of the respondents
4.1.4.1 Sources of information
All the possible sources of information were selected, identified and
presented in Table 4.13. The finding reveals that in the study area, RAEO/SADO
ranked first being utilized by 71.87 per cent of respondents. The study also reveals
that 53.13 per cent of the respondents had obtained the information from
progressive farmers, followed by 34.37 per cent of respondents obtained the
information from friends, relatives (28.12%), neighbours (25.00%), T.V. (18.75%),
agricultural magazines (15.62%), news papers (12.50%) were other popular
sources of information. (Fig. 4.7) In addition to above, some other sources of
information like both panchayat leaders, farmers faire (7.50%), (KCC) kishan call
centers (1.88%), both (KVK) krishi vigyan kendra and agricultural scientists
(1.25%) were also utilized by the respondents for receiving the information about
maize production in study area.
Table 4.13: Distribution of respondents according to their sources of information
Sl. No. Use of different information sources Frequency* Percentage Rank
1 Friends 55 34.37 III
2 Relatives 45 28.12 IV
3 Neighbours 40 25.00 V
4 Panchayat leaders 12 7.50 IX
5 Progressive farmers 85 53.13 II
6 RAEO/SADO 115 71.87 I
7 News papers 20 12.50 VIII
8 Agricultural magazines 25 15.62 VII
9 Radio 10 6.25 X
10 T.V. 30 18.75 VI
11 Farmers faire 12 7.50 IX
12 KVK(krishi vigyan Kendra) 2 1.25 XII
13 KCC(kishan call centers) 3 1.88 XI
14 Agricultural scientists 2 1.25 XII
*Data are based on multiple responses
56
Fig. 4.7 Distribution of respondents according to their sources of information
0
10
20
30
40
50
60
70
80
34.3728.12 25
7.5
53.13
71.87
12.5 15.626.25
18.757.5
1.25 1.88 1.25
Per
centa
ge
Particulars
Sources of information
57
Data regarding number of information sources being utilized by the
respondents was recorded and presented in Table 4.14. The data reveals that the
majority (54.37%) of respondents were utilizing 4-6 sources of information,
followed by 29.38 per cent of the respondents were utilizing 1-3 sources of
information and only 16.25 per cent of the respondents were utilizing more than 6
information sources.
Table 4.14: Distribution of respondents according to utilization of number of
information sources
Sl. No. Use of information Frequency Percentage
1 Low utilization (up to 3 sources) 47 29.38
2 Medium utilization (4-6 sources) 87 54.37
3 High utilization (above 6 sources) 26 16.25
X= 4.50, S.D.=1.44
4.1.5 Marketing practices
4.1.5.1 Marketing channel
A marketing channel is the people, organizations and activities necessary to
transfer the ownership of goods from the point of production to the point of
consumption. Data regarding marketing channel of maize are presented in Table
4.15. Regarding marketing channel of cob, most of the respondents (30%) had
taken produce to market, 25 per cent producers sold it to whole sale market. As
grain most of the respondents (71.87%) sold it to shopkeeper, 6.25 per cent of
respondents sold through krishi upaj mandi and only 2.50 per cent of respondents
had taken as a green leaf fodder producer to dairy farm. (Fig. 4.8)
Table 4.15: Distribution of respondents according to their marketing channel
of maize
Sl. No. Channel Frequency* Percentage
1 Producer to whole sale market (cob) 40 25.00
2 Producer to market (cob) 48 30.00
3 Producer to krishi upaj mandi (grain) 10 6.25
4 Producer to shopkeeper (grain) 115 71.87
5 Producer to dairy farm (green leafs fodder) 04 2.50
*Data are based on multiple responses
58
Fig. 4.8 Distribution of respondents according to their marketing channel of maize
2530
6.25
71.87
2.5
0
10
20
30
40
50
60
70
80
Producer to whole sale
market (cob)
Producer to market
(cob)
Producer to krishi upaj
mandi (grain)
Producer to
shopkeeper (grain)
Producer to dairy farm
(green leafs fodder)
Per
cen
tage
Categories
Marketing channel
59
4.1.5.2 Mode of marketing
The data regarding mode of marketing of maize crop are presented in Table
4.16. The result reveals that the maximum (78.12%) of the respondents had
marketing as a grain, where as 48.75 per cent respondents as cob and only 2.50 per
cent were of marketing as a green leafs fodder. (Fig. 4.9)
Table 4.16: Distribution of respondents according to their mode of marketing of
maize
Sl. No. Product Frequency* Percentage
1 Corn(cob) 78 48.75
2 Grain 125 78.12
3 Green leafs fodder 04 2.50
*Data are based on multiple responses
4.2 Dependent variables
4.2.1 Extent of adoption of maize production technology
Data are presented in Table 4.17, shows that among the 15 selected
practices wise of maize production technology, all the respondents had the extent
of adoption under level of adoption category as follows: (Fig. 4.10)
Maximum respondents (68.12%) of the had low level of adoption regarding
storage, followed by disease management (67.50%), seed treatment (63.12%),
insect management (57.50%), manures (55.00%), weed management (48.13%),
spacing (28.75%), irrigation & drainage (26.87%), time of sowing (25.62%),
fertilizer (25%), preparation of land (24.38%), seed rate (22.50%), method of
sowing (21.88%) and selection of improved varieties (12.50%), respectively.
While under medium level of adoption categories, it was found that
maximum respondents (47.50%) had of adoption towards selection of improved
varieties, followed by method of sowing (44.37%), seed rate (42.50%), weed
management (41.87%), spacing (40.63%), fertilizer (39.38%), both time of sowing
and irrigation & drainage (38.13%), insect management (35.63%), preparation of
land (34.37%), time of harvesting and cutting (31.88%), seed treatment (30.63%),
disease management (25%), storage (23.75%), respectively.
Whereas under high level had the extent of adoption category, maximum
60
Fig. 4.9 Distribution of respondents according to their mode of marketing of maize
Corn(cob) Grain Green leafs fodder
48.75%
78.12%
2.5%
Mode of marketing
61
respondents (41.25%) of the about preparation of land, selection of improved
varieties (40%), time of sowing (36.25%), fertilizer (35.62%), seed rate and
drainage & irrigation (35%), method of sowing (33.75%), spacing and time of
harvesting & cutting (30.62%), manure (15.62%), weed management (10%),
storage (8.13%), disease management (7.50%), insect management (6.87%), seed
treatment (6.25%), respectively.
Table 4.17: Distribution of respondents according to their practices wise extent of
adoption regarding maize production technology
Sl.
No.
Practices Extent of adoption
Low Medium High
F (%) F (%) F (%)
1 Preparation of land 39 (24.38) 55 (34.37) 66 (41.25)
2 Time of sowing 41 (25.62) 61 (38.13) 58 (36.25)
3 Selection of
improved varieties
20 (12.50) 76 (47.50) 64 (40.00)
4 Seed rate(kg/ha) 36 (22.50) 68 (42.50) 56 (35.00)
5 Method of sowing 35 (21.88) 71 (44.37) 54 (33.75)
6 Seed treatment 101 (63.12) 49 (30.63) 10 (6.25)
7 Spacing 46 (28.75) 65 (40.63) 49 (30.62)
8 Manure (tonne/ha) 88 (55.00) 47 (29.38) 25 (15.62)
9 Fertilizer (kg/ha) 40 (25.00) 63 (39.38) 57 (35.62)
10 Irrigation & drainage 43 (26.87) 61 (38.13) 56 (35.00)
11 Weed management 77 (48.13) 67 (41.87) 16 (10.00)
12 Insect management 92 (57.50) 57 (35.63) 11 (6.87)
13 Disease management 108 (67.50) 40 (25.00) 12 (7.50)
14 Time of harvesting
& cutting
60 (37.50) 51 (31.88) 49 (30.62)
15 Storage 109 (68.12) 38 (23.75) 13 (8.13)
F= Frequency, %=Percentage
62
Fig.4.10 Distribution of respondents according to their practices wise extent of adoption regarding maize production technology
0
10
20
30
40
50
60
70
Per
cen
tage
Practices
Adoption level
63
It is clearly indicated from the Table 4.18, that 51.25 per cent respondents
had medium level of adoption about maize production technology, whereas 26.25
and 22.50 per cent of them having high and low level of adoption respectively.
Table 4.18: Distribution of respondents according to their overall extent of
adoption regarding maize production technology
Sl. No. Extent of adoption Frequency Percentage
1 Low (up to 10 score) 36 22.50
2 Medium (11 – 17 score) 82 51.25
3 High (above 17 score) 42 26.25
X= 14.15, S.D. = 3.68
4.2.2 Productivity
The data regarding total production and productivity of maize crop in study
area presented in Table 4.19. In year 2015-16, reveal that the maximum
respondents (50%) their productivity (21-25 q), followed by 37.50 per cent of
respondents had productivity (16-20 q), while 6.25 per cent the respondents had
productivity (up to 15 q), were 3.75 per cent of respondents of productivity (26-30
q) and only 2.50 per cent of respondents productivity of the more than (30 q).
Farmers had total production of 2175.54 q, in total cultivated area in maize
96.56 ha and average productivity 22.53 q/ha of respondents.
Table 4.19: Distribution of respondents according to their production and
productivity of maize crop in study area
Productivity (grain) Frequency Percentage
Up to 15 q/ha 10 6.25
16-20 q/ha 60 37.50
21-25 q/ha 80 50
26-30 q/ha 6 3.75
More than 30 q/ha 4 2.50
Total Production (in q) 2175.54
Total Area (in ha) 96.56
Average Productivity (q/ha) 22.53
64
4.3 Correlation analysis of independent variables with adoption of
recommended maize production technology by the maize growers
Correlation coefficient between the selected characteristics of the
respondents with adoption of recommended maize production technology among
maize growers was also worked out and the values of correlation coefficient are
presented in Table 4.20.
Table 4.20: Correlation analysis of independent variables with extent of
adoption regarding maize production technology
Sl. Independent variables
No.
Correlation coefficient (r)
Adoption
1 Age 0.069NS
2 Education 0.220**
3 Family size 0.273**
4 Social participation 0.154*
5 Farming experience 0.315**
6 Source of information 0.013NS
7 Land holding 0.168*
8 Irrigation facility 0.044NS
9 Occupation 0.270**
10 Annual income 0.209**
11 Credit acquisition 0.397**
12 Marketing channel 0.116NS
13 Mode of marketing 0.715**
14 Domestic consumption 0.571**
15 Benefit-cost ratio 0.331**
16 Scientific orientation 0.256**
17 Knowledge level 0.805**
** Significant at 0.01 level of probability (“r” value = 0.202)
*Significant at 0.05 level of probability (“r” value = 0.154)
NS= Non Significant
It can be seen from the table that out of all selected characteristics viz.
education, family size, farming experience, occupation, annual income, credit
65
acquisition, mode of marketing, domestic consumption, benefit-cost ratio,
scientific orientation, level of knowledge were found to be positive and highly
significant correlated with the adoption at 0.01 level of probability.
Whereas, the variables like social participation, land holding were found to
be positively and significantly correlated with the adoption 0.05 level of
significance.
The other variables age, source of information, irrigation facility and
marketing channel showed non- significant correlation with the extent of adoption
of recommended maize production technology.
4.4 Multiple regression analysis of independent variables with adoption of
recommended maize production technology by the maize growers
The result of regression analysis is presented in Table 4.21. The result of
multiple regression analysis is revealed that independent variables viz. education,
farming experience, land holding, mode of marketing, benefit-cost ratio,
knowledge level contributed highly significant at 0.01 per cent level of probability,
whereas social participation, domestic consumption were found significantly with
adoption at 0.05 per cent level of significance and remaining variables viz. age,
family size, source of information, irrigation facility, occupation, annual income,
credit acquisition, marketing channel and scientific orientation did not indicate any
significant contribution to the adoption of recommended maize production
technology.
66
Table 4.21: Multiple regression of independent variables with extent of
adoption of maize production technology
Sl. Independent variables
No.
Regression
coefficient “b” value
“t” value
1 Age 0.441NS 0.772
2 Education 2.361** 1.675
3 Family size 0.736NS 0.462
4 Social participation 1.981* 0.927
5 Farming experience 2.688** 0.356
6 Source of information 0.577NS 0.648
7 Land holding 2.601** 0.352
8 Irrigation facility 1.015NS 0.291
9 Occupation 0.903NS 0.337
10 Annual income 0.284NS 1.075
11 Credit acquisition 0.680NS 0.497
12 Marketing channel 0.943NS 0.070
13 Mode of marketing 4.871** 2.182
14 Domestic consumption 1.998* 1.98
15 Benefit- cost ratio 8.290** 3.289
16 Scientific orientation 1.265NS 0.216
17 Knowledge level 6.151** 3.444
** Significant at 0.01 level of probability (“t” value= 2.607)
*Significant at 0.05 level of probability (“t” value= 1.975)
NS = Non Significant
𝑅2 = 0.591
F value of R = 13.254
67
4.5 Constraints faced by the maize growers in adoption of recommended
maize production technology
Multiple responses were taken to ascertain the constraints faced by the
maize growers in adoption of recommended maize production technology. Various
constraints are presented in Table 4.22, which indicates that under the constraints.
Table 4.22: Constraints faced by the maize growers in adoption of recommended
maize production technology and marketing
Sl. No. Constraints F* % Rank
1 Low level of education 14 8.75 X
2 Lack of knowledge and non- availability of
improved variety at appropriate time
60 37.50 III
3 Lack of knowledge about recommended
fertilizer dose and accurate time for
application of fertilizer
07 4.37 XI
4 Non- availability of fertilizer at appropriate
time
50 31.25 IV
5 Lack of knowledge about pesticides and
herbicides and its accurate quantity for
application
69 43.12 I
6 Lack of irrigation facility 64 40.00 II
7 Lack of training on maize cultivation 40 25.00 V
8 Lack of marketing place for more quantity of
product
25 15.62 VII
9 Non availability of information in proper
time
36 22.50 VI
10 Lack of motivation 15 9.37 IX
11 Labour problems 24 15.00 VIII
*Data are based on multiple responses, F= Frequency, %= Percentage
Maximum respondents (43.12%) were reported that, lack of knowledge
about pesticides and herbicides and its accurate quantity for application, followed
by 40 per cent respondents were lack of irrigation facility, lack of knowledge and
non- availability of hybrid variety at appropriate time (37.50%), non- availability
of fertilizer at appropriate time (31.25%), lack of training on maize cultivation
(25%), non availability of information in proper time (22.50%), lack of marketing
place for more quantity of product (15.62%), labour problems (15%), lack of
motivation (9.37%), low level of education (8.75%) and that lack of knowledge
68
about recommended fertilizer dose and accurate time for application of fertilizer
(4.37%).
4.6 Suggestions from the maize growers for increasing the adoption of
recommended maize production technology
It was found from the data presented in Table 4.23, that majority of the
respondents (56.25%) suggested that the protection method and materials during
cob formation against birds and animals should be available, followed by 51.25
per cent respondents suggested that the irrigation facility should be available, while
50.62 per cent respondents suggested knowledge about accurate quantity & time of
fertilizer application is needed, knowledge about pesticides and herbicides is
needed (30.32%), information and seed should be provided about hybrid variety at
appropriate time (30.00%), extension agent should convey information about
maize production technology at regular basis (28.75%), subsidies should be
increased on fertilizer and seed of hybrid variety (25.62%), training should be
organized on maize production technology (25%), Minimum Support Price of
maize should be increased (23.75%), infrastructure facilities such as road,
transportation etc. should be increased for marketing (15%) were the major
suggestions suggested by the respondents for improvement of adoption regarding
recommended maize production technology.
69
Table 4.23: Suggestions given by maize growers for solving the constraints
faced by them during the adoption of recommended maize production
technology and marketing
Sl. No. Suggestions F* % Rank
1 Information and seed should be provided
about hybrid variety at appropriate time
48 30.00 V
2 Extension agent should convey information
about maize production technology at regular
basis
46 28.75 VI
3 Protection method and materials during cob
formation against birds and animals should
be available
90 56.25 I
4 Knowledge about accurate quantity & time
of fertilizer application is needed
81 50.62 III
5 Knowledge about pesticides and herbicides
is required
49 30.32 IV
6 Training should be organized on maize
production technology
40 25.00 VIII
7 Irrigation facility should be available 82 51.25 II
8 Subsidies should be increased on fertilizer
and seed of hybrid variety
41 25.62 VII
9 Minimum Support Price of maize should be
increased
38 23.75 IX
10 Infrastructure facilities such as road,
transportation etc. should be increased for
marketing
24 15.00 X
*Data are based on multiple responses, F= Frequency, %= Percentage
70
CHAPTER – V
SUMMARY AND CONCLUSIONS
The main purpose of this chapter is to summarize the results and to state the
conclusions on the basis of the fore going analysis and to indicate some of their
implications for actions.
The present research entitled “A study on production, consumption and
marketing pattern of maize among the tribal farmers of Surguja district of
Chhattisgarh” was carried out during 2016-17 in the Indira Gandhi Krishi
Vishwavidyalaya, Raipur, (C.G.) with following objectives:
1. To study the socio economic profile of tribal maize growing farm family.
2. To study the extent of adoption of maize cultivation practices by the tribal
farmers.
3. To analyses the consumption and marketing pattern of maize among tribal
families.
4. To identify the constraints faced by tribal farmers in production and
marketing of maize and obtain their suggestions to overcome the
constraints.
Agriculture plays an important role in India’s economy. Since the
independence, India has made great achievements in agriculture i.e. from import
food grains to self sufficiency and export of major agricultural commodities with a
contribution of 17.6 per cent to nations GDP (2015-16). Maize is one of the most
important cereal crops. In India, maize is cultivated in about 6 million ha with
production ranging between 7-10 million tones. As it has yield potential far higher
than any other cereal, it is sometimes referred to as the miracle crop or the ‘Queen
of Cereals’.
In Chhattisgarh state, maize is the second important crop next to paddy of
food grain production. Maize crop is cultivated in Chhattisgarh in 71.75 mha area
& production 134.16 mt and its productivity is 1886 kg/ha. Annual rainfall of CG
in average 1200-1400 mm. Coupled with 137 per cent cropping intensity.
Surguja district of Chhattisgarh state is most maize growing areas. Surguja
district in total maize cultivated areas 0.40 mha & production 0.72 mt and it’s a
productivity is 1806 kg/ha.
71
Methodology
The study was carried out during 2016-17 in the 4 selected blocks of
Surguja district. 16 villages were randomly selected and data were collected
through personal interview method from 160 respondents. Collected data were
analyzed by using appropriate statistical methods viz. mean, percentage, S.D.,
correlation and multiple regressions etc.
The major findings of this study are summarized as follow:
Independent variables included in the study were socio personal (age,
education, family size, social participation, farming experience), socio economic
(land holding, irrigation facility, occupation, annual family income, credit
acquisition, benefit-cost ratio, domestic consumption), socio psychological
(scientific orientation, knowledge level about maize production technology),
communicational (source of information), marketing (marketing channel, mode of
marketing) and extent of adoption of maize production technology and
productivity of maize crop was considered as dependent variable for this study.
The data were collected through personal interview and analyzed with appropriate
statistical methods.
1. Independent variables
Socio personal characteristics of the respondents
The majority (52.50%) of the respondents were found in middle age group
(36 to 55 years). The maximum respondents (27.50%) were found to be educated
middle school, followed by 23.75 per cent of the respondents educated primary
school, whereas 8.75 per cent respondents were illiterate, 2.50 per cent respondents
were graduation and above level of education. 62.50 per cent respondents had
medium size of family (6 to10) members. The maximum respondents (63.12%)
had membership in one organization. Experience of maize cultivation is 11-20
years of respondents (53.75%).
Socio economic characteristics of the respondents
The maximum respondents (35.62%) had marginal farmers, size of land
holding (up to 1 ha). Maximum respondents (60.44%) were having tube-wells for
irrigation. Agriculture was found to be their main occupation. The maximum
respondents (46.88%) were having annual income Rs. 50,001 to Rs. 1,00,000.
72
Maximum respondents (68.03%) had taken loan from cooperative society. About
cultivation of maize most of the respondents (46.87%) of hybrid variety (DMH-
8255). The benefit-cost ratio is 1.70 of maize crop. The cent per cent of the
respondent’s used corn (cob) for domestic consumption.
Socio psychological characteristics of the respondents
Majority of the respondents (79.38%) were having medium level of
scientific orientation. In case of practice wise level of knowledge, majority of the
respondents (60.62%) had low level of knowledge about disease management.
Maximum respondents (51.88%) were having medium knowledge about selection
of improved varieties. Similarly, 48.75 and 45.63 per cent of the respondents were
having high knowledge about land preparation and irrigation & drainage practices,
respectively. In case of overall level of knowledge about maize production
technology, 38.12, 32.50 and 29.38 per cent respondents were found under
medium, low and high category, respectively.
Communicational characteristics of the respondents
As a regards to use of information sources, maximum respondents
(71.87%) were receiving by RAEO/SADO, followed by progressive farmers
(53.13%), friends (34.37%). Overall use of communication sources the majority of
the respondents (54.37%) were utilized medium level of information sources.
Marketing practices of the respondents
The maximum respondents (71.87%) had use of marketing channel as
shopkeeper. The majority respondents (78.12%) of marketing as a grain in product
of maize.
2. Dependent variables
In case of practice wise adoption of maize production technology,
maximum respondents (68.12%) had low level of adoption of storage. Maximum
respondents (51.88%) were found of medium level of adoption toward selection of
improved varieties. Similarly, high levels of adoption were found about land
preparation (41.25%). About 51 per cent respondents were having medium level of
overall adoption.
Maize crop amongst respondents’ total production was recorded as 2175.54
q and average productivity 22.53 q/ha.
73
Correlation and multiple regression analysis
In correlation analysis, the finding revealed that out of 17 independent
variables, 13 variables i.e. education, family size, social participation, farming
experience, land holding, occupation, annual income, credit acquisition, mode of
marketing, domestic consumption, benefit- cost ratio, scientific orientation, level of
knowledge were found to be positive and significantly correlated with extent of
adoption of recommended maize production technology, at 0.01 and 0.05 level of
probability. Other variables viz. age, source of information, irrigation facility and
marketing channel were having non-significant correlation with the extent of
adoption of recommended maize production technology. In multiple regression
analysis, out of 17 independent variables, 8 variables viz. education, social
participation, farming experience, land holding, mode of marketing, domestic
consumption, benefit-cost ratio, knowledge level had positive and significant
contribution to the adoption of recommended maize production technology and
remaining 9 variables viz. age, family size, sources of information, irrigation
facility, occupation, annual income, credit acquisition, marketing channel,
scientific orientation did not indicate any significant contribution to the adoption of
recommended maize production technology.
Constraints
Constraints faced by maximum respondents (43.12%) were reported that,
lack of knowledge about pesticides and herbicides and its accurate quantity for
application, followed by 40 per cent respondents were lack of irrigation facility,
lack of knowledge and non- availability of hybrid variety at appropriate time
(37.50%), non- availability of fertilizer at appropriate time (31.25%), lack of
training on maize cultivation (25%), non availability of information in proper time
(22.50%), lack of marketing place for more quantity of product (15.62%), labour
problems (15%), lack of motivation (9.37%), low level of education (8.75%) and
that lack of knowledge about recommended fertilizer dose and accurate time for
application of fertilizer (4.37%).
Suggestions
The major suggestions, the majority of the respondents (56.25%) suggested
that the protection method and materials during cob formation against birds and
74
animals should be available, followed by 51.25 per cent respondents suggested that
the irrigation facility should be available, while 50.62 per cent respondents
suggested knowledge about accurate quantity & time of fertilizer application is
needed, knowledge about pesticides and herbicides is needed (30.32%),
information and seed should be provided about hybrid variety at appropriate time
(30.00%), extension agent should convey information about maize production
technology at regular basis (28.75%), subsidies should be increased on fertilizer
and seed of hybrid variety (25.62%), training should be organized on maize
production technology (25%), Minimum Support Price of maize should be
increased (23.75%), infrastructure facilities such as road, transportation etc. should
be increased for marketing (15%) were the major suggestions suggested by the
respondents for improvement of adoption regarding recommended maize
production technology.
Conclusion
The finding of the study is indicated that most of the maize growers were in
middle age category with respect to their extent of adoption regarding
recommended maize production technology. Thus, there is an urgent need
to increase the extent of adoption of maize growers about recommended
maize production technology, through proper utilization of source of
information, exhibition, kishan mela and training programmes in different
aspects of maize production technology.
Majority of the maize growers were having medium level of knowledge
regarding recommended maize production technology. Hence, extension
efforts should be made to increase the level of knowledge of maize growers
about recommended maize production technology by use of suitable mass
media like T.V., radio, news papers etc.
Farmers had total production of 2175.54 q and total cultivated area in
maize 96.56 ha and average productivity 22.53 q/ha of respondents in
study areas.
There is an urgent need to increase their education level and knowledge
level through training, demonstrations, field trips and proper guidance. By
conducting demonstration on use of various practices of maize crop may
75
help to change the attitude of maize growers and also convince them and
help in promoting the extent of adoption of maize production technology.
Suggestions for future research work
The independent variables selected for the studies were socio personal,
socio economic, socio psychological, communicational characteristics and
marketing practices. The attributes that are considered for study may be limited to
determine the extent of adoption of maize growers regarding recommended maize
production technology. Hence, some additional attributes may be added to make
the study more comprehensive. There is a wide scope for the study of
psychological and socio-economic characteristics of the respondents. Few
researches are available on this aspect. Hence, deeper probe into the matter is
needed by Agricultural University and Department of Agriculture should evaluate
various reasons for non adoption of various practices of maize production
technology by considering the feedback of maize growers. In this regard, further
more research studies are needed.
76
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87
APPENDIX- A
d`f’k foLrkj foHkkx
bafnjk xka/kh df’k fo”ofo|ky;] jk;iqj] ¼N-x-½
^^NŸkhlx<+ jkT; ds ljxqtk ftys esa tutkrh; d’kdksa }kjk eDdk mRiknu] miHkksx ,oa
foi.ku i)fr dk v/;;u^^
Lkk{kkRdkj iz”ukoyh
iz”ukoyh Øa---------------- fnukad -------------------
ijke”kZnkrk “kks/kdrkZ
Jh ih-ds- lkaxksMs+ x.ks”k dqekj
Lkgk- izk/;kid ,e-,l-lh-¼df’k½ vafre o’kZ
df’k foLrkj foHkkx df’k foLrkj foHkkx
df’k egkfo|ky;] jk;iqj ¼N-x-½ df’k egkfo|ky;] jk;iqj ¼N-x-½
1- lekU; ifjp; %&
1- d’kd dk uke &---------------------------------------------------- 2- xzke & --------------------
3- fodkl [k.M &---------------------------------------------------- 4- ftyk & --------------------
5- mez &------------------------------------------------------- 6- mitkfr & --------------------
8- f”k{kk dk Lrj &1-vf”kf{kr] 2-izkFkfed] 3-ek/;fed] 4-gkbZ Ldwy] 5-mPprj ek/;fed] 6-LUkkrd o
vf/kd
2- vkids ifjokj ds lnL;ksa dh la[;k %&
Ø- LknL; Lak[;k
1- iq:’k
2- Efgyk
3- cPpsa
4- ;ksx
3- vkids xzke esa dkSu&dkSu lh laLFkk,¡@laxBu gS rFkk mlesa viuh lgHkkfxrk ds ckjs esa fuEu tkudkfj;k¡
nhft;s %&
Ø- xzkeh.k laLFkk,¡@laxBu ¼gkW@ugh½ lnL;rk
1- xzke iapk;r
2- lgdkjh lfefr
3- ;wok e.My
4- lkaLdfrd eap
88
5- vkaxu ckM+h
6- Ldwy
7- izkFkfed LoLFk; dsUnz
8- vU; 1------------------------------
2------------------------------------
4- vkidk eq[; O;olk;@lgk;d O;olk; ls lacaf/kr fUkEu tkudkfj;k¡ nhft;s &
Ø- O;olk; gkW@ugha
1 df’k
2- Ektnwjh
3- Ik”kqikyu
4- O;kikj
s5- ukSdjh
6- vU; 1---------------------
2---------------------------
5- vkidk fofHkU; L=ksarksa ls dqy okf’kZd vk; fdruh gS] di;k tkudkjh nhft;saA
Ø- O;olk; okf’kZd vk; ¼:i;s esa½
1- df’k
2- Ektnwjh
3- Ik”kqikyu
4- O;kikj
5- ukSdjh
6- vU; 1---------------------------------
2-------------------------------------
7- dqy okf’kZd vk; ¼:i;s esa½
6- di;k Hkwfe dh tkudkjh nhft;s & ¼dqy Hkwfe ---------- gs-½
Ø- Hkwfe flafpr Hkwfe ¼g-sa½ vflafpr Hkwfe ¼g-sa½ dqy Hkwfe ¼gsa-½
1- df’k ;ksX; Hkwfe
2- yht esa yh xbZ Hkwfe
89
7- vkids ikl flapkbZ ds dkSu&dkSu ls lk/ku gS %&
Ø- flapkbZ ds lk/ku flapkbZ miyC/krk dqy flafpr {ks= ¼gsa-½
[kjhQ jch Tkk;n
1 dqvk¡
2 V~;wosy
3 ugj @cak/k
4 unh
5 ukyk
6 rkykc
7 vU; 1------------
2----------------
8- D;k vkius df’k mRiknu ds fy;s _.k fy;k gS\ gka@ugha ;fn gkW rks crkb;s fdu&fdu L=ksrksa ls _.k
izkIr fd;k gS %&
9- di;k eDdk Qly ds ckjs esa tkudkjh nhft;s %&
Qly dk uke
{ks=Qy ¼gs-½
flafpr vflafpr dqy
{ks= mit {ks= mit {ks= mit
eDdk
ns”kh fdLe
mUur fdLe
gkbZfczM fdLe
10- vkids }kjk eDdk dh [ksrh fdruss o’kksZ ls dh tk jgh gS--------------------------------------------
Ø- L=ksr gka@ugha jkf”k _.k dh vof/k
1- Lkgdkjh laLFkk,¡
2- {ks=h; xzkeh.k cSad
3- Lkkgwdkj
4- fe=
5- iM+kslh
6- fj”rsnkj
7- vU; 1--------------
90
11- d`i;k eDdk dh mRiknu ds ckjs es crk;s&
Ø mRikn mRiknu ¼fDaoVy½ dqy mRiknu
¼fDaoVy½ flafpr vflafpr
1- nkuk@vukt 2- HkwV~Vk
3- gjk&pkjk
4- vU; 1-------------------- 2-----------------
12- vkidks eDdk mRiknu ls lacaf/kr tkudkjh fdu&fdu L=ksrksa ls feyrh gS &
Ø- L=ksr gka@ugha 1- fe= 2- fj”rsnkj 3- iM+kslh 4- Iakp@ljiap 5- mUur d’kd 6- xzk- d`- fo- v- @o- d- fo- v-
7- lkekpkj i= 8- df’k if=dk,W 9- jsfM;ksa 10- Vh-oh- 11- fdlku esayk 12- df’k foKku dsUnz 13- fdlku dkWy lsUVj 14- df’k oSKkfud 15- vU; 1--------------------------
2--------------------------
13- vki eDdk dk fdu&fdu lkezxh ds :i esa ?kjsyq mi;ksx djrs gS\ di;k bldh tkudkjh nhft;s&
Ø- miHkksx ds izdkj gka@ugh ek=k
1- HkwV~Vk ds :Ik es
2- ykbZ ds :Ik es
3- vkVk@jksVh
4- Ik”kqvksa dks nkuk f[kykus
5- Ik”kqvksa dks gjs pkjs
91
14- vki eDdk dk foØ; fdl&fdl :Ik es o dkSu&dkSu ls foi.ku lk/kuks dk mi;ksx djrs gS&
Ø- mRikn dk
izdkj
foi.ku gsrq lk/ku
Fkksd cktkj cktkj df’k mit e.Mh futh nwdkunkj Ms;jh QkeZ vU; ------------------
ek=k eqY; ek=k eqY; ek=k eqY; ek=k eqY; ek=k eqY; ek=k eqY;
1- HkwV~Vk
2- vukt
3- gjk pkjk
5- vU;
1----------
2--------
92
15- eDdk dh mRiknu rduhdh ds ckjs esa vki vius oSKkfud nf’Vdks.k ds laca/k esa jk; O;Dr dhft;s&
Ø nf’Vdks.k iqqq.kZr%
lger
lger
dqN
ugh dg
ldrs
vlger
iqqq.kZr%
vlger
1 eDdk dh oSKkfud mRiknu rduhdh dks
viukus ls ijEijkxr [ksrh dh vis{kk T;knk
ykHk feyrk gsSaA
2 eDdk mRiknu dh ijEijkxr rduhd vkt ds
oSKkfud mRiknu rduhd ls vPNh gSaaaA
3 eDdk dh oSKkfud mRiknu rduhd dks
viukuk vkt dh ekax gSA
4 lQYk eDdk mRiknd d’kd ogh gS] tks
eDdk dh oSKkfud mRiknu rduhd dks viukrs
gSA
5 thou LRkj lq/kkjus gsrq vkidks eDdk dh
oSKkfud mRiknu rduhd dks viukuk vfuok;Z
gSA
6 Cktkj Hkko dks /;ku esa j[krs gq;s eDdk dk
mRiknu oSKkfud fcf) ls vf/kd ls vf/kd
fd;k tkuk pkfg;sA
16- vki eDdk dh [ksrh ds ckjs esa fuEu tkudkjh nhft;s &
Ø eDdk dh mRiknu rduhd dh Kku Kku dk Lrj
iw.kZ vkaf”kd fuEu
1- eDdk mRiknu ds fy;s Hkwfe dh rS;kjh dSls djuk pkfg;s------------------------
-------------------------------------------------------------------------------------------------------------------------------------
2- eDdk dh cksokbZ ds fy;s mi;qDr le; crkb;s---------------------------------------
-------------------------------------------------------------------------------------------------------------------------------------
3- eDdk mRiknu ds fy;s dkSu&dkSu lh fdLeks dks yxkuk pkfg;s&-------
fdLe dk uke vof/k vkSlr mit
ns”kh fdLe
------------------------------------------
------------------------------------------
----------------------------------------
----------------------------------------
---------------------------------------
---------------------------------------
93
mUur fdLe
-------------------------------------
-------------------------------------
----------------------------------
----------------------------------
--------------------------------------
---------------------------------------
gkbZfczM fdLe
--------------------------------------
-------------------------------------
----------------------------------
-----------------------------------
---------------------------------------
---------------------------------------
4- eDdk mRiknu gsrq cht dh cksokbZ ds fy;s dkSu&dkSu lh fcf/k dk
mi;ksx djuk pkfg;s---------------------------------------------------------------------------------------------
5- eDdk mRiknu es izfr gs- fdruk cht nj mi;ksx djuk pkfg;s&(fd-
xzk-+@gsa)
eDdk ns”kh fdLe mUur fdLe gkbZfczM
fdLe
fNMdkok
ykbZu
6- eDdk mRiknu ds fy;s fct mipkj gsrq dkSu lh nok dk mi;ksx
djuk pkfg;s&
nok dk uke ek=k xzk-@fd-xzk- cht
1-
2-
7- eDdk mRiknu ds fy;s drkj&drkj o ikS/kk&ikS/kk nwjh fdruh j[kuh
pkfg;s&
ns”kh fdLe mUur fdLe gkbZfczM fdLe
8- eDdk mRiknu gsrq [kkn izfr gs- fdruk Mkyuk pkfg;s-----------------------------
9- eDdk mRiknu gsrq izfr gs- fdruk moZjd Mkyuk pkfg;s &
moZjd eDdk ek=k fd-xzk-+@gsa
N:P:K
ns”kh fdLe
mUur fdLe
gkbZfczM fdLe
vU;---------------------------------------------------------------------------------------------------------------------------
10 eDdk mRiknu gsrq flapkbZ o ty fudkl dSls djuk pkfg;s------------------
-------------------------------------------------------------------------------------------------------------------------------------
11 eDdk mRiknu esa [kjirokj fu;a=.k gsrq dkSu lh nok dk mi;ksx djuk pkfg;s&
94
[kjirokj nok ek=k
12 eDdk dh Qly esa dhV fu;a=.k gsrq dkSu&dkSu lh nok dk mi;ksx djuk pkfg;s &
dhV nok ek=k
13 eDdk dh Qly esa jksx fu;a=.k gsrq dkSu&dkSu lh nok dk mi;ksx
djuk pkfg;s &
jksx nok ek=k
14 eDdk dh dVkbZ o rqMkbZ dkSu lh mi;qDr voLFkk es djuk pkfg;s --
-------------------------------------------------------------------------------------------------------------------------------------
15 eDdk dks Hk.Mkj.k djus ds fy;s dkSu lh mi;qDr fof/k dk mi;ksx
djuk pkfg;s-------------------------------------------------------------------------------------------------------------
95
17- di;k vki eDdk dh mRiknu rduhd dk vaxhdj.k ds laca/k esa fooj.k nsosa &
Ø- vaxhdj.k vaxhdj.k dk Lrj
iw.kZ vkaf”kd fuEu
1 vki eDdk mRiknu ds fy, Hkwfe dh rS;kjh dSls djrs gS------------------------------------------------------------------------------------------------------------------------------------------------------------
2 vki eDdk dh cksokbZ dc djrs gS-------------------------------------------------------------------
3 vki eDdk dh dkSu&dkSu lh fdLeksa dks yxkrs gS&
fdLe vof/k mit
1-ns”kh fdLe
2-mUur fdLe
3-gkbZfczM fdLe
4 vki eDdk mRiknu es fdruk cht nj mi;ksx djrs gS&(fd-xzk-+@gs-)
eDdk ns”kh fdLe mUur fdLe gkbZfczM fdLe fNMdkok ykbZu
5 vki eDdk dh cqvkbZ ds fy;s dkSu&dkSu lh fcf/k dk iz;ksx djrs gS-------------------------------------------------------------------------------------------------------------------------------------
6 vki eDdk mRiknu ds fy;s fct mipkj gsrq dkSu lh nok dk mi;ksx djrs gS& -------------------------------------------------------------------------------------------------
nok dk uke ek=k xzk-@fd-xzk- cht
7 vki eDdk mRiknu ds fy;s drkj&drkj o ikS/kk&ikS/kk nwjh fdruh j[krs gS&
ns”kh fdLe mUur fdLe gkbZfczM fdLe
8 vki eDdk mRiknu gsrq [kkn izfr gs- fdruk Mkyrs gS ------------------------------------------------------------------------------------------------------------------------------------------------------------
9 vki eDdk mRiknu gsrq izfr gs- fdruk moZjd Mkyrs gS& moZjd eDdk fd-xzk-@gs-
N:P:K
ns”kh fdLe mUur fdLe gkbZfczM fdLe
96
18- di;k vki eDdk mRiknu ds laca/k esa vk;&O;; ds ckjs esa crkb;sa &
Ø- fdLe dqy O;; ¼:Ik;s @gs) dqy vk; ¼:Ik;s @gs)
1 ns”kh fdLe 2 mUur fdLe 3 gkbZfczM fdLe
vU;------------------------------------------------------------------------------------------------------------------------
10 vki eDdk mRiknu gsrq flapkbZ o ty fudkl dSls djrs gS&--------------------------------------------------------------------------------------------------------------------------------------------------
11 vki eDdk mRiknu esa [kjirokj fu;a=.k gsrq dkSu lh nok dk mi;ksx djrs gS&
[kjirokj nok ek=k
12 vki eDdk dh Qly esa dhV fu;a=.k gsrq dkSu&dkSu lh nok dk mi;ksx djrs gS&
dhV nok ek=k
13 vki eDdk dh Qly esa jksx fu;a=.k gsrq dkSu&dkSu lh nok dk mi;ksx djrs gS&
jksx nok ek=k
14 vki eDdk dh dVkbZ o rqMkbZ dkSu lh mi;qDr voLFkk es djrs gS----------------------------------------------------------------------------------------------------------------------------------------
15 vki eDdk dks Hk.Mkj.k djus ds fy;s dkSu lh mi;qDr fof/k dk mi;ksx djrs gS-------------------------------------------------------------------------------------------------------
97
19- vkidks eDdk mRinku o foi.ku i)fr esa fdu&fdu ck/kkvksa dk lkeuk djuk iM+rk gS\ di;k
crkb;sa&
1----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
3---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
4---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
20- vkidks eDdk mRiknu o foi.ku i)fr esa vkus okyh ck/kkvksa dks nwj djus ds fy;s vius lq>ko
nhft;s&
1----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
3----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
4----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
98
APPENDIX – B
Photographs
99
Photographs
100
Photographs
101
Photographs of data collection during study
102
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