EA EA EA Economic Affairs 0424-2513 0976-4666 AESSRA India EA-66-03-0377 10.46852/0424-2513.3.2021.3 Research Paper Growth Rate of Pulses in Eastern Uttar Pradesh a Zone-wise Analysis PandeyEkta1 Supriya2 MishraP.3 * MehtaVishal1 KarakayaKadir4 AbotalebMostafa5 Department of Agricultural Statistics, College of Agriculture, Acharya Narendra Deva University of Agriculture and Technology (ANDUA & T), Kumarganj, Ayodhya, Uttar Pradesh, India Department of Agricultural Economics, College of Agriculture, Acharya Narendra Deva University of Agriculture and Technology (ANDUA & T), Kumarganj, Ayodhya, Uttar Pradesh, India College of Agriculture, Powarkheda, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Madhya Pradesh, India Selçuk University, Faculty of Science, Department of Statistics, Konya, Turkey Department of System Programming, South Ural State University, Chelyabinsk, Russia Corresponding author: pradeepjnkvv@gmail.com (ORCID ID: 0000-0003-4430-886X) 09 2021 66 03 377 382 20 04 2021 25 07 2021 05 08 2021 © AESSRA, India 2021 AESSRA, India Abstract

Attempts are made in this paper to investigate the trend of pulses in Eastern Uttar Pradesh, as well as their instability and non-linear model. This time series data on pulses pertains to the period 1980-1981 to 2014-15 and includes information on the area, production, and productivity of pulses. Pulses have had negative growth in terms of area, production, and productivity in all three zones of Eastern Uttar Pradesh, namely, the North Eastern plain zone, the Eastern plain zone, and the Vindhyan zone. Since 1980-81, there has been a rise in the area and output of pulses in the Vindhyan zone, as seen by the percentage change. The Eastern plain zone has the most stable pulse crop in terms of instability.

HIGHLIGHTS

Zone wise study of growth rates of pulses crops helps in agricultural planning and determining agricultural operation at the state level to meet rising food and nutritional security.

 Growth trend linear growth rate (LGR) Instability index non- linear regression <p>Pulses belong to the Fabaceae or Leguminos as family and are the third largest flowering clusters in the world. Since the dawn of the farming of the principal plants in the globe, people have grown pulses to be domesticated. Pulses are a vital constituent of the super molecule in the diet of an overwhelming majority of the poor and eating in Asia (<xref ref-type="bibr" rid="R2">Devi <italic>et al</italic>. 2021</xref>). In addition to grains, pulses offer a great blend of eater super high biological value molecules. Asian countries continue to be home to the precious gold of the world’s ill-fed people. Asian countries are the largest producers, businessmen and buyers of pulses, representing twenty fifths of world production in thirty-fifths of the world’s space <xref ref-type="bibr" rid="R15">Vishwajith <italic>et al</italic>. (2014)</xref>. About 15.2 percent of people in Asian squares are poorly fed. This shows the importance of food and nutrition pulses for Indians (<xref ref-type="bibr" rid="R16">Vani and Mishra, 2019</xref>). Pulses are produced mostly in Asian countries, particularly in the Indian subcontinent. Various pulse crops are large measured in the Asiatic country in a wide variety of agro-climatic circumstances therefore it is a major global pulse participant. Pulses do not encompass crops which square measure unrecovered (e.g. green peas, unrecognized beans) are categorized as vegetable crops. The assembly of pulses in Asia has been caught in the vicious circle of low and unsafe yields, which is less likely to produce pulses on irrigated and fertile land, leading to unstable and low returns. These crops must be supplemented with superior cereals and financial crops for resources, analysis and infrastructure.</p> </sec> <sec> <title>MATERIALS AND STRATEGIES

The statistic knowledge concerning the amount from 1980-81 to 2014-15 on space, production and productivity of various crops are wont to study the expansion trends. These statistic knowledge are procured from the Bulletins of board of directors of Agricultural Statistics and Crop-Insurance, Krishi Bhawan, Lucknow, Government of state. Loads of efforts are created by Government of India to enhance the state of affairs of various crops production within the country within the past. Therefore, the statistic knowledge has been classified into 3 decade to review the decadal growth pattern of the world, production and productivity of pulses.

Applied math Methodologies

The applied math methodologies used for the analysis of your time series knowledge to satisfy the objectives of the thesis are delineate within the following sub-sections.

Growth Models

The trend and growth rates in space, production and productivity completely different of various} cereal crops have been figured out by fitting the subsequent 5 different functions (Mishra et al. 2021):

1. Simple linear operate

Yt = a + bt + µt

2. Compound operate

Yt = at (1 + r) t µt

Where,

Yt : statistic knowledge on area/production/ productivity of various cereal crops at time t, a & b are parameters of the operate to be calculable.

t: Time index (t= 1,2,…..,n)

r: Average compound rate every year

t: error term at t and is assumed to follow severally distributed.

However, before fitting the higher than functions, the statistic knowledge on space and production were smoothened by 3 years moving-average methodology.

 Computation of rate 1. For linear operate

Once fitting the linear trend operate by leastsquare methodology, we tend to get the estimate of b denoted by (say). Then, annual linear rate is computed as follows (Dhekale et al. 2014). r=b^Y¯×100

Where, Y¯ is mean value of Yt.

 2. Compound rate

To get annual compound rate, the third operate was initial linearised by taking natural go online each aspect, i.e. log⁡Yt=log⁡a+tlog⁡(1+r) or Yt∗=a+bt

Where, Yt∗=log⁡Yt, a* = log a and b = log (1 + r)

The higher than linear operate was fitted by least sq. methodology and estimate of b as b^ was obtained. The annual compound rate is then computed as, r=( antilog of b^−1)× a hundred 

All growth rates are expressed in share. The most effective fitted operate was judged on the idea of R2 (coefficient of determinations).

 Measure of instability in crop production

High growth and low instability in crop production and agricultural property performance conditions. Vital issue is that the technological modification in the development of crops has increased the variability to one in all the food safety hazards. Given the scale of agricultural growth and instability for policy makers, the level of instability in space, crop production and productivity will be an adequate mathematical mistreatment calculable. The constant of variation is typically used to live the degree of instability. The straight forward coefficients of variation (C.V.) typically contain the trend element and therefore over estimate the amount of instability in statistic information characterized by future trend. To beat this drawback, a live of instability is calculable by mistreatment cook-house Della Valle Index that corrects the constant of variations and it’s given by  Instability index =CV1−R2

Where, R2 is that the constant of determination from a time trend regression adjusted by the amount of degree of freedom. Curve knowledgeable skilled is employed for fitting sixty seven linear and non- linear functions like rational model, Weibull model, provision power etc.

 RESULTS AND DISCUSSION Trends in space, production and productivity of total pulses

The average triennium space (in 1000 hectares), production (1000 tones), and productivity (kg/ hectare) and their percent change over many decadal periods are measured by the total pulses square in Table 1 to 3 (Mishra et al. 2014). The average area of the triennium and its percentage changes in the three eastern Uttar Pradesh zones over a decadal period of total pulses. The area of total pulses has dropped in all three regions, save in the vindhyan zone.

Vindhyan zone has increased by 17.67% due to favorable weather conditions and adequate irrigation facilities. The triennium average of production and its percentage change has increased in the Vindhyan zone, but decreased in the North Eastern plain zone from 1980-81 to 1990-91. Because of the efficient use of fertilizer, production in the eastern plain zone is high. In all three productivity zones, the triennium average of total pulses has decreased. Although the area has grown, productivity has decreased dramatically due to unfavorable weather and inadequate irrigation facilities (Vani and Mishra 2019).

Triennium averages ending at year shown of space (in ‘000’ ha.), production (in ‘000’ tones) and productivity (in kg/ha) of total pulses and its dynamic pattern in North Eastern Plain Zone

Triennium averages ending at year shown of space (in ‘000’ ha.), production (in ‘000’ tones) and productivity (in kg/ha) of total pulses and its dynamic pattern in Eastern Plain Zone

Triennium averages ending at year shown of space (in ‘000’ ha.), production (in‘000’ tones) and productivity (in kg/ha) of total pulses and its dynamic pattern in Vindhyan Zone

The area under total pulses has nominal downfall at the rate of 1.68 per cent during the entire period under study. The positive growth rate is found 1.19 per cent in first period. However, the second and third period witnessed the negative growth rate of 4.07 and 1.84 per cent, respectively (Table 4).

Annual average simple and compound growth rate of the area, production and productivity of total pulses during a different period in the North Eastern Plain Zone

Similar is the case of production it has declined considerably at the rate of 1.06 per cent annually since 1980-81 onwards. The second period has experienced more downfalls at the rate of 5.21 per cent per annum as compared to negative growth rate of 2.23 per cent during third period. The productivity of total pulses has been found 0.62 per cent since 1980-81 onwards. The growth rate has been found to be more in first period i.e. 1.66 per cent. The negative growth rate is found 1.15 per cent during second period (Table 5).

Annual average simple and compound growth rate of area, production and productivity of total pulses during a different period in the Eastern Plain Zone

The total pulses has registered tremendous downfall in its area at the rate of 2.30 per cent annually since 1980-81 to 2014-15. It can also be seen from the above table that this decline is more prominent during third period 2.29 per cent as against 2.06 and 1.73 per cent during the first and second period, respectively. The production of total pulses has declined by the rate of 2.32 per cent during the entire period of study. The negative growth rate has been found during all periods. The overall period has registered a nominal downfall in the growth of productivity, i.e. by 0.02 per cent per annum. The maximum growth of productivity is 1.37 per cent during first period (Table 6).

Annual average of the simple and compound growth rate of the area, production and productivity of total pulses during different periods in the Vindhyan Zone

The area under total pulses has increased at the rate of about 0.67 per cent annually since 1980-81 to 2014-15. The increased in growth rate is prominent during the second period 1.49 per cent. However, the third period has witnessed negative growth rate of about 0.62 per cent. The production of total pulses has increased at the rate of 0.52 per cent annually. The maximum growth rate is obtained 2.87 per cent during third period as against 2.85 per cent during second period The productivity of total pulses has declined at the rate of 0.16 per cent annually. The maximum growth rate is obtained 3.49 per cent during third period (Table 6).

Instability index (in %) of Total Pulses during 1980-81 to 2014-15

In the table 7 high instability of total pulses has been found in case of area, production and productivity in Vindhyan Zone and low instability has been found in Eastern Plain Zone this shows that pulse crop is most stable in Eastern Plain Zone (Sahu and Mishra, 2014). From the table 8 of non-linear regression model shows the top two results of the zones of Eastern Uttar Pradesh.

Linear and Non- Linear regression models for total pulses in North Eastern Plain Zone, Eastern Plain Zone and Vindhyan Zone

Non-linear graph of North Eastern Plain Zone for different crops

Non-linear graph of Eastern Plain Zone for different crops

Non-linear graph of Vindhyan Zone

Eastern plain zone shows best result of R2 i.e. 8.38 in Weibull model,−6.48 Sinusoidal model in North Eastern plain zone and 1.83 MMF model in Vindhyan zone (Table 8). This shows that the value of R2 for total pulses in Eastern Uttar Pradesh shows beneficial results in all the three zone (Fig. 1 to 3).

 CONCLUSION

The data indicate that pulse productivity has increased annually in the North Eastern Plain Zone. Additionally, the Vindhyan Zone has the highest level of instability. As a result, officials at the state and national levels must initiate another mission-mode approach to boost pulse generation. Additionally, farmers must be provided with facilities and incentives for cereal production in general, and pulse production in particular. To supplement the supply of pulses in the current context, a public distribution system will not only provide pulses to the needy and improve nutritional security, but will also help stabilize prices and boost farmer incomes through secured procurement. Government procurement would give growers with enough marketing support. Alternative marketing structures such as contract farming and farmer producer cooperatives should be developed.

 ACKNOWLEDGMENTS

The work was supported by Act 211 Government of the Russian Federation, contract № 02.A03.21.0011.

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