Journal of Global Resources
Volume 6 (01)August 2019-January 2020
Page 227-232
UGC–CARE Listed Journal in Group D
ISSN: 2395-3160 (Print), 2455-2445 (Online)

36
CHANGING SCENARIO OF LIVESTOCK IN SELECTED DISTRICTS OF RAJASTHAN
Om Prakash
Assistant Professor, Department of Geography, JNV University Jodhpur (Rajasthan)
Email: oprjnvu@gmail.com
Abstract: Livestock population and productivity is greatly influenced by climatic conditions. The
climate has a significant impact not only on cattle but also on other livestock. Along with climate
livestock are also get influenced by the availability of good soil/land and rainfall supply.
Rajasthan is a state of fluctuating local distinctiveness of land and climate. The cattle
population of Rajasthan shows variations in different districts. As per the reports, Rajasthan
and other parts country display poor livestock production. This article analyses the livestock of
Total three districts with the help of study of total livestock available in these districts in different
years since 1961 to 2012 including all the data for separate districts. The data is collected for
different livestock that includes Cattle, Buffalo, Sheep, Goat, Horses & Ponies, Donkey, Cameland others.
Introduction
The rural population of India consists of more than 70 percent. Hence, probably land ispressurized more as almost the entire village population relies on agriculture, resulting in an
unfavorable landman ratio. Merely agriculture cannot provide gainful employment to all the rural
areas as the population is exploding resulting in the increasing pressure on land. Thus, allied
activities like animal husbandry can be considered as an effective instrument for supplementing
the income and providing employment to the weaker sections in rural areas. Domesticatedanimals are prominently known as “live banks”, are the significant contributors to our national
wealth and therefore help in enhancing the living standards of rural people. The livestock
population in Rajasthan has increased from 255.16 lacs in 1951 to 577.32 lacs; about 11.27
percent of Livestock population of country is available in Rajasthan”. In this way animalhusbandry remains the Prime occupation in Rajasthan. 19th Enumeration of livestock was donein 2012 when the number of total domestic animal found to be 577.32 lacs and their density
was 169 per sq. km. livestock sector provide consistent growth rate of over 6 percent per
annum round the year employment opportunity with more than 50 percent of total house holdincome in arid region as against national average of 22.5 percent and produce 11 percent milk,
30 percent wool and10 percent meat of the country. Rajasthan has Rank 1st in wool production,
Rank 1st in live meat animals (goat, sheep, and buffalo) to the tune of about 40,000 heads per
day Rank 2nd in milk production in country more than 80 percent rural households keep animals
which continue to provide subsistence income during scarcity.
In the arid and semi-arid zone livestock rearing is the primary occupation and the principal
source of livelihood for the people and is only next to agriculture in importance. The study area
(Jodhpur, Barmer and Nagaur Districts) is main part of this zone and has 12.60 percent ofRajasthan’s total livestock. Barmer is one of leading district in having largest number of sheep(14.04lacs) goats (28.96 lacs), Horses (2591), donkeys and pony (17495), camels (43172) andtotal livestock (53.66lakh) according to 19th livestock census 2012. Study area is comparatively
dry, rainless, hot and water scarcity area due to which the animal which can either survive on
small quantity of water like sheep goats or prolong their life cycle for a longest period withoutwater like camels and donkeys, livestock is the major source of livelihood for study area.
Study Area
The study area includes - Barmer, Jodhpur and Nagaur districts located between 24O 58' and
27O 40' North latitude and 70O5' and 75O15' East longitude. The study area is bounded on thenorth by Churu and Bikaner districts on the east by Sikar, Jaipur and Ajmer districts, on thesouth by Pali, Jalore districts and Gujrat state and on the west Jaisalmer district. The total
geographical area of study area is 68,955 square kilometre.
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Present Scenario of Livestock
Rajasthan is majorly driven by the Service sector but farming and allied activities are still major
sources of livelihood in villages. Livestock is the primary vocation of Rajasthan as 61.1 percentof the aggregate area is desert. The 19thLivestock census, 2012 (GOI, 2014) stated that one of
the biggest livestock in the world is that of India with a holding of 11.6 percent of world livestock
population which consists buffaloes (57.83 percent), cattle (15.06 percent), sheep (7.14
percent), goats (17.93 percent), camel (2.18 percent), equine (1.3 percent), pigs (1.2
percent), chickens (4.72 percent) and ducks (1.94 percent). India possesses a huge livestock
population of 512 million nos. This mainly includes cattle, buffaloes, goats, sheep, and pigs.
There was a decrease of 33 percent of the livestock population in India as compared to theprevious census. The cattle, buffalo, sheep, goat, pig, and others contribute 37.28, 21.23,
12.71, 26.4, 2.01 and 0.5 percent, respectively in total livestock population. The livestock
population India has substantially increased in Gujarat (15.36 percent), Uttar Pradesh (14.01
percent), Assam (10.77 percent), Punjab (9.57 percent), Bihar (8.56 percent), Sikkim (7.96
percent), Meghalaya (7.41 percent) and Chhattisgarh (4.34 percent). Adeline has been notedin the population of cattle, sheep, goats, and pigs by 4.1, 9.07, 3.82 and 7.54 percent,respectively while the population of buffalo and poultry increased by 3.19 and 19 percent,respectively in the last inter-censual period. A significant increase of 20.18 percent has beenregistered in the Exotic and crossbred cattle population while the indigenous cattle diminishedby 8.94 percent. 729.21 million the total poultry population of India, which includes 692.65,
23.54 and 13.02 million chickens, duck and turkeys & other poultry, respectively There is a
growth trend in total poultry population quite more as compared to the total livestock population(Islam, Anjum, Modi & Wadhwani, 2016) as per the observation.
Objectives
 Analyze the livestock population structure geographically.
 To analyze the role of livestock in balancing against risks.
 To identify the effect of modernization on livestock scenario.
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Research Methodology
The study area “Jodhpur, Barmer and Nagaur” district is quite backward in socio – economic
status as it lies in Western arid Rajasthan where people are chiefly engaged in livestock
occupation. This geographical study aims at analysing present scenario of livestock which has
emerged as one of the key components of agriculture growth in arid region in recent years.
Causal research is conducted in order to identify the extent and nature of cause-and-effectrelationships.
Sampling Procedure
The present study is confined to study of secondary data for the livestock population of Barmer,
Nagaur and Jodhpur districts of Rajasthan and the factors affecting livestock productivity andlivestock occupation of rural people of the three districts.
Data Analysis
Table 01: Density of Livestock in Barmer, Jodhpur and Nagaur
Year

Area of(B+J+N)

CattleDensity

Buffalo
Density

Sheep
DensityGoat
Density

Horses &PoniesDensity

1961
1966
1972
1977
1983
1988
1992
1997
2003
2007
2012

68525.568525.5
68738
68738
68955
68955
68955
68955
68955
68955
68955

74
84
58
70
74
49
63
76
62
71
93

9.70
10.65
10.30
13.86
17.52
16.94
24.68
37.26
58.35
41.47
52.32

65
91
95
122
160
100
143
194
118
135
114

62
79
110
113
139
96
110
184
158
214
259

0.27
0.23
0.14
0.18
0.14
0.15
0.11
0.13
0.15
0.14
0.29

DonkeyDensity
1.32
1.29
1.33
2.03
2.19
1.52
2.16
2.13
1.48
1.06
0.90

Camel
Density

Other
Density

Total
Livestock
Density

5.8
7.3
8.5
9.0
8.3
6.9
8.6
7.5
4.7
4.0
2.9

0.048
0.059
0.100
0.114
0.233
0.400
0.653
0.716
1.021
0.281
0.469

218
273
283
331
401
271
391
502
404
468
524

Source: livestock census reports 1961-2012, Board of Revenue Ajmer* Population Density of livestock = Number of Livestock/Land Area.

Table 1 shows the combined density of livestock in all the three districts taken for study
viz. Barnmer, Nagaur and Jodhpur district. From above table it is quite evident that Goat
density (259) and Sheep density (114) are highest followed by cattle density at the third place.
We have already seen in the separate analysis of livestock densities of the three districts thatgoat, cattle and sheep are the highly maintained live stocks in the three districts. Also from thetable it is clear that total livestock density from 1961 to 2012 is mainly increasing with only two
declines noticed in the year 1988 and 2003. Thus the total livestock is witnessing an increaseduring the time period under consideration. To find the significance growth of livestock
population in Barmer, Jodhpur and Nagaur districts during the period of 1961 to 2012 following
hypothesis has been formulated and tested with the help of regression analysis.
H01:H1:-

There is no significant growth of Livestock population in Barmer, Jodhpur andNagaur district during the period of 1961 to 2012.
There is a significant growth of Livestock population in Barmer, Jodhpur and Nagaur
district during the period of 1961 to 2012.
Table 02: Statistics for Livestock in Barmer, Jodhpur and Nagaur

CategoryN
CattleBuffalos
Sheep
Goat
Horses & Ponies
Donkey
Camel
Other
Total
Source: calculated by author

11
11
11
11
11
11
11
11
11

Mean
70.36
26.64
121.55138.55
.18
1.58
6.68
.37
369.6364

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Std. Deviation
12.20917.75335.69160.120
.060
.466
2.056
.316
102.32524

Std. Error Mean
3.681
5.353
10.761
18.127
.018
.141
.620
.095
30.85222

Table 2 presented the mean, standard deviation with standard error mean has been
given in the table. Table above depicts that the mean score value of the Cattle (70.36 ±12.209), Buffalos (26.64 ± 17.753), Sheep (121.55 ± 35.691), Goat (138.55 ± 60.12), Horses &Ponies (0.18 ± 0.06), Donkey (1.58 ± 0.466), Camel (6.68 ± 2.056), other (0.37 ± 0.316) andTotal (369.6364 ± 102.32524).
Table 03: Regression for Livestock in Barmer, Nagaur and Jodhpur
a

Model
1

Sum ofSquares2789.383
75.5262864.909

ANOVA
Df

Mean Square

F

Sig.
b

Regression
9
309.9314.104.0367
Residual
175.526Total
10
a. Dependent Variable: Yearb. Predictors: (Constant), Total, Donkey, Cattle, Other, Horses ponies, Camel, Sheep, Buffalos, Goat
Source: calculated by author

Table 3 indicates that the regression model predicts the dependent variable significantly
well. Here, p =.03367, which is less than 0.05, and indicates that, overall, the regression model
statistically significantly predicts the outcome variable (i.e., it is a good fit for the data). The
Coefficients table provides us with the necessary information to predict livestock from year, as
well as determine whether livestock contributes statistically significantly to the model (bylooking at the "Sig." column). The significant value is less than 0.05 (p value). This means wehave to reject the null hypothesis and accept the alternative hypothesis that there is asignificant growth of Livestock population in Barmer, Nagaur and Jodhpur district during theperiod of 1961 to 2012. Thus during last 5 decades livestock has grown up to a significant level
due to the combined efforts made by government and rural people. To find the trend line
equations and predicted values and also for their regression analysis following table andgraphs are used;
Table 04: Trend Line Equation and Predicted Value of Cattle in Barmer, Jodhpur and Nagaur
Year
Area of B+J+N
Cattle Density
Predicted Values (Y=0.0826X - 93.76652)
1961
68525.574
68.212
1966
68525.5
84
68.625
1972
68738
58
69.121
1977
68738
70
69.534
1983
68955
74
70.029
1988
68955
49
70.442
1992
68955
63
70.773
1997
68955
76
71.186
2003
68955
62
71.681
2007
68955
71
72.012
2012
68955
93
72.425
Source: Livestock census reports 1961-2012, Board of Revenue, Ajmer

Above table represents the cattle density for years ranging from period of 1961 to 2012,
the cattle population of Barmer, Nagaur and Jodhpur district along with its corresponding
predicted value is also shown. The predicated value is calculated on the basis of following trendline equation;
Y = 0.0826X - 93.76652
Where Y= predicted value and X= year
A trend line is a line drawn on a chart based on data points on the chart and whichhelps to determine a trend and help make trading decisions. Trend lines are commonly used todecide entry and exit timing when trading securities. Trend lines are an important tool intechnical analysis for both trend identification and confirmation. It is a straight line that connects
two or more variable points and then extends into the future to act as a line of support orresistance.
Uptrend LineAn uptrend line displays a positive slope and is formed simply by joining two or
more low points. To have a positive slope the second low must be higher than the first one for a230

line to have a positive slope. Uptrend lines act as support and indicate that net-increase(increase in livestock) is increasing even as the year wise distribution displaying fluctuations.
Downtrend LineA downtrend line shows a negative slope and is formed merely by joining two or
more high points. Here in this case the second high must be lower than the first for the line tohave a negative slope. Downtrend lines act as resistance, and indicate that net-increase(increase in livestock) is decreasing even as the time increasing.
Graph 01: Trend Line Equation and Predicted Value of Cattle in Barmer, Jodhpur and Nagaur
100
84

80

74

60

58

y = 0.0826x - 93.767
93
R² = 1
76
71
70 74
63
62
49

40

Predicted Values (Y = 0.0826X 93.76652)

20
0
1950

Cattle Density

Linear (Predicted Values (Y =0.0826X - 93.76652))
1960

1970

1980

1990

2000

2010

2020

Source: Calculated by author

R-squared is a statistical measure of how close the data are to the fitted trend line.
Just by looking at the regression line running up through the data, predictions can be done. For
2012, it looks like the line will be somewhere between 80 and 100 cattle density! That might be“good enough”, but regression also gives a useful equation, which for this chart is:
Y = 0.0826X - 93.76652
What that means is, we can plug in an x value (the year) and get a pretty good estimate ofcattle density for any year. For example, 2007:
Y = 0.0826(2007) - 93.76652= 74.018 density, which is exactly same as the actual figure of
72.012 cattle density for that year.
Best of all, we can use the equation to make predictions. For example, how much cattle density
will grow in 2017?
Y = 0.0826(2017) - 93.76652= 93.76 cattle density.
Regression also gives an R squared value, which for this graph is 1. This number tells
how good the model is. The values range from 0 to 1, with 0 being a terrible model and 1 beinga perfect model. As it can be probably seen, 1 is a fairly an excellent model so it can be fairly
confident in cattle density prediction!
Furthermore the trend line here has a positive slope showing an uptrend line but with avery little slope displaying very less increase in net cattle density value for the course of timeand an increase in this value can also be predicted for the future. Thus to make the increment
in density significant combined effort needs to be made by the govt. as well as rural people.
Also it can be easily interpreted from the graph that cattle density is witnessing regularfluctuations. From 1961 to 2012 cattle density can be viewed as fluctuating due to thevulnerable climatic conditions of Barmer, Nagaur and Jodhpur districts. Regression also gives
an R squared value, which for this graph is 1. This number tells how good the model is. The
values range from 0 to 1, with 0 being a terrible model and 1 being a perfect model. As it canprobably be viewed, 1 is a fairly an excellent model so it can be fairly confident in total livestock
density prediction. Results show the combined density of livestock in all the three districts
taken for study viz. Barmer, Nagaur and Jodhpur districts that Goat density and Sheep density
are highest followed by cattle density at the third place. Additionally the trend line for total
livestock has a positive slope showing an uptrend line displaying increase in net total livestock
density value for the course of time and also for the future. Also it can be viewed from the graph231

that total livestock density in Barmer, Nagaur and Jodhpur district from the year 1961 to 2012 ison an increasing trend with the lowest density recorded in the year 1988 and 2003.
Conclusion
The study of Changing Livestock scenario in Jodhpur, Barmer and Nagaur districts was proved
as important as Rajasthan is the largest state of India gifted with big livestock production andthe significance of agriculture and allied sector in the state gross domestic product isconsiderably higher. Livestock was thus successfully proved to be life saviour in much distress,
especially in case of drought in the study area. Livestock provides a potentially significant
source of diversified income to smallholder operating in the difficult climatic condition in thethree districts under observation. Through this study significance and development of livestockand specific approaches for the growth of the livestock were identified.
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