Improving Water Productivity and Reducing Water and Energy Consumption in Rice Production Through Natural Farming-Based Management Practices in Southern India

Abstract

Natural farming (NF) has emerged as a promising agro-ecological tactic to enhance resource use and reduce dependence on synthetic agricultural inputs. However, comprehensive field-based evidence across diverse agro-climatic regions remains limited. This study assessed the effects of NF on water use, water and crop productivity, economic returns, energy consumption, and soil fertility across four agro-climatic zones of Andhra Pradesh, India, using a paired-field approach during 2023–2025. Compared with conventional farming (CF), NF reduced total water utilization by 16.1–39.0%, resulting in a 15.0–55.5% improvement in water productivity. Although rice yield declined marginally by 4.40–8.40% in the Southern, Krishna, and High-Altitude zones during some seasons, yields remained comparable in the Godavari zone. The cost of cultivation decreased substantially by 20.6–35.1%, while gross returns remained largely comparable between production systems, varying from −7.0% to +5.05%. Consequently, NF increased net returns by 8.8–29.0% and improved the benefit-cost ratio by 23.7–47.8% relative to CF. Irrigation-related energy consumption was reduced by 21.8–57.7%, indicating greater resource-use efficiency under NF. The sustainable yield index values remained high (0.68–0.91), demonstrating stable crop productivity despite reduced external inputs. Natural farming practices also improved soil health by buffering soil pH towards neutrality; soil organic carbon (SOC) enhanced from 0.38–0.73% under CF to 0.57–1.01% under NF. Similarly, available nitrogen, phosphorus, and potassium increased under NF. Overall, these findings demonstrate that natural farming improves water and energy productivity, reduces production costs, and increases farm profitability while maintaining stable rice productivity across diverse agro-climatic conditions. The results highlight the potential of natural farming as a climate-resilient and resource-efficient strategy for sustainable rice production in India.

1. Introduction

Rice (Oryza sativa L.) sustains more than half of the global population and plays a vital role in ensuring food security, particularly in South Asia [1,2]. India is the world’s second-largest rice producer, cultivating approximately 51.27 million hectares, producing about 150.18 million tonnes with average productivity around 2929 kg ha⁻¹ of rice annually [3]. However, maintaining this level of production is becoming increasingly difficult because of growing pressure on natural resources and changing climatic conditions. Among the natural resources, water is one of the most important ones for sustaining paddy farming and plays an important role in food security. India supports nearly 17.7% of the global population and is the world’s largest consumer of freshwater, with an annual demand of approximately 3000 billion m³ [4], making it the largest consumer of freshwater and largest extractor of groundwater (245 billion cubic meters) in the world [5]. Although India receives nearly 4000 billion m³ of annual precipitation, less than half is effectively stored in surface and groundwater systems because of runoff, river discharge, evaporation, and evapotranspiration losses [6,7]. Furthermore, nearly 88–90% of the extracted groundwater is utilized for agricultural irrigation [8]. Rice cultivation is one of the most water-demanding agricultural enterprises, requiring approximately 3000–5000 L of water to produce one kilogram of grain [9]. Among the other crops, the paddy crop has the highest rainfall effectiveness and higher water requirement [10,11]. This high-water requirement is largely attributed to the widespread practice of transplanting nursery-grown seedlings into puddled fields, a method used for nearly 75% of the global rice-growing area [12]. Besides intensive water use, conventional rice cultivation depends heavily on external inputs and energy, contributing to soil degradation, ecosystem deterioration, and environmental pollution [13]. In view of increasing demand for water for agriculture and other purposes, there is an urgent need for judicious use of water.

Natural farming (NF) has emerged as an agroecological production system that aims to reduce dependence on synthetic external inputs while enhancing ecosystem functions through biological nutrient cycling and improved soil health [14]. The approach emphasizes the use of locally available biological soil-enrichment formulations together with crop residue mulching, premoonson dry sowing (PMDS) with green manuring and a mixture of leguminous crops, biological pest management, crop diversification, and improved soil moisture management [15,16]. These practices are intended to stimulate soil microbial activity, improve soil organic carbon, enhance nutrient cycling, conserve soil moisture, and reduce cultivation costs while minimizing environmental impacts [17,18]. The soil and water conservation practices such as tank silt application, grass filters, mulching, application of FYM, etc., significantly improved soil fertility without the addition of any synthetic fertilizers [19,20,21,22,23,24].

Collectively, the literature suggests that NF’s productivity response is strongly conditioned by crop type, soil class, and local agroecological context—a pattern the specific evidence from Andhra Pradesh in this study is intended to help resolve.

An important research gap therefore concerns the integrated evaluation of farming-system performance. Existing studies have often examined individual dimensions such as crop yield, farm profitability, soil health, and water use and energy consumption, separately. Consequently, there is limited evidence from farmers’ fields that simultaneously evaluates resource use, productivity, economic performance, and soil health across contrasting agro-climatic environments. This limitation is particularly relevant for rice-based systems in Andhra Pradesh, where NF is being implemented at a large scale but its performance under diverse production conditions remains insufficiently documented. A multidimensional assessment is therefore necessary to determine whether reductions in external inputs and water use are accompanied by acceptable productivity, profitability, and soil-health outcomes.

Building on the evidence and research gaps identified above, the present study has the following research questions (RQ):

RQ1. To what extent does natural farming reduce total water use and improve water productivity in paddy cultivation compared with conventional farming across different agro-climatic zones and cropping seasons in Andhra Pradesh?

RQ2. How does natural farming affect irrigation-related energy consumption, rice yield, cost of cultivation, and economic returns, including gross returns, net returns, and benefit–cost ratio, under farmers’ field conditions?

RQ3. How does natural farming influence yield sustainability and soil health, as reflected by yield stability and key soil chemical properties (pH, soil organic carbon, and available N, P, and K) across different agro-climatic zones?

To address the above research questions, the present study was undertaken with the following objectives: (i) to evaluate the impact of natural farming practices on water and energy savings in paddy cultivation, (ii) to assess the impact of natural farming practices on crop productivity, profitability, sustainability, and soil health in a rice-based system. The findings are expected to provide scientific evidence on the capacity of natural farming to conserve natural resources while supporting sustainable rice production under diverse agroecological conditions.

The remainder of this paper is organized as follows: Section 2 presents the background and related literature on natural farming, with emphasis on crop productivity, water use, energy consumption, economic performance, sustainability, and soil health. Section 3 describes the materials and methods, including the study design, data collection, indicators, and analytical procedures. Section 4 presents the results, while Section 5 discusses the findings in relation to previous research and their implications for sustainable rice production. Finally, Section 6 presents the conclusions and implications of this study.

2. Background and Related Work

2.1. Natural Farming, Rice Productivity, and Economic Performance

Natural farming (NF) has shown contrasting effects on rice productivity across locations, indicating that its performance is strongly influenced by agro-climatic conditions, soil fertility, nutrient availability, and management practices (Table 1). Kumar et al. [25] reported higher NF productivity in Andhra Pradesh but lower productivity in Karnataka. Galab et al. [26] observed 5.18% and 6.83% lower paddy yields under NF during the Kharif and Rabi seasons, respectively, while Shyam et al. [27] reported an approximately 12.0% yield reduction. In contrast, Jayaraj and Periyasamy [28] and Saharan et al. [17] reported 15.4% and 6.60–11.5% higher yields, respectively. More recent studies also reported contrasting responses, including 21.4% lower yield under NF in North Coastal Andhra Pradesh [29] and 5.34% lower rice yield under traditional multi-nutrient NF [30]. Similarly, Ghasal et al. [31] reported substantially lower rice yield and economic returns under natural farming than integrated crop management, and Sidhu et al. [32] observed marked reductions in maize and wheat yields under complete natural farming because of nutrient limitations. Field comparisons in acidic Alfisols have reinforced this pattern, with NF yielding 14.4% less paddy than an intensively managed integrated-crop-management treatment even as it delivered the highest soil organic carbon and micronutrient status among the treatments tested [33] in contradiction of this, controlled trials in Andhra Pradesh and a large multi-farm household survey in Himachal Pradesh found NF sustaining comparable yields alongside improved soil quality and farm-level biodiversity outcomes, with no systematic yield penalty across participating farms [34,35,36].

Economic performance also varies among studies. NF commonly reduces cultivation costs through lower expenditure on synthetic fertilizers and pesticides, but the resulting profitability depends on the balance between yield and production costs. Babalad et al. [37] reported lower cultivation costs under ZBNF but also lower paddy yield and absolute returns, whereas Jayaraj and Periyasamy [28], Saharan et al. [17] and Shyam et al. [27] reported higher net returns despite lower cultivation costs and, in some cases, lower yields. Thus, assessment of NF performance requires simultaneous consideration of productivity, cultivation cost, and profitability, rather than yield alone.

2.2. Water Use and Energy Consumption

Andhra Pradesh has become one of the largest examples of large-scale adoption of natural farming through the Andhra Pradesh Community Managed Natural Farming (APCNF) programme, providing an ideal opportunity to evaluate its agronomic, environmental, and economic performance under farmers’ field conditions, and reported that water savings of up to 50% and farmer income gains of 38–66% under the programme [38,39]. An independent four-district survey by the Centre for Study of Science, Technology and Policy similarly found that NF plots required 50–60% less water and electricity than conventionally farmed plots across paddy, groundnut, chilli, cotton, and maize, translating into 45–70% lower input energy and 55–85% lower greenhouse-gas emissions for irrigated crops [40]. Farm-level economic evidence points the same way: Bharucha et al. [41] reported that the adoption of NF reduced production costs and improved farm resilience by decreasing dependence on purchased external inputs.

As shown in Table 1, most NF studies have not quantified total water use or water productivity. Evidence from alternative rice-growing practices demonstrates the potential importance of this dimension. Deelstra et al. [42] reported 33.4–55.8% lower water application, 104.5–168.2% higher water productivity, and 21.4–29.7% higher rice yield under alternative practices such as AWD, direct-seeded rice, and modified rice intensification compared with conventional paddy rice. Similarly, Carrijo et al. [43] demonstrated substantial water-saving potential from AWD, although yield responses varied with management and soil conditions. These studies provide useful benchmarks but do not directly establish the water-saving potential of NF.

Kumar and Jain [44] reported approximately 24.0% lower energy consumption under NF, while Lakhani et al. [45] reported 20.0–30.0% energy savings. Pagani et al. [46], using organic paddy systems as supporting evidence, reported more than 50.0% lower energy inputs with an approximately 8.0% yield reduction compared with conventional production. However, quantitative evidence linking NF with both water and energy savings under farmer-managed paddy systems remains limited.

2.3. Soil Health and Fertility

Improved soil health is a major rationale for NF, but reported effects are not consistent across indicators. Smith et al. [47] suggested that biological nitrogen fixation under zero-budget natural farming may provide only 52–80% of the nitrogen supplied through conventional fertilizer application, which can constrain yield in intensive systems. Shyam et al. [27] reported higher soil organic carbon and total nitrogen under ZBNF, while Saharan et al. [17] observed increased soil organic carbon and available micronutrients (Table 1). Darjee et al. [30] similarly reported improvements in soil organic carbon and microbial biomass under traditional multi-nutrient NF. Conversely, Ghasal et al. [31] found lower soil organic carbon and available N and P under NF than the comparison system. According to Mishra et al. [48], a four-scenario trial on rice-based Vertisol systems likewise found that conservation and organic management improved soil carbon and microbial indicators without necessarily matching conventional yields. These findings indicate that NF may improve selected soil-health attributes without necessarily producing uniform improvements in all soil fertility parameters. Therefore, assessment using multiple indicators such as pH, soil organic carbon, and available N, P, and K is necessary.

2.4. Synthesis and Research Gap

The literature summarized in Table 1 demonstrates that previous research has generated valuable evidence on individual aspects of NF performance, but these dimensions have rarely been evaluated together. Most studies have focused on yield and economics, soil health, or water and energy efficiency separately, and many were conducted at a single location or over a limited number of seasons. In particular, quantitative evidence integrating water use, water productivity, irrigation-related energy consumption, rice yield, cultivation cost, profitability, and soil fertility under the same NF–CF comparison is scarce. This limitation is especially relevant to Andhra Pradesh, where NF is implemented across diverse rice-growing environments. The present study addresses this gap through a multidimensional farmer-field assessment of NF and CF across agro-climatic zones and cropping seasons, enabling evaluation of both the benefits and potential trade-offs among resource conservation, productivity, economic performance, and soil health.

Table 1. Synthesis of previous research on natural farming (NF) vs. conventional farming (CF) and key sustainability indicators in rice-based systems.

Author(s)	Location	Farming System	Water Use	Water Productivity (WP)	Energy Consumption	Yield/Productivity Change Under NF vs. CF	Cost of Cultivation	Gross Returns	Net Returns	Benefit–Cost Ratio	Soil Health/Fertility Change	Research Gap
Carrijo et al. [43]	Global rice meta-analysis; 56 studies, 528 comparisons	AWD vs. continuous flooding	25.7% ↓	24.2% ↑	NR	5.40% ↓	NR	NR	NR	NR	NR	AWD reduces water use and improves WP, but yield response depends on AWD severity and soil conditions; not an NF study.
Deelstra et al. [42]	Guntur, Andhra Pradesh and Nalgonda, Telangana, India	AWD vs. conventional paddy rice	33.4–55.8% ↓	104.5–168.2% ↑	NR	21.4–29.7% ↑	NR	NR	NR	NR	NR	The study did not evaluate NF specifically or provide an integrated NF–CF assessment across multiple seasons and agro-climatic conditions.
Shyam et al. [27]	Andhra Pradesh, India	NF vs. CF	NR	NR	NR	12.00% ↓	23.90% ↓	NR	92.17% ↑	NR	SOC: 52.1% ↑; total N: 70.0% ↑	Limited soil sampling; yield penalty and variability require long-term, multi-location validation.
Kumar et al. [25]	Andhra Pradesh and Karnataka, India	NF vs. CF	NR	NR	NR	AP: 11.8% ↑; Karnataka: 14.3% ↓	AP: 5.4% ↓; Karnataka: 30.7% ↓	NR	NR	AP: 29.4% ↑; Karnataka: 256.8% ↑	NR	Water, WP and energy not quantified; soil-health evidence largely qualitative.
Galab et al. [25]	13 districts, Andhra Pradesh, India	NF vs. CF	NR	NR	NR	Kharif: 5.18% ↓; Rabi: 6.83% ↓	Kharif: 13.72% ↓; Rabi: 28.76% ↓	NR	Kharif: 8.52% ↑; Rabi: 47.59% ↑	NR	NR	No quantitative paddy-specific water, WP or energy assessment.
Shrine et al. [49]	Andhra Pradesh, India	NF vs. CF	NR	NR	38.15% ↓	13.06% ↑	6.24% ↓	3.14% ↑	77.41% ↑	9.73% ↑	NR	Water use/WP and soil-health changes not assessed.
Bharucha et al. [41]	Andhra Pradesh, India	NF vs. CF	NR	NR	NR	16.50% ↑ (rainfed)	23.70% ↓	14.20% ↑	50.00% ↑	NR	NR	Water, WP and energy not quantified; systematic longitudinal soil-health assessment required.
Koner and Laha [50]	West Bengal, India	NF vs. CF	NR	NR	NR	25.00% ↓	11.62% ↓	27.68% ↓	41.42% ↓	18.52% ↓ †	NR	One ZBNF cluster; no quantitative water, energy or measured soil-fertility assessment.
Babalad et al. [37]	Karnataka, India	NF vs. CF	NR	NR	NR	30.26% ↓	30.09% ↓	30.27% ↓	30.37% ↓	1.09% ↓	NR	Water, WP and energy not quantified
Laishram et al. [35]	Himachal Pradesh, India	NF vs. CF	NR	NR	NR	3.08–7.98% ↑	6.86–30.7% ↓	NR	NR	NR	NR	Water, WP, energy and soil fertility changes were not quantified.
Jayaraj and Periyasam [28]	Tamil Nadu, India	NF vs. CF	NR	NR	NR	15.38% ↑	27.29% ↓	15.38% ↑	114.69% ↑	59.15% ↑	NR	Single-district study; no quantitative water, energy or measured soil indicators.
Kumar et al. [51]	Visakhapatnam & Vizianagaram, Andhra Pradesh, India	NF vs. non-NF	NR	NR	NR	4.20% ↑	5.44% ↓	NR †	NR †	NR †	NR	Water/energy savings not quantified; NF practices not standardized; long-term controlled experiments needed.
Kumar et al. [51]	Mandya, Ramanagara and Tumakuru, Karnataka, India	NF vs. non-NF	NR	NR	NR	16.35% ↓	40.34% ↓	NR †	NR †	NR †	NR	Standardized NF practices and long-term controlled experiments needed.
Saharan et al. [17]	Kurukshetra, Haryana, India	ZBNF vs. farmer practice	NR	NR	NR	PR114: 11.54% ↑; CSR30: 6.56% ↑	PR114: 30.54% ↓; CSR30: 28.21% ↓	PR114: 16.08% ↑; CSR30: 45.00% ↑	PR114: 45.37% ↑; CSR30: 111.34% ↑	PR114: 67.18% ↑; CSR30: 102.38% ↑	SOC: 46.0% ↑; available P and micronutrients increased	Short duration; water/energy not quantified; long-term yield and nutrient dynamics require validation.
Manisha et al. [29]	North Coastal Andhra Pradesh, India	NF vs. CF	NR	NR	NR	21.42% ↓	15.45% ↓	6.38% ↓	27.44% ↑	10.24% ↑	NR	Water, WP, energy and soil health not quantified; limited spatial and temporal coverage.
Darjee et al. [30]	Gautam Budh Nagar, Uttar Pradesh	NF vs CF	NR	NR	NR	5.34% ↓ (rice)	NR	NR	NR	NR	SOC: 20.22% ↑; MBC: 37.51% ↑; MBN: 80.58% ↑	Water, WP, energy and economic indicators not reported; longer-term assessment required.
Ghasal et al. [31]	Meerut, Uttar Pradesh, India	NF vs. ICM	NR	NR	NR	51.17% ↓ (rice)	10.59% ↓	46.35% ↓	67.23% ↓	39.85% ↓	SOC: 8.33% ↓; N: 3.70% ↓; P: 34.00% ↓; K: 1.60% ↑	Substantial productivity/economic penalty; water, WP and energy not evaluated.
Athawale et al. [52]	Arunachal Pradesh, India	NF vs. CF	NR	NR	NR	11.89% ↓	29.49% ↓	14.79% ↓	17.06% ↑	NR	NR	Water, WP and energy not quantified.
Yadav et al. [53]	Kangra, Himachal Pradesh, India	NF vs. CF	NR	NR	NR	1.37–5.99% ↑	NR	9.04–29.80% ↑	NR	NR	NR	No integrated assessment of water, WP, energy and measured soil health.
Supraja et al. [54]	YSR Kadapa, Andhra Pradesh, India	NF vs. CF	NR	NR	NR	20.0% ↑	9.55% ↓	43.30% ↑	166.41% ↑	NR	NR	Single district and limited farmer sample; water, energy and soil-health indicators not quantified.
Majhi et al. [55]	Jagatsinghpur, Odisha, India	NF vs. CF	NR	NR	NR	NR	NR	NR	NR	NR	SOC: 4.65% ↑; N: 6.46% ↑; bacteria: 47.5% ↑; fungi: 40.12% ↑; actinomycetes: 70.4% ↑	Two-season study; water, WP and energy not quantified; long-term multi-location validation required.

NR—not recorded; AWD—alternate wetting and drying; PR114 and CSR30: rice varieties; SOC—soil organic carbon; N—available nitrogen. ↑ and ↓ indicate an increase and decrease, respectively. † Data derived from farmer surveys/on-farm observations, not replicated controlled on-station experiments.

Table 1. Synthesis of previous research on natural farming (NF) vs. conventional farming (CF) and key sustainability indicators in rice-based systems.

Author(s)	Location	Farming System	Water Use	Water Productivity (WP)	Energy Consumption	Yield/Productivity Change Under NF vs. CF	Cost of Cultivation	Gross Returns	Net Returns	Benefit–Cost Ratio	Soil Health/Fertility Change	Research Gap
Carrijo et al. [43]	Global rice meta-analysis; 56 studies, 528 comparisons	AWD vs. continuous flooding	25.7% ↓	24.2% ↑	NR	5.40% ↓	NR	NR	NR	NR	NR	AWD reduces water use and improves WP, but yield response depends on AWD severity and soil conditions; not an NF study.
Deelstra et al. [42]	Guntur, Andhra Pradesh and Nalgonda, Telangana, India	AWD vs. conventional paddy rice	33.4–55.8% ↓	104.5–168.2% ↑	NR	21.4–29.7% ↑	NR	NR	NR	NR	NR	The study did not evaluate NF specifically or provide an integrated NF–CF assessment across multiple seasons and agro-climatic conditions.
Shyam et al. [27]	Andhra Pradesh, India	NF vs. CF	NR	NR	NR	12.00% ↓	23.90% ↓	NR	92.17% ↑	NR	SOC: 52.1% ↑; total N: 70.0% ↑	Limited soil sampling; yield penalty and variability require long-term, multi-location validation.
Kumar et al. [25]	Andhra Pradesh and Karnataka, India	NF vs. CF	NR	NR	NR	AP: 11.8% ↑; Karnataka: 14.3% ↓	AP: 5.4% ↓; Karnataka: 30.7% ↓	NR	NR	AP: 29.4% ↑; Karnataka: 256.8% ↑	NR	Water, WP and energy not quantified; soil-health evidence largely qualitative.
Galab et al. [25]	13 districts, Andhra Pradesh, India	NF vs. CF	NR	NR	NR	Kharif: 5.18% ↓; Rabi: 6.83% ↓	Kharif: 13.72% ↓; Rabi: 28.76% ↓	NR	Kharif: 8.52% ↑; Rabi: 47.59% ↑	NR	NR	No quantitative paddy-specific water, WP or energy assessment.
Shrine et al. [49]	Andhra Pradesh, India	NF vs. CF	NR	NR	38.15% ↓	13.06% ↑	6.24% ↓	3.14% ↑	77.41% ↑	9.73% ↑	NR	Water use/WP and soil-health changes not assessed.
Bharucha et al. [41]	Andhra Pradesh, India	NF vs. CF	NR	NR	NR	16.50% ↑ (rainfed)	23.70% ↓	14.20% ↑	50.00% ↑	NR	NR	Water, WP and energy not quantified; systematic longitudinal soil-health assessment required.
Koner and Laha [50]	West Bengal, India	NF vs. CF	NR	NR	NR	25.00% ↓	11.62% ↓	27.68% ↓	41.42% ↓	18.52% ↓ †	NR	One ZBNF cluster; no quantitative water, energy or measured soil-fertility assessment.
Babalad et al. [37]	Karnataka, India	NF vs. CF	NR	NR	NR	30.26% ↓	30.09% ↓	30.27% ↓	30.37% ↓	1.09% ↓	NR	Water, WP and energy not quantified
Laishram et al. [35]	Himachal Pradesh, India	NF vs. CF	NR	NR	NR	3.08–7.98% ↑	6.86–30.7% ↓	NR	NR	NR	NR	Water, WP, energy and soil fertility changes were not quantified.
Jayaraj and Periyasam [28]	Tamil Nadu, India	NF vs. CF	NR	NR	NR	15.38% ↑	27.29% ↓	15.38% ↑	114.69% ↑	59.15% ↑	NR	Single-district study; no quantitative water, energy or measured soil indicators.
Kumar et al. [51]	Visakhapatnam & Vizianagaram, Andhra Pradesh, India	NF vs. non-NF	NR	NR	NR	4.20% ↑	5.44% ↓	NR †	NR †	NR †	NR	Water/energy savings not quantified; NF practices not standardized; long-term controlled experiments needed.
Kumar et al. [51]	Mandya, Ramanagara and Tumakuru, Karnataka, India	NF vs. non-NF	NR	NR	NR	16.35% ↓	40.34% ↓	NR †	NR †	NR †	NR	Standardized NF practices and long-term controlled experiments needed.
Saharan et al. [17]	Kurukshetra, Haryana, India	ZBNF vs. farmer practice	NR	NR	NR	PR114: 11.54% ↑; CSR30: 6.56% ↑	PR114: 30.54% ↓; CSR30: 28.21% ↓	PR114: 16.08% ↑; CSR30: 45.00% ↑	PR114: 45.37% ↑; CSR30: 111.34% ↑	PR114: 67.18% ↑; CSR30: 102.38% ↑	SOC: 46.0% ↑; available P and micronutrients increased	Short duration; water/energy not quantified; long-term yield and nutrient dynamics require validation.
Manisha et al. [29]	North Coastal Andhra Pradesh, India	NF vs. CF	NR	NR	NR	21.42% ↓	15.45% ↓	6.38% ↓	27.44% ↑	10.24% ↑	NR	Water, WP, energy and soil health not quantified; limited spatial and temporal coverage.
Darjee et al. [30]	Gautam Budh Nagar, Uttar Pradesh	NF vs CF	NR	NR	NR	5.34% ↓ (rice)	NR	NR	NR	NR	SOC: 20.22% ↑; MBC: 37.51% ↑; MBN: 80.58% ↑	Water, WP, energy and economic indicators not reported; longer-term assessment required.
Ghasal et al. [31]	Meerut, Uttar Pradesh, India	NF vs. ICM	NR	NR	NR	51.17% ↓ (rice)	10.59% ↓	46.35% ↓	67.23% ↓	39.85% ↓	SOC: 8.33% ↓; N: 3.70% ↓; P: 34.00% ↓; K: 1.60% ↑	Substantial productivity/economic penalty; water, WP and energy not evaluated.
Athawale et al. [52]	Arunachal Pradesh, India	NF vs. CF	NR	NR	NR	11.89% ↓	29.49% ↓	14.79% ↓	17.06% ↑	NR	NR	Water, WP and energy not quantified.
Yadav et al. [53]	Kangra, Himachal Pradesh, India	NF vs. CF	NR	NR	NR	1.37–5.99% ↑	NR	9.04–29.80% ↑	NR	NR	NR	No integrated assessment of water, WP, energy and measured soil health.
Supraja et al. [54]	YSR Kadapa, Andhra Pradesh, India	NF vs. CF	NR	NR	NR	20.0% ↑	9.55% ↓	43.30% ↑	166.41% ↑	NR	NR	Single district and limited farmer sample; water, energy and soil-health indicators not quantified.
Majhi et al. [55]	Jagatsinghpur, Odisha, India	NF vs. CF	NR	NR	NR	NR	NR	NR	NR	NR	SOC: 4.65% ↑; N: 6.46% ↑; bacteria: 47.5% ↑; fungi: 40.12% ↑; actinomycetes: 70.4% ↑	Two-season study; water, WP and energy not quantified; long-term multi-location validation required.

NR—not recorded; AWD—alternate wetting and drying; PR114 and CSR30: rice varieties; SOC—soil organic carbon; N—available nitrogen. ↑ and ↓ indicate an increase and decrease, respectively. † Data derived from farmer surveys/on-farm observations, not replicated controlled on-station experiments.

3. Material and Methods

3.1. Study Area

Natural Farming was introduced in Andhra Pradesh in 2016 as Zero Budget Natural Farming (ZBNF) through the RythuSadhikaraSamstha (RySS), Government of Andhra Pradesh, with the objective to reduce cultivation costs, improve soil health, enhance farmers’ incomes, and improve the resilience of agricultural systems to climate variability. In 2018, the programme was expanded and renamed Andhra Pradesh Community Managed Natural Farming (APCNF) to promote its large-scale adoption across diverse agro-climatic regions of the state. As the selected farmers have been practicing natural farming for 5–6 years systematically, this duration was considered sufficient to assess the long-term effects of natural farming on soil health, crop productivity, and resource use efficiency under different cropping systems.

This study was carried out across four agro-climatic zones of Andhra Pradesh, India, representing a wide range of climatic conditions, rainfall patterns, soil types, and cropping systems (

Table 2. Climatic and soil characteristics of the selected study districts across six agro-climatic zones of Andhra Pradesh, India.

Agro-Climatic Zone	Districts Covered	Climate Type	Avg. Annual Rainfall (mm)	Avg. Annual Min–Max Temp (°C)	Soil Type	Soil Texture
Southern Zone	Nellore, Tirupathi, Chittor, Kadapa, Annamayya	Semi-arid tropical	600–1000 mm	20–42	Black soil (Vertisols)	Clay
Krishna Zone	Krishna, Guntur Bapatla, NTR, Palnadu and parts of Prakasam	Sub-humid tropical (Aw)	700–1100 mm	22–41	Black soil (Vertisols)	Clay/sandy clay/sandy clay loam
Godavari Zone	Eluru, Kakinada, Konaseema, West Godavari, East Godavari	Sub-humid maritime tropical (Aw)	1000–1200 mm	22–39	Deep alluvial soils (Entisols and Inceptisols)/Black soil (Vertisols)	Sandy clay loam/clay/sandy loam
High Altitude and Tribal Zone	Manyam, Alluri Seetaramaraju	Humid subtropical highland	>1400 mm	12–32	Red soil (Alfisols), with lateritic soils (Ultisols)	Loamy/sandy loam

).

3.2. Experimental Design

A paired-field experiment was conducted across four agro-climatic zones of Andhra Pradesh, namely the High Altitude and Tribal zone, Godavari zone, Krishna zone, and Southern zone. The number of field sites selected in each agro-climatic zone varied according to the extent of paddy cultivation. A total of 6 paired farmer fields were selected during the kharif season from the Southern zone, 20 paired farmer fields in the Godavari zone, 23 paired farmer fields in the High Altitude and Tribal Area zone, and 29 paired farmer fields in the Krishna zone. Similarly, in the rabi season, 6, 16, 9, and 24 paired farmer fields were selected from the Southern, Krishna, Godavari, and High Altitude and Tribal Area zones, respectively. Each selected pair comprised one natural farming (NF) field and one adjacent conventional farming (CF) field located within the same location to minimize variability arising from soil type, climatic conditions, rainfall, topography, and crop management practices. For each paired field, observations on all study parameters were recorded from three replications. The field sizes ranged from 4000 m² to 8000 m².

3.3. Crop Management Practices

The natural farming fields followed APCNF recommendations, including biological soil enrichment formulations, mulching, green manuring, crop residue recycling, pre-monsoon dry sowing (PMDS), and application of botanical extracts for pest management [34,56]. Conventional farming fields were managed using synthetic fertilizers, chemical pesticides, and recommended agronomic practices. Key natural farming practices in paddy include treating seeds with cow-dung formulations, enriching soil with fermented microbial cultures, and adopting water-saving, root-enhancing techniques like alternate wetting and drying, rotational irrigation, etc., to boost yields. Natural farming in paddy basically depends on improving soil health and ecological balance rather than synthetic inputs.

Green Manuring: Green manuring is practiced through pre-monsoon dry sowing (PMDS) of fast-growing leguminous crops such as sunn hemp (Crotalaria juncea) and dhaincha (Sesbania aculeata) before the rice-growing season. Under the Andhra Pradesh Community Managed Natural Farming (APCNF) system, this practice is further enhanced by the pre-monsoon dry sowing of Navadhanya (nine-grain mixture) along with other cover crop species during the pre-kharif or pre-rabi period. The green biomass is incorporated into the soil at approximately 50% flowering or just before transplanting the main crop. This practice enriches soil organic matter, enhances biological nitrogen fixation, improves soil structure, suppresses weed growth, reduces soil erosion, and promotes soil moisture conservation, thereby contributing to improved soil fertility and long-term sustainability of the production system.

Seed treatment (Beejamrit): Seeds were treated with Beejamrit, a microbial inoculant prepared from indigenous cow dung, cow urine, lime, and water, before sowing. For transplanted rice, seedlings were uprooted from the nursery, and their roots were dipped in Beejamrit prior to transplanting. This practice helps protect seeds and seedlings from soil- and seed-borne pathogens, enhances seed germination, promotes vigorous root establishment, and stimulates beneficial microbial activity in the rhizosphere [57].

Soil enrichment (Jeevamrit and Ghanajeevamrit): Soil fertility was enhanced through the application of Jeevamrit (liquid formulation) and Ghanajeevamrit (solid formulation), prepared by fermenting indigenous cow dung, cow urine, jaggery, pulse flour, and undisturbed native soil. Jeevamrit was applied through irrigation water or as a soil drench, whereas Ghanajeevamrit was broadcast uniformly in the field. These microbial formulations enhance the abundance and activity of beneficial microorganisms, stimulate nutrient mineralization, improve soil biological processes, and increase the availability of essential nutrients to crops [58,59].

Early transplantation and direct seeding: Rice seedlings were transplanted at a young age (10–14 days after sowing) with a wider spacing (approximately 25 cm × 25 cm) to promote better root development, increased tillering, and improved crop growth. In suitable fields, pre-germinated seeds were also established through direct seeding using a drum seeder under puddled conditions. These practices reduce transplanting shock, improve water-use efficiency, and enhance crop establishment while maintaining optimum plant population.

Water management (Whapasa): Alternate wetting and drying, instead of keeping the field continuously flooded at 5 cm, allow for intermittent drying. The Whapasa emphasizes maintaining an optimum balance of air and moisture in the soil to create favourable conditions for root growth, promoting healthier root respiration and soil biological activity while reducing irrigation requirements.

Pest and weed control: Alleyway formation: The formation of alleyways of 20 cm for every 2 m distance reduces brown planthopper (BPH) incidence and also allows intercultural operations. Intercrop with marigold or legumes on field bunds to trap pests. For direct pest control, application of fermented botanical extracts like Dashparni (made from 10 types of local leaves like neem and papaya) or Agniastram (a mix of garlic, chili, and cow urine). Spraying neem seed kernel extract or neem oil as prophylactic pest control.

3.4. Soil Sampling and Analysis

Soil samples were collected from all experimental fields following standard soil sampling procedures after the harvest of the rice crop. Composite soil samples were obtained from the 0–15 cm soil depth by combining three subsamples collected randomly from each field. The samples were air-dried, gently crushed, passed through a 2-mm sieve, and analyzed for selected soil properties using standard analytical methods. Soil pH was determined in a 1:2.5 soil-to-water suspension using a digital pH meter following the method of Jackson [60]. Soil organic carbon (SOC) was estimated by the Walkley and Black wet oxidation (titrimetric) method as described by Walkley and Black [61]. Available nitrogen was estimated following the alkaline-permanganate (KMnO₄) method of Subbiah and Asija [62] using a Micro-Kjeldahl distillation assembly. Available phosphorus was determined using the Bray and Kurtz No. 1 extraction method using ammonium fluoride (0.03 N NH₄F) and hydrochloric acid (0.025 N HCl) for acidic soils [63] and the Olsen extraction method using sodium bi-carbonate (0.5 M NaHCO₃, pH 8.5) for neutral and alkaline soils [64], followed by colorimetric determination using the ascorbic acid method. Available potassium was extracted using neutral 1 N ammonium acetate and determined by flame photometry following the method described by Jackson [60].

3.5. Measurement of Irrigation Water

In most of the experimental sites, the irrigation water source was wells, and in a few locations the water source was surface water harvesting and diversion systems such as tanks. To measure the irrigation water applied through pumping from wells, both in natural and conventional farming, digital water meters were installed in each experimental site following standard technical guidelines to ensure accuracy and consistency of measurements. Periodic calibrations and field verifications were carried out to minimize observational and instrumental errors. A water meter measures the quantity (volume) of water passing through a pipe. These meters record and transmit data in three modes: (i) real-time transmission to a centralized dashboard, (ii) SMS alerts to registered mobile numbers, and (iii) on-screen display on the meter unit. The dashboard provides detailed information on the volume of irrigation water used (m³) and pumping duration. Each irrigation event, volume of water applied, and duration of the irrigation event were recorded in the data dashboard. At the experimental locations where irrigation water was supplied through gravity-fed canals from tanks, flumes were installed to measure the quantity of water applied during each irrigation event (Figure 1).

3.6. Estimation of Energy Consumption for Irrigation

Based on digital water meter readings, the volume of irrigation water applied and the corresponding pump operating time were recorded for each irrigation event. Pump discharge was calculated as the ratio of the measured water volume to the pumping duration. Irrigation energy consumption was then estimated using the calculated pump discharge, total pumping head (depth of water lifting), water density, gravitational acceleration, and an assumed pump efficiency of 60%. The energy consumed during all irrigation events was summed to estimate the total seasonal energy consumption (kWh) for each cropping system.

$$Energy consumption\left(\mathrm{k}\mathrm{W}\mathrm{h}\right)=Power\left(\mathrm{k}\mathrm{W}\right)\times Time\left(\mathrm{h}\mathrm{r}\right)$$

$$Power\left(\mathrm{k}\mathrm{W}\right)={\displaystyle \frac{Q\times g\times \rho \times h}{1000\times \mathsf{\eta }}}$$

where:

Q = Pump discharge (m³ s⁻¹);

g = Acceleration due to gravity = 9.81 m s⁻²;

ρ = Density of water = 1000 kg m⁻³;

h = Total pumping head/depth of water lifting (m);

η = Pump efficiency = 0.60 (60%).

Pump discharge (m³ s⁻¹):

$$Q={\displaystyle \frac{V}{t}}$$

where:

V = Volume of irrigation water applied during the irrigation event (m³);

t = Pump operating time for the irrigation event (s).

The total seasonal energy consumption was obtained by summing the energy consumed across all irrigation events:

$$E_{total}={\displaystyle \sum _{i=1}^n}EC$$

where:

E_total = total energy consumption during the cropping season (kWh);

ECi = energy consumed during the ith irrigation event;

n = total number of irrigation events during the cropping season.

3.7. Crop Productivity

Crop yield was measured using the standard Crop Cutting Experiment (CCE) method [65]. It was estimated using three representative locations within each farmer’s field. Each crop-cutting quadrat (10 × 10 m²) was harvested separately at maturity, and the grain yield was recorded. The yield from each quadrat was converted to kg acre⁻¹ based on the sampled area, and the arithmetic mean of the three quadrats was considered the estimated yield of the respective farmer’s field. Thus, the crop-cutting observations served as subsamples for estimating field-level yield rather than as independent experimental replications. Standard sampling and survey procedures, as described by Ahmad et al. [66] were followed for conducting the crop-cutting experiments.

3.8. Estimation of Water Productivity

The total irrigation water applied during the cropping season was determined from the water meter readings. Crop yield data obtained from the crop-cutting experiments were analysed to estimate the yield. Based on the irrigation water applied and the corresponding crop yield, water productivity (WP) was calculated. Water productivity was computed as the ratio of crop yield to the total irrigation water applied during the cropping season and was calculated as:

$$WP={\displaystyle \frac{Y}{TWU}}$$

where,

WP = Water productivity (kg m⁻³);

Y = Crop yield (kg acre⁻¹);

TWU = Total water utilization (m³ acre⁻¹).

The total water utilization (TWU) was calculated as:

$$TWU=IW+ER$$

where,

IW = Total irrigation water applied (m³ acre⁻¹);

ER = Effective rainfall during the cropping season (m³ acre⁻¹).

3.9. Computation of Economic Analysis

The economics of NF and CF were evaluated by estimating the cost of cultivation, gross returns, net returns, and benefit–cost ratio (BCR) for each cropping system. Gross returns were calculated based on the market value of the harvested produce, while net returns were obtained by deducting the total cost of cultivation from the gross returns.

$$Gross return(\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1})=Total output\left(grain yield;\mathrm{k}\mathrm{g} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1}\right)\times Selling price\left(RS\right)$$

$$Net return\left(\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1}\right)=Gross return (RS {acre}^{-1})-Cost of cultivation(\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1})$$

$$Cost of cultivation\left(\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1}\right)=Cost incurred (\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1} )for various inputs$$

$$\mathrm{Benefit}-Cost Ratio (BCR)={\displaystyle \frac{Gross return (\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1})}{Cost of cultivation (\mathrm{R}\mathrm{S} {\mathrm{a}\mathrm{c}\mathrm{r}\mathrm{e}}^{-1})}}$$

3.10. Sustainable Yield Index

The sustainable yield index (SYI) of an individual crop was calculated using the following equation [67]:

$$Sustainable yield index (SYI)={\displaystyle \frac{Y_{mean}-\sigma }{Y_{max}}}$$

where

Ymean—is mean yield;

σ—is treatment standard deviation;

Ymax—is maximum yield in the experiment over the years.

3.11. Statistical Analysis

The measured parameters, including total water utilization, crop yield, water productivity, energy consumption, and economic indicators, were analyzed using a 2-sample t-test with equal variance to compare NF and CF under paired-field conditions [68]. The statistical analysis was performed using R-software Rversion 4.6.1 [69], and differences between the two farming systems were considered statistically significant at p < 0.05.

4. Result

4.1. Total Water Utilization

The total water utilization (TWU) (irrigation water plus effective rainfall) under NF and CF across different agro-climatic zones of Andhra Pradesh, pooling observations from all study years, is presented in

Table 3. Comparative evaluation of total water utilization (m³ acre⁻¹) (irrigation + effective rainfall) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Water Saving (%)	p-Value	Significance
			Total Water Utilization (m3 acre−1)
Kharif	Southern Zone	6	5003 ± 133 ¥	6979 ± 299	28.3	<0.001	***
	Krishna Zone	29	4983 ± 409	6695 ± 1216	25.6	<0.001	***
	Godavari Zone	20	5041 ± 538	6147 ± 1019	18.0	<0.001	***
	High Altitude Zone	23	4808 ± 247	7853 ± 253	38.8	<0.001	***
Rabi	Southern Zone	6	5062 ± 288	6851 ± 239	26.1	<0.001	***
	Krishna Zone	16	4850 ± 483	6201 ± 1197	21.8	0.001	**
	Godavari Zone	9	4950 ± 462	6565 ± 861	24.6	0.001	**
	High Altitude Zone	24	4851 ± 242	7956 ± 260	39.0	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.01 (**).

. Across all zones and seasons, NF consistently required lower total water utilization than CF, demonstrating its potential to improve water use under diverse climatic conditions. During the kharif season, the greatest reduction in total water utilization was observed in the Southern Zone, where NF used 5003 ± 133 m³ acre⁻¹ compared with 6979 ± 299 m³ acre⁻¹ under CF, representing a 28.3% reduction (p < 0.001). Similarly, the High-Altitude Zone recorded a 38.8% reduction in total water utilization under NF (4808 ± 247.3 m³ acre⁻¹) compared with CF (7853 ± 253 m³ acre⁻¹) (p < 0.001). The Krishna Zone also exhibited substantial water savings of 25.6%, with total water utilization decreasing from 6695 ± 1216 to 4983 ± 408.9 m³ acre⁻¹ under NF (p < 0.001). In the Godavari Zone, NF reduced total water utilization by 18.0% relative to CF (p < 0.001). These results indicate that NF effectively reduced irrigation water requirements during the rainy season while maintaining crop production under varying agro-climatic conditions. A similar trend was observed during the rabi season, although the magnitude of water savings varied among agro-climatic zones. The High-Altitude Zone again recorded the highest reduction, with NF requiring 4850 ± 242 m³ acre⁻¹ compared with 7956 ± 260 m³ acre⁻¹ under CF, corresponding to a 39.0% reduction (p < 0.001). In the Southern Zone, total water utilization declined by 26.1%, while reductions of 21.8% and 16.1% were observed in the Krishna and Godavari Zones, respectively.

4.2. Water Productivity

Water productivity integrates crop yield with total water consumption and is a reliable indicator of irrigation efficiency under different production systems. During the kharif season, water productivity under NF ranged from 0.432 ± 0.017 to 0.490 ± 0.045 kg m⁻³, compared with 0.285 ± 0.014 to 0.400 ± 0.100 kg m⁻³ under CF (

Table 4. Comparative evaluation of water productivity under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Improvement (%)	p-Value	Significance
			Water Productivity (kg m−3)
Kharif	Southern Zone	6	0.432 ± 0.017 ¥	0.324 ± 0.018	33.1	<0.001	***
	Krishna Zone	29	0.490 ± 0.045	0.395 ± 0.079	24.0	<0.001	***
	Godavari Zone	20	0.477 ± 0.071	0.400 ± 0.100	18.8	<0.001	***
	High Altitude Zone	23	0.443 ± 0.027	0.285 ± 0.014	55.5	<0.001	***
Rabi	Southern Zone	6	0.445 ± 0.079	0.321 ± 0.066	38.6	<0.001	***
	Krishna Zone	16	0.502 ± 0.054	0.436 ± 0.068	15.0	0.012	*
	Godavari Zone	9	0.521 ± 0.070	0.416 ± 0.131	25.4	0.002	**
	High Altitude Zone	24	0.449 ± 0.023	0.294 ± 0.013	52.8	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.01 (**), p < 0.05 (*).

). The greatest improvement was recorded in the High-Altitude Zone, where NF observed a water productivity of 0.490 ± 0.045 kg m⁻³, representing a 55.5% increase over CF (0.285 ± 0.014 kg m⁻³, p < 0.001). Similarly, water productivity increased significantly by 33.1% in the Southern Zone (p < 0.001), 24.0% in the Krishna Zone (p < 0.001), and 18.8% in the Godavari Zone (p < 0.001). A similar trend was observed during the rabi season, where water productivity under NF ranged from 0.445 ± 0.079 to 0.521 ± 0.070 kg m⁻³, whereas CF ranged from 0.294 ± 0.013 to 0.436 ± 0.068 kg m⁻³. The greatest improvement was again observed in the High-Altitude Zone, where NF recorded 0.449 ± 0.023 kg m⁻³, representing a 52.8% increase over CF (p < 0.001). Significant improvements were also observed in the Southern Zone (38.6%; p < 0.001), Godavari Zone (25.4%; p = 0.002), and Krishna Zone (15.0%; p = 0.012).

4.3. Energy Consumption

Irrigation-related energy consumption is a key indicator of both the economic and environmental sustainability of agricultural systems, especially in groundwater-dependent regions.

Table 5. Comparative evaluation of energy consumption (kWh) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Reduction Under NF (%)	p-Value	Significance
			Energy Consumption (kWh)
Kharif	Southern Zone	6	2859 ± 1573 ¥	5758 ± 2830	50.3	0.0170	*
	Krishna Zone	18	910.7 ± 386.6	1543 ± 551.9	40.9	<0.001	***
	Godavari Zone	20	2327 ± 358.8	2974 ± 527.2	21.7	<0.001	***
	High Altitude Zone	11	542.8 ± 185.5	1283 ± 415.8	57.7	<0.001	***
Rabi	Southern Zone	6	2841 ± 1774	3987 ± 2424	28.7	0.0383	*
	Krishna Zone	16	1193 ± 442.6	1865 ± 532.3	36.0	<0.001	***
	Godavari Zone	9	2623 ± 562.9	3513 ± 808.4	25.3	0.0018	**
	High Altitude Zone	12	722.7 ± 204.8	1502 ± 480.9	51.9	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.01 (**), p < 0.05 (*).

shows that NF practices consistently reduced energy consumption compared with CF across all agro-climatic zones during both the kharif and rabi seasons. In the kharif season, energy consumption under NF was significantly lower by 50.3% in the Southern Zone (2859 vs. 5758 kWh; p = 0.017), 40.97% in the Krishna Zone (910.7 vs. 1543 kWh; p < 0.001), 21.7% in the Godavari Zone (2327 vs. 2974 kWh; p < 0.001), and 57.7% in the High-Altitude Zone (542.8 vs. 1283 kWh; p < 0.001). During the rabi season, NF also recorded significantly lower energy consumption, with reductions of 28.7% in the Southern Zone (2841 vs. 3987 kWh; p = 0.038), 36.0% in the Krishna Zone (1193 vs. 1865 kWh; p < 0.001), 25.3% in the Godavari Zone (2623 vs. 3513 kWh; p = 0.0018), and 51.9% in the High-Altitude Zone (722.7 vs. 1502 kWh; p < 0.001). Overall, NF reduced energy consumption by 21.8–57.7% across the studied agro-climatic zones, with the greatest reductions observed in the High-Altitude Zone. Notably, absolute energy consumption was higher in rabi than in kharif season under both management systems, particularly in the Krishna and Godavari zones.

4.4. Rice Productivity

Crop productivity is a critical indicator for evaluating the agronomic performance of NF, as the long-term adoption of any sustainable production system depends on its ability to maintain yields while reducing external resource inputs. Rice yield under NF varied across agro-climatic zones and seasons, indicating that the response of NF was strongly influenced by local climatic conditions and crop cultivation practices (

Table 6. Comparative evaluation of rice yield under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Yield Change (%)	p-Value	Significance
			Rice Yield (kg acre−1)
Kharif	Southern Zone	6	2160 ± 65.20 ¥	2260 ± 41.80	−4.40	0.011	*
	Krishna Zone	29	2428 ± 134.6	2559 ± 170.1	−5.10	<0.001	***
	Godavari Zone	20	2374 ± 210.7	2367 ± 244.8	+0.30	0.929	NS
	High Altitude Zone	23	2125 ± 82.40	2243 ± 74.30	−5.30	<0.001	***
Rabi	Southern Zone	6	2237 ± 263.9	2192 ± 394.2	+2.10	0.557	NS
	Krishna Zone	16	2411 ± 77.70	2633 ± 120.9	−8.40	<0.001	***
	Godavari Zone	9	2566 ± 218.4	2523 ± 301.7	+1.70	0.655	NS
	High Altitude Zone	24	2173 ± 47.20	2337 ± 62.40	−7.00	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.05 (*), and NS = not significant (p ≥ 0.05).

). During the kharif season, rice yield under NF ranged from 2125 to 2428 kg acre⁻¹, whereas, in the case of CF, it ranged from 2243 to 2559 kg acre⁻¹. In the Southern Zone, NF recorded a significant (p = 0.011) decrease in rice yield by 4.40% compared to CF (2260 ± 41.8 kg acre⁻¹). Similarly, yield was significantly lower under NF in the Krishna Zone (2428 ± 134 vs. 2559 ± 170 kg acre⁻¹), corresponding to a 5.10% decrease. The High-Altitude Zone also exhibited a significant yield reduction of 5.30% under NF (p < 0.001). In contrast, the Godavari Zone showed statistically comparable yields between the two production systems, with NF recording a marginal 0.30% increase over CF (p = 0.929). A similar trend was observed during the rabi season. Rice yield under NF ranged from 2173 to 2566 kg acre⁻¹, while CF recorded 2192 to 2633 kg acre⁻¹. In the Southern Zone, a slightly higher yield (2237 ± 263.9 kg acre⁻¹) was recorded under NF than CF (2192 ± 394.2 kg acre⁻¹), representing a 2.10% increase, although the difference was not statistically significant (p = 0.557). Likewise, in the Godavari Zone, NF achieved a marginal but non-significant 1.70% yield advantage over CF (p = 0.655). Conversely, significant yield reductions were observed under NF in the Krishna Zone (8.40%; p < 0.001) and High-Altitude Zone (7.00% lower; p < 0.001), indicating that the productivity response of NF varied considerably across agro-climatic conditions. The observed variation in rice yield across agro-climatic zones reflects the complex interaction among nutrient availability, soil moisture dynamics, climatic conditions, and the stage of transition from conventional to natural farming. The modest yield reductions of 4.40–8.40% observed under NF in the Southern, Krishna, and High-Altitude zones are consistent with the transition effect frequently reported during the initial years of adopting biologically based production systems.

4.5. Economic Analysis

Cost of cultivation:

The cost advantage of NF was evident from the component-wise cost budget presented in

Table 7. Comparative average variable cost of paddy cultivation under natural and conventional farming systems.

S. No.	Package of Practices/Operations	Natural Farming	Conventional Farming	Reduction Under NF over CF (RS acre−1)
		Cost of Cultivation (RS acre−1)
1	Land preparation (Ploughing, puddling, levelling)	5000 *	5000	0
2	Seeds	1100	1100	0
3	Seed treatment (Beejamrit/insecticide and fungicide)	100	300	200
4	Transplantation (Labour and related transplanting expenses)	5000	5000	0
5	Fertilization (Jeevamruth, green manure/NPK, micronutrients)	1400	4900	3500
6	Irrigation (Labour and irrigation-related expenses)	800	1600	800
7	Intercultural operations (Weeding and other field operations)	1600	2600	1000
8	Disease and pest management (Neem oil, pheromone traps, biopesticides/chemical pesticides)	1800	3400	1600
9	Harvesting, threshing and packing (post-harvest handling)	2500	2500	0
	Total	19,300	26,400	7100

* Values presented in the table represent the average estimated cost per acre and may vary depending on the location, agro-climatic zone, prevailing input prices, labour rates, and farm-specific management practices.

. The cost budget included land preparation, seed treatment, transplantation, fertilization, irrigation, intercultural operations, disease and pest management, and harvesting, threshing and packing. The total average variable cost was RS19,300 acre⁻¹ under NF compared with RS26,400 acre⁻¹ under CF, representing a saving of ₹7100 acre⁻¹ (26.9%) under NF. However, it may vary depending on the location, agro-climatic zone, prevailing input prices, labour rates, and farm-specific management practices. The largest cost differences were observed for fertilization (RS3500 acre⁻¹), disease and pest management (RS1600 acre⁻¹), intercultural operations (RS1000 acre⁻¹), and irrigation (RS800 acre⁻¹).

This reduction in input expenditure was significantly lower under natural farming (NF) than conventional farming (CF) across all agro-climatic zones during both kharif and rabi seasons (

Table 8. Comparative evaluation of cost of cultivation (CC) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Reduction Under NF (%)	p-Value	Significance
			Cost of Cultivation (RS acre−1)
Kharif	Southern Zone	6	16,800 ± 1304 ¥	25,900 ± 742.0	35.1	<0.001	***
	Krishna Zone	29	18,631 ± 3077	26,994 ± 3984	31.0	<0.001	***
	Godavari Zone	20	20,964 ± 2330	27,898 ± 3913	24.9	<0.001	***
	High Altitude Zone	23	18,225 ± 1737	25,274 ± 2287	27.9	<0.001	***
Rabi	Southern Zone	6	20,460 ± 1545	25,783 ± 1822	20.6	<0.001	***
	Krishna Zone	16	18,475 ± 3001	24,045 ± 2778	23.2	<0.001	***
	Godavari Zone	9	21,699 ± 2267	28,216 ± 3312	23.1	<0.001	***
	High Altitude Zone	24	18,837 ± 1287	27,151 ± 1516	30.6	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***).

). The reduction in cultivation cost under NF ranged from 20.6 to 35.1%, with all differences being highly significant (p < 0.001). During the kharif season, the cost of cultivation under NF ranged from RS16,800 to RS20,964 acre⁻¹, compared with RS25,274 to RS27,898 acre⁻¹ under CF. The largest reduction was recorded in the Southern Zone, where NF reduced cultivation costs by 35.1% (RS16,800 ± 1304 vs. RS25,900 ± 742 acre⁻¹; p < 0.001). Significant cost reductions were also observed in the Krishna Zone (31.0%), High Altitude Zone (27.9%), and Godavari Zone (24.9%) compared with CF. A similar trend was observed during the rabi season. Cultivation costs under NF varied between RS18,475 and RS21,699 acre⁻¹, whereas CF required RS24,045 to RS28,216 acre⁻¹. The High-Altitude Zone recorded the greatest reduction in cultivation cost (30.6%), followed by the Krishna Zone (23.2%), Godavari Zone (23.1%), and Southern Zone (20.6%).

Gross return: Gross return (GR) varied between natural farming and conventional farming across agro-climatic zones and seasons, largely reflecting the differences in grain yield obtained under the two production systems (

Table 9. Comparative evaluation of gross return (GR) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Change (%)	p-Value	Significance
			Gross Return (RS acre−1)
Kharif	Southern Zone	6	49,680 ± 1499 ¥	51,980 ± 962.0	−4.42	0.011	*
	Krishna Zone	29	55,190 ± 3367	56,738 ± 3336	−2.73	0.023	*
	Godavari Zone	20	53,565 ± 4669	52,031 ± 2771	+2.95	0.269	NS
	High Altitude Zone	23	48,885 ± 1895	51,600 ± 1709	−5.26	<0.001	***
Rabi	Southern Zone	6	52,543 ± 6470	50,017 ± 8928	+5.05	0.153	NS
	Krishna Zone	16	54,280 ± 3283	57,692 ± 4235	−5.91	<0.001	***
	Godavari Zone	9	53,420 ± 4802	52,740 ± 3960	+1.29	0.695	NS
	High Altitude Zone	24	49,987 ± 1086	53,748 ± 1435	−7.00	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.05 (*), and NS = not significant (p ≥ 0.05).

). In the kharif season, GR under NF ranged from RS48,885 to RS55,190 acre⁻¹, while CF recorded values between RS51,600 and RS56,738 acre⁻¹. In the Southern Zone, NF generated a GR of RS49,680 ± 1499 acre⁻¹, which was 4.42% lower than CF (RS51,980 ± 962 acre⁻¹), with the difference being significant (P = 0.011). Similarly, GR under NF declined significantly by 2.73% in the Krishna Zone (P = 0.023) and by 5.26% in the High-Altitude Zone (P < 0.001). In contrast, the Godavari Zone recorded a slightly higher GR under NF (RS53,565 ± 4669 acre⁻¹) than CF (RS52,031 ± 2771 acre⁻¹), representing a 2.95% increase, although the difference was not statistically significant (P = 0.269). During the rabi season, GR under NF ranged from RS49,987 to RS54,280 acre⁻¹, whereas CF varied from RS50,017 to RS57,692 acre⁻¹. The Southern Zone recorded a 5.05% higher GR under NF (RS52,543 ± 6470 acre⁻¹) than CF (RS50,017 ± 8928 acre⁻¹); however, the difference was not statistically significant (P = 0.153). Similarly, GR in the Godavari Zone was 1.29% higher under NF than CF (P = 0.695). Conversely, NF recorded significantly lower gross returns in the Krishna Zone (5.91% lower, P < 0.001) and High-Altitude Zone (7.00% lower, P < 0.001) compared with CF. Overall, GR under NF were comparable to those under CF across most agro-climatic zones, with differences generally ranging between −7.00% and +5.05%. Significant reductions in GR were observed primarily in zones where NF produced lower grain yields, whereas statistically similar gross returns were recorded in the Southern and Godavari zones during the rabi season. These findings indicate that the modest variation in GR under NF was primarily driven by differences in crop productivity rather than changes in market price or production costs.

Net return: Net return (NR) represents the ultimate indicator of farm profitability as it integrates both production costs and gross income. As presented in

Table 10. Comparative evaluation of net return (NR) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Increase Under NF over CF (%)	p-Value	Significance
			Net Return (RS acre−1)
Kharif	Southern Zone	6	32,880 ± 1611 ¥	26,080 ± 1306	26.1	<0.001	***
	Krishna Zone	29	36,547 ± 5249	29,730 ± 5083	22.9	<0.001	***
	Godavari Zone	20	34,640 ± 4255	26,846 ± 4881	29.0	<0.001	***
	High Altitude Zone	23	30,031 ± 2098	25,454 ± 2728	18.0	<0.001	***
Rabi	Southern Zone	6	31,633 ± 5006	24,783 ± 7416	27.6	0.003	**
	Krishna Zone	16	33,902 ± 4164	31,170 ± 4221	8.80	<0.001	***
	Godavari Zone	9	33,938 ± 5323	27,407 ± 5406	23.8	0.005	**
	High Altitude Zone	24	31,160 ± 1339	26,613 ± 2284	17.1	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.01 (**).

, net return was consistently higher under NF than CF across all agro-climatic zones during both kharif and rabi seasons. During the kharif season, NR under NF varied from RS30,031 to RS36,547 acre⁻¹, compared with RS25,454 to RS29,730 acre⁻¹ under CF. The highest increase in NR was observed in the Godavari Zone, where NF increased net return by 29.0% (RS34,640 ± 4255 vs. RS26,846 ± 4881 acre⁻¹; p < 0.001), followed by the Southern Zone (26.1%), Krishna Zone (22.9%), and High-Altitude Zone (18.0%), with all differences being highly significant (p < 0.001). A similar trend was observed during the rabi season. The NR under NF varied from RS31,160 to RS33,938 acre⁻¹, whereas CF ranged from RS24,783 to RS31,170 acre⁻¹. The greatest increase was recorded in the Southern Zone, where NF improved net return by 27.6% (p = 0.003), followed by the Godavari Zone (23.8%, p = 0.005), High Altitude Zone (17.1%, p < 0.001), and Krishna Zone (8.8%, p < 0.001).

Benefit–Cost Ratio (BCR): The BCR provides a comprehensive measure of economic efficiency by relating the monetary returns obtained from crop production to the total cost of cultivation. The results demonstrated that NF significantly improved the BCR compared with CF across all agro-climatic zones during both kharif and rabi seasons (

Table 11. Comparative evaluation of Benefit–Cost Ratio (BCR) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years of 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Increase Under NF (%)	p-Value	Significance
			Benefit–Cost Ratio (BCR)
Kharif	Southern Zone	6	2.97 ± 0.20 ¥	2.01 ± 0.07	47.8	<0.001	***
	Krishna Zone	29	3.07 ± 0.58	2.14 ± 0.34	43.2	<0.001	***
	Godavari Zone	20	3.00 ± 0.81	2.12 ± 0.38	41.6	<0.001	***
	High Altitude Zone	23	2.60 ± 0.19	1.99 ± 0.18	30.9	<0.001	***
Rabi	Southern Zone	6	2.57 ± 0.23	1.93 ± 0.20	33.1	<0.001	***
	Krishna Zone	16	2.72 ± 0.45	2.20 ± 0.26	23.7	<0.001	***
	Godavari Zone	9	2.83 ± 0.61	2.12 ± 0.37	33.2	<0.001	***
	High Altitude Zone	24	2.66 ± 0.15	1.99 ± 0.14	34.0	<0.001	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***).

). The BCR under NF and CF ranged from 2.60 to 3.07 and from 1.99 to 2.14, respectively. The significant (p < 0.001) greatest improvement was recorded in the Southern Zone, where BCR increased by 47.8% (2.97 ± 0.20 vs. 2.01 ± 0.07), followed by the Krishna Zone (43.2%), Godavari Zone (41.6%), and High-Altitude Zone (30.9%). Similar to the kharif season, in the rabi season, NF recorded BCR values ranging from 2.57 to 2.83, compared with 1.93 to 2.20 under CF. The largest increase was observed in the High-Altitude Zone by 34.0%, followed by the Godavari Zone (33.2%), Southern Zone (33.1%), and Krishna Zone (23.7%). Overall, NF improved the BCR by 23.7–47.8% across agro-climatic zones, indicating superior economic efficiency over CF.

4.6. Sustainable Yield Index (SYI)

The Sustainable Yield Index (SYI) was used to evaluate the yield stability and sustainability of NF relative to CF across different agro-climatic zones over the three-year study period (2023–2025). The results revealed that the response of SYI to NF varied among agro-climatic zones and cropping seasons (

Table 12. Comparative evaluation of Sustainable Yield Index (SYI) under natural farming (NF) and conventional farming (CF) across agro-climatic zones of Andhra Pradesh (pooled across study years 2023–2025).

Season	Agro-Climatic Zone	n	Natural Farming	Conventional Farming	Change Under NF (%)	p-Value	Significance
			Sustainable Yield Index (SYI)
Kharif	Southern Zone	6	0.911 ¥	0.964	−5.56	0.0111	*
	Krishna Zone	29	0.796	0.829	−3.97	0.0006	***
	Godavari Zone	20	0.739	0.726	+1.90	0.9295	NS
	High Altitude Zone	23	0.869	0.923	−5.81	0.0000	***
Rabi	Southern Zone	6	0.680	0.620	+9.76	0.5570	NS
	Krishna Zone	16	0.833	0.897	−7.11	0.0000	***
	Godavari Zone	9	0.796	0.753	+5.66	0.6547	NS
	High Altitude Zone	24	0.868	0.928	−6.52	0.0000	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.05 (*), and NS = not significant (p ≥ 0.05).

). In the kharif season, SYI under NF ranged from 0.739 to 0.911, whereas CF recorded values between 0.726 and 0.964. Significant reductions in SYI under NF were observed in the Southern Zone (5.56%), Krishna Zone (3.97%), and High-Altitude Zone (5.81%) (p < 0.05), while the Godavari Zone showed a marginal 1.90% increase, although the difference was not statistically significant (p = 0.9295). In the rabi season, contrasting responses were evident among agro-climatic zones. The Southern and Godavari zones recorded numerically higher SYI under NF, with increases of 9.76% and 5.66%, respectively, but these improvements were not statistically significant. Conversely, significant (p < 0.001) declines were observed in the Krishna Zone (7.11%) and High-Altitude Zone (6.52%). Overall, the SYI values under NF remained high (>0.68) across all locations, indicating that despite moderate reductions in some regions, the farming system maintained relatively stable and sustainable crop productivity under diverse agro-climatic conditions.

4.7. Soil Health

Soil pH

The farming practices significantly influenced soil pH in all agro-climatic zones, although the direction of change depended on the native soil condition. In the Southern and Godavari zones, where soils were moderately alkaline under CF, NF reduced soil pH from 7.81 to 7.23 and from 7.82 to 7.08, respectively (Figure 2;

Table 13. Comparison of soil chemical properties under conventional farming (CF) and natural farming (NF) across different agro-climatic zones of Andhra Pradesh, India.

Agro-Climatic Zone	Natural Farming	Conventional Farming	Change Under NF (%)	p-Value	Significance
Soil pH
Southern zone	7.23 ± 0.24 ¥	7.81 ± 0.34	−7.43	0.0035	**
Krishna zone	6.78 ± 0.30	5.79 ± 0.35	+17.1	<0.0001	***
Godavari zone	7.08 ± 0.15	7.82 ± 0.22	−9.46	<0.0001	***
High Altitude zone	6.81 ± 0.32	5.79 ± 0.39	+17.6	<0.0001	***
Soil organic carbon (%)
Southern zone	0.58 ± 0.09	0.39 ± 0.05	+48.7	0.0008	***
Krishna zone	0.65 ± 0.08	0.41 ± 0.04	+58.5	<0.0001	***
Godavari zone	0.57 ± 0.12	0.38 ± 0.08	+50.0	<0.0001	***
High Altitude zone	1.01 ± 0.11	0.73 ± 0.05	+38.3	<0.0001	***
Available nitrogen (kg ha−1)
Southern zone	323 ± 24.2	290 ± 13.5	+11.3	0.0105	*
Krishna zone	266 ± 22.6	223 ± 20.7	+19.3	<0.0001	***
Godavari zone	279 ± 36.7	244 ± 30.0	+14.3	0.0018	**
High Altitude zone	327 ± 16.1	285. ± 9.91	+14.7	<0.0001	***
Available phosphorus (kg ha−1)
Southern zone	38.8 ± 2.34	33.3 ± 3.73	+16.5	0.0073	**
Krishna zone	34.0 ± 2.83	27.9 ± 3.18	+21.8	<0.0001	***
Godavari zone	25.9 ± 3.39	20.7 ± 3.07	+25.1	<0.0001	***
High Altitude zone	25.7 ± 3.36	22.2 ± 1.87	+15.7	<0.0001	***
Available potassium (kg ha−1)
Southern zone	336 ± 17.8	294 ± 25.2	+14.3	0.0042	**
Krishna zone	328 ± 31.4	279 ± 27.6	+17.5	<0.0001	***
Godavari zone	317 ± 20.8	274 ± 21.0	+15.7	<0.0001	***
High Altitude zone	323 ± 30.5	291 ± 20.5	+11.0	0.0002	***

^¥ Values are expressed as mean ± SD. Differences between natural farming (NF) and conventional farming (CF) were compared using a paired t-test. Significance levels are denoted as p < 0.001 (***), p < 0.01 (**), p < 0.05 (*).

). Conversely, in the relatively acidic Krishna and High-Altitude zones, NF increased soil pH from 5.79 to 6.78 and from 5.79 to 6.81, respectively.

Soil organic carbon

Across the four agro-climatic zones, soil organic carbon (SOC) under natural farming (NF) ranged from 0.57 to 1.01% (medium to high), whereas under conventional farming (CF) it ranged from 0.38 to 0.73% (low to medium) (Figure 2; Table 13). The lowest SOC values were observed in the Godavari zone (0.57%) under NF and the Godavari zone (0.38%) under CF, while the High-Altitude zone recorded the highest SOC under both farming systems (1.01% under NF and 0.73% under CF). Compared with CF, NF increased SOC by 38.3–58.5% across the agro-climatic zones, indicating a substantial improvement in soil carbon accumulation under NF.

Available nitrogen

Across the four agro-climatic zones, available nitrogen under NF and CF ranged from 266 to 327 kg ha⁻¹ and 223 to 290 kg ha⁻¹, respectively (Figure 2; Table 13). The highest available nitrogen was recorded in the High-Altitude zone (327 kg ha⁻¹ under NF and 285 kg ha⁻¹ under CF), while the lowest values were observed in the Krishna zone (266 kg ha⁻¹ under NF and 223 kg ha⁻¹ under CF). Due to the impact of NF, available nitrogen increased by 11.3–19.3% compared with CF across the agro-climatic regions.

Available phosphorus

Across the four agro-climatic zones, available phosphorus under NF ranged from 25.7 to 38.8 kg ha⁻¹, whereas under conventional farming (CF) it ranged from 20.7 to 33.3 kg ha⁻¹ (Figure 2; Table 13). The Southern zone recorded the highest available phosphorus (38.8 kg ha⁻¹ under NF and 33.3 kg ha⁻¹ under CF), while the High-Altitude and Godavari zones recorded comparatively lower values (25.7–25.9 kg ha⁻¹ under NF and 20.7–22.2 kg ha⁻¹ under CF). Natural farming significantly (p ≤ 0.0073) increased available phosphorus by 15.7–25.1% compared with CF across all agro-climatic zones. The highest increase was observed in the Godavari zone (25.1%), followed by the Krishna zone (21.8%), Southern zone (16.5%), and High-Altitude zone (15.7%).

Available potassium

The available potassium under NF ranged from 317 to 336 kg ha⁻¹, while under CF it varied from 274 to 294 kg ha⁻¹, across the agro-climatic zones (Figure 2; Table 13). The Southern zone recorded the highest available potassium (336 kg ha⁻¹ under NF and 294 kg ha⁻¹ under CF), whereas the Godavari zone recorded the lowest values (317 kg ha⁻¹ under NF and 274 kg ha⁻¹ under CF). However, the status of available potassium in soil was high across the different agro-climatic zones. Natural farming enhanced available potassium by 11.0–17.5% over conventional farming across all agro-climatic zones. The largest increase was recorded in the Krishna zone (17.5%), followed by the Godavari (15.7%), Southern (14.3%), and High Altitude (11.0%) zones. These improvements were statistically significant across all agro-climatic zones (p ≤ 0.0042). Natural farming significantly improved available potassium across all agro-climatic zones, with increases ranging from 11.0 to 17.5% compared with conventional farming.

5. Discussion

5.1. Resource Conservation

The present study demonstrated a consistent and statistically significant (p ≤ 0.002) reduction in seasonal water requirements under NF during the dry season. Across the agro-climatic zones and cropping seasons, NF reduced total water utilization by 16.1–39.0%, indicating a substantial improvement in water conservation under farmer-field conditions. The largest water savings were observed in the High-Altitude and Southern Zones, whereas comparatively lower but significant reductions were recorded in the Godavari and Krishna zones. These improvements can be attributed to the adoption of NF practices such as alternate wetting and drying; continuous soil cover through mulching reduces evaporative losses and irrigation demand, while enhanced soil organic matter through green manuring improves soil aggregation, infiltration, and water-holding capacity [70], consistent with regional findings that natural farming enhances soil water retention through increased organic matter formation [71]. Although the magnitude of water savings observed in the present study was lower than the 50–60% reductions reported by CEEW [72], the latter estimates were derived from farmer-reported survey data, whereas the present study employed direct field measurements using digital water meters. Consequently, the present results provide a more rigorous field-based assessment of irrigation water use under NF across diverse agro-climatic zones.

The higher water productivity under NF was primarily driven by reduced irrigation requirements rather than increased water application. Earlier results from the present study showed that NF reduced total water utilization by 16.1–39.0%, while crop yield remained largely comparable to CF. Consequently, more grain was produced per unit of water consumed, resulting in a significant improvement in physical water productivity. This finding highlights that efficient water management, rather than greater water input, is fundamental to sustaining agricultural productivity under water-limited conditions. The magnitude of improvement varied among agro-climatic zones, reflecting differences in rainfall, soil characteristics, and irrigation practices. Larger gains in the Southern and High-Altitude zones indicate that moisture-conserving practices become increasingly effective where water availability is relatively constrained or rainfall distribution is more variable. In contrast, the relatively smaller improvements observed in the Krishna and Godavari zones may be associated with comparatively greater irrigation availability, where the scope for reducing water application is inherently lower. Nevertheless, the consistent increase in water productivity across all regions demonstrates that the benefits of NF are applicable under a wide range of agro-ecological conditions. The findings of Sawargaonkar et al. [73] demonstrate that resource-conserving rice production systems can substantially reduce water (52.5%) and energy (24.5%) requirements while minimizing environmental impacts over conventional rice farming.

The present study showed that absolute energy consumption was consistently higher during the Rabi season than during Kharif, particularly in the Krishna and Godavari zones. This seasonal difference is attributable to lower rainfall during the rabi season, which increases dependence on groundwater pumping, whereas monsoon rainfall during kharif partially offsets crop water demand and lowers irrigation-related energy use. Despite this seasonal variation, the relative energy-saving advantage of NF over CF remained consistent, indicating that its benefits are not season-specific but instead stem from underlying improvements in soil-water dynamics. Mechanistically, the reduced irrigation energy demand under NF can be linked to enhanced soil moisture retention, greater soil organic carbon content, improved soil aggregation, higher infiltration rates, and lower evaporative losses associated with continuous biological soil cover. These factors collectively improve crop water-use efficiency, thereby reducing both the frequency and duration of irrigation pumping-one of the largest on-farm energy inputs in Indian agriculture. Variation in energy savings across zones likely reflects differences in rainfall distribution, groundwater table depth, pumping requirements, and inherent soil moisture-holding capacity. The pronounced savings in the High Altitude and Southern zones suggest that NF delivers the greatest benefit where baseline irrigation energy demand is high. Conversely, the comparatively modest gains in the Godavari Zone may result from naturally favourable rainfall and higher residual soil moisture, which limit the additional water-conservation benefits achievable through NF. These results align with earlier assessments by Kumar and Jain [44], who reported that NF reduced total energy consumption by 24.0% in Anantapur, 21.0% in Chittoor, and 27.0% in Kurnool compared with CF, while irrigation and mechanization energy use in Guntur decreased by 30.0% and 29.0%, respectively. Furthermore, Lakhani et al. [45] reported 20.0–30.0% energy savings under NF practices over CF. These findings corroborate the present study, which also demonstrated significantly lower irrigation energy consumption under NF across agro-climatic zones.

5.2. Productivity

The variable yield response observed under NF indicates that its effect on rice productivity was strongly dependent on agro-climatic conditions and season. The relatively small yield reductions of 4.40–8.40% observed in the Southern, Krishna and High-Altitude zones are within the range commonly reported during the transition from conventional input-intensive farming to biologically based production systems. During the initial transition period, nutrient supply under NF may differ from that under CF because readily available synthetic fertilizers are replaced by biological and locally sourced inputs. Consequently, nutrient release through microbial mineralization may not always coincide with the periods of maximum crop nutrient demand, potentially contributing to modest reductions in crop growth and grain yield [26,74,75]. The greater yield reduction observed in the Krishna and High-Altitude zones, particularly during Rabi, may also reflect differences in soil fertility, moisture availability, climatic conditions, and nutrient-supply dynamics. In contrast, the absence of a significant yield penalty in the Godavari Zone in both seasons and the slightly higher, although non-significant, yield under NF in the Southern Zone during Rabi suggest that NF can maintain rice productivity under favourable production conditions. These results support the view that the effectiveness of NF is influenced by the interaction between management practices and local agroecological conditions rather than being uniformly positive or negative. The present findings are consistent with earlier studies reporting yield penalties under NF. Darjee et al. [30] reported that rice yield under natural farming was 14.2% lower than under the Integrated Nutrient Management (INM) treatment, although yields were significantly higher than the control and sole FYM treatments. Ghasal et al. [31] observed substantially lower productivity under natural farming, with grain yields declining by 51.2% in rice and 58.6% in wheat relative to INM, despite improvements in soil biological properties. A possible reason for the reduction in yield under NF, attributed to nitrogen mineralization and nutrient release, may not fully synchronize with the peak nutrient demand of rice during early crop growth, resulting in slightly reduced biomass accumulation and grain yield compared with synthetic fertilizer-based systems. However, a strong positive response under NF was observed; synthetic fertilizers are replaced by on-farm biological inputs such as Jeevamrit, Beejamrit, Ghanajeevamrit, mulching, and green manures, which gradually these practices may contribute to improved nutrient availability and soil functioning through enhanced organic matter inputs and nutrient recycling. Irrespective of inputs, Whapasa fosters a favorable soil microclimate that boosts microbial populations in the root zone, enhancing nutrient solubilization and uptake. Previous studies conducted by Bharucha et al. [41] and Duddigan et al. [71] in Andhra Pradesh and other regions of India where natural farming has generally maintained yields as compared with conventional systems after several years of adoption. Furthermore, Tripathi et al. [76] reported that NF increased crop yields by 8.0–32% across paddy, groundnut, black gram, maize, and chilli compared with conventional farming in the Andhra Pradesh region. However, yield responses varied across production environments, suggesting that the benefits of NF are strongly dependent on agro-ecological and management conditions [77]. As organic matter continues to accumulate over time, the initial yield gap observed in some agro-climatic zones is expected to narrow further, suggesting that long-term adoption of natural farming can simultaneously enhance environmental sustainability and farm profitability without substantial sacrifice in crop productivity. The absence of a statistically significant difference in rice yield between NF and CF in the Godavari Zone is noteworthy and may be associated with the favourable production environment of the region. The Godavari Zone is characterized by fertile alluvial soils, substantial irrigation infrastructure and a strong rice-based production system, providing relatively favourable conditions for crop growth. Such conditions may have reduced nutrient and water limitations and enabled the biological nutrient cycling and soil-moisture conservation associated with NF to support crop productivity comparable with CF. Similarly, the lack of a significant yield difference between NF and CF during the Rabi season in the Southern Zone may reflect relatively favourable seasonal growing conditions and adequate resource availability during crop establishment and growth. Previous research has demonstrated that rice yield responses to climatic and irrigation conditions vary considerably among agro-climatic zones of Andhra Pradesh [78]. Therefore, the comparable performance of NF and CF in these environments suggests that the productivity response to NF is context-specific and depends on the interaction between management practices and local soil, climatic, and water-resource conditions.

5.3. Profitability

The substantial reduction in cultivation cost under natural farming primarily resulted from the elimination of synthetic fertilizers, pesticides, and other externally purchased agrochemicals, which constitute a major proportion of production costs in conventional rice cultivation. Instead, NF relies on farm-derived biological inputs, including Jeevamrit, Ghanajeevamrit, Beejamrit, botanical extracts, mulching, and crop residues, which are prepared using locally available materials such as cow dung, cow urine, pulse flour, and jaggery. Consequently, dependence on commercial agricultural inputs is considerably reduced, leading to significant savings in production expenditure. These findings agree with earlier studies on Andhra Pradesh Community Managed Natural Farming, which reported reductions of 20.0–35.0% in cultivation costs due to decreased dependence on purchased agricultural inputs while maintaining comparable crop productivity [34,41,72,79,80]. Therefore, the significant reduction in cultivation costs observed across all agro-climatic zones highlights the economic viability of NF and supports its potential as a climate-resilient and resource-conserving production system for sustainable agriculture.

NF enhanced net returns by 8.80–29.0% across agro-climatic zones, despite slight reductions in gross returns in some locations. Previous studies have demonstrated the economic benefits of NF; for instance, the CEEW [80] reported a 51.0% increase in the income of paddy farmers practicing NF compared with CF, while Kumar and Jain [44] reported a 36.0% increase, confirming the positive impact of NF on farm profitability. Furthermore, Koner and Laha [50] reported that although NF reduced crop yield after conversion, the substantial reduction in cultivation costs enabled farmers to achieve higher net income than CF. Significantly higher net returns under NF were primarily attributable to the substantial reduction in cultivation costs, which more than compensated for the modest yield reductions observed in some agro-climatic zones. Although gross returns under NF were comparable to or slightly lower than those under CF, the 20.6–35.1% reduction in production costs resulted in 8.80–29.0% higher net returns across all agro-climatic zones. Similar findings were reported by Tripathi et al. [76], who observed higher farm profitability under NF because of reduced dependence on purchased agricultural inputs. The present results demonstrate that the economic advantage of NF is driven primarily by lower input costs rather than higher crop yields, making it a profitable and resource-efficient production system for rice cultivation.

The consistently higher BCR under NF reflects its superior economic efficiency arising from a substantial reduction in production costs while maintaining crop productivity comparable to conventional management. Unlike conventional agriculture, which relies heavily on costly chemical fertilizers, pesticides, and other external inputs, NF utilizes low-cost, farm-derived biological formulations, crop residue mulching, and ecological crop management practices that considerably reduce production expenditure. Since gross returns remained largely comparable between the two production systems, the reduction in cultivation costs substantially increased the return generated per unit of investment, thereby improving the BCR. The results obtained from the present study aligned with Pathania and Spehia [81], who reported that despite a 19.1% lower pea yield under NF compared with CF, the substantially lower cultivation cost improved economic returns, resulting in a higher BCR (2.13) than CF (1.52). Similarly, Majhi et al. [56] reported that NF reduced the cost of cultivation by 12.4–14.1% across brinjal, okra, and tomato crops compared with CF. Although crop yields under NF were 10.8–18.0% lower, the lower production costs resulted in a slightly higher BCR, increasing by 1.80–3.20% over CF. These findings suggest that the economic advantage of NF is primarily driven by reduced cultivation costs, which can offset moderate yield reductions and improve overall farm profitability. However, a contrary result obtained by Ghasal et al. [31] reported that, compared with integrated crop management, NF reduced the cost of cultivation by 10.6%, whereas the lower basmati rice productivity under NF resulted in 46.4% lower gross returns, 67.2% lower net returns, and a 39.9% lower BCR (1.63 vs. 2.71). These findings indicate that although NF reduced input costs, the substantial decline in crop productivity outweighed the savings in cultivation costs, making ICM economically more profitable under the rice–wheat production system.

5.4. Yield Stability and Soil Health

The Sustainable Yield Index (SYI) is a quantitative indicator used to assess the sustainability and stability of crop production under different management practices [67,82]. It considers both the average yield and its variability over the study period. A higher SYI indicates greater yield stability and sustainability, whereas a lower value indicates greater yield variability and comparatively lower sustainability. The index has been used to evaluate the sustainability of long-term cropping systems in India and to compare the stability of crop production under different management practices [83,84]. The variation in SYI among agro-climatic zones suggests that the influence of NF on yield stability is strongly governed by local environmental conditions, soil characteristics, and the duration of ecological transition. The slightly lower SYI observed under NF in several agro-climatic zones may reflect the initial adaptation phase associated with reduced synthetic nutrient inputs, during which biological nutrient cycling and soil ecological processes are still developing. Nevertheless, the relatively high SYI values (0.68–0.91) recorded under NF across all locations indicate that crop production remained reasonably stable over the study period despite substantial reductions in external inputs. The marginal improvement in SYI observed in the Godavari Zone during both seasons and in the Southern Zone during rabi indicates a potential improvement in yield stability under NF in these agro-climatic conditions. This response may partly reflect differences in soil moisture management and nutrient availability between farming systems, although these mechanisms were not directly quantified in the present study.

The contrasting changes in soil pH across agro-climatic zones indicate that NF may have a soil-buffering effect, with the direction of change depending largely on the initial soil reaction. The increase in pH observed in the acidic Krishna and High-Altitude zones suggests that NF may help alleviate soil acidity and move soil conditions toward a more favourable range for nutrient availability and microbial activity. Conversely, the reduction in pH in the moderately alkaline Southern and Godavari zones indicates that NF may moderate excessive alkalinity. These responses may be associated with the continuous application of organic inputs such as farmyard manure, Jeevamrutha, and Ghanajeevamrutha, whereas conventional farming (CF) mainly depends on chemical fertilizers. As organic materials decompose, they release calcium, magnesium, and potassium, which help neutralise soil acidity through buffering and bicarbonate accumulation [85]. This explains why, in the acidic Krishna and High-Altitude zones, NF increased soil pH and brought it closer to neutral. In contrast, decomposition of organic matter under aerobic conditions also generates organic acids and carbon dioxide [86], and mineralization of manure-derived organic N and S releases H⁺ ions; in alkaline soils, these processes help lower excess pH. This is consistent with the decrease in soil pH observed in the Southern and Godavari zones, where NF shifted pH toward a more neutral range. These results demonstrate that NF tended to buffer soil reaction toward near-neutral conditions, which are generally considered optimal for nutrient availability and microbial activity. This buffering effect may be attributed to continuous additions of organic amendments, enhanced microbial decomposition, and improved cation exchange processes that moderate soil acidity or alkalinity, consistent with the accumulation of base cations and increased base saturation reported under organic amendment [87]. Similar improvements in soil pH under organic and natural farming systems have been reported due to increased biological activity and greater buffering capacity of organically managed soils [88,89,90]. Enhanced SOC under NF can be attributed to regular incorporation of organic inputs (FYM, Jeevamrutha), crop residues, green manuring, mulching, reduced soil disturbance, and greater root biomass, all of which increase carbon inputs while minimizing carbon losses through oxidation [91]. Higher SOC enhances aggregate stability, water-holding capacity, and nutrient cycling, thereby improving overall soil health [92]. According to Kourgialas [93], organic farming practices strengthen the soil–water–crops–energy nexus by enhancing soil organic matter, which improves fertility, water retention, and carbon storage, making soils more resilient to droughts and floods. These findings corroborate previous studies demonstrating that natural and organic farming systems promote carbon sequestration and improve soil quality through continuous organic matter enrichment [71,90].

The increased nitrogen availability under NF is likely associated with the addition of biological inputs such as farmyard manure or compost, enhanced microbial mineralization of organic materials, greater biological nitrogen fixation, and reduced nitrogen losses resulting from improved soil structure and moisture conservation [71,91]. The regular application of biologically active formulations such as Jeevamrit may further stimulate microbial activity, which may be responsible for nitrogen cycling, thereby increasing plant-available nitrogen; Jeevamrutha has been shown to substantially enrich populations of free-living nitrogen-fixing bacteria and other beneficial microbial groups relative to conventionally managed soils, as previously documented by Kulkarni and Gargelwar [94] and Duraivadivel et al. [95]. The variation in available nitrogen across the agro-climatic zones was mainly attributed to differences in rainfall patterns, soil moisture availability, temperature regimes, and landscape physiography, which regulate soil organic matter dynamics and microbial processes [96]. Higher rainfall and cooler temperatures in the High-Altitude zone favored greater organic matter accumulation and nitrogen mineralization, whereas the warmer climate, intensive cropping, and relatively lower soil organic carbon in the Krishna zone accelerated nitrogen depletion through greater crop uptake and enhanced nitrogen losses.

The higher phosphorus availability under NF is primarily attributed to the regular addition of organic inputs such as FYM, Jeevamrutha, Ghanajeevamrutha, and crop residues, which accumulated organic matter in soil [71]. During decomposition, organic materials release organic acids that solubilize insoluble phosphorus compounds and reduce phosphorus fixation by calcium, iron, and aluminum, thereby increasing the pool of plant-available phosphorus [97]. As reported by Kalayu [98], enhanced populations of phosphate-solubilizing microorganisms under NF further improve phosphorus mobilization and availability to crops by lowering rhizosphere pH and chelating Fe, Al, and Ca ions. The variation in available phosphorus across the agro-climatic zones was mainly influenced by differences in soil type, rainfall distribution, soil moisture regime, temperature, and phosphorus fixation capacity. The Southern and Krishna zones recorded relatively higher available phosphorus because their clay-rich Vertisols possess greater nutrient-holding capacity and moderate moisture conditions that may favor microbial phosphorus mineralization [99]. In contrast, the comparatively lower phosphorus content in the Godavari and High-Altitude zones may be associated with greater rainfall and weathering intensity, which increase phosphorus fixation and runoff losses despite higher organic matter inputs [100]. Nevertheless, the proportional increase under NF remained highest in the Godavari zone (25.1%), indicating that organic management was particularly effective in improving phosphorus availability in soils with relatively low native phosphorus status.

The higher potassium availability under NF can be attributed to the continuous addition of organic manures, which release potassium during decomposition and facilitate the dissolution of potassium-containing minerals in response to naturally occurring acids, such as fulvic and humic acids, and reduce fixation [101]. The result obtained in this study aligns with the findings of Wafaa and Mona [102] and Darjee et al. [30]. The enhanced microbial activity under NF also promotes mineral weathering, thereby releasing non-exchangeable potassium into plant-available forms [103]. Furthermore, increased soil organic carbon improves potassium retention and reduces nutrient losses through leaching and erosion. The variation in available potassium across the agro-climatic zones was primarily governed by differences in parent material, clay mineralogy, rainfall, soil moisture, temperature, and crop nutrient removal. The Southern zone recorded the highest potassium content, likely because the clay-rich Vertisols possess high potassium reserves and greater cation exchange capacity, enabling better potassium retention. Conversely, the relatively lower potassium content in the Godavari zone may be attributed to higher rainfall and more intense weathering, which promote potassium leaching and depletion. The Krishna and High-Altitude zones exhibited intermediate potassium levels, reflecting differences in soil mineral composition and climatic conditions that regulate potassium release and retention. The greatest percentage increase under natural farming was observed in the Krishna zone (17.5%), suggesting that organic inputs and enhanced biological activity substantially improved potassium availability even in soils with comparatively lower native fertility.

6. Conclusions

The present study demonstrates that natural farming (NF) can improve resource-use efficiency and economic performance of rice production across diverse agro-climatic zones of Andhra Pradesh. Regarding RQ1, NF substantially reduced total water utilization by 16.1–39.0% compared with conventional farming (CF), while water productivity increased by 15.0–55.5% across agro-climatic zones and cropping seasons. These findings indicate that NF can conserve irrigation water while improving the efficiency with which available water is converted into rice yield. Addressing RQ2, NF reduced irrigation-related energy consumption by 21.8–57.7% and cultivation costs by 20.6–35.1% relative to CF. Although rice yield under NF was modestly lower by 4.40–8.40% in some zones, gross returns remained broadly comparable with those under CF. The reduction in production costs therefore more than compensated for the modest yield reduction, resulting in 8.80–29.0% higher net returns and a 23.7–47.8% higher benefit–cost ratio under NF. These results demonstrate that the economic advantage of NF was primarily associated with reduced cultivation expenditure rather than higher gross returns. In relation to RQ3, NF maintained relatively stable rice productivity across the study environments, as indicated by Sustainable Yield Index values ranging from 0.68 to 0.91. In addition, NF improved soil chemical properties by shifting soil pH toward a more neutral range and increasing soil organic carbon and available N, P, and K across the agro-climatic zones. Thus, the findings suggest that NF can simultaneously support soil fertility and yield stability while reducing dependence on synthetic agricultural inputs. Despite the clear resource-conservation and economic benefits demonstrated by NF, its widespread adoption among rice producers is likely to be gradual. The principal barriers include higher labour requirements during the transition period, limited availability of raw materials for preparing bio-inputs, concerns regarding yield stability, and the need for timely biological management of weeds, pests, and diseases. Beejamrit, Jeevamrit, and Ghanajeevamrit are generally prepared by farmers using locally available materials, although these inputs are also available through village-level Bio-input Resource Centres (BRCs) maintained by RYSS. Successful adoption therefore depends less on access to commercial inputs than on practical training and extension support. Field demonstrations, farmer-to-farmer learning, and village-level capacity-building programmes are particularly important because they enable farmers to gain confidence in bio-input preparation, dosage, water management, and pest management under real field conditions. The findings of this study will be communicated through RySS extension activities, farmer field schools, demonstration plots, and training workshops, providing scientifically validated evidence to support the wider adoption of natural farming in rice-based production systems.