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Statement of the Problem

Farmers choose crops for cultivation based on a variety of criteria including physical, social, and economic considerations. They may plant a variety of crops on their farms and rotate a specific crop combination throughout time. However, it is worth noting that the best farming techniques always include certain cropping patterns and cropping systems to increase productivity and maintain soil fertility.

A cropping pattern refers to the proportion of land under cultivation of various crops at different points of your time. This indicates the time and arrangement of crops during a particular acreage. Changing cropping pattern would cause changes within the proportion of land under different crops, space sequence and time of crops.

The cropping pattern in India is mostly determined by the average rainfall, temperature, climate, technology, and the type of soil used for agriculture. The different patterns of cropping are practised to obtain the maximum yield. A cropping pattern that evolves across time and space is a dynamic idea. It can be defined as the percentage of land covered by diverse crops at any given period. In other terms, it is a yearly pattern of sowing and fallowing on a certain region. Cropping patterns in India are influenced by rainfall, climate, temperature, soil type, and technology.

Cropping patterns in India can be depicted by using the primary crops as the base crop and all other possible alternative crops as alternative crops. It is critical to recognise crops and their agro-climatic conditions to categorise them. Wheat, barley, and oats, for example, are grouped.

The soil types and climatic characteristics that govern the entire agro-ecological setting for sustenance and the acceptability of a crop or set of crops for production dictate Indian agriculture. In India, there are three distinct agricultural seasons: Kharif, Rabi, and Zaid. The Southwest Monsoon kicked off the Kharif season, allowing for the production of tropical crops such as rice, cotton, jute, jowar, bajra, and tur. The Rabi season begins in October-November with the arrival of winter and concludes in March-April. Zaid is a short-term summer farming season that begins after Rabi crops have been harvested.

Variation in cropping systems has been one of the main characteristics of Indian agriculture and it is credited to rain-fed agriculture and existing socio-economic condition of crop growing community. Fundamentally, cropping pattern entails the proportion of area under various crops at a point of time. Cropping pattern is, however, a dynamic notion as it changes over space and time. Cropping systems of an area are decided by several soil and climatic parameters which determine overall agro-ecological setting for nourishment and appropriateness of a crop or set of crops for cultivation. However, at farmers’ level, potential productivity and financial benefits act as guiding principles while opting for a particular crop/cropping system.

These decisions with respect tochoose of crops and cropping systems are further narrowed down under influence of several other forces related to infrastructure facilities, socio-economic factors and technological developments, all operating interactively at micro-level. These factors are:

1. Infrastructure Facilities: Irrigation, transport, storage, trade and marketing, post-harvest handlig and processing etc.

2. Socio-economic Factors: Financial resource base, land ownership, size and type of land holding, household needs of food, fodder, fuel, fibre and finance, and labour availability etc.

3. Technological Factors: Enhanced varieties, cultural requirements, mechanization, plant protection, access to information, etc.

In the study area, agriculture is still mainly subsistent in character. As a result, the food grain crops occupy over 76 per cent of the gross cropped area. The study area grows almost each and every crop. Among the cereals maize and rice rank first and second correspondingly. Soyabean, mango and vegetables are the major cash crops.Among pulses; black gram, green gram, pigeon peas are important. The subsistent cropping patterns of the study area are based on consumption of the natural fertility of the soil without the much use of contemporary inputs and technology.

Study Area

Banswara district is situated in the southern most part of the Rajasthan state and lies between 23⁰11′ to 23⁰56′ N latitudes and 73⁰ 58′ to 74⁰ 49′ E longitudes. It is surrounded by Pratapgarh district in the north, Ratlam district of Madhya Pradesh in the east, Sagwara and Aspur tehsils of Dungarpur district in the west and Jhabua district of Madhya Pradesh in the south. The district also touches boundary of Panchamahal district of Gujarat in the south-west. The Vagad Region represents a rugged terrain undulated by short ridges in west of Banswara while the eastern part is occupied by flat-topped hills of the Deccan Trap. It also has the southern end of the Aravalli Mountains.

The district occupies prominent place in the Agro-climatic Zone-IV B, i.e., Humid Southern Plain Zoneof Rajasthan comprising 8 Sub- Divisions, 12 Tehsils and 8 Panchayat Samities. The total geographical area of the district is 453,612 ha, accounting 1.31 per cent of the total area of the Rajasthan State. The total Gram Panchayats and Revenue Villages in the district are 346 and 1532, respectively.

The River Mahi is the important source of canal irrigation by covering an area of 64,503 ha (60.28 per cent). The district is drained by Mahi River and its tributaries namely Anas, Haran and Chap in which Mahi and Anas are the only perennial rivers. River Mahi enters the eastern part of the district south of village Ambapara flows in the northerly direction. It takes sudden westerly turn near Sarodia. At Dhalwara, it takes a south westerly course, flowing along the boundary between Banswara and Dungarpur districts before entering the Gujarat state.

The principal source of irrigation in the district is canal in all tehsils except Kushalgarh where only groundwater is used for irrigation. Groundwater is utilized through dug-wells, dug-cum-bore wells, and tube-wells. Canal irrigation is mainly available by Mahi Dam Project. Tanks also form an important source of irrigation in the district. The constant rise in population, urbanization, industrialization and agricultural growth has caused decrease in per capita availability of water. The details of the gross irrigated area by different sources are furnished in following table.

Table 1: Source-wise Irrigated Area (Area in Ha)

S. No.	Tehsil	Total Irrigated Area	Tube-wells & wells	Ponds & Tanks	Canals	Dug-wells
1	Bagidora	19387	1527	247	11795	3246
2	Banswara	23390	1469	698	16608	3191
3	Garhi	20703	351	580	12723	2297
4	Ghatol	22891	200	417	17893	2184
5	Kushalgarh	13857	285	2410	Nil	3249

Source: District Statistical Abstract, 2019-20

The agro-climatic conditions of the district are sub-humid and sub-tropical climate with mean daily minimum temperature varies from 11.8⁰C in January to 26⁰C in June. Likewise, the mean daily maximum temperature ranges from 21.8⁰C in January to 43.8⁰C in May. The average annual rainfall is about 82.59 cm.

Out of 4.53 lakh ha geographical area, 0.91 lakh ha is under forest, 2.24 lakh ha net cultivated area, 3.42 lakh ha gross cultivated area and 0.12 lakh ha pasture land. The area under irrigation is 1.07 lakh ha comparising 47.77 per cent of the net sown area. The main irrigation sources are canals, wells and tube-wells.

The soils of the district fall under two broad categories- Black soil and Red soil. Black soil is found predominantly in the district mostly in northern, southern, central and eastern parts. Red soil is mostly found in western portion of the district from north to south.

The total population of the district is 17.98 lakh with population density of 399 as against 201 in the State. Out of this, more than 75 percent population belongs to scheduled tribe category and 92.88 per cent population is living in villages. The literacy rate is 57.20 per cent. The 61.77 per cent farm families of the district belongs to marginal category followed by 20.56 per cent small, 12.65 per cent semi-medium, 4.68 per cent medium and only 0.34 per cent in the large farmer’s category.

Rehimaet al. (2013) initiated a primary study on 393 farmers to catch up the diversification status in Ethopia. The scenario of diversification has been seen by Margalef index of richness and Heckman two stage model. Probit and OLS has been worked out for estimating the factors affecting crop diversification in Ethopia. The variable gender has positive impact on diversification implying the probability of diversification is higher in female headed households. Further education, size of landholdings, number of plots and distance from market positively affects the diversification. The drivers such as knowledge about trade, association with social organization and fertility of plots have significant negative impact on crop diversification.

Joshi et al. (2004) identified determinants of agriculture diversification in South Asia. From the estimation, it was found that the agricultural diversification moved towards high-value commodities. It is because of the changing factors of development such as an increase in per capita income, changing food consumption patterns, increasing urbanization and infrastructure development. These drivers are encouraging for future growth and agricultural diversification. However, the degree of diversification has been seen less in most of the South Asian economies. It is because food security issues and the government policies are obsessed with self-sufficiency in cereals. Benin et al. (2003) found the factors of crop diversification of inter-and infra-specific diversity in Ethiopian Highlands. Physical and household characteristics of the farms such as livestock assets and the proportion of adults are showing statistically significant impact on diversity among and within cereal crops. Demographic aspects such as age of household head and adult education levels affect only infra-specific diversity of cereals.

Weiss and Briglauer (2002) estimated the impact of household characteristics on the dynamic on-farm diversification in Austria. The study has framed from 1980, 1985, and 1990 period of time and found that the small size of farms are more specialized than large size farms. Basavarajet al. (2016) explained nature, extent and factors influenced the crop diversification at the micro level in Gadag district in Karnataka. The primary data were collected from 30 sample in 1997, while the secondary data area under major crop groups were obtained to the period from 1998-99 to 2011-12. The results showed the growth rate is higher for area under horticultural crops and pulses as compare to area under cereals, oilseeds, fiber and other crop groups. The estimation revealed that proportion of cereal crop groups has fall down from 32.53 percent to 28.81 percent and that of fruits and vegetables has increased considerably from 0.10 percent to 0.25 percent for fruits and from 4.66 percent to 7.80 percent for vegetables. Further, farm size, gross irrigated area, and net return per farm were the major factors which influenced the crop diversification.

Kumar and Gupta (2015) present the performance of diversity in crops during 1990-91 to 2011-12 in India. Simpson diversification index has shown Indian agriculture system is changing from traditional survival agriculture system to high-value return system but it is not equally distributed across states as well as across different crop sub-sectors. The study also made efforts to know the determinants of crops diversification by using Fixed Effect Model (FEM). The results of FEM have shown that cropping intensity, average annual rainfall, and gross irrigated area to be the key factors of crop diversification. Based on the findings, it argued that policy support in terms of improved cropping intensity, gross irrigated area, insurance coverage, and infrastructure development need to be extended to the farmers. Dasgupta and Bhaumik (2014) described the role of crop diversification on agriculture growth along with the ‘expansion effect’ and ‘substitution effect’ in West Bengal. This study completely used secondary data from 1980-81 to 2009-10.

The results revealed that a major change in area under the crops (i.e., boro rice, oilseeds and potatoes) occurred due to substitution effect. The substitution effect has shown significantly negative and stronger than the expansion effect for aus, aman and pulses. However, in the case of fruits and vegetable both substitution and expansion effects have a strong and positive impact. Kumar et al. (2012) estimated the performance and determinants of crop diversification in four eastern states namely Bihar, Jharkhand, Odisha, and West Bengal of India. Tobit model was applied to find the factors of diversification. The regression outcomes found the technology, level of education, modern implements, and road connectivity has shown significant positive impact on diversification towards higher-return crops. The study also suggested that smallholders have a large interest for cultivation of horticultural crops.

Furthermore, outcome of the impact of crop diversification on income reveals that various type of economic benefit is associated with the diversified cropping pattern. It is found that the income level of the farmers has increased who diversified the crops. A study put forwarded by Rahman (2009) attempted to elaborate the economic determinants of crop diversity in farms of Bangladesh. The 406 sample of farmers in 21 villages have taken. Herfindahl, Margalef and Shannon indices have been used to compute the concentration, richness and evenness of crop, respectively. Logit and OLS have been used to identify the factors that affecting diversity in cropping pattern. The result of regression analysis explicit that likelihood of crop diversification is positively affected by farm size, owner operator, education of farmer, farmer’s membership in NGO’s and developed infrastructure region while it is negatively affected by less developed irrigation facility and decline price of fertilizers and animal power service.

Both primary and secondary data related to land use, cropping pattern and socio-economic life of the farmers are collected for the study. The primary data based on schedule are collected from 42 sample villages situated in the study area. The sample villages comprise all the characteristics to fulfil the attainment for the assumed objectives. The collection of data and information regarding irrigated area, irrigation intensity, cropping pattern, crop-ranking, crop intensity and efficiency, yield per hectare, income generation and change in socio-economic status of farmers as well as agricultural labourers is done based on schedule. The respondents were farmer, agricultural labourers, village heads and people engaged in allied activities. Whereas secondary data collected from various departments such as Irrigation, Land use and Agriculture, Krishi Vighyan Kendra, Udaipur; Maharana Pratap University of Agriculture and Technology, Udaipur, and Indian Meteorology Department, Banswara.

Outcome of the Study

Maize, rice, blackgram, soyabean and cotton are the predominent kharif crops; while wheat, gram and rabi maize are major rabi crops. In Zaid,vegetables cultivation is also a common practice. Cereal crops-maize and rice constitute 71.89 per cent of gross cultivated area followed by pulses (blackgram, pigeon pea and) 15.78 per cent and oilseeds 4.09 per cent (soyabean). The fertilizer consumption in the district is 40.7 kg/ha.

The common crop sequences are maize, rice, soyabean, cotton-fallow, kharif pulses-fallow, kharif pulses- gram under rainfed condition; whereas maize, rice, cotton, soybean gram, and soybean-rabi maize under irrigated conditions. The productivity of maize and rice are higher as compared to state average. Due to continuous efforts of State and Central Governments, social workers and NGOs for adoption of technologies, the agriculture scenario of district is diversifying. At present, the district has diversified agriculture scenario with number of field crops, vegetables, spices, medicinal crops, orchards and flowers. The total area under orchards (mango, guava and lime) and vegetables is more than 6000 ha.

Presently, seed replacement rate in maize is 67 per cent, cotton 100 per cent, kharif pulses 31 per cent, soybean 63 per cent, wheat 29 per cent, rabi maize 91 per cent and in gram it is 9 per cent. Due to diversification in agriculture chemical pesticides are gaining undue importance in the district, especially in cash crops like vegetables and soyabean by large farmers. Use of mechanical power like tractors, threshers and seed- cum- ferti drills is becoming indispensible due to labour problem in agriculture.

Table 2 : Crops Grown in Mahi Dam Catchment Area

S.No.	Types of Crops	Utilisation	Major Crops
1	Food grains	Crops that are used for human consumption	Maize, Rice, Millets, Pulses and Oilseeds
2	Commercial Crops	Crops which are grown for sale either in raw form or in semi-processed form	Sugarcane, Cotton and Oilseeds
3	Horticulture	Sections of agriculture in which Fruits and Vegetables are grown	Fruits and Vegetables

Source: Based on Field Survey

The Government of Rajasthan approves proposals worth Rs 2629 crore big boost for irrigation projects in Banswara district Rs 2500 crore approved for Upper High Level Canal from Mahi Project. The additional villages (121) included in command area under the project by covering an area of 41903 ha of 338 villages in Banswara to be irrigated. It also includes construction of 105 km long canal with a cost of Rs 129.19 crore approved for strengthening of Haridev Joshi Canal System.

To extend flow irrigation regime there exists widespread network of canal system. Out of total 80,000 ha originally envisaged CCA of Mahi Project, 44,060 ha is under Left Main Canal system and rest 35,940 ha is taken care of by Right Main Canal system. The total length of hitherto constructed canal network in original command is 1260 km which gives about 15.5 m length of channel per ha CCA. The major constraints in agriculture are:

1. Majority of farmers are marginal (67.23per cent) and small (22.69per cent);

2. Low productivity of livestock, oilseeds and pulses; and

3. Lack of processing industries,resulting large portion of benefit is going in the hands of middle men.

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