Rice based integrated farming systems: An exploratory analysis

Abstract

In developing economies like India, achieving pro-poor growth and economic development depends on flourishing of agricultural sector and improved farmer incomes. The limited operational landholding sizes in Telangana (1 ha) and Kerala (0.18 ha), as per the Agricultural Census 2015-16, restrict horizontal expansion, making vertical intensification through efficient resource use essential. Integrated Farming System (IFS) is a practical strategy, combining complementary enterprises to ensure year-round income, employment, and food and nutritional security. With rice as the dominant crop, rice-based IFS have considerable importance, as these systems utilize the rice ecosystem efficiently and integrate fisheries, livestock, poultry, horticulture and other enterprises. This integration helps reduce production risk, promote resource recycling, and sustain livelihoods. Telangana is the leading producer of rice, and the state has the highest average rice productivity of about 6,338 kg/ha., surpassing the national average. But the semi- arid nature necessitates drought tolerant crops and sustainable farming practices such as Integrated Farming Systems (IFS) to maintain productivity and economic viability. Rice the staple food crop of Kerala is cultivated in limited land and the production is decreasing. Palakkad (AEU 10) is the granary of Kerala and is comprised of fertile lands that supports integration of various components to maximize productivity, year- round income and maintain ecological balance. Kuttanad is known as the rice bowl of Kerala that has unique paddy cultivation below Mean Sea Level (MSL), rice based IFS plays a very important role to ensure profitability, food security and resilience against natural hazards. Analyzing the rice based IFS models adopted by farmers provides insights into their structure and performance, which can inform better, location-specific rice based IFS models that maximize productivity, profitability, and resilience. With this background, a study on “Rice based Integrated Farming Systems: An exploratory analysis” was taken up to study the performance of selected rice-based Integrated Farming Systems in Telangana and Kerala, delineate the factors affecting the performance of rice based IFS, assess the perceived environmental benefits and to evolve strategies for improving the rice based IFS. From the three agro-climatic zones of Telangana, one district each was selected i.e. Jagityal from North zone, Nalgonda from South zone and Khammam from Central zone. From each selected district, three mandals were chosen, and from each chosen mandal, two villages were selected. Ten farmers with rice-based integrated farms were randomly selected from each village, resulting in a total of 180 farmers (60 per district). Also, ten extension personnel and ten agricultural scientists were selected from each zone (30 + 30), totaling the sample to 240 (180 farmers + 30 extension personnel + 30 scientists) from Telangana.

In Kerala, two major rice-growing tracts i.e., the Agro Ecological Unit Kuttanad (AEU 4) and Palakkad (AEU 10) were selected. From Kuttanad, the gram panchayaths Kumarakom and Kainakary were chosen, and from Palakkad, Muthuthala and Thrithala were selected. Fifteen farmers with rice-based integrated farms were chosen from each panchayath, giving a total of 60 farmers. Additionally, 30 extension personnel and 30 agricultural scientists were included as respondents, bringing the Kerala sample to 120 (60 farmers + 30 extension personnel + 30 scientists). Thus, the total sample size of Telangana and Kerala for the study was 360 respondents. More than half (53.33 %) of Jagityal and Nalgonda farmers, 70.00 percent of Khammam farmers, 66.67 percent of Palakkad farmers, and 46.67 percent of Kuttanad farmers were in medium level of perceived efficiency of rice based IFS in terms of productivity, profitability and employment generation. The overall trend indicates that the farmers were having medium perception about the efficiency of rice based IFS. Palakkad farmers average mean value is 4.24 which is higher than the other region farmers, followed by Khammam with average mean value of 4.09. The farmers from Palakkad and Khammam exhibited higher levels of perceived efficiency. The greater enterprise diversification and higher net returns from the rice based IFS positioned farmers from those regions to have higher perceptions. Farmers of Kuttanad recorded lower perception levels due to limited diversification and environmental constraints such as frequent flooding, soil salinity, and acidity. While farmers of Nalgonda had lower awareness about enterprise diversification. Performance analysis using the Performance Analysis Index (PAI), considering economic and social dimensions was developed. The PAI revealed that in all the regions the farms were performing better socially than economically. The detailed region wise analysis confirmed that Khammam district in Telangana had the highest performance score of 46.96, followed by Jagityal and Nalgonda at 40.12 and 35.48, respectively. In Kerala, Palakkad outperformed with a score of 53.64, while Kuttanad scored 34.35. The Classification and Regression Tree (CART) analysis classified the farms into high and low performing based on the performance mean score and identified net returns, livestock possession, social networks, members working on farm and off farm as the most influential performance indicators. In Jagityal, more than half i.e., 55.00 percent of the farms (Terminal Node (TN) 5, TN 6 and TN 7) were in low performing and 45.00 percent of the farms were classified as high performing (TN 8 and TN 9). A total of twenty-four rice based IFS models were delineated. The dominant models i.e. rice + other field crops + dairy + ox/bullock showed higher performance score with 52.40, followed by rice + other field crops + horticulture + dairy with 42.48. In rice + other field crops + dairy + ox/bullock model although the ox/bullock enterprise is not economically viable, the farmers continue to use these animals for agricultural operations due to their emotional attachment and adherence to traditional practices. At the same time, they complement animal power with mechanization and utilize animal waste to enhance soil fertility. Among Nalgonda farmers 68.00 percent of the farms (TN 6, TN 9, TN 10 and TN 11) were high performing and 32.00 percent of the farms were classified as low performing (TN 4 and TN 5). A total of twenty-three models were delineated. Out of the identified dominant models rice + other field crops + dairy + ox/bullock performed better with performance score of 42.57, followed by rice + dairy + poultry + small ruminants with 40.57, and rice + other field crops + dairy + poultry with 40.31.

In Khammam the TN 6 and TN 7 together about 63.00 percent of the farms were high performers. Whereas TN 3 and TN 4 comprising of 37.00 percent of farms are classified as low performing. Fifteen models were identified in Khammam district, and among the predominant models rice + other field crops + horticulture + fodder + dairy + poultry showed high performance with 53.13 score, followed by rice + other field crops + horticulture + dairy + poultry + small ruminants (50.03), rice + other field crops + horticulture + fodder + dairy (47.89), rice + other field crops + horticulture + dairy + poultry (47.33). Altogether in Palakkad 43.33 percent of the farms were classified as high performers, and the remaining 56.67 percent were low performing farms. Thirteen models were identified, and the predominant models that exhibited high performance are rice + horticulture + dairy + goat + poultry + biogas + apiculture (64.59), rice + horticulture + fodder + dairy + poultry + fish (62.19), rice + other field crops + horticulture + dairy + poultry + biogas (57.11), rice + other field crops + horti + dairy + poultry (53.03), rice + horticulture + dairy + biogas (52.99), rice + horticulture + dairy + goat + poultry (52.97), rice + horticulture + dairy + poultry + fish + biogas + apiculture (52.69),rice + horticulture + dairy + poultry (50.18), rice + horticulture + dairy (47.83). Further in Kuttanad it is identified that 37.00 percent of the farms were high performing and 63.00 percent of the farms were classified as low performing. Out of the seventeen models identified in Kuttanad, rice-fish + horticulture + nutrition garden had high performance score of 41.38. The farmers of this model were having coconut plantations along the rice bunds ensuring higher returns. Partial Least Square Structural Equation Modelling (PLS SEM) identified key factors influencing rice based IFS performance. In Telangana, annual farm income, farm factors, and farmer factors significantly improved performance, and farmer factors also correlated positively with the use of communication channels. The PLS SEM of Kerala confirmed that communication channels, farm factors, and farmer factors all had a significant positive effect on performance, with farmer factors also enhancing communication channel utilization. This highlights the role of farmer attributes in driving rice based IFS outcomes. A scale to measure the perceived environmental benefits of rice based IFS was developed using Exploratory Factor Analysis (EFA) and PLS SEM. The developed scale was administered among the stakeholders (Farmers, extension personnel and scientists) of both the states. It showed that in all the groups of stakeholders, the largest share of individuals were in medium level. Scientists of both states exhibited higher mean in perception and lower standard deviation (SD) values, indicating less variability in their perceptions. In contrast, farmers showed lower mean in perception and higher SD values, which reflects greater variability. Extension personnel and scientists tend to have the most consistent scores. The comparison of mean indicates that the scientists (57.40) have higher perception than the other two groups, while extension personnel (54.32) are in middle ground and have very close mean to farmers (52.40). The reason could be that the extension workers perceptions align more closely with farmers due to their frequent interaction. The key strategies aimed at improving the efficiency and productivity of rice- based IFS in Telangana include promotion of diversified rice based IFS models, promoting improved breeds of livestock and improved scientific management practices. The better/high performing farms of each region are to be scientifically assessed, refined and promoted for large scale adoption. Providing agriculture input dealers with updated agronomic information can enhance their facilitating role beyond input supply, making them vital for technology transfer. Persuading farmer factors through education, extension, and supportive networks would lead to higher performance of the farms in the region. Promoting risk mitigation strategies like crop and livestock insurance plays a crucial role in protecting farmers from unexpected losses. Promotion of Farmer Producer Organizations (FPO’s) and other farmer organizations is essential for strengthening the collective power of farmers. Establishing village level cold storage facilities helps reduce post-harvest losses. Encouraging farmers, farm women and rural entrepreneurs to process and add value to perishable products. Promoting the adoption of scientific storage techniques. To ensure the long-term productivity, farmers need more short-term subsidies, so the government should provide sustained financial support, such as low-interest loans, and grants. The major approaches to strengthen the performance of rice-based IFS in Palakkad include encouraging the cultivation of short-duration rice varieties. Promoting organic rice cultivation and developing local branding initiatives. Establishing small- scale rice based IFS units at the panchayat level. Regular maintenance of minor irrigation systems. Encouraging soil test-based fertilizer application. Investing in post- harvest infrastructure such as cold storages, milk chilling units, and vegetable collection centers to minimize spoilage. Promoting small-scale, farmer-friendly machinery, facilitating the use of drones for pesticide spraying, fertilizer application. Farmers should be encouraged to adopt the alternate wetting and drying method in paddy cultivation. Developing farm tourism in Palakkad can create alternative income sources and strengthening of group dynamics. The major strategies for Kuttanad include effective utilization of waterlogged paddy fields for fish cultivation before or after the rice-growing season. Encouraging farmers to grow vegetables on large bunds and in grow bags or sacks ensures efficient space utilization and additional income generation. Promoting agro-tourism through traditional rice farming experiences. Integrating fruit crops along field boundaries and promoting mushroom cultivation. Recognizing the ecosystem benefits, the paddy production bonus can be enhanced to reward farmers for maintaining these ecological functions.