Journal of Global Resources
Volume 6 (02)
July 2020
Page 43-48
doi.org/10.46587/JGR.2020.v06i02.007
ISSN: 2395-3160 (Print), 2455-2445 (Online)

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CROP DIVERSIFICATION AND ITS DETERMINANTS: A COMPARATIVE STUDYBETWEEN CUTTACK AND KANDHAMAL DISTRICTS OF ODISHA, INDIA
Chinmaya Ranjan Kumar
Doctoral Fellow (UGC-NET-JRF) in Rural Development, Department of Economics,
Ravenshaw University, Cuttack, Odisha, India
Email: ckumar.rd@ravenshawuniversity.ac.in
Abstract: The crop diversification is considered as an important pathway for agrariandevelopment. It means not just raising a greater variety of crops in a geographical limit over a
period of time but also a movement of resources from a low value agriculture to a high value
agriculture. The present study aims at examining the status of crop diversification in Odisha visa-vis the comparison between the coastal district Cuttack and southern tribal Kandhamal
district of the state. It is measured through Thiele’s Entropy Index (TEI) by considering gross
cropped area under eight varieties of crops through secondary data in the year 2015-16 andthe two districts have been scrutinized through primary investigation in the year 2018-19. The
variables irrigation, fertilizer, high yielding variety seeds, credit, income from agriculture,electricity used for agriculture, telecommunication and farm mechanisation like tractor/ power
tiller and statistical tool linear multiple regression have been employed to examine thedeterminants of crop diversification.
Key words: Crop diversification index, Determinants, Regional disparity, Livelihood
Introduction
Agriculture continues to remain the predominant sector of Indian economy particularly in the
backward states like Odisha. Among them 32.1 percent of the family are in Below Poverty Line
which seems their livelihood is insecure and they are in challenging and stressed situation.
About two-third of the state’s works force is still engaged in agriculture which provides them
livelihood directly or indirectly even though its share in gross state domestic product (GSDP)
has declined from over 70 per cent in the early 1950s to 15.39 per cent in the year 2014-15.
The catastrophes, inconsistence of monsoon, climate change risks such as flood, drought
which leads to insufficient production of various agricultural products and fluctuation of prices
arises owing to inconsistent and become a matter of concern now a day (Birthal and Hazarana,2019) and it is expected that extreme calamities events rise in future scenario (World Bank,2013). Under this backdrop, what seems paramount to raise productivity and sustainableagriculture in Odisha’s context is to rely heavily on crop diversification. Diversification ofagriculture may help to overcome these overriding problems of state’s agriculture.
Crop diversification is essential for agriculture based economy in the current scenario. It
is defined as movement of production-portfolio from a low-value commodity to high-valuecommodity making a shift from traditional to commercial crops (Joshi et al., 2004). Diversifying
the farm activities helps to mitigate both the climatic risks as well as price risks. Crop rotationand diversification were practiced in farming to control weeds, pest and soil erosion, and tomaintain soil fertility. Crop diversification aids in adapting with consumption pattern. Foodconsumption patterns change noticeably, as consumers in developing countries become richer(Joshi, 2010). People move away from a diet based on staples to one with a greater content ofanimal products such as meat, eggs and dairy and fruits and vegetables. Diversifying from themonoculture of traditional staple crops can have important nutritional benefits which benefits infood security as well as nutritional security (Lin, 2011). Diversification of agriculture in favour of43

more competitive and high-value enterprises is considered as an important strategy to augment
farm income, generate employment, alleviate poverty and conserving the ecological biodiversity
and aiding sustainable agricultural transformation (Pingali and Rosegrant 1995, Von Braun,
1995; Joshi et al., 2004; Birthal et al. 2015; King and Hofmockel, 2017; Thapa et al. 2017;
Birthal and Hazrana 2019). Diversification in agriculture has tremendous impact on agro socioeconomic and uplifting of resource for poor farming communities. It generates income andemployment for rural youth for the ultimate benefits of the farmers in the country (Singh, 2009).
Developing country farmers have had considerable success by diversifying crops that can meet
export market demand.
Determinants of diversification have several forces to influence the nature and speed ofagricultural diversification from staple food to high value commodities. Studies by Joshi et al.
(2004) and Rao et al. (2006) have observed that production of high-value commodities isdemand-driven, determined mainly by rising income and urbanisation. Hazra (2001) has
enlisted other determinants of crop diversification, viz. resource related factors like rainfall,
irrigation, fertilizers; technology related factors like High Yielding Variety (HVY) seeds,
household related factors like education, income from agriculture; institution related factors likecredit, insurance, Minimum Support Prices (MSP), and infrastructure related factors likeelectricity, telecommunication facilities, road and markets.
The study has attempted To measure the level of crop diversification in all districts of Odisha.
 To examine the status and compare the level of diversification between Cuttack andKandhamal Districts.
 To explore the determinants of crop diversification in the study area.
The limitation of the study is that the present study is made on the available of primary data
to examine the determinants of crop diversification where could not covered the variables likeagro-climatic zone, soil fertility, rainfall, road connectivity, Minimum Support Price (MSP),
marketing facility, education of the farmer and cold storages, food processing units and agrobased industries etc.
Methodology
In this section an attempt has been made to describe the different as aspects of themethodology adopted in the present study.
Data and Sample Design
The study has been based on both primary data and secondary data. The secondary data has
been collected from various sources like Agricultural Statistics of Odisha and Economic
Surveys. The primary data has been collected from two districts of Odisha i.e. Cuttack district
and Kandhamal district. In the Cuttack district, the data has been collected mainly from two
Gram Panchayats (GP) consists of four villages. One is Govindpur G.P. which consisting of twovillages named Biswanathpur, and Jariapda and other is Salagaon G.P. which consisting ofSalagaon and Nakhara villages of Tangi- Chaudwar block. In Kandhamal district, has beencollected from Balaskumpa and Gudari Gram Panchayat of Khajuripada Block. Primary
investigation data has been collected from the households through structured questionnaire. To
examined the status of crop diversification of Odisha i.e. district wise, secondary data has beenused in the year 2015-16. In the primary study, total sixty numbers respondents were takenfrom both Cuttack and Kandhamal district each having thirty numbers of farmer’s household in
the year 2018-19. Both purposive sampling and random sampling technique has been used to
select the samples in this study.
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Figure 01: Map of the Study Area

Measurement of Crop Diversification
Gross Cropped Area (GCA) of eight variety of crops which have been used for measure the
Crop Diversification Index (CDI) of Odisha as well as both the Cuttack district and Kandhamal
district. These eight varieties of crops are as follows: Cereals, Pulses, Oil seeds, Vegetables,
Fruits, Spices, Fibres and Sugarcane. Crop Diversification has been measured on the basis of
Theil Entropy Index (TEI), termed as crop diversification index(CDI) where Pi =the proportion ofarea under ith crop in gross cropped area (GCA), n= the number of crops i.e. Cereals, Pulses,
Oil seeds, Vegetables, Fruits, Spices, Fibres and Sugarcane.
𝑇𝑇ℎ𝑒𝑖𝑙 𝐸𝑛𝑡𝑟𝑜𝑝𝑦 𝐼𝑛𝑑𝑒𝑥(𝐶𝐷𝐼 ) =∑𝑛𝑖 𝑃𝑖 𝑙𝑜𝑔

1
𝑃𝑖

Range: 0 < 𝐶𝐷𝐼 𝑇 < 1

log 𝑛when 𝐶𝐷𝐼 =0, there is complete concentration (no diversification), and where 𝐶𝐷𝐼 = 1, there iscomplete diversification.
Measure the Determinants of Crop Diversification
Linear Regression Method
The impact of the selected explanatory variables on CDI is assessed by linear regressions. The
left hand side CDI variable is dependent and right hand side variables like irrigation, electricity,
telecommunication, tractor/ power tiller, Credit, fertilizer, HYV, Per capita income fromagriculture.
𝐶𝐷𝐼 𝑇 𝑖 = 𝛽0 + 𝛽1 𝑃𝐺𝐼𝐴𝑖 + 𝛽2 𝐸𝐿𝐶𝑇𝑖 +𝛽3 𝑇𝐸𝐿𝐶𝑖 +𝛽4 𝑇𝑅𝐶𝑇𝑖 + 𝛽5 𝐶𝑅𝐷𝑇𝑖 + 𝛽6 𝐹𝐸𝑅𝑇𝑖 + 𝛽7 𝐻𝑌𝑉𝑖 + 𝛽8 𝑃𝐶𝐼𝑖 + Є𝑖
Where i= 1 ………30 no. of households

Variables
Variables used to measure determinants of crop diversification are described as follows:
Table 01: Variables used for Determining Crop Diversification
Variable taken

Abbreviation

Definition

PGIA
ELECT

Percentage of gross irrigated area to gross cropped area
Rural households with electricity connection

TELC

Rural household with Mobile connection

Tractor/Power Trailers

TRCT

CreditCRDT

Beneficiary having own tractor or power trailers for using
agricultural purpose
Agricultural credit per hectare of gross cropped area

Fertiliser
Seed type
Per Capita Income

FERT
HYV
PCI

NPK (in kg) used per hectare of gross cropped area
Percentage of gross cropped area under HYV
Per Capita Income from agriculture

Irrigation
Electricity
usedagriculture
Telecommunication

for

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RESULT AND DISCUSSION
Crop diversification in Odisha
Crop diversification can be measured in a number of ways such as Theil’s Entropy Index,
Herfindhal Index, Simpson’s Index, Ogive Index etc. However, the present study has been
employed Theil Entropy Index to measure crop diversification index (CDI). An attempt has been
made to understand the relative positions of all the thirty districts of Odisha in relation to crop
diversification. There are eight varieties of crops like cereals, pulses, oil seeds; fibre, spices,
vegetables, fruits and sugarcane have been included. The position of all the thirty districts ofthe state in CDI is presented in Table 2. Surprisingly, a backward district like Kandhamal
districts remains in the top rank with CDI value 0.70 in the years 2015-16. Baragarh district,which is considered as the rice bowl of Odisha, is in the last rank of the state. The study
observes that mostly the tribal dominated KBK districts are in the top ten positions, whereas therelatively richer coastal districts of Odisha except Jajpur are in the bottom. The costal districts
like Baleswar, Bhadrak, Jagatsinghpur and Kendapara are in last ten rank of the state. The
central Odisha districts are also relatively better in diversification i.e. Angul, Dhenkanal,
Keonjhar, Debagarh are in the top ten rank of the state.
Table 02: District-wise Crop Diversification Index of 2015-16
DistrictHigh
Rank
Kandhamal
10.70
Rayagada
2
0.61
Malkangiri
3
0.55
Dhenkanal
4
0.54
Koraput5
0.54
Anugul6
0.54
Gajapati
7
0.54
Keonjhar8
0.48
Debagarh9
0.48
Jajapur10
0.47
Source: Authors’ calculation

Rank
11
12
13
14
15
16
17
18
19
20

District
Balangir
Kalahandi
Sambalpur
Jharsuguda
Sundargarh
NuapadaNayagarh
Cuttack
Khordha
Puri

Medium
0.45
0.44
0.44
0.43
0.43
0.42
0.42
0.41
0.40
0.39

Rank
21
22
23
24
25
26
27
28
29
30

District
Baudh
Jagatsingpur
GanjamNabarangpur
Baleshwar
Sonepur
Kendrapara
Mayurbhanj
BhadrakBaragarh

Low
0.39
0.39
0.38
0.37
0.37
0.35
0.35
0.34
0.33
0.28

Figure 02: District-wise Crop Diversification Status of Odisha

Comparison between Cuttack and Kandhamal district
The Crop Diversification Index (CDI) for Cuttack and Kandhamal districts have been used same
methodology as applied in Odisha. In this section, CDI was measured through Thiel’s Entropy
Index and the result reveals that Kandhamal district has high CDI, i.e. 0.78 and the Cuttack
district has low CDI, i.e. only 0.43. In the above table, the Crop Diversification Index (CDI)46

shows that the Cuttack district has bottom the status of the CDI result of the Odisha, same
situation as in the primary investigation. The result of primary investigation in Cuttack district
shows that the CDI is less than the average CDI in comparative to the secondary data
investigation. The primary study result shows that average CDI of Cuttack district is 25.4. Incomparison to the whole district study in the year 2015-16 shows the CDI of Cuttack is morethan the primary data collected from Salagaon and Govindapur G.P.s of Tangi-Chodwar blockof Cuttack district. The CDI scenario of Cuttack district might be different in other blocks. As inthe secondary data study of Odisha reveals that Kandhamal district is in the top rank of Odisha
i.e. CDI is 0.70. In the primary investigation in Kandhamal district, it is found that the mean of
the CDI of Kandhamal district is 0.49. But in the district level investigation through secondary
data shows more CDI in comparison to the primary investigation.
Determinants of Crop Diversification
The study has examined several determinants of crop diversification in Kandhamal district. This
district has been selected on the basis of the highest crop diversification index in the state aswell as in the primary investigation in compared to the Cuttack district. As average CDI of the
Kandhamal district shows 0.49 in primary and 0.70 in secondary investigation which is quite
high comparison to CDI of Cuttack district which is very less i.e. 0.25 and 0.41 in in primary andsecondary investigation respectively. Therefore, it was prudent to take the CDI of Kandhamal
district for exploring the determinants of crop diversification. Due to very low CDI in Cuttack
district it would be superfluous to examine the exact determinants of crop diversification. Simple
statistical tools like linear multiple regressions has been employed to examine the determinantsof primary investigation in Kandhamal district. The present study has considered a list ofvariables which could influence crop diversity. This includes irrigation, electricity,
telecommunication, tractor/power trailers, credit, fertiliser, seed type and per capita income
from agriculture has been used as independent variables. CDI was taken as the dependent
variable in the regression model.
Table 03: Regression results: Determinants of Crop Diversification
Variables
Constant
Irrigation
Electricity used for agriculture
Telecommunication
Tractors/ Power trailers
CreditFertilizers
High Yielding Variety (HYV) seeds
Per Capita Income from Agriculture
R sqaure
Adjusted R sqaureF
P-Value
Source: Author’s Calculation

Unstandardized Coefficient
Beta
SE
.166
.049
.001
.001
.000
.034
.033
.034
.056
.025
7.317E-006
.000
.001
.001
.000
.000
4.238E-006
.000
.869
.819
17.0450.000

P-Values
.003
.211
.989
.338
.035
.003
.285
.292
.002

The analysis has fitted a linear multiple regression models for the primary data collectedin the year 2018-19 with CDI as the left hand side variables and the variables explained in table
no. 1. as the right hand side variables. The impact of the selected explanatory variables on CDI
is assessed by linear regressions in which the regresses. The left hand side CDI variable isdependent and right hand side variables are independent variables. The results of the study
show in the table no. 3, that aggregately all the determinants have significant impact on crop
diversification in Kandhamal district of Odisha i.e. the p- value is 0.000. But variables such as
tractor/power trailers, credit, and per capita income from agriculture are individually significant
and have positive impact on crop diversification i.e. leads to crop diversification in Kandhamal
47

district of Odisha. In contrast, the factors like irrigation, electricity used for agriculture,telecommunication, and fertilizer and HYV seeds have no significant impact on crop
diversification in the study area.
Conclusions
The study finds that crop diversification in Odisha is low. Economically backward district like
Kandhamal is ahead in diversification compare to coastal district like Cuttack which gives aparadoxical scenario. It shows that maximum people are engaged in paddy cultivation in
Cuttack district rather cultivating numerous crops. But in Kandhamal district, it shows that there
has been cultivating different crops such as pulses, vegetables, fruits, oilseeds, spices,plantation crops etc. which leads to crop diversification. The study has examined several
determinants of crop diversification in Kandhamal district which shows the highest Crop
Diversification Index in the state. In the context of Kandhamal, the factors like credit, tractor/
power trailers and per capita income from agriculture have significant impact on crop
diversification. Irrigation, electricity used for agriculture, telecommunication, HYV seeds andfertilizers have no significant impact crop diversification but aggregately all the variables havesignificant impact on crop diversification. Based on the findings of the study we can suggestthat to accelerate the pace of diversification from cereals to high value crops/ commercial crops
in the state, steps need to be taken to improve credit disbursement for agriculture purpose,
farm mechanisation like tractor/ power trailers. Lastly, without consistent policy signals,
autonomous efforts by farmers are unlikely to be sufficient to create a sustainable, productive
and resilient agriculture sector.
References
1. Birthal, P. S. & Hazarana, J. (2019). Crop diversification and resilience of agriculture to climatic
shocks: Evidence from India. Agricultural Systems, 173: 345–354.
2. Birthal, P. S., Roy, D. & Negi, D.S. (2015). Assessing the impact of crop diversification on farm
poverty in India. World Development, 72.
3. Hazra, C. R. (2001). Crop Diversification in India, in Papademetriou, M. K. & Dent, F. J. (Ed),
Crop Diversification in the Asia-Pacific Region, Bangkok, Thailand: Food and Agriculture
Organization of the United Nations Regional Office for Asia and the Pacific.
4. Joshi, P. K., Gulati A & Jr. Cummings, R., (2010). Agriculture Diversification in South Asia:
Beyond Food Security, in Joshi P.K., Gulati A and Jr. Ralph Cummings (eds.) Agriculture
Diversification and Smallholders in South Asia, Academic Foundation, New Delhi.
5. Joshi, P.K., Gulati, A., Birthal, P.S. & Tewari, L. (2004). Agriculture diversification in South Asia:
Patterns, determinants and policy implications. Economic and Political Weekly, 39(18): 24572467.
6. King, A. E. & Hofmockel, K. S. (2017). Diversified cropping systems support greater microbial
cycling and retention of carbon and nitrogen. Agriculture, Ecosystems & Environment, 240(1):66-76. Chicago, USA.
7. Lin, B. B. (2011). Resilience in agriculture through crop diversification: adaptive management
for environmental change. Bioscience, 61(3):183–93.
8. Pingali, P. L. & Rosegrant, M. W. (1995). Agricultural Commercialization and Diversification:
Process and Policies. Food Policy, 20(3), 171-186.
9. Rao, P., Birthal., P. S. & Joshi, P. K. (2006). Diversification toward s High Value Agriculture,
Role of Urbanisation and Infrastructure. Economic and Political Weekly, 41(26): 2747-2753.
10. Singh, A., Boukerrou, L. & Miller, M. (2009). Diversification in Agriculture, in: Encyclopaedia ofEarth, (Eds.) Cutler J. Cleveland, Washington D.C.
11. Thapa, G., Kumar, A., Roy D. & Joshi, P.K. (2017). Impact of crop diversification on rural
poverty in Nepal. Canadian Journal of Agricultural Economics, 1–35.
12. Von Braun, J. (1995). Agricultural commercialization: Impacts on income and nutrition andimplications for policy. Food Policy, 20 (3): 187-202.
13. World Bank, (2013). Turn Down the Heat: Climate Extremes, Regional Impacts, and the Casefor Resilience: A Report of the World Bank. World Bank, Washington D.C., U.S.

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