Accelerating Farm Incomes (AFI) Baseline Report: Building Sustainable Soil Health, Markets and Productivity in Telangana State, India
Context The Government of India (GoI) aims to double farmers’ income during the next five years through various policies and strategies along with innovative technologies. A number of strategies are identified to promote sustainable intensification in terms of improving soil quality, applying integrated nutrient management, strengthening extension network, improving quality of livestock, promoting horticulture, etc. While most of these strategies are directed toward sustainable intensification, they are also likely to improve viability of agriculture. Apart from the government, private sector, private-public partnerships, and corporate social responsibility (CSR) initiatives are being encouraged in this direction. The Walmart Foundation awarded the International Fertilizer Development Center (IFDC) a development project titled “Accelerating Farm Incomes (AFI): Building Sustainable Soil Health, Markets, and Productivity in Telangana State, India. This AFI project has a 34-month intervention strategy starting in October 1, 2019. It is designed to strengthen and reorient agricultural production systems in the peri-urban agriculture (PUA) and rural areas of the Telangana State, India. The AFI project is being implemented in three districts of Telangana State – Mahabubnagar, Medak, and Rangareddy. The project aims to directly and indirectly enhance the productivity of 90,000 farmers by 25% and income by U.S. $200 per year. Directly the project would cover 30,000 farming households. It will contribute substantially to technology diffusion, capacity building, and micro-enterprise development. The project is expected to achieve an immediate impact on improved yields and increased farmer income through improved resource use efficiency and linking farmers with markets. Emphasis is on dissemination of good agricultural practices (GAPs), including improved technologies, to PUA farmers. The diffusion of improved technologies requires attention to both demand- and supply-side issues – to create farmer awareness and improve knowledge of the use and benefits of GAPs and technology (a precursor to demand growth) and concurrently to stimulate entrepreneurial investment in agro-input and quality product supply. A baseline survey is required to understand the current demographic situation and socio-economic conditions of the farm families, including current agriculture production and soil fertility management practices, and cropping systems, as well as market requirements and existing gaps. AFI Baseline Report 2 The baseline assessment will help identify appropriate interventions and forms the basis for monitoring and evaluation. The baseline data will be used to measure project impacts as defined by the results indicators, such as increased yields of selected crops, gross/net margins of farmers, increasing area under GAPs (use of good quality seed, balanced doses of fertilizers, and micronutrients, irrigation management, maintaining proper spacing in crop plantation, etc.), number of farmers reached by the project, and increased use of balanced fertilizers and soil amendments (micronutrients and organic soil amendments). The baseline will also help identify the existing market infrastructure and avenues in the project locations, number of markets/bazaars, trade organizations, farmer producer organizations (FPOs), supermarkets, etc. The focus will be on tracing the value chain for rice, vegetable crops, maize, and pulses. Approach For the purpose of the baseline survey, 1.3% of the targeted 30,000 households, i.e., 397 households, were covered in the three sample districts as per their respective size (number of farming households). As per the share of farm households, one mandal (sub-district) each in Rangareddy and Medak and two in Mahabubnagar were selected. In each mandal, villages were selected using the criteria of distance from the town/marketplace. The sample villages represent closest, farthest, and mid-reach locations (to markets). A sample of 33 households was covered in each village, keeping 10% leverage for poor responses. Accordingly, the sample size in Rangareddy district worked out to be 132,165 in Mahabubnagar and 100 in Medak. The sample is drawn in proportion to the actual distribution of farm-size classes in the sample villages to represent small, marginal, medium, and large farmers. Both qualitative and quantitative data were collected. Qualitative data were collected at the community and village levels. Qualitative methods, such as focus group discussions (FGDs), key informant interviews (KIIs), etc., were used to capture the perceptions pertaining to GAPs at the community level (FGDs) and with local (mandal) officials, extension workers, etc. (KIIs). The analysis was carried out at two levels – village/community level and household level – for various economic (farm size) groups in order to understand differences in performance. Qualitative assessment was used to complement as well as validate the quantitative analysis. Descriptive statistics were used to assess the yield gaps of various crops. Multiple regression analysis was used to identify the factors responsible for the existing yield gaps among the farmers. Production function analysis also helped to understand the resource allocation efficiencies. Results and Discussion The analysis helped in understanding the context, status, potential, and constraints for improving farm incomes in the selected districts. The following is a summary ofsome of the important aspects in this regard. These may be taken as pointers for designing the future interventions. 1. Some of the peri-urban villages are fast becoming urban in nature, as agriculture is no longer a priority. Farmers are more interested in non-farm avenues and unlikely to continue AFI Baseline Report 3 agriculture and learn GAPs. In fact, there may not be much cultivable land left for agriculture. While planning the interventions, the villages need to be assessed for their interest and demand for such interventions in order to avoid inefficient use of resources. 2. Land is not a constraining factor while water is a constraint. Water use efficiency is low, as most farmers allocate their water to water-intensive paddy crop, and they adopt flood irrigation. Though some farmers use micro irrigation (MI), it is mainly due to the subsidies they receive and area covered is marginal. There is good scope for improving water use efficiency and crop production through promotion of less water-intensive crops. Given the scarce water conditions coupled with heavy dependence on groundwater, there is potential to promote micro irrigation in the region. 3. Marginal and small farmers account for more than 75% of the farming households. They do not appear to have advantages in terms of access to resources, use of inputs (including labor), access to markets, etc. They no longer have the edge over medium and large farmers in terms of yield rates (land productivity). And, they are at a disadvantage position in terms of net returns. Focusing the interventions on these farmers would provide a better return on investment. 4. All the sample villages adopt a combination of two crop – paddy-pulses (red gram); paddyjowar; cotton-pulses (red gram); and paddy-maize. There are no major changes in cropping pattern in recent years. Only paddy and a few vegetables are grown during rabi season and the crop intensities are about 120%. Reallocation of water may help to increase the crop intensities. At present, area under vegetable crops is very marginal; the scope for increasing the area under vegetable, especially in the peri-urban locations, needs to be assessed and promoted for enhancing farm incomes. A shift away from paddy to low water-intensive crops with micro irrigation can substantially improve the area under protective irrigation and crop yields. Even the existing crops, such as cotton and maize, could be provided with one or two irrigations, which could enhance their productivity substantially. 5. Present input use is highly biased toward chemical fertilizers with nominal organic (farmyard manure [FYM]) applications. Farmers are not very familiar with using other organic manures, such as vermicompost, green manure, etc. There is a clear need for increasing the application of organic matter (at least doubling). Promoting vermicomposting and green manure preparation activities at the household level for self-consumption as well as a business model could be explored. 6. Labor is the single largest component of the cost composition. Of late, labor has become a constraining factor in the so-called labor surplus economy. Any crop changes or technology interventions need to consider this. That is, labor-intensive (even marginally) crop practices may not be acceptable or sustainable. Profit gains must be substantial in order to make them adoptable. 7. Given the low share of fertilizers in the total cost composition, there is little incentive to reduce or fertilizer use or use efficient fertilizer technology. At the same time, improved soil nutrition AFI Baseline Report 4 management could enhance productivity of some crops, such as cotton. Building awareness among farmers might help adoption of GAPs in this regard. 8. At the aggregate level, maize is the most profitable crop but is not grown everywhere. Constraints for expanding the area under maize need to be explored. However, blanket crop shifts may not be sustainable, as observed in the case of paddy and cotton in Mahabubnagar. While cotton is more profitable than paddy in all other locations, they are equal in Mahabubnagar. 9. Access to markets in the sample villages continue to be traditional (high dependence on traders and middlemen). Farmers neither use nor are aware of e-markets nor are they linked directly to urban markets or supermarkets. There are no FPOs functioning in the region. In the absence of evolved market systems, it is difficult to promote new crops, such as vegetables. Establishing better market linkages with improved price realization is critical for improving farm incomes. 10. The yield gap analysis indicates that there are wide variations in yields of various crops. These variations could be observed within the village, between the villages, and between the districts. This points to the potential for increasing the yield rates in the given agroecological and technological context. Bridging the yield gaps through adoption of GAPs in the present crop systems could result in a 9% increase in household income from agriculture. This can be further increased by reallocating the area under crops. Reallocating more area to cotton from other crops or reallocating the water from paddy (by reducing the area under paddy) to other crops could further increase the net gains. Gains from the latter (reallocating water) may increase the gains from the cotton crop as well. 11. There are wide variations in adoption of some of the GAPs across the farm households, villages, and districts. Low rates of GAP adoption and/or wide variations in adoption across farmers indicates the potential for reducing the yield gaps. 12. Factors explaining the variations in yield rates suggest that better soil nutrition and pest management practices could help enhance yields and incomes in crops such as cotton. Overall, there is potential for improving input management for enhanced crop performance. GAPs need to focus on soil nutrition and pest management practices. At the same time, labor and water are the main constraints and, hence, adoption of labor- and water-saving methods and approaches would be acceptable to the farming communities. 13. Apart from crop production, livestock rearing is a potential source of household income. In some of the sample villages, the share of livestock income in the total household income is as high as 20%. Identifying the potential and constraints for increasing the share of livestock in household income in the other villages could be a viable proposition. Increasing livestock holdings has the dual benefits of increasing the availability of FYM (organic matter) and providing regular cash income at the household and village levels. Besides, small farmers appear to gain more from livestock rearing. 14. Analysis of labor contribution in crop production confirms the “feminization of agriculture” argument, as women’s labor account for two-thirds of total labor use in crop production. Also, AFI Baseline Report 5 some of the villages have substantial number of women farmers. Women farmers/workers face different problems when compared to their male counterparts and, hence, their needs are expected to be different. Understanding their requirements and providing exclusive support (training and technologies) to them is critical for improving their conditions. The baseline assessment provides insights into the status and context of the three sample districts. Crop production in the sample villages is driven by resource and market constraints with little or no support from extension services. As a result, resource allocation inefficiencies and unsustainable farm practices are widespread. There is potential to increase farm income through better allocation of resources, enhancing input productivities, and greater price realization. Water use efficiency could be improved by shifting to low water-intensive crops and water-saving techniques (micro irrigation). This could be achieved within the existing cropping pattern and/or introducing new crop/farming systems that are acceptable and profitable to the farmers. Livestock farming is a viable complementary livelihood activity, which requires water, fodder, and market support. Labor availability appears to be a major constraint in these villages and, hence, any new intervention must take this into account. Improving access to markets and creating value chains need a broader policy push. Promotion of FPOs and other direct marketing arrangements at the village or cluster level could be prioritized. This would incentivize farmers to shift to nontraditional crops, such as vegetables, that are less water-intensive and more remunerative.
Crop production, Soil degradation, Nutrient management