Methane production potential, soil health and rice yields under inorganic and organic management in the Brahmaputra Valley of Assam, India

Abstract

Methane (CH₄), a powerful greenhouse gas emitted from flooded rice soils is a major contributor to climate change. Its production is significantly influenced by on-farm nutrient management practices. The present study compared the effects of long-term inorganic and organic management practices on methane production potentials, selected soil health indicators, and grain yields in farmers’ rice fields of Assam. We hypothesized that long-term organic nutrient management increases soil CH₄ production potential due to enhanced carbon availability, but simultaneously improves soil health and rice productivity compared to inorganic fertilization. Considering both the years of study, CH₄ production potential ranged between ~133 and ~236 CH₄ g^-1 day^-1, organic carbon between 0.38 and 0.70%, microbial biomass carbon between 400 and 547 µg g^-1, and grain yield between ~2809 and ~5684 kg ha^-1 in the inorganic fields. Similarly, in the organic fields, CH₄ production potential, organic carbon, microbial biomass carbon and grain yield ranged between ~167 and 344 CH₄ g^-1 day^-1; 0.50 and 0.91%; 300 and 890 µg g^-1; ~5267 and ~7731 kg ha^-1 respectively. Comparatively higher CH₄ production rates in organic fields may be due to enrichment of the soil organic carbon pool via decomposition of applied organic amendments, leading to enhanced microbial biomass and activity. CH₄ production under organic management showed good association with soil pH, organic carbon, and microbial biomass carbon. However, higher CH₄ production in organic fields was partly compensated by improved soil properties and rice yields than inorganic fields. Higher grain carbohydrate in organic fields indicate efficient carbohydrate partitioning to the grains and better nutrient utilization by the crop. Vermicompost and vermiwash applied fields recorded lower CH₄ production among the organic treatments and higher yield among all the studied treatments. Cow manure and Azolla application also significantly reduced CH₄ production but improved yield to a comparatively lesser extent. Our findings suggest that appropriate organic management practices could reduce CH₄ production rates in rice soils while enhancing soil health and crop yield.

1 Introduction

Ensuring food security for a burgeoning world population while reducing the environmental footprint of agriculture is one of the central challenges of the twenty-first century. The adverse effects of a changing climate on crop production make the scenario even more challenging. To achieve these dual goals, there is an urgent need to develop sustainable strategies that can meet the food demand while protecting soil health and reducing agricultural greenhouse gas (GHG) emissions (Chataut et al., 2023; Mrabet, 2023; Mondal et al., 2024; Singh et al., 2024). Agriculture is a major contributor to global GHG emissions, accounting for approximately 10-12% of the total emissions of methane (CH₄), the second most important GHG after carbon dioxide (CO₂), having a global warming potential 28 times that of CO₂ (IPCC, 2021).

Rice is the staple food for half of the world’s population. The global population is expected to reach almost nine billion by 2050, which will lead to a 70% increase in food demand (FAO, 2009; Tripathi et al., 2019). Rice production is projected to increase from 676 million tons in 2010 to 852 million tons in 2035 and an additional 176 million tons in the next 25 years worldwide (Ahmed et al., 2017; Hussain et al., 2022). The anaerobic environment in flooded rice fields provides suitable substrates for the activity of CH₄-producing bacteria (methanogens) through the decomposition of organic matter (Pandey et al., 2021), making rice cultivation a major source of CH₄. The emissions of CH₄ to the atmosphere are regulated by complex and dynamic interactions among plants, microorganisms, and production-oxidation potential rates of the ecosystems (Mitra et al., 2012; Arianti et al., 2022). Although soil carbon promotes the production of CH₄ by methanogenic bacteria, a part of the CH₄ produced is oxidized into CO₂ and H₂O by methanotrophic bacteria (Conrad, 2007; Fazli et al., 2013). Therefore, CH₄ production and oxidation rates are important determinants of net CH₄ emissions from soils.

Nutrient management practices employed for crop cultivation considerably influence soil conditions and microbial activities, determining overall CH₄ emissions from rice fields. Two broad nutrient management approaches adopted worldwide, namely, inorganic and organic, have their own pros and cons in terms of CH₄ emissions, soil health and food production. With respect to CH₄ emissions, varying effects of inorganic fertilizers have been reported. In some cases, the application of N-fertilizers has increased CH₄ emissions probably due to an increase in the carbon substrates for methanogenic bacteria (Banger et al., 2012; Trinh et al., 2017; Gu et al., 2022), whereas some reports have shown inhibitory effects (Yuan et al., 2017; Hou et al., 2020). Excessive application of inorganic fertilizers leads to a reduction in soil fertility, and increases environmental as well as human health-related hazards (Baweja et al., 2020; Hossain et al., 2022). The application of inorganic fertilizers improves crop production by providing nutrients only for a short period but it deteriorates soil health and reduces food production in the long run (Tripathi et al., 2020; Pahalvi et al., 2021). Organic amendments can potentially replace inorganic fertilizers to meet nutrient requirements for crop growth and promote soil health by regulating the physico-chemical and biological properties (Dong et al., 2021; Samui et al., 2024). However, amending soils with organic fertilizers generally adds to the labile C pool and increases soil CH₄ emissions in flooded conditions (Yuan et al., 2018; Pandey et al., 2021; You et al., 2022). Moreover, some studies report lower rice yield under organic management compared to inorganic management (Hou et al., 2020; Kumar et al., 2023).

India is the second most rice-producing country in the world (Annamalai and Johnson, 2023). Studies from India have reported organic and integrated nutrient management practices as feasible options for reducing CH₄ emissions from rice fields while boosting crop yields (Kumar et al., 2022; Senthilraja et al., 2023). The Brahmaputra Valley floodplain is a major crop-growing area within the state of Assam in Northeast India due to its highly rich alluvial soil, and has long been a key rice-producing region, not only within India but also across Southeast Asia (Bhuyan et al., 2024). The farmers of this region adopt diverse nutrient management practices for rice cultivation which can be broadly categorized into inorganic and organic. However, there is limited information on the effects of these long-term farmer practices on the CH₄ production potential (CH₄-pp) rates of the rice soils. Therefore, this study aims to carry out a comparative assessment of CH₄-pp rates, soil properties and grain yields in existing inorganic and organic farmers’ rice fields of Assam, which will generate new insights into their relative contributions to climate change and food security.

2 Materials and methods

2.1 Details of study area and selection of rice fields

The study was carried out in the state of Assam in India, located between 90.00° - 96.00° E longitudes and 24.00° - 28.00° N latitudes. It has a tropical monsoon rainforest climate with high humidity and rainfall. A moderate climate with warm summers and mild winters exists throughout the year. The average temperature fluctuates from 35-38 °C in summer and 6-8 °C in winter. The state receives an annual rainfall of about 2376.7 mm, with the Southwest monsoon being the primary source of rainfall. The present study was conducted in three major rice-growing agro-climatic zones of Assam viz., Upper Brahmaputra Valley Zone (UBVZ), Lower Brahmaputra Valley Zone (LBVZ) and North Bank Plain Zone (NBPZ) during the rain-fed rice season (July-November/December) of 2018 and 2019. The study area map was constructed using QGIS (Version 3.16.7) (Figure 1).

Figure 1

A preliminary survey was conducted among the farmers of the selected zones to gather information about the prevailing nutrient management practices in the rice fields. Based on the information obtained from the survey, two districts having both inorganic and organic rice fields were selected from each zone (Figure 1). The districts were namely, Jorhat and Golaghat from UBVZ; Kamrup (Rural) and Kamrup (Metro) from LBVZ; Biswanath Chariali and North Lakhimpur from NBPZ. Within each district, adjacent inorganic and organic rice fields having similar climatic and soil characteristics were identified for the study. According to local farmers, these fields had been treated with either organic or inorganic fertilizers for approximately 20 years. This made a total of twelve rice fields (six inorganic and six organic) across six districts for sampling (Table 1). Controlled experiments were not conducted in this study, rather, soil samples were collected from farmers’ fields under various existing nutrient management practices. Detailed information on fertilizer types, combinations and application rates supplied in the selected fields during the study period were obtained by interviewing the farmers and are shown in Table 1. Soil samples collected from these fields were analyzed in the laboratory for selected variables, which were then compared using statistical analyses.

Other agronomic approaches employed in the selected fields were the same as the general practices followed for rain-fed rice cultivation in Assam. For instance, the tillage method is conventional tillage and the source of water during the rice growing season is rainfall received from the Indian monsoon. Rice is grown only in the rain-fed season, followed by other crops or vegetables in the dry period. Cultivation of high yielding varieties like Ranjit was prevalent in both inorganic and organic farms. Organic methods of pest management were adopted in the organic fields.

2.2 Soil sample collection, processing and analysis

Soil samples were randomly collected from each of the twelve rice fields (n=4x12 = 48; 24 samples from inorganic and 24 from organic fields) at the maximum-tillering stage of the rice plants. Soils from each pair of inorganic and organic neighboring fields were sampled consecutively on the same day. Each uniformly treated field was spatially demarcated into smaller subplots and independent composite soil samples were collected from these subplots. Sampling was done from 0–15 cm soil depth using a soil core measuring 5 cm in diameter. Each composite sample was prepared by pooling multiple soil cores collected within a defined subplot. The samples were then sealed in zip-lock bags and transported to the laboratory. Air-dried, ground and sieved samples were stored for analysis of various soil parameters. The composite samples derived from the subplots were analyzed independently and considered as true replicates in the statistical analysis. Within each composite sample, laboratory (technical) replicates were analyzed to minimize the error and their values were averaged prior to statistical analysis.

2.2.1 Soil physicochemical and biochemical parameters

Gravimetric soil moisture (SM) content was determined by oven-drying a known weight of fresh soil at 105 °C for 24 hours or more until a constant dry weight was obtained. Differences in fresh and dry weights were used to calculate the moisture content which was expressed as a percentage. The remaining portion of soil samples were air-dried at room temperature, gently crushed to break soil aggregates, and passed through a 2 mm stainless steel sieve. The sieved soil samples were stored and used for subsequent analyses of other parameters.

Soil pH and electrical conductivity (EC) were measured in a 1:2.5 (w/v) soil-to-distilled water suspension after shaking for 30 minutes. Soil pH was recorded using a digital pH meter (GeNei), and EC was measured using a conductivity meter (Systronics Type 304). Soil organic carbon (SOC) content was determined by the modified Walkley and Black (1934) wet oxidation method. In this method, the organic matter in the sample is oxidized using potassium dichromate, and then, the sample is back-titrated with standard ferrous ammonium sulfate solution, allowing for calculation of SOC after comparison with a blank (without soil) sample. Soil microbial biomass carbon (SMBC) was estimated using the chloroform fumigation-extraction method described by Brajendra Latha et al. (2014). Extracts were prepared from chloroform fumigated and non-fumigated soil samples and the difference in extractable carbon was used to calculate SMBC. Soil respiration (SR) was measured following the alkali absorption method, wherein carbon dioxide (CO₂) evolved during soil incubation was trapped in 0.05 M NaOH and subsequently quantified by titration with 0.1 M HCl (Brajendra Latha et al., 2014).

Soil nitrate (NO₃^-) was determined by the phenol disulphonic acid method (Jackson, 1973). Nitrate extracted from soil was made to react with phenol disulphonic acid for development of a yellow color. The absorbance of the colored solution was read at 410 nm in a UV-visible spectrophotometer (Shimadzu UV 1900), allowing for calculation of nitrate content. Available phosphate (PO₄^-) was determined by the Bray and Kurtz (1945) method. Phosphorous bound to soil was extracted using Bray and Kurtz No.1 extracting solution containing hydrochloric acid and ammonium fluoride. The extract was reacted with ammonium molybdate for the development of a blue color. The intensity of blue color was measured in a spectrophotometer (Shimadzu UV 1900) at 882 nm, allowing for calculation of available phosphorous.

The activities of soil enzymes, namely acid phosphatase (APs) and alkaline phosphatase (ALP), were assayed using 4-nitrophenyl phosphate disodium as the substrate as described by Brajendra Latha et al. (2014). After incubation, the intensity of the yellow color produced was measured spectrophotometrically at 410 nm using a UV-visible spectrophotometer (Shimadzu UV-1900), and enzyme activity was expressed on a soil dry weight basis.

2.2.2 CH₄ production potential rate (incubation experiment)

Methane production potential (CH₄-pp) was determined as described by Mitra et al. (2002) with minor modifications. In brief, 20 grams of dry soil were mixed with 40 mL deionized water in 100 mL glass beakers, which were capped with a butyl rubber stopper with two openings. Two openings were used: one for N₂ flushing and another with a silicone septum for gas sampling. Twenty-four hours before each sampling, the beakers were flushed with N₂ at 250 mL min^-1 for three minutes. The flasks were shaken constantly during flushing to remove accumulated CH₄ and establish anaerobic conditions. Then, the samples were incubated at 30°C for 40 days in a Biological Oxygen Demand (BOD) incubator. Gas samples were collected by an airtight syringe every third and fourth day, starting on the sixth day after the incubation began. After sampling at 6, 9, 13, 16, 20, 23, 27, 30, 33, 37, and 40 days of incubation, gas samples were analyzed using a gas chromatograph (Thermo Scientific GC, Trace 1110). The gas chromatograph was equipped with a flame ionization detector (FID) and a packed column. Column, injector, and detector temperatures were maintained at 30°C, 80°C, and 240°C, respectively. The gas chromatographic system was calibrated periodically with a standard obtained from CALIPORT, Chemtron Science Laboratories Pvt. Ltd. Nashik, Mumbai, India. Nitrogen (N₂) (99.999% pure) was used as a carrier gas whereas, hydrogen (H₂) (99.999% pure) and zero air (99.999% pure) were used for ignition of the flame in the FID. Soil pH and EC were also recorded on each sampling day using a pH meter (model GeNei) and a conductivity meter (model SYSTRONICS TYPE 304) respectively. After the gas sampling, the beakers were flushed again with N₂ for 30 seconds and put back in the incubator.

CH₄-pp rates were calculated using the following equation given by Mitra et al. (2002):

Where C_i= CH₄ concentration (µg CH₄ g^-1 soil d^-1); C_a=CH₄ concentration in the headspace; V_hs= volume of headspace; MW=molecular weight of CH₄ (mg mmol^-1); MV=molar volume of CH₄ at 30°C (mmol ml^-1); W_s= weight of dry soil (g); d= numbers of incubation days.

2.3 Yield and grain parameters

To determine grain yield, an area of 1metre square was demarcated in each field with the consent of the farmers. The rice plants within this area were harvested, and threshed, and the grain weight was recorded using a weighing balance. Using this method, four replicated readings of grain yield were taken from each field. The total carbohydrate (TC) content of the grains was calculated by the method given by Hedge and Hofreiter (1962). A total of 100 mg of finely powdered grain sample was hydrolyzed in a water bath for three hours before digesting with 5 mL of 2.5 N HCl. Sodium carbonate was used to neutralize the contents until the effervescence ceased. The neutral extract was then diluted with 100 mL of distilled water and filtered using Whatman No. 1 filter paper. The filtrate was reacted with 4 mL of anthrone reagent for 8 minutes in a boiling water bath, upon which the green color developed. The absorbance of the solution was measured with a Shimadzu UV 1900 spectrophotometer at 630 nm, using D-glucose as the standard.

2.4 Statistical analysis

Six varying nutrient management practices were reported under inorganic management and six under organic management. Significant treatment differences in the studied variables within these two management categories were analyzed using ANOVA followed by Duncan’s multiple range test (DMRT). Further, independent t-test was performed to analyze differences in CH₄-pp rates and grain yields between inorganic and organic fields at each location. To account for year and zone effects, a linear mixed-effects model analysis was performed for CH₄-pp rates and rice yields. Pearson’s correlation analysis was performed to determine the statistically significant relationships among the studied variables. The software package SPSS version 20.0 was used for statistical analysis and Origin pro software was used for constructing the graphs.

3 Results

3.1 Methane production potential rates

CH₄ production rate (CH₄-pp) in inorganic fields ranged from 132.89-236.38 µg CH₄ g^-1 soil day^-1 during the first year (Figure 2a) and from 137.89-234.81 CH₄ g^-1 soil day^-1 during the second year (Figure 2b). In both the years, the inorganic field of Golaghat showed lower mean values of CH₄-pp compared to similar fields of other locations, indicating variable effects of inorganic fertilizer combinations by location (Figures 2a, b). Among the organic fields, CH₄-pp ranged from 166.63-334.47 µg CH₄ g^-1 soil day^-1 in the first year (Figure 2c); and from 171.63-344.47 µg CH₄ g^-1 soil day^-1 in the subsequent year (Figure 2d). Organic soils of Golaghat amended with cow manure and Azolla, and those of North Lakhimpur amended with only cow manure showed the lowest and highest CH₄-pp values respectively, in both the years (Figures 2c, d).

Figure 2

3.2 Soil parameters

3.2.1 pH, EC and SM

Basic soil properties like pH and EC of organic fields were generally higher than that of inorganic fields (Tables 2, 3). Soil pH ranged from 5.27-5.80 in inorganic fields and from 5.62-6.14 in organic fields. Among the organic fields, soils of Golaghat amended with cow manure and Azolla recorded the lowest pH, whereas those amended with a combination of vermicompost and vermiwash in Kamrup (M) recorded the highest pH (Table 3). Similarly, soil EC varied from 325.06-612.89 µS cm^-1 in inorganic fields and from 402.94-625.39 µS cm^-1 in organic fields (Tables 2, 3). Soils of Kamrup (R) supplied with cow manure and vermiwash showed lower values of EC; whereas soils of Biswanath Chariali with combined application of cow manure, vermicompost and Azolla showed higher EC compared to other organic treatments (Table 3). Individual effect of treatment (T) and interactive effects of treatment and year (TxY) were significant (p<0.01) for both pH and EC (Tables 2, 3). The soil moisture (SM) content ranged from 35.14-46.14% in inorganic fields and from 30.73-45.69% in organic fields. Organic fields of Kamrup (R) and Kamrup (M) showed higher SM retention than inorganic fields of the same locations, whereas the opposite pattern was noted in the other locations (Tables 2, 3). This suggests that different types or combinations of inputs differ in their capacity to retain moisture. Treatment effects on soil moisture were significant (p<0.01) in both management types (Tables 2, 3).

3.2.2 SOC, SMBC and SR

Organic fields generally exhibited higher mean SOC over inorganic fields in both the years, with the exception of Biswanath Chariali in the second year (Figure 3). SOC in inorganic fields ranged from 0.38-0.50% during the first year (Figure 3a) and from 0.46-0.70% during the second year (Figure 3b). In both the years, inorganic soils of Kamrup (R) showed lower mean SOC compared to those of other locations. In organic fields, SOC ranged from 0.50-0.91% in the first year (Figure 3a); and from 0.60-0.90% in the subsequent year (Figure 3b). Under organic management, soils of North Lakhimpur amended with cow manure showed the lowest SOC in both the years; whereas soils of Biswanath Chariali amended with cow manure, vermicompost and Azolla showed the highest SOC in the first year and those of Golaghat amended with cow manure and Azolla showed the highest SOC in the second year (Figure 3). Treatment effects on SOC were significant (p<0.05) in both management types (Figure 3). SMBC levels in organic fields were higher than their inorganic counterparts in all the locations except North Lakhimpur (Figure 4). SMBC in inorganic fields ranged from 400.00-547.00 µg g^-1 during the first year (Figure 4a) and from 430-530.26 µg g^-1 during the second year (Figure 4b). Inorganic fields of Golaghat in the first year and Kamrup (R) in the second year recorded lower SMBC than those of other locations (Figure 4). SMBC in organic fields ranged from 402.77-890.00 µg g^-1 in the first year (Figure 4a); and from 300-873.88 µg g^-1 in the subsequent year (Figure 4b). The organic field of North Lakhimpur amended with cow manure recorded the lowest SMBC, whereas that of Biswanath Chariali amended with cow manure, vermicompost and Azolla recorded the highest SMBC in both the years (Figure 4). Treatment effects on SMBC were significant (p<0.01) in both management types (Figure 4) suggesting that SMBC responds to variations in input types and application rates. The SR rates ranged from 0.09-0.43 mg CO₂ g soil^-1–24 h^-1 in the inorganic fields and from 0.08-0.45 mg CO₂ g soil^-1–24 h^-1 in the organic fields. No clear pattern of SR variation between inorganic and organic management was noted in the study (Tables 2, 3). Under organic management, soils of North Lakhimpur amended with cow manure recorded the lowest SR, whereas soils of Jorhat amended with cow manure and rice straw compost recorded the highest levels of SR (Table 3). Interactive effects of treatment and year (TxY) on SR levels were significant (p<0.05) in both management types (Tables 2, 3).

Figure 3

Figure 4

3.2.3 Soil nutrients

Inconsistent variation in soil NO₃^- content was observed between inorganic and organic fields of the studied locations, however, PO₄^- content was generally higher in inorganic fields (Tables 2, 3). NO₃^- content ranged from 5.26-7.56 kg ha^-1 in inorganic fields and from 3.26-6.66 kg ha^-1 in organic fields. Similarly, PO₄^- content ranged from 20.20-36.22 kg ha^-1 in inorganic fields and from 16.35-23.15 kg ha^-1 in organic fields. Organic soils of Kamrup (R) treated with cow manure and vermiwash recorded the lowest NO₃^- level but showed the highest PO₄^- content (Tables 2, 3). These differences highlight amendment-specific influences on soil nutrient status. Individual effect of treatment and interactive effects of treatment and year on nutrient levels were significant under both management types (Tables 2, 3).

3.2.4 Soil enzymes

Soil ALP activity showed inconsistent variation between inorganic and organic management types (Tables 2, 3). ALP activity ranged from 58.24-144.00 g pnp g dry soil^-1 hr^-1 in inorganic fields and from 88.16-114.00 g pnp g dry soil^-1 hr^-1 in organic fields (Tables 2, 3). Among the organic fields, the lowest ALP activity was found in soils of Kamrup (M) treated with vermicompost and vermiwash; whereas, highest activity occurred in Kamrup (R) soils treated with cow manure and vermiwash (Table 3). Similarly, the APs activity ranged from 220.17- 533.49 g pnp g dry soil^-1 hr^-1 in inorganic fields and from 255.09-364.75 g pnp g dry soil^-1 hr^-1 in organic fields. APs activity was generally higher in inorganic fields over organic fields, except in Biswanath Chariali and North Lakhimpur (Tables 2, 3). Among organic fields, soils treated with cow manure and vermiwash in Kamrup (R) recorded the lowest APs activity, whereas the soils treated with vermicompost and vermiwash in Kamrup (M) recorded the highest APs activity (Table 3). Treatment effects were significant for ALP activity in both inorganic and organic systems, but for APs activity, no significant treatment effect was noted in the organic system (Tables 2, 3).

3.3 Grain yield and TC

In both the years, comparatively higher rice yield was observed in organic management over inorganic management (Figure 5). In the inorganic system, rice yield ranged from ~2809–5818 kg ha^-1 in the first year (Figure 5a) and from ~3236–5684 kg ha^-1 in the second year (Figure 5b). In both the years, soils of Biswanath Chariali treated with Urea, SSP and MOP in the ratio 53:30:30 kg ha^-1 produced higher rice yields compared to other inorganic fields. In the organic system, the yield ranged from ~5267–7731 kg ha^-1 in the first year (Figure 5c) and from 6032–7612 kg ha^-1 in the subsequent year (Figure 5d). Organic soils of Kamrup (M) amended with vermicompost and vermiwash produced higher yield in both the years compared to other organic fields. Treatment effects were significant (p<0.01) for both the years and management types (Figure 5). The total carbohydrate (TC) of the grains varied from 17.43-28.76% in the inorganic fields, and from 24.14-44.08% in the organic fields, with significant treatment and year effects (Tables 2, 3). Treatment with cow manure and Azolla in organic fields of Golaghat and combined application of cow manure, vermicompost and Azolla in organic fields of Biswanath Chariali produced grains with significantly higher TC content than the other treatments (Table 3).

Figure 5

3.4 Independent t-test and linear mixed-effects analysis

Independent t-test analysis on pooled data of two years revealed significant differences in CH₄-pp and grain yield between the pair of inorganic and organic fields at each study location (Table 4). Irrespective of the zone or district/location, both CH₄-pp and grain yield were significantly higher in organic fields over inorganic ones (Table 4). CH₄-pp was further analyzed using a linear mixed-effects model with management, year, and zone as fixed effects and location as a random effect. The analysis revealed significant individual effects of management (F = 214.26, p < 0.001) and year (F = 5.54, p = 0.022) on CH₄-pp but a non-significant effect of zone alone (Table 5). However, the management × zone interaction was highly significant (F = 10.74, p < 0.001), indicating that the magnitude of management effects on CH₄ production varied among zones. Additionally, a zone × year interaction was significant (F = 3.18, p = 0.049), suggesting that temporal changes in CH₄ production differed across zones. The management × year and management × zone × year interactions were not significant (p > 0.05), indicating that management effects were consistent between years and not jointly modified by spatial and temporal factors. A similar analysis for grain yield revealed a highly significant effect of management on grain yield (F = 696.96, p < 0.001) but non-significant effects of year and zone alone. A highly significant management × zone interaction was observed (F = 49.37, p < 0.001), demonstrating that the magnitude of management effects on grain yield varied among the zones. Furthermore, the interaction between management, zone and year was significant (F = 5.630, p = 0.006), indicating that management effects on grain yield are influenced by spatiotemporal factors.

3.5 Correlations

In the inorganic system, soil variables like pH, SM, SOC, SMBC and NO₃^- were weakly associated with CH₄-pp rates (Figure 6a). In contrast, pH, SOC, SMBC and ALP activity showed good correlation with CH₄-pp in the organic system (Figure 6b). Significant association of SMBC with both SOC (R = 0.671, p<0.01) and CH₄-pp rates (R = 0.573; p<0.01) under organic management may indicate a potential relationship between the three variables. An inverse relationship between grain yield and CH₄-pp rates were seen in both management types (Figure 6), suggesting that higher CH₄-pp rates may be associated with lower rice yields, irrespective of the nutrient management practice. CH₄-pp rates also recorded a poor association with grain TC under both management types (Figure 6). However, further validation of the correlations is required to ascertain causal relationships among the above variables.

Figure 6

4 Discussion

4.1 Variations in CH_4-pp rates in inorganic and organic rice fields

Mean CH_4-pp rates differed significantly among inorganic and organic fields of different locations (Figure 2). In general, CH_4-pp rates in organic fields were higher than those in inorganic ones (Table 4). This may be attributed to fundamental differences in substrate availability for CH₄ production in organic versus inorganic management. There are reports stating that the effects of fertilizers on CH₄ emissions depend on fertilizer type, application rates, time of application and cropping systems (Banger et al., 2012; Hu et al., 2013; Sun et al., 2016). Although net field CH₄ emissions were not estimated, the nature and amounts of inputs may have influenced the CH₄ production pathway, leading to variation in CH₄-pp rates among inorganic (Banik et al., 1996; Datta et al., 2013) and organic (Kimura et al., 2004; Shibu et al., 2006; Menšík et al., 2018) fields. Organic amendments provide abundant labile carbon substrates that directly stimulate methanogenic activity, whereas inorganic fertilizers contribute primarily mineral nutrients with limited carbon inputs, resulting in comparatively lower CH₄-pp rates. The effect of management alone on CH₄-pp was significant but interactive effects of zone, management, and year were insignificant (Table 5), implying that CH₄-pp was primarily influenced by the management type.

Cow manure and Azolla resulted in the lowest CH₄-pp rates in the present study, indicating that these inputs could be potentially used to reduce field emissions of CH₄. The slow decomposition rate of cow manure and the oxygen-releasing capacity of Azolla into floodwater increase the redox potential and inhibit methanogens (Xu et al., 2017; Malyan et al., 2021), which could have lowered the CH₄-pp rates. Oxygenation and redox potential are reported to strongly mediate CH₄ flux in rice paddies (Dubey et al., 2015; Yuan et al., 2018). Similarly, the combination of vermicompost and vermiwash resulted in the second-lowest CH₄-pp rates among organic treatments, indicating their potential role in emission mitigation. Although the CH₄-pp rate does not exactly reflect the net CH₄ emissions, the use of appropriate organic inputs to reduce the initial production of CH₄ can contribute to reduced net emissions. Differential effects of organic amendments like cowmanure, rice straw compost, and vermicompost on CH₄ production and emission reported by several authors (Dhanuja et al., 2019; Wu et al., 2019; Haque et al., 2021; Iqbal et al., 2023), indicate that organic inputs cannot be treated as a uniform category with respect to greenhouse gas dynamics.

4.2 Soil parameters in inorganic and organic rice fields

A higher soil pH and EC were observed in organic fields than in inorganic fields (Tables 2, 3). Long-term applications of inorganic fertilizers are reported to reduce soil pH and EC over time (Ozlu and Kumar, 2018; Pahalvi et al., 2021), which is consistent with our results. Organic soils of Kamrup (M) supplied with vermicompost and vermiwash recorded comparatively higher pH (6.14). This is in agreement with Tharmaraj et al. (2011), who reported that soil pH was neutral when vermicompost and vermiwash were applied together in rice cultivation. Lower pH of soils supplied with cow manure and Azolla in Golaghat might be due to the growth of Azolla acting as a physical barrier, inhibiting algal photosynthesis, and lowering the CO₂ consumption rate (Liu et al., 2017; Yang et al., 2020; 2021). Many methanogen species prefer an optimum pH between 6.4 and 7.1, and may be inhibited in soil pH less than 6.0 (Liu and Wu, 2004). Lower pH in inorganic rice fields than organic ones (Tables 2, 3) may have affected the soil’s methanogenic activity, causing a decline in CH₄-pp rates. A better moisture retention capacity is reported for organic fields over inorganic ones (Sandhu et al., 2020), which was observed in LBVZ (Tables 2, 3). However, similar observations were not recorded for the other zones.

SOC and SMBC were generally higher in organic soils compared to inorganic ones (Figures 3, 4), which is consistent with the findings of Xu et al. (2018). Higher SOC and SMBC observed in cow manure treated soils of North Lakhimpur might be responsible for the higher CH₄-pp rates in this field (Figures 2c, d). In contrast, the combined application of cow manure and Azolla in organic fields of Golaghat resulted in lower CH₄-pp rates (Figures 2c, d) possibly due to the use of a lesser quantity of cow manure than other fields (Table 1), and also due to oxygen liberated by Azolla into the field water causing CH₄ oxidation (Bharati et al., 2000; Xu et al., 2017). Our finding is well corroborated with Malyan et al. (2021), who reported that an increase in soil redox potential facilitated by Azolla may suppress the activity of methanogenic bacteria, leading to lower CH₄-pp. In terms of SR rates, no general pattern of variation could be established between inorganic and organic fields (Tables 2, 3). The inorganic field of Kamrup (M) showed higher SR than its organic counterpart, while the opposite trend was seen in Jorhat. This may be due to the application of cow manure and rice straw compost in the organic field of Jorhat, which potentially improves soil-beneficial microbial populations and activities (Zhang et al., 2020; Huang et al., 2023).

Soil nitrate in the inorganic fields of Kamrup (R), Kamrup (M), Biswanath Chariali, and Jorhat was higher than or comparable to that of their corresponding organic fields (Table 2, 3). This may be because chemical fertilizers are quick to hydrolyze in the soil, readily releasing nutrients like nitrate (Pahalvi et al., 2021). However, the reverse trend was seen in the fields of North Lakhimpur and Golaghat. The application of cow manure in North Lakhimpur and combined incorporation of Azolla and cow manure in Golaghat might have had synergistic effects on nutrient availability in the soil, leading to enhanced nitrate content. Nguyen et al. (2020) reported that cow manure compost supplies more N, which may enhance the nitrate content in the field. Azolla carries out symbiotic nitrogen fixation (Akhtar et al., 2020) and is reported to enhance the available N content in soil (Alemayehu et al., 2025). Similarly, inorganic fields exhibited higher soil phosphate content than organic ones, with the exception of Kamrup (R) (Tables 2, 3). Cow manure and vermiwash are reported to be rich sources of P (Nguyen et al., 2020; Awadhpersad et al., 2021), which may have elevated the P level in the organic field of Kamrup (R).

Inconsistent variation in ALP activity was observed between inorganic and organic fields. ALP activity in the organic fields of Kamrup (R) and Biswanath Chariali was higher than their inorganic counterparts, which was not seen in the case of the other fields (Tables 2, 3). This may be due to the long-term application of organic fertilizers such as vermiwash, vermicompost, cow manure and Azolla, which improve the soil’s physicochemical characteristics and enzymatic activities, thus enhancing the phosphate bioavailability in the soil. Generally, higher APs activity observed in inorganic fields over organic ones (Tables 2, 3) may be due to the lower pH of the inorganic soils. Among the organic fields, soils treated with vermicompost and vermiwash in Kamrup (M) recorded the highest APs activity. This is consistent with Saha et al. (2008), who reported that vermicompost increased the acid phosphatase activity in soil, creating a better environment for plant root growth, and enriching the microbial biomass P and available P in the soil.

Soil factors like organic matter, pH, nutrient availability, anaerobic environment, and abundance of methane producing bacteria are reported to influence CH₄-pp rates (Dubey et al., 2015; Malyan et al., 2016; Yuan et al., 2018). Several studies have found that organic sources of fertilizers increase the availability of methanogenic bacteria leading to the production of more CH₄ (Ye et al., 2015; Yuan et al., 2018). Authors have reported a direct significant relationship between CH₄ production potential and methanogenic bacterial population size in rice soils (Dubey et al., 2013; 2015). In the present study, the observed significant correlations of CH₄-pp rates with pH, SOC, and SMBC in organic management (Figure 6) could indicate a possible influence of these factors on methanogenic populations and subsequent CH₄ production. However, only weak correlations among these variables were observed in the inorganic system (Figure 6), necessitating further validation of the findings.

4.3 Grain yield in inorganic and organic rice fields

Although organic fields recorded comparatively higher CH₄-pp rates, the grain yield was also higher than that of inorganic fields (Figure 5; Table 4). Some studies report lower rice yield under organic management (Hou et al., 2020; Kumar et al., 2023), while others suggest that long-term organic management can improve rice yields over inorganic management by enhancing soil health and fertility (Xu et al., 2018; Gao et al., 2023). Organic fertilizers enrich soil with SOC, which helps to retain soil moisture, thus improving soil health (Jiménez et al., 2008; Sihi et al., 2017). The decomposition of SOC also enhances the nutrient reserve in soil, which is necessary for crop growth and yield development (Preethi et al., 2013; Paul, 2016). Among the organic fields, vermicompost and vermiwash-applied soils of Kamrup (M) produced the highest grain yield (Figures 5c, d) with reduced soil CH₄-pp rates (Figure 2). Mixed-effects modeling revealed a significant interactive effect of zone, year, and management on grain yield, however the individual effects of zone and year were not significant (Table 5). Total grain carbohydrate in organically grown rice (Table 3) was higher than that of inorganically grown rice (Table 2), indicating better grain quality. Good soil health in organic fields may enhance crop health and disease resistance, thus facilitating better nutrient acquisition and assimilation capacity in the plants, ultimately improving grain quality (Tahat et al., 2020; Shahane and Shivay, 2021). In conclusion, inorganic and organic systems differ in their nutrient release dynamics, which may differentially influence soil properties, nutrient availability, and nutrient use efficiency in the long-term, thereby leading to yield differences in these contrasting systems.

4.4 Inorganic vs organic management from an agronomical viewpoint

Inorganic systems showed lower CH₄-pp rates, while organic systems recorded better soil health and higher grain yields. Despite the higher CH₄-pp rates in organic systems, a concurrent increase in grain yield may ultimately reduce the overall emission intensity, i.e., emission per kilogram of rice produced. Moreover, the grain quality in terms of total carbohydrate content was better under organic management. The combined application of vermicompost and vermiwash in the fields of Kamrup (M) not only produced the highest grain yield but also recorded the second-lowest CH₄-pp. From an agronomical perspective, this practice can potentially mitigate farm emissions by limiting CH₄ production and increase farm resilience by improving yield. Slow-release nutrient sources like vermicompost and Azolla (Seleiman et al., 2022; Manzoor et al., 2024) synchronize nutrient availability with crop demand and improve nutrient use efficiency, while the gradual decomposition of organic inputs improves SOC and SMBC, contributing to greater carbon stabilization in soil. Long-term conservation of nutrients and organic carbon leading to soil health improvement is desirable from an agronomical point of view. Moreover, soils with more organic carbon are reported to have greater water retention capacity, making them resilient to drought (Kačergius et al., 2025). This is desirable for efficient water management in agriculture in the present scenario of climate change. To sum up, it is evident that organic management can contribute to more agronomically sound farming practices than inorganic management in the long run, in terms of lower CH₄ production, healthier soils, better grain production, and enhanced farm resilience.

4.5 Limitations and future scope of the study

Firstly, the present study investigated the CH₄ production potentials of inorganic and organic rice field soils; however, the CH₄ oxidation rates were not estimated. To gain a comprehensive understanding of net CH₄ emissions from rice agro-ecosystems, both production and oxidation potential processes should be examined. Secondly, this study did not investigate direct field emissions of CH₄ and the roles of methanogenic and methanotrophic bacteria due to feasibility constraints. Thirdly, as this study was conducted on farmer-managed fields, potential confounding factors such as crop management, residue handling, and input variability may have existed but were beyond the scope of this investigation. While acknowledging these limitations, our findings provide valuable insights into the CH₄ production potential of rice fields under different fertilizer management regimes and identify key areas for future research, including the factors not addressed here.

5 Conclusions

Our findings suggest that CH₄-pp rates in rice fields of Assam are influenced by the nature of nutrient management practices adopted by the farmers and the soil characteristics during the growing season. Organic inputs improve soil health and grain yield, despite causing an increase in the soil CH₄-pp rates over inorganic inputs. However, higher CH₄-pp rates in organic fields could be controlled by changing the types or combinations of organic fertilizers and by regulating the application rates, providing added benefits for soil health and grain yields. Moreover, a higher CH₄-pp rate may not necessarily mean a higher emission, as the net emissions are a function of both CH₄ production and oxidation potentials, determined by the relative abundance and activity of methanogenic and methanotrophic bacteria. SOC and SMBC were identified as important factors regulating the CH₄-pp rates in soil. Farmers in the study area were found to apply various forms of organic inputs in rice cultivation, especially cow manure, which is easily available in rural areas. Cow manure improved the rice yield but increased the CH₄-pp rates. In contrast, vermicompost and vermiwash application improved the yield with a simultaneous reduction in CH₄-pp rates in LBVZ of Assam. Therefore, the combined application of vermicompost and vermiwash can be considered a potential approach for reducing soil CH₄-pp rates without compromising rice yields. Reduction in CH₄-pp may contribute to a subsequent reduction of net field CH₄ emissions. Region-specific policy interventions like financial support to facilitate the adoption and local production of vermicompost, Azolla and other low-emission compost could encourage climate-friendly agriculture.

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