Assessment of profitability, sustainability, and system productivity of conservation agriculture-based crop diversification in light soils of Prakasam District, Andhra Pradesh

Introduction

The livelihoods of millions of subsistence farmers are supported by rainfed agriculture, which accounts for nearly 51% of the net sown area in India (www.agriwelfaregov.in). Nevertheless, these regions are notoriously susceptible to erratic rainfall, terminal moisture stress, and low soil fertility, which frequently lead to unstable crop yields. Conservation agriculture (CA) practices, in conjunction with agricultural diversification, provide a viable approach to improving sustainability, profitability, and productivity in such fragile ecosystems (Pushkar deva et al., 2023) [14] . Crop diversification, which involves the integration of crops, particularly cereals and legumes, through intercropping, crop rotation, and integration, not only mitigates production risks but also enhances resource utilisation efficiency and guarantees household food and nutritional security. Diversified systems are more resilient to climatic variability because they exploit various rooting depths, enhance nutrient cycling, and utilise soil moisture over a longer period (Beillouin et al., 2021) [6] . Prakasam District is characterised by southern light soils, which are characterised by low fertility and water retention, weak organic matter, and a propensity for crusting. These soils range from sandy loam to sandy clay loam. In Kharif, it has been reported that there is diversification index of approximately 0.8, which is significantly higher than that of other districts. Prakasam has one of the highest levels of crop diversification in Andhra Pradesh. Diversification is positively correlated with an increase in agricultural and horticultural Gross Value Added (GVA), which is facilitated by market access, finance, and phosphorus inputs. Diversified cultivation results in increased farm income, particularly in regions with restricted irrigation and larger farm sizes, according to research published in AP (Venkata Subbaiah et al., 2024). However, tenant farmers and small farms encounter additional obstacles to its implementation. In the rain-fed regions of Prakasam, there is a requirement for a novel agronomic practice and an efficient cultivation system that can withstand moisture stress, thereby providing improved yield stability and economic returns during the rabi season (Ram et al., 2014) [15] . In addition to diversification, conservation agriculture practices, including the incorporation of above-ground biomass and the implementation of beneficial soil microbial solutions, are essential for the enhancement of soil health, the reduction of erosion, the conservation of scarce precipitation, and the enhancement of soil organic carbon. These practices contribute to the development of soil structure, the regulation of soil temperature, and the enhancement of infiltration, thereby fostering a more conducive environment for crop growth in rainfed environments (Anurag and Aarti, 2025). The combination of crop diversification and conservation agriculture is a comprehensive approach to rainfed cultivation. In addition to contributing to long-term sustainability by restoring soil fertility, enhancing biodiversity, and mitigating the deleterious impacts of climate change, they also stabilise yields and improve farm profitability. (Dubey et al., (1991) [7] .

Materials and Methods

A field experiment was conducted at the agricultural research station Darsi, Prakasam district of Andhra Pradesh during the kharif and rabi seasons of 2022-23, 2023-24, and 2024-25. The experimental site is situated at an elevation of 110 m above mean sea level, between 15.7701 o N latitude and 79.6793 o E longitude (www.mapsofindia.com). The region experiences a sweltering and humid monsoon, which is followed by a mild winter. The average annual precipitation is approximately 463.51 mm. During the summer, the maximum temperature can reach 45.0 °C, while the minimum temperature can drop to 24.0 °C in the winter. Sandy loam soil with a medium organic carbon content (32%), low nitrogen (~180 kg ha⁻¹), medium phosphorus (~12 kg ha⁻¹), and medium potassium (~160 kg ha⁻¹) was present at the experimental site. The soil was saline-alkaline (pH range 7.9-8.2) (Vijay Kumar,2009) [17] . Experiment was carried in split plot design with three replications. Treatments (Cropping systems) are sole Redgram, sole Bajra, Redgram + Korra (Intercropping system) and Cowpea (rabi season crop) in place of kharif bajra. Varieties used were Redgram: LRG-52, Bajra: WCC-75, Korra (Little millet): Lepakshi and Cowpea: TPTC 29. Recommended package of practices for each respective crop were followed. Soil organic carbon was estimated by Walkley-Black chromic acid wet oxidation method(www.fao.org)

Data Analysis

The recorded crop yield and economic data were analyzed to assess the comparative performance of different cropping systems. The following indices and formulas were used:

Redgram Equivalent Yield (REY)

To compare yields across systems, all yields were converted into Redgram Equivalent Yield (REY) on a price basis: REY = Yi × (Pi / P redgram) Where: Yi = yield of intercrop/crop (kg ha⁻¹) Pi = price of intercrop/crop (Rs. kg⁻¹) P redgram = price of redgram (Rs. kg⁻¹).

Relative Economic Efficiency (REE)

The Relative Economic Efficiency compares the economic advantage of a cropping system over sole redgram: REE (%) = [(NRcs -NRsr) / NRsr] × 100. Where: NRcs = Net return from cropping system (Rs. ha⁻¹) NRsr = Net return from sole redgram (Rs. ha⁻¹).

Sustainable Yield Index (SYI)

The SYI measures the sustainability of cropping systems across years: SYI = (Ymean -σ) / Ymax. Where: Ymean = mean yield of the system (kg ha⁻¹) σ = standard deviation of yield across years, Ymax = maximum yield observed across treatments and years.

Land Use Efficiency (LUE)

The LUE estimates the extent of land utilization in a year: LUE (%) = (ΣDc / 365) × 100 Where: ΣDc = total duration of crops in the system (days).

Economic Analysis

Economic performance was evaluated based on Gross Returns, Net Returns, and Benefit: Cost ratio using the following formula: B:C ratio = Gross Return / Cost of Cultivation. The data was analysed statistically using analysis of variance techniques. Agri-Analyze software was used for analysis.

Results and Discussion

The analysis of variance conducted over two consecutive years for yield and soil organic carbon (%) revealed that cropping systems (main plot treatments), component crops/management techniques (subplot treatments), and their interactions all had a significant impact on system productivity. The replication effect is significant (p = 0.020408, p = 0.0195) (Table -1, Table-2) which reflects field heterogeneity. The main plot factor (different cropping systems) had a highly significant effect (P= 0.0004, 0.00041). This indicates that the choice of cropping system strongly influenced system productivity. The subplot factor also shows a highly significant effect (p = 7.1 × 10 -11 , 7.01 × 10 -11) which means subplot treatments contributed substantially to productivity variations. Indicates strong effects of management practices or intercrops. The interaction effect is highly significant (p = 1.7 × 10⁻⁵, p = 1.69 × 10⁻⁵) (Table -1, Table-2). This shows that the performance of subplot treatments depends on the main plot treatments. For example, a subplot practice (like cowpea in rabi) may perform better under redgram than under bajra. Hence, best treatment recommendations should consider specific crop combinations rather than main/sub-plot effects in isolation. Error component depicts that experiment was done with acceptable precision similar kind of findings was reported by Kumar et al (2012) [11] . Analysis of variance for Soil organic carbon (%) results show Replication effects (P= 0.0039) Main plot effects (p = 1.9 x 10 -05) and Subplot effects (4.8 x 10 - 11) were also highly significant (p < 0.01) (Table-3, This indicates that both cropping systems and their combinations with component crops strongly influenced productivity, profitability, and sustainability, with interaction showing that the effect of a subplot was highly dependent on the main plot system. Similar kind of findings was reported by Wanjari et al,2004 [2] and Jat et al 2011 [1] respectively. However, the main plot × subplot interaction was not significant (0.1183), suggesting that in the performance of subplot treatments was relatively stable across cropping systems. the constancy of main plot and subplot relevance across both years clearly shows that cropping system selection and the inclusion of component crops are the primary drivers of yield and system performance under rainfed conditions. The shift in interaction significance over time demonstrates the influence of climatic variability and rainfall distribution on treatment responses, as is common in rainfed ecosystems. Overall, the pooled ANOVA results over years show that cropping systems and component crops have a considerable impact on system productivity, economic efficiency, and sustainability. This highlights the significance of crop diversification techniques in stabilising yields and increasing farm returns under rainfed circumstances. Similar reports were communicated by Prasad et al., (2013) [13] [12] suggested similar kind of reports (Table - [9] respectively. Land Use Efficiency (LUE): The time-wise use of land was highest in Redgram + Korra (63.12%), indicating prolonged and efficient utilization of land resources. Sole Redgram (54.36%) and Cowpea (48.77%) were moderately efficient, while sole Bajra (32.14%) had the poorest land utilization, leaving land fallow for longer durations. Profitability (Rs/day/ha): Profitability expressed as daily net return per hectare further supported these findings. Redgram + Korra (₹400.56 ha⁻¹ day⁻¹) was the most profitable system, followed by sole Redgram (₹241.35 ha⁻¹ day⁻¹) and Cowpea in rabi (₹220.12 ha⁻¹ day⁻¹). Sole Bajra (₹57.50 ha⁻¹ day⁻¹) was the least profitable system. Similar kind of reports have been made by Kaushik et al., (2018) [10] (Table -10).

Conclusion

The results clearly indicate that Redgram + Korra intercropping under BIM is the most productive, profitable, and sustainable cropping system in rainfed conditions. It not only ensured higher system productivity and economic returns but also maintained yield stability and improved resource-use efficiency. Sole Bajra, on the other hand, was the least efficient and least sustainable option. Thus, legume-based diversification, particularly Redgram + Korra intercropping, offers a superior alternative to monocropping systems, ensuring both short-term profitability and long-term sustainability in rainfed farming systems.

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