ISSN: 2347-4688, Vol. 06, No.(1) 2018, pg.

45-53

Current Agriculture Research Journal

www.agriculturejournal.org/

Performance of Pulses in Gujarat: A District level Assessment

More Sachin Sudhakar rao1*, Narendra Singh2 and B.K.Bhatt2

1
Department of Agricultural Economics, NMCA, NAU, Navsari, Gujarat, India.
Department of Agricultural Economics, ACHF, NAU, Navsari, Gujarat, India.
2

Abstract
A research was conducted to assess the performance of pulses in one of the
most important agriculture states of India. Performance of pulse crops was Article History
judged on two important parameters i.e. growth and instability. Compound
Received: 07 July 2017
growth rate was estimated by fitting non linear model to the area, production
Accepted: 28 March
and productivity data for the period from 1970-71 to 2011-12. The fitted model 2018
was analyzed using Marquardt algorithm. Instability was assessed by employing
Cuddy-Della Valle instability index. The results show that, the production of Keywords:
pulsesincreased in the state during the entire study period. The increase in
Pulses,
pulse crops in the state was due to area expansion coupled with marginal
Cuddy-Della Valle,
improvement in yield up to the year 1990 after that, increase in production was Index,
mainly from improvement in the yield of pulse crops as area was stagnated. Growth,
Area under pulse crops increased consistently up to year 1990 afterwards it was Gujarat,
stagnated. Consistent improvement in the yield of pulses was a notable feature Instability,
Marquardt algorithm,
which shows that improved technology has payoff in the state. High growth in
Performance.
area, production and yield of pulse crops was associated with high level of
instability during first sub period. Yield variability in pulse crops was relatively
higher than area variations which clearly indicated that yield instability was a
major source of variation in the production of pulses. Therefore attempt should
be made to stabilize the yield level in pulse crops.

Introduction there has been a reduction in the consumption of

Pulses are versatile crops that are better for pulses over the past decade. For that reason, UN
nutritional security and soil health. It is long declared 2016 as the international year of pulses to
established fact that, pulses are important part of rekindle interest and knowledge on pulses and bring
daily diets, particularly in Asian continent. However, them back in to our diets1.

CONTACT Sachin S. More sachinmorehope@gmail.com Department of Agricultural Economics, NMCA, NAU, Navsari, Gujarat,
India.
© 2018 The Author(s). Published by Enviro Research Publishers
This is an Open Access article licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
(https://creativecommons.org/licenses/by-nc-sa/4.0/ ), which permits unrestricted NonCommercial use, distribution, and reproduction in
any medium, provided the original work is properly cited.
To Link to this Article: http://dx.doi.org/10.12944/CARJ.6.1.06
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 46

India happens to be the major producer, consumer Performance of Pulsesin major states have become
and importer of pulses2; Pulses are a chief source of stagnated and minor pulse producing states have
protein for a massive section of Indian particularly for real potential in pulse development programme as
the poor and most of the conventionally vegetarian yield of pulse crops in these minor states was higher
population17. India accounts for 33% of the world area than the national average25. These states might bring
and 22% of the world production of pulses. Pigeon real breakthrough in pulse production in India by
pea (Cajanuscajan), chickpea (Cicerarietinum), black which we can reduce import dependency, stabilize
gram (Vignamungo), green gram (Vignaradiata), the prices of pulses, reduce food inflation and save
lentils and peas are major pulses cultivated in India. valuable foreign currency. Gujarat is recognized as
About 90% of the global pigeonpea, 65% of chickpea one of the minor pulse producing states25.This state
and 37% of lentil area falls in India, corresponding is having potential to contribute in pulse production at
to 93%, 68% and 32% of the global production, national level. Inrecent times, the state has achieved
respectively9. spectacular growth in agriculture sector including
pulses among all Indian states11. Hence his research
In India, pulses are grown nationwide. During the was undertaken to study the performance of pulses
year 2014-15, total domestic production of pulses at state and district level.Similarly, study also aims
in India was 17.15 million tonnes. India imported to identify the major districts, which have recorded
4.58 million tonnes of pulses and expor ted sustainable growth with stability in its yield.
0.22 million tonnes to rest of the world. During
same period, total availability of pulses for domestic Materials And Methods
consumption was 21.51 million tones3. The most The Study Area
important pulse producing states in India are Madhya This particular study was undertaken in Gujarat.
Pradesh, Rajasthan, Maharashtra, Karnataka, Uttar Major Eighteen agricultural districts of Gujarat state
Pradesh etc. Indians utilize around 30 per cent of the namely Ahmedabad, Amreli, Banaskantha, Bharuch,
world’s pulses, but domestic production of pulses Baroda (Vadodara), Bhavnagar, Valsad, Dang,
which become stagnated in recent time has not kept Jamnagar, Junagadh, Kheda, Kutch, Mehsana,
pace with population growth. The net availability of Panchmahal, Rajkot, Sabarkantha, Surat and
pulses has dropped from 60.70 g per day per person Surendranagar (As per 1971 census) were covered
in 1951 to 43.30 g per day per person in 2013 as under present study.
against recommendation of65 g per day per person
by Indian council of Medical Research4. Import of Data
pulses in India has increased, it currently accounts Districts are the lowest administrative unit at which
for about 15–20 per cent of total domestic availability. reliable agricultural data is available in Gujarat
Canada, Myanmar, Australia and Tanzania are the hence performance of pulses was analysed at
foremost exporters of pulses to India. district level along with state. Secondary time seies
data of area, production and yield (APY) were
The growth of pulses has always been unenthusiastic collected from various sources. viz; Season and Crop
in spite of the remarkable growth of Indian agriculture. Reports, Department of Economics and Statistics
The Ministry of Agriculture and Cooperation has (DES), Government of Gujarat, online data bank
focused on improving pulse production through of International Crop Research Institute for Semi-
various programme like Technology Mission (1986), Arid Tropics26 and Economic and Political Weekly
National Pulse Development Project (1990-91), (EPW) data bank [www.epwrfits.in]. The data were
Integrated scheme of Oilseeds, Pulses, Oil palm collected for the years from 1970-71 to 2011-12.
and Maize (2004), National Food Security Mission The CGR and instability were estimated for overall
(2007-08) and A3P i.e. Accelerated Pulses Production period i.e. 1971-72 to 2011-12 and two sub-periods.
Programme but supply always stay behind the These sub-periods approximately represents phase
demand and country has to greatly relied on imports of green revolution and post-green revolution. The
to meet up the supply-demand gap. period-I starts from the year 1971-72 to 1989-90,
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 47

which represent a period of green revaluation. CGR is compound growth rate for the period under
Second period (Period-II) starts from the year consideration
1991-92 to 2011-12. This period was known as post
green revolution period in which we have seen wider The data were smoothened with the help of three
dissemination of technology5. year central moving average techniques to remove
bias from the data if any induced by the outliers
Analytical Tools [Sawant, 1983; Sawant and Achuthan, 2007 and
Growth Singh et al., 1997]. The Marquardt algorithm was
The growth rateswere estimated based on its fit using used to estimate the parameters of equation4.
non linear models, especially, the exponential model. The significance of regression coefficient ‘b’
The exponential model is more commonly used in (slope coefficient) was tested by applying standard ‘t’
econometric analysis. Usually, the compound growth test procedure [Gujarati and Sangeetha, 2007].
rates were estimated after converting the growth
model to semi-log form and estimated through Instability
Ordinary Least Square (OLS) technique assuming The method that may use to examine instability in
multiplicative error term. a variable over time should satisfy two minimum
conditions. First, it should not include deviations in
Yt = b0 * b1t * et ...(1) the data series that arise due to secular trend or
growth. Second, it should be comparable across the
ln (Yt) = b0+t * ln b1 +et ...(2) data sets having different means [Mehra, 1981 and
Hazell, 1984]. Simple coefficient of variation (CV)
Where, overestimates the level of instability in time series
ln (Yt) is the natural logarithm of time series data for data, characterised by the long-term trends. To
area / production / yield for year t, avoide the problem of overestimation, Cuddy-Della
b0 is the constant term, Valle, 1978 ; Mehra, 1981 ; Hazell, 1982 ; and Ray,
t is the time trends for years of interest, 1983 have propsed alternative methods to estimate
et is the error term and instability in time series data. However, Mehra, 1981
b1 is growth rate for the period under consideration and Hazell, 1982 methods have been criticized for
(i.e. slope coefficient). measuring instability around arbitrarily assumed
trend line, which greatly influences inference
Then, Compound growth rate was calculated using regarding changes in instability, hence these two
following equation methods were not slected in present study. In recent
time, international fraternity have mostly used
Compound Growth Rate = [(Antilog b1)-1]*100 Cuddy-Della Valle Index to measure the instability
...(3) because of its supearity over other methods [Weber
and Sievers, 1985; Singh and Byerlee, 1990 and
But, this method have several problems including the Deb et al., 2004], hence we have used Cuddy-Della
difficulty in estimating standard error of estimates of Valle Index as a measure of variability in the present
original parameters18. Thus, a non-linear estimation study. This index is a modification of coefficient
technique for solving exponential model assuming of variation [CV] to accommodate trend, which is
additive error terms were employed to estimate the commonly present in time series economic data. It
compound growth rates. is superior over other scale dependent measures
such as Standard Deviation or Root Mean Square
Yt = constant *(1+CGR)t +et ...(4) of the residuals (RMSE) obtained from the fitted
trend lines of the raw data, and hence suitable for
Where, cross comparisons [Cuddy and Della Valla, 1978
Yt is the time series data for area / production / yield and Della Valle, 1979].
for year t,
t is the time trends for years of interest, The Cuddy-Della Valle Index (Ix) was calculated as
et is the error term and follows:
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 48

annum during two sub-periods and overall period at

SEE state level, respectively (Table 1). It was statistically
Ix = * 100
y
significant at 1 per cent level of significance. This
shows that, maximum growth in area of pulse crops
Where, has been occurred during first period (1971-1990).
Ix = Instability index During second period, area under pulse crops was
SEE = Standard error of the trend line estimates decreased. Yield of pulse crops has shown positive
y= Average value of the time series data and significant trend in all the three period of study
but maximum growth was observed during first
The SAS macros for econometric analysis-I available period. The CGR of yield during two sub-periods
on web adrees of Indian Agricultural Statistical and overall period was 2.57, 1.71 and 1.44 per cent,
Research Institute, New Delhi (http :// www. iasri. res. respectively. The positive growth in area and yield
In / sscnars / ecoanlysis.aspx) was used to analyse during first period leads significant high positive
the data with the help of Statistical Analysis System growth in production of pulse crops i.e. 5.48 per
(SAS) software, Version 9.3.[www.iasri.res.in]. cent per annum. Positive and significant trend in
production of pulse crops was also seen in overall
Results and Discussion period. During this period CGR of production was
Growth medium (1.77 per cent per annum).
The annual compound growth rate (CGR) in area of
pulse crops was 3.91, -0.84 and 0.76 per cent per

Table 1: Growth rates of area, production and yield of pulses in various districts of Gujarat

Districts Area Production Yield

Period-I Period-II Overall Period-I Period-II Overall Period-I Period-II Overall

Ahmedabad 3.73** 0.53NS 1.18** 4.78* 1.44NS 1.71** 3.09* 0.75NS 0.99**
Amreli 2.25NS 3.70** 4.20** 4.17NS 7.64** 6.85** 2.28NS 3.30** 1.82**
Banaskantha 0.53NS -1.90** -0.33NS 3.04 * -1.03NS 1.27** 2.85* 1.22NS 2.02**
Bharuch 10.22** -4.30** 0.82NS 10.08** -2.65** 1.45* 2.78** 1.94** 1.60**
Bhavnagar 1.24* -0.22NS 0.49NS 3.78* 1.20NS 1.67** 3.28* 2.26** 1.58**
Dang 1.04** 0.77NS 0.73** 2.81** 2.94** 2.49** 1.84* 1.59** 1.61**
Jamnagar 10.30* 2.27** 4.53** 9.87* 7.42** 7.41** 1.79NS 4.86** 3.07**
Junagadh 4.50* 5.79** 4.37** 6.25NS 10.20** 6.46** 3.61* 4.32** 1.69**
Kheda 1.46** -3.77** -0.58* 4.73** -3.86** 0.85NS 3.42** -0.33NS 1.78**
Kachchh 0.75NS -0.10NS -0.99** 2.28NS 2.86** -0.60NS 1.85NS 3.06** 0.73NS
Mehsana 1.87** 3.19** 1.98** 3.51NS 2.86** 1.87** 2.32NS -0.50NS 0.27NS
Panchmahal 0.77* 0.90NS 2.06** 2.04** 1.39NS 3.02** 1.30* 0.31NS 0.99**
Rajkot 7.23** 1.57** 3.10** 6.40* 4.58** 5.18** 1.31NS 3.59** 2.77**
Sabarkantha 8.48** -3.83** 1.50* 8.89** -5.58** 1.68* 1.31NS -1.52* 0.84*
Surat 2.85** -1.63** -0.05NS 4.40** -0.55* 0.87** 1.76** 1.02** 1.22**
Surendranagar 4.34** -1.63* 0.77* 4.21* 5.77** 3.31** 1.08NS 5.15** 2.47**
Vadodara 8.08** -1.53** 1.68** 8.12** 0.43NS 2.77** 2.32* 2.31** 1.86**
Valsad -0.21NS -0.38NS -1.09** 0.19NS 1.16* -0.59* 0.35NS 1.32** 0.57**
Gujarat 3.91** -0.84** 0.76** 5.48** 0.89NS 1.77** 2.57** 1.71** 1.44**

Note: Period-I: 1970-71 to 1989-90 Period-II: 1990-91 to 2011-12 Overall: 1970-71 to 2011-12 * significant at 5 % **
significant at 1%
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 49

The district level results shows that, in first sub- Only one district i.e. Jamnagar has registered high
period of study (1971-1990), except Valsad district (More than 3 per cent) CGR in yield of pulse crops
all the districts has shown positive trend in area of in overall period. Rest of the districts has seen low
pulse crops but high CGR i.e. more than 3 per cent to medium (Between 0 to 3 per cent) level of CGR in
was recorded in Ahmedabad, Bharuch, Jamnagar, yield of pulse crops. During overall period, production
Junagadh, Rajkot, Sabarkantha, Surendranagar of pulse crops was seen high in Amreli, Jamnagar,
and Vadodara districts. During second sub-period, Junagadh, Panchmahal, Rajkot and Surendranagar
many of the districts shown negative trends in area districts where magnitude of CGR was greater than
of pulse crops. Important of them were Banaskantha, 3 per cent per annum. During first sub period, area
Bharuch, Kheda, Sabarkantha, Surat, Surendranagar expansion coupled with yield improvement was a
and Vadodara districts. Only few districts viz; Amreli, reason for increase in production of pulse crops
Jamnagar, Junagadh, Mehsana and Rajkot districts in the state but during second period, increase in
have shown positive trend in area of pulse crops in production was mainly comes from improvement in
second sub-period of study. In overall period, except the yield of pulse crops. Results of decomposition
Kachchh, Valsad and Kheda, rest of the districts have analysis reported by More et al., 2015 also stated
registered positive trend in area of pulse crops. that, improvement in yield of pulse crops was the
main reason behind the increase in production
Magnitude of CGR in regards to production and followed by interaction of yield in to area which
yield of pulses was seen higher in first sub-period supports our view.
compared to second sub-period of study. Few
districts viz;Amreli, Junagadh, Kachchh and Instability
Surendranagar have registered prominent CGR in State and district level estimates of instability in
yield and production during second sub-period. In regards to area, production and yield of pulse crops
overall period, all the districts have shown positive for three periods viz; 1971-1990, 1991-2012 and
trend in production and yield of pulse crops. (Except 1971-2012 were presented in table 2 and figure 1.
production of pulse crops in Valsad district).

Fig. 1: District wise instability in area, production and yield of pulses

in Gujarat (1970-71 to 2011-12)
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 50

Table 2: Instability in area, production and yield of pulses in various districts of Gujarat

Districts Area Production Yield

Period-I Period-II Overall Period-I Period-II Overall Period-I Period-II Overall

Ahmedabad 34.10 25.60 29.80 62.18 35.01 46.87 37.14 17.00 27.68
Amreli 55.94 56.10 60.83 85.48 56.03 69.74 46.66 24.85 34.80
Banaskantha 19.18 14.73 19.04 47.19 40.17 43.96 36.88 35.61 35.92
Bharuch 21.19 16.41 45.60 39.47 28.52 47.87 26.44 17.99 21.64
Bhavnagar 14.45 49.83 39.58 49.85 64.80 60.90 43.68 26.90 34.20
Dang 08.15 39.66 31.80 25.15 52.91 50.07 24.94 14.69 18.48
Jamnagar 104.66 27.75 43.95 101.35 41.40 55.10 41.16 27.32 33.97
Junagadh 58.68 32.46 44.89 108.16 46.98 74.48 46.44 25.59 37.54
Kheda 11.91 17.72 24.74 41.58 34.45 50.25 35.97 24.38 30.76
Kachchh 35.65 22.91 33.63 71.99 52.41 69.52 57.21 40.65 49.97
Mehsana 17.50 17.47 18.98 51.90 29.42 39.05 39.29 18.72 30.83
Panchmahal 11.88 16.48 17.53 29.79 31.94 33.71 24.97 21.41 22.54
Rajkot 51.87 17.41 28.79 86.17 41.95 52.65 52.16 35.63 41.88
Sabarkantha 16.43 12.26 41.61 50.85 32.83 63.86 31.97 30.35 32.31
Surat 09.83 15.59 18.04 28.96 15.64 26.69 20.26 17.40 18.39
Surendranagar 25.09 32.31 33.28 48.06 63.35 65.86 38.70 32.86 40.89
Vadodara 13.85 06.69 26.66 48.13 20.75 33.12 36.27 19.15 26.05
Valsad 06.66 18.56 14.75 24.46 21.17 25.16 20.59 10.60 16.01
Gujarat 13.42 09.08 17.31 35.90 22.65 30.14 25.72 16.93 20.66

Note: Period-I: 1970-71 to 1989-90 Period-II: 1990-91 to 2011-12 Overall: 1970-71 to 2011-12

In Gujarat state, instability in area of pulse crops (Jamnagar) and during second sub-period, it was
during the study periods was 13.42, 9.08 and 17.31 ranged from 6.69 per cent (Vadodara) to 56.10 per
per cent per annum, respectively. Area under pulse cent (Amreli). During first sub-period of study, low
crops in the state was relatively stable in second level of instability was seen in Valsad, Dang and Surat
sub-period compared to first. Similarly, production districts and high level of instability was recorded in
and yield of pulse crops was also stable in second Jamnagar, Junagadh, Amreli, Rajkot, Kachchh and
sub-period compared to first sub-period. Instability Ahmedabad districts. In rest of the districts, instability
in production of pulse crops was reduced to 22.65 in area of pulse crop was moderate.
percent from 35.90 per cent in sub-sequent periods.
Instability in yield was also decreased to 16.93 per In second sub-period of study, many of the
cent from 25.72 percent. Yield variability in pulse districts except Amreli, Panchmahal, Surat, Kheda,
crops was relatively higher than area variations Surendranagar, Valsad, Dang and Bhavnagar
which again clearly indicated that, yield variation showed decrease in the level of area instability
was a major source of variation in production of in pulse crops which is good sign. Among these
pulsecrops in the state. A study by Mehta (2013) districts, maximum increase of instability was seen
alsomentionedsimilar resultson the yield of pulse in Dang and Bhavnagar districts.
crops being mostly unstable compared to area in
the Gujarat state. It is obvious that, magnitude of production instability
of pulse crops was high compared to its area
District level results shows that, during first sub- and yield. Such type of results is seen because
period, instability in area of pulse crops was ranged production is interaction of area and yield series.
from 6.66 per cent (Valsad) to 104.66 per cent The range of instability in production of pulse crops
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 51

was from 24.46 per cent (Valsad) to 108.16 per per cent) districts during first and second sub-period
cent (Junagadh) in first sub-period and from 15.64 of the study, respectively whereas highest level of
per cent (Surat) to 64.80 per cent (Bhavnagar) in yield instability was seen in Kachchh (57.21 and
second sub-period of the study. In both the periods, 40.65 percent) district during both the sub-period
moderate to high level of production instability was of the study.Even though the magnitude of yield
seen in various districts of Gujarat state. instability was reduced in second sub-period of study,
moderate to high level of instability in yield of pulse
When compared to first sub-period, instability in crops was observed in various districts of Gujarat
production of pulse crops was reduced in second state. Instability in yield was reduced utmost in Amreli
sub-period except in Panchmahal, Bhavnagar, followed by Junagadh, Mehsana, Ahmedabad,
Surendranagar and Dang districts. Vadodara, Bhavnagar, Kachchh etc. districts. In
Panchmahal, Surat, Sabarkantha and Banaskantha
Lowest level of yield instability in pulse crops was districts, instability in yield were reduced marginally
recorded in Surat (20.26 per cent) and Valsad (10.60 i.e. less than 5 per cent.

Annexure 1: Area dynamics in pulse crops among various districts of Gujarat State

Districts 1971-80 1981-90 1991-00 2001-13 % change in % change in % change in

1981-90 1991-00 2001-10
over base over base over base

Ahmedabad 17.83 29.59 28.35 30.27 165.99 159.05 169.79

Amreli 3.12 4.90 8.82 11.68 157.05 282.69 374.20
Banaskantha 66.79 66.62 70.46 55.45 99.75 105.49 83.02
Bharuch 42.50 155.24 134.01 86.75 365.27 315.32 204.12
Bhavnagar 7.53 8.36 10.01 8.24 111.02 132.93 109.45
Dang 8.31 9.25 9.99 11.22 111.31 120.22 134.98
Jamnagar 1.37 14.39 23.24 27.19 1050.36 1696.35 1984.79
Junagadh 6.44 14.69 15.56 29.55 228.11 241.61 458.85
Kheda 113.94 129.67 89.18 88.59 113.81 78.27 77.75
Kachchh 22.37 27.77 29.78 16.58 124.14 133.12 74.09
Mehsana 37.29 46.58 47.66 68.53 124.93 127.81 183.80
Panchmahal 57.74 64.69 104.21 104.13 112.04 180.48 180.35
Rajkot 4.49 12.12 15.85 18.29 269.93 353.01 407.39
Sabarkantha 25.49 61.61 94.20 56.48 241.70 369.56 221.59
Surat 41.85 60.17 51.34 45.57 143.78 122.68 108.88
Surendranagar 12.97 22.05 20.76 19.18 170.01 160.06 147.84
Vadodara 40.54 103.38 118.88 98.09 255.01 293.24 241.96
Valsad 34.10 34.01 26.02 25.49 99.74 76.30 74.76
Gujarat 574.42 891.14 877.2 802.99 155.14 152.71 139.79

Note: Base Year was 1971-80

Conclusion yield of pulse crops as area was stagnated. Area

The production of pulse crops was recorded to under pulse crop was increased consistently up to
increase in Gujarat during entire study period. The year 1990 afterwards it was stagnated. Consistent
increase in pulse crops in the state was due to area improvement in the yield of pulses was a notable
expansion coupled with marginal improvement in feature which shows that improved technology has
yield up to the year 1990 after that, increase in payoff in the state. High growth in area, production
production was mainly from improvement in the and yield of pulse crops was associated with high
 rao et al., Curr. Agri. Res., Vol. 6(1), 45-53 (2018) 52

level of instability during first sub period. Yield instability was a major source of variation in the
variability in pulse crops was relatively higher than production of pulse crops. Hence efforts should be
area variations which clearly indicated that yield made to stabilize the yield level in pulse crops.

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