Changing Cropping Pattern in Kheri District, Uttar Pradesh, India Moin Khan* and Ateeque Ahmad
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Economic Affairs, Vol. 64, No. 4, pp. 803-812, December 2019 DOI: 10.30954/0424-2513.4.2019.16 ©2019 EA. All rights reserved Changing Cropping Pattern in Kheri District, Uttar Pradesh, India Moin Khan* and Ateeque Ahmad Department of Geography, Aligarh Muslim University, Aligarh, Uttar Pradesh, India *Corresponding author: [email protected] (ORCID ID: 0000-0003-3780-9850) Received: 07-07-2019 Revised: 09-10-2019 Accepted: 21-11-2019 ABSTRACT The aim of this study is to examine the cropping pattern in Kheri District, Uttar Pradesh, India. This paper also estimated the changing cropping pattern at the block level between 2009-10 and 2014-15, how the choices of the farmers are changing for the alteration of crops with the time motivated by modern technologies, land disintegration, frequent flash floods, deforestation, fluctuation on the market, etc. Kheri district has been considered as the study area for this research paper. The study has been carried out at the block level. The data has been derived from the district statistical handbooks. Field visits and personal interviews have been done to fathom the real situations and motivating factors for the changing crop pattern. The findings demonstrate that there is a net loss in the cropped area in the district during 2010 and 2015. The crop pattern changed in these five years. The area under cereal crops declined and sugarcane cultivation accelerated. Market and flash floods were the main factors to affect the acreage of the crops. Highlights m Being a major producer of sugarcane in the country, Kheri district is gaining the area under sugarcane cultivation with the time. Keywords: cropping pattern, agriculture, Kheri district Cropping pattern refers to the proportion of area (Shiyani and Pandya, 1998, Mandal, 2010,). Many under various crops at a point of time, change in researchers suggested in 1980s and 1990s that poor this distribution over a period of time and factors farmers are risk adverse-i.e. they are supposed to affecting this change in distribution (Misra & Puri, accept low income but with low risk than being 2011). In fact, the Cropping pattern is a dynamic excited to get higher income attached with higher concept as it changes with time and space. In risk (Binswanger 1980; Antle 1988; Anderson and any particular area, it is subjected to change from Dillon 1992; Ali and Ali 2006). time to time with the affecting conditions. The Indian agriculture growth in the post-independence cropping pattern of an area is largely determined period can be identified in four different periods- by the physical, socio-cultural and historical factors the pre-green revolution phase, the first phase (Akhtar, 2015). Cropping patterns concerned with of the green revolution, second phase of green the extent to which the arable land under different revolution and liberalization phase (Subrahmanyam agriculture can be put to use (Singh and Dhillon, and Shekhar, 2003). Since, the advent of green 2005; Seitinthang, 2013,). A diversified cropping revolution in India, agriculture pattern has pattern is considered a good strategy to cope with risk and uncertainty associated with agriculture How to cite this article: Khan, M. and Ahmad, A. (2019). Changing caused by climatic and biological vicissitude cropping pattern in Kheri district, Uttar Pradesh, India. Economic Affairs, 64(4): 803-812. Khan and Ahmad undergone substantial transformation, much production. Rice and wheat are other important of which is reflected in the changing cropping crops throughout the district. pattern of the country. Consequently, a significant variation in the cropping pattern throughout India Literature Review has been witnessed (Dhinsa and Sharma, 1995). Ghosh (2011) examined cropping pattern changes After the introduction of modern technologies, in Indian Agriculture in the duration of 1970-71 to monoculture of commercially important crops, 2006-07. It has been found out the cropping pattern intensive cultivation of high yielding varieties, in India in terms of area under cultivation is skewed overlapping of cropping seasons and excessive use towards food grains. However, the farmers, recently, of agrochemicals have increased the potential of adopted some popular non-food grain cash crops pests and diseases (Shetty, 2004). such as sugarcane, oilseeds cotton, and vegetables The proportion of area under different crops at a (Bhalla and Singh, 1997). The crop pattern of a point of time is referred to as the cropping pattern specific area is influenced by various factors like of that particular area or region. A number of the spread of irrigation leading to area shrinkage of factors are responsible for any specific cropping dry crops, the technological change among crops, pattern of a region, therefore, cropping pattern is market intervention and support by the government prone to change every year with the variability of in particular crops but not in other crops, and, various factors affecting the crops. For example, perhaps the most important of all, the changing the cropping pattern of India is determined by the relative prices between different crops (Ray, 1983, intensity of monsoon to a great extent. In the years, Datewala, 1986). However, in the Mekong Delta, when the monsoon is good, rice is widely planted the rice cropping pattern drastically changed. In the throughout the country while in the monsoon failure tide-affected floodplain (middle reach of the delta), years, the dry crops like bajra, maize, groundnut, new methods like direct-seeding sa chai replaced urad, sesame, etc. which need less amount of water the conventional double transplantation and year- are largely cultivated. Although, the disintegration round cultivation replaced single cropping. The of lands with increasing population, market failure, cultivation of floating rice in the high flood plains and environmental risk leads to the introduction was reduced by the acceleration in the cultivation of new copping pattern. Besides, the crops are of high-yielding rice varieties (Fukui 1974, Chiem also intensified with the help of modern means 1994). of technology and HYV (High Yielding Variety) In Egypt, there was a significant decline in the seeds that also resulted in the crop specialization. area under onion, garlic, barley, flax, chickpeas, For Instance, two crops of rice are being cultivated lentil, fenugreek and lupine crops since they in the semi-arid region of Punjab, Haryana and were considered as non-strategic crops. However, Western Uttar Pradesh with the help of modern strategic crops such as wheat, maize, clover, rice, means of irrigation. sugar and cotton experienced no change (Boustani Agriculture is the predominant economic activity & Moahammadi 2010; Osama et al. 2017). While in Kheri district. Indian Census 2011 revealed discussing the usefulness of alternative levels of that about 65 percent of the main and marginal water use over the fixed yield approach when workers were engaged in agriculture and this sector there is a restraint on water. In the multi-crop farm supports nearly 80 percent of the population directly models used, a water production work for each crop or indirectly, which explicitly shows the over- could be incorporated so that one has the decision dependency of the population on agriculture. Lying of choosing alternative levels of water use on the in the Terai plains of India, Kheri district exhibits basis of water availability (Kumar and Khepar, fertile land and adequate amount of underground 1980). Crop diversity affected yields in three crops, water which helps in the acceleration of agriculture the strongest effects of crop rotation were on maize, productivity. The overall economic development where overyielding was over 100 percent in some of district is largely depending on the progress treatments. In the period of three years, a significant of agriculture sector. Kheri district is widely positive linear relationship was reported between notable for the sugarcane cultivation and sugar the number of crop species in the rotation and Print ISSN : 0424-2513 804 Online ISSN : 0976-4666 Changing Cropping Pattern in Kheri District, Uttar Pradesh, India maize yield (Smith et al. 2008). In India, the cropping Methodology pattern in Assam state is highly disturbed every The present study is based on secondary sources year by the frequent floods. The crops, livestock of data. The data has been calculated from the and property are damaged every year, therefore, the district statistical handbook of Kheri district of farmers had to adjust their cropping pattern every respective years. The cropping pattern of the district year (Mandal 2010). There was very little change has been examined by taking into account nine in cropping pattern in Manipur state during the significant crops- rice, wheat, sugarcane, oilseeds, period under investigation. The district in Imphal pulses, fodder, maize, vegetables and barley. Rice is valley experienced significant change under the produced twice in a year in the Kharif season and influence of modern technologies while the hilly Zayed season, both are included in the calculation. districts continued with the traditional type of Oilseeds consist of mustard, peanuts, sunflower,alsi, shifting cultivation (Seitinthang 2013). The cropping til, soyabean. Moreover, the main crop pulses that pattern of Jammu and Kashmir union territory are recorded in study are arhar, peas, gram, masur, was traditionally subsistence having no surplus or moong, and urad. The area under the cultivation of negligible amount of products. But the advent of potato and onion is included in the vegetables. The New Agricultural Strategy, the cultivation of high- percentage area under different crop to the total value crops had accelerated. These crops aided in cropped area in the year 2009-10 and 2014-15 was employment generation, poverty alleviation, income calculated and the changes in the cropping pattern augmentation and export promotion (Akhtar 2015). in these five years were assessed. MS office and A total of 177 cropping patterns in the whole Bogra ARC GIS 10.2 were used in the data analysis and region.