- Topics
- Feature
- Opportunities & Events
- Data
- Hindi Portal
- Topics
- Feature
- Opportunities & Events
- Data
- Hindi Portal
With changing climatic and market conditions, Indian agriculture sector needs appropriate transition in cropping patterns to ensure sustainability in growth of the sector and inclusiveness of land-constrained farmers in the intensification process.
The need for transition in cropping patterns has been accentuated further following the COVID-19 pandemic that has led to loss of non-farm livelihood opportunities for millions and thus created further pressure on agriculture. Nevertheless, promoting transition in the sector would require deeper understanding of the underlying factors and addressing them through appropriate intervention strategies.
A recent paper ‘Climate change and transition in cropping patterns: District level evidence from West Bengal’ in the journal Environmental Challenges attempts this for West Bengal that houses significant number of land-constrained farmers.
More than 8% of India's food production come from West Bengal that has just 2.7% of the total land area, but accommodates 7.6% of the population. Cultivators and agricultural labourers make up the vast majority of the state's population. However, natural disasters such as floods, landslides, droughts, cyclones affect agricultural production and yield in different districts.
The state is divided into six agro-climatic zones, which are located in three major agro-climatic regions, viz., the Eastern Himalayan Region, the Lower Gangetic Plain Region, and the Eastern Plateau & Hill Region.
Using panel data of 18 districts for the period from 2004 to 05 to 2013–14, the paper finds crop diversification, irrigation, fertilizer use, road connectivity and market and storage facilities as the major drivers of agrarian transition in favour of non-foodgrains.
In addition, the climatic factors such as relative humidity and variations in temperature also influence such transition. While the findings apparently suggest for further development of infrastructure facilities, sustaining the transition would also require agricultural education, extension services and development of human and social capitals in a decentralized manner to incorporate various local level dynamics.
This paper estimates panel data econometric models to identify and analyse the factors influencing farmers’ crop choice decisions toward non-foodgrains. Here, two alternative set of panel data models are specified to examine the impact of the explanatory variables on crop choice.
Initiation of economic reforms in 1991 opened up the domestic agriculture produce to the global market and created new opportunities for agricultural exports leading to greater diversification in cropping patterns toward non-food crops. The share of non-food grains as a percentage of total area cultivated has increased from 2004 to 05 to 2013–14 in five districts of West Bengal namely, Burdwan, Bankura, Darjeeling, Cooch Behar and Purulia.
Among these districts, Darjeeling has shown a significant increase in non-food crop cultivated area from 18.03% in 2004–05 to 42.53% in 2013–14, whereas there is only marginal increase in rest of the districts. Nevertheless, share of area under non-foodgrains in total area cultivated is more than 25% in Hooghly, 24-Parganas (N), Nadia, Murshidabad, Uttar Dinajpur Jalpaiguri, Cooch Behar and Darjeeling.
These districts have also registered high crop diversification index ranging from 0.71 to 0.86. Among all the districts, Nadia has comparatively higher share of non-food crop area (37.84%) along with the highest extent of crop diversification whereas Purulia has the least share (2.60%) with least crop diversification. Thus, one may expect a direct association between crop diversification and share of area under non-food crops.
The cropping patterns and crop diversification depend on a number of factors such as climatic conditions, nature of soil, irrigation facilities, expected profits, landholding size, labour availability, marketing and storing facilities, etc. In addition, cropping intensity is likely to depend largely on availability of seeds, fertilizers, irrigation, post-harvest processing, storage and marketing.
The study reveals a significant increase in irrigation intensity and hence groundwater extraction in Birbhum, Howrah, Hooghly, Darjeeling, Cooch Behar and Purulia, but the cropping intensity in some of these districts have fallen. Notably, crop diversification, cropping intensity and irrigation intensity have moved in the same direction in Medinapore (E), Medinapore (W), 24-Parganas (N) and 24-Parganas (S). It is vital to enhance food production in order to attain food security.
The district Howrah, 24-Parganas (S), Darjeeling and Cooch Behar witnessed a significant increase in fertiliser use over the years 2004–2014. On the other hand, the district, 24-Parganas (N) shows a marginal rise in fertiliser intensity. The rest of the district's fertilizer intensity has tremendously reduced in the given years.
Since irrigation is required for effective fertiliser use, a direct relationship between the irrigation intensity and fertiliser intensity is seen in the respective districts (except Birbhum, Hooghly, 24-Parganas (S), Nadia, Uttar Dinajpur, Malda and Purulia).
The above discussions suggest that there have been significant changes in the trends and patterns of key indicators such as change in cropping patterns in different districts of West Bengal. This section aims at identifying and analysing the factors that have influenced the cropping patterns in favour of non-food grains using panel data regression analysis.
The determining factors include environmental, institutional, technological, and economic. The key environmental variables that are included in the model are average annual rainfall, total annual rainfall, coefficient of variation of the monthly difference between the average maximum and minimum temperatures, and average relative humidity.
Road density, numbers of market yards, numbers of beneficiaries using warehouse and cold storage facilities are considered as infrastructure parameters in this estimation. Technological variables that are incorporated in the models are fertilizer intensity, crop diversification, and irrigation intensity.
The study suggests that presence of infrastructure facilities influence crop choice in favour of non-foodgrains. For instance, availability of better storage facilities and road networks would positively drive diversification of crops in favour of such crops. Similarly, improved market conditions provide conducive atmosphere for better bargaining power of the farmers along with low marketing costs. This facilitates disposal of produces at the right time and thus decreases post-harvest losses, particularly of perishable crops.
Here, the coefficients of average relative humidity and the variations in temperature are significant and positive, indicating that higher humidity and temperature are likely to influence crop choice in favour of non-foodgrains as an adaptation strategy.
The agro-climatic conditions tend to influence the farmer's adaptation measures to counter adverse effects of climate change and often it is observed that intercropping and mixed cropping strategies are followed in many parts of West Bengal.
This paper identifies the determinants of differences in cropping patterns in favour of non-foodgrains in West Bengal using district level panel data. It is found that crop choice decisions made by the farmers and hence cropping patterns largely depend on the infrastructure facilities (road density, warehouse and storage facilities and conducive market conditions), technology applied (crop diversification, irrigation intensity and fertilizer intensity) and ecological conditions (rainfall, humidity and temperature).
While various infrastructural factors including irrigation, fertilizer intensity and climatic aspects like humidity and temperature influence adoption of non-food crops positively, there is no significant impact of rainfall on crop choices. The findings suggest for efforts toward widening extension services including promotion of universal education among farming communities and investment in rural infrastructure development.
It is also important to raise capacities and capabilities of the farmers to adapt to the changing climatic conditions with appropriate cropping patterns. Nevertheless, further studies using primary data will provide useful insights to capture household level dynamics.
The full paper can be accessed here