Rice straw-derived biochar reduces nitrogen losses and greenhouse gas emissions while improving rice productivity and agronomic efficiency in a tropical paddy soil

Rice straw-derived biochar reduces nitrogen losses and greenhouse gas emissions while improving rice productivity and agronomic efficiency in a tropical paddy soil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Rice straw-derived biochar reduces nitrogen losses and greenhouse gas emissions while improving rice productivity and agronomic efficiency in a tropical paddy soil Saowalak Somboon, Benjamas Rossopa, Sujitra Yodda, Phrueksa Lawongsa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8607079/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Balancing nitrogen (N) productivity with environmental sustainability is critical in flooded rice systems, where N losses by leaching and gaseous emissions are substantial. This study conducted a system-level comparison of four treatments in a continuously flooded tropical paddy field: an unfertilized control, chemical fertilizer (CF), rice straw with CF (RS + CF), and rice straw-derived biochar with CF (BC + CF). We quantified major N-loss pathways, agronomic efficiency of applied N (NAE), and N gas-related global warming potential (GWP N ). The results indicate that BC + CF minimized total N loss to 33% of total N input, compared to 38% under RS + CF and 43% under CF. Compared with CF, BC + CF significantly reduced NH 3 volatilization and NH 4 + -N leaching, driven by increased soil cation exchange capacity and mineral N retention. While RS + CF yielded the lowest N 2 O emissions, it presented greater NH 4 + -N leaching than BC + CF. Both organic amendments reduced GWP N and greenhouse gas intensity (GHGI) compared to CF; however, BC + CF resulted in superior grain yield and NAE. Conversely, the unfertilized control produced the highest GHGI due to low productivity. These findings demonstrate that integrating rice straw-derived biochar with chemical fertilizer represents an optimal system-level strategy for mitigating N losses, enhancing agronomic efficiency, and lowering climate impacts of flooded rice production. Earth and environmental sciences/Climate sciences Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Agricultural wastes Nitrogen losses Rice production Greenhouse gas emissions Climate change Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Nitrogen (N) is an essential nutrient for plant growth and a major determinant of crop productivity and food security. To achieve high yields, N fertilizer is often applied in excess of crop demand, increasing production costs, whereas the global N use efficiency typically remains below 40% [ 1 – 2 ]. Inefficient N use leads to substantial losses to the environment, accelerating soil acidification, eutrophication, groundwater contamination, air pollution, and greenhouse gas (GHG) emissions [ 3 ]. Rice is a staple food for more than half of the world’s population and dominates cultivated areas in Asia, with approximately 165 million hectares globally [ 4 ]. N management in flooded rice systems is particularly challenging because more than 60% of applied N can be lost via multiple pathways, including mineral N leaching (ammonium-nitrogen (NH 4 + -N), and nitrate-nitrogen (NO 3 − -N); 0.1–33%), ammonia (NH 3 ) volatilization (10–60%), and nitrous oxide (N 2 O) emissions (5–35%) [ 5 – 8 ]. Among these, N₂O is a potent GHG with a global warming potential (GWP) that is 273 times greater than that of carbon dioxide (CO 2 ) [ 9 ], underscoring the urgency of integrated N management strategies that reduce losses while sustaining yield. Rice straw (RS) management offers both opportunities and trade-offs for mitigating N losses in paddy soils [ 10 – 11 ]. The incorporation of RS can increase soil total organic carbon (TOC) and total N, improving soil fertility and rice yield [ 12 – 13 ]. Several studies have reported reduced mineral N leaching following RS incorporation, attributed to the immobilization of inorganic N into organic pools and improved N sequestration, which limits N mobility [ 6 , 14 – 15 ]. For example, RS incorporation decreased NO 3 − -N in leachate from saline–sodic paddy soils [ 14 ], and Yang et al. [ 15 ] reported 13% mitigation of NO 3 − leaching in a temperate arid region. RS can also reduce NH 3 volatilization and N 2 O emissions by lowering NH 4 + -N in floodwater and promoting N immobilization, including a reported 41% reduction in NH 3 volatilization under subtropical monsoon conditions [ 16 ]. However, rapid RS decomposition increases NH 3 volatilization [ 17 – 18 ] and elevates N 2 O emissions by supplying labile carbon for denitrification [ 19 ]. These contrasting outcomes highlight the need for system-level evaluation of RS effects across all major N loss pathways. Biochar, which is produced by the pyrolysis of crop residues under limited oxygen, is widely proposed as a complementary strategy for improving soil fertility and mitigating N losses. Biochar can increase TOC and total N, enhance nutrient retention, improve yield, and reduce N losses through both leaching and gaseous pathways [ 14 , 16 – 17 , 20 ]. Its high carbon stability, porosity, and cation exchange capacity (CEC) support the adsorption and retention of NH 4 + -N and NO 3 − -N and can influence microbial immobilization and soil buffering [ 18 , 20 – 21 ]. Field evidence indicates that rice straw-derived biochar (BC) reduces NO 3 − -N leaching (30–38.6%) and total N leaching (12.8–13.4%) and decreases NH 3 volatilization and N 2 O emissions by 11.5–17.8% in subtropical monsoon climates [ 20 ]. Selvarajh et al. [ 22 ] further reported that enriched BC (5–10 t ha − 1 ) reduced NH 3 volatilization by increasing the adsorption capacity and buffering pH, whereas Yang et al. [ 23 ] reported 45.1–74% reductions in cumulative N 2 O emissions (1–5% w/w) linked to increased soil pH and reduced NO 3 − reductase activity. Nonetheless, biochar application increases NH 4 + -N leaching when nitrification is suppressed, as retained NH 4 + can accumulate in the soil solution [ 20 ]. Thus, the effects of biochar should be assessed together with other N-loss pathways and agronomic outcomes. Despite extensive studies on RS and BC, direct comparisons that quantify all major N loss pathways within a single flooded rice system remain limited. Many studies emphasize one pathway (e.g., NH 3 or N 2 O) without integrating mineral N leaching, agronomic efficiency, and climate metrics. In particular, GHGI is often reported without system-level indices such as nitrogen gas-related global warming potential (GWP N ), which requires concurrent quantification of NH 3 volatilization and N 2 O emissions. These knowledge gaps preclude a comprehensive evaluation of the net environmental benefits and inherent biogeochemical trade-offs between rice straw and biochar amendments. Here, we conduct a comparative, system-level assessment of RS and BC applications in tropical flooded paddy soil by linking mineral N leaching (NH 4 + -N and NO 3 − -N), NH 3 volatilization, and N 2 O emissions with rice yield, the agronomic efficiency of applied N (NAE), and climate-relevant indices (GWP N and GHGI). We hypothesized that both RS and BC enhance soil fertility and rice productivity, but the greater stability and CEC of BC would result in greater reductions in total N losses across the leaching and gaseous pathways, resulting in lower GWP N and GHGI. Our objectives were to (1) quantify N losses via NH 4 + -N and NO 3 − -N leaching, NH 3 volatilization, and N 2 O emissions, (2) evaluate rice grain yield and NAE, and (3) assess GWP N and GHGI under RS combined with chemical fertilizer (CF), BC combined with CF, and CF in a tropical paddy soil system. Results Soil chemical properties during rice cultivation The soil chemical dynamics under the control, chemical fertilizer (CF), rice straw combined with CF (RS + CF), and rice straw-derived biochar combined with CF (BC + CF) treatments are shown in Fig. 1 . The soil pH remained nearly neutral (6.5–7.3) across the treatments during the season (Fig. 1 a). Across treatments, the mean redox potential (Eh) decreased from − 86 mV (seedling) to -324 mV (panicle initiation) and then increased to 166 mV at harvest (Fig. 1 b). TOC was consistently greater in the RS + CF (3,367–6,133 mg kg − 1 ) and BC + CF (3,667–5,668 mg kg − 1 ) treatments than in the CF (2,367–4,467 mg kg − 1 ) and the control (2,933–4,200 mg kg − 1 ) treatments (Fig. 1 c). Cation exchange capacity (CEC) increased at the seedling stage under RS + CF and BC + CF (13 cmol kg − 1 ) but converged among treatments from tillering to panicle initiation (10–12 cmol kg − 1 ); at harvest, BC + CF remained higher (11 cmol kg − 1 ) than the RS + CF, CF, and control (10 cmol kg − 1 ) (Fig. 1 d). The seasonal dynamics of total N, organic N, mineral N, and exchangeable NH 4 + -N followed similar patterns across treatments, peaking at the tillering stage and gradually decreasing thereafter (Fig. 1 e–h). The total N content was significantly greater in the RS + CF (167–2,167 mg kg − 1 ) and BC + CF (170–2,213 mg kg − 1 ) treatments than in the CF (94–692 mg kg − 1 ) treatments and control (92–621 mg kg − 1 ) treatments (Fig. 1 e). The peak total N at tillering reached 2,167 mg kg − 1 (RS + CF) and 2,213 mg kg − 1 (BC + CF), and at harvest, BC + CF presented the highest total N (1,070 mg kg − 1 ), followed by RS + CF (786 mg kg − 1 ), whereas the CF (128 mg kg − 1 ) and the control (97 mg kg − 1 ) presented the lowest total N. Organic N dominated total N (88–2,171 mg kg − 1 ), whereas mineral N was relatively low (1.5–43 mg kg − 1 ) (Fig. 1 f–g). Exchangeable NH 4 + -N increased from seedling (13–15 mg kg − 1 in RS + CF and BC + CF) to tillering (35–43 mg kg − 1 ) and remained higher at harvest (25–36 mg kg − 1 ) than in the CF and the control (0.25–3.3 mg kg − 1 ) (Fig. 1 h). Unlike other N components, exchangeable NO 3 − -N remained low (0–0.95 mg kg − 1 ) and presented stage-dependent peaks, particularly at panicle initiation (0.69 mg kg − 1 in RS + CF and 0.95 mg kg − 1 in BC + CF) (Fig. 1 i). Rice yield and agronomic efficiency The organic amendments significantly increased the rice yield and NAE (Table 1 ). BC + CF produced the highest grain yield (11,823 kg ha -1 ), significantly outperforming RS + CF (10,577 kg ha -1 ) and CF (6,333 kg ha -1 ), whereas the control yielded 1,609 kg ha -1 . BC + CF also produced the highest white grain (7,331 kg ha -1 ) and husk (4,492 kg ha -1 ) yields. The straw biomass was greatest in BC + CF (17,600 kg ha -1 ), but was not significantly different from that in RS + CF (14,726 kg ha -1 ) or CF (15,962 kg ha -1 ). Table 1 Rice yield and agronomic efficiency under different treatments. Abbreviations: NAE: agronomic efficiency of applied nitrogen; Control: no fertilizer or organic application; CF: soil treated with chemical fertilizer; RS + CF: soil treated with rice straw and chemical fertilizer; BC + CF: soil treated with rice straw-derived biochar and chemical fertilizer. Lowercase letters in the same column represent significant differences among treatments according to the LSD test, with p < 0.05. Treatment Total N input (kg ha -1 ) Yield (kg ha -1 ) NAE (kg kg -1 ) Straw Grain White rice grain Husk Control 0 4,100c 1,609d 913d 696d - CF 188 15,962ab 6,333c 3,855c 2,479c 25c RS + CF 252 14,726b 10,577b 6,466b 4,112b 36b BC + CF 203 17,600a 11,823a 7,331a 4,492a 50a p -value - 0.006 0.001 < 0.001 0.001 < 0.001 Pearson correlation analysis (Table S1 ) revealed a strong positive correlation between rice grains and white grains and husks ( r = 1.00 for both; p < 0.01). Additionally, grain yield was positively correlated with TOC ( r = 0.91), soil total N ( r = 0.91), organic N ( r = 0.91), exchangeable NH 4 + -N ( r = 0.89), exchangeable NO 3 − -N ( r = 0.86), and the mineral N content ( r = 0.89) ( p < 0.01). Both the RS + CF and BC + CF amendments significantly enhanced NAE (Table 1 ). The NAE increased from 25 kg kg − 1 (CF) to 36 kg kg − 1 (RS + CF) and 50 kg kg − 1 (BC + CF), and was strongly correlated with grain yield, white grains, and husks ( r = 0.98 for all) and with straw biomass ( r = 0.73) ( p < 0.01) (Table S1 ). Soil nitrogen losses NH 4 + -N and NO 3 - -N concentrations in the soil solution at 0–20 cm depth Across the fertilized treatments, NH 4 + -N dominated the soil solution (0.16–17 mg L -1 ), whereas NO 3 - -N remained low (0.01–0.20 mg L -1 ) (Fig. 2 a–b). In contrast, the control had a lower NH 4 + -N concentration (0.12–2.39 mg L -1 ), while the NO 3 - -N concentration ranged from 0.06–0.16 mg L -1 . The NH 4 + -N concentration in the soil solution exhibited similar dynamics under the RS + CF and BC + CF treatments but differed from those under the control and CF treatments (Fig. 2 a). After the first fertilization at 7 days after transplanting (DAT), the NH 4 + -N concentration peaked at 8 DAT in RS + CF and BC + CF (16 mg L − 1 ), and at 9 DAT in CF (14 mg L − 1 ). RS + CF (4.9˗14 mg L − 1 ). The BC + CF (1.9–8.7 mg L − 1 ) amendments resulted in higher NH 4 + -N concentrations than did the CF and control treatments from 35–46 DAT. After the second fertilization, the NH 4 + -N concentration in the CF treatment increased again to 4.4 mg L − 1 at 43 DAT and then gradually declined (Fig. 2 a). The NO 3 − -N concentrations differed among the treatments throughout the season, ranging from 0.01 to 0.20 mg L − 1 (Fig. 2 b). The NO 3 − -N concentrations generally peaked approximately 7 DAT (0.18–0.20 mg L − 1 ) and then declined; by 112 DAT, the NO 3 − -N concentration was lower in the RS + CF and BC + CF treatments (0.04 mg L − 1 ) than in the CF (0.10 mg L − 1 ) and control (0.11 mg L − 1 ) treatments. NH 4 + -N and NO 3 - -N leaching at 20–60 cm depth NH 4 + -N was the predominant mineral N in the leachate (0–11 mg L -1 ), whereas NO 3 - -N in the leachate was lower (0–0.22 mg L -1 ) (Fig. 2 c–d). The leachate NH 4 + -N dynamics were similar in the RS + CF and BC + CF treatments (Fig. 2 c), with peaks at 8 DAT after the first fertilization (8.6 and 6.2 mg L -1 , respectively). A second elevated period occurred at 21–35 DAT, during which RS + CF reached 10.7–11.0 mg L -1 and BC + CF reached 3.2–6.1 mg L -1 . In contrast, the CF peaked earlier at 9 DAT (8.4 mg L -1 ), whereas that of the control remained low and relatively stable (0–2.1 mg L -1 ) (Fig. 2 c). The NO 3 - -N concentrations in the leachate in the CF and control treatments were relatively stable (0.07–0.16 and 0.08–0.18 mg L -1 ), whereas those in the RS + CF and BC + CF treatments were more variable (0–0.19 and 0–0.22 mg L -1 , respectively) (Fig. 2 d). RS + CF and BC + CF peaked at 7 DAT (0.14 and 0.22 mg L -1 , respectively) and declined rapidly by 8 DAT. During the first 7 days after each fertilization, NO 3 - -N in the leachate was generally greater in the CF and control treatments than in the RS + CF and BC + CF treatments. Later-season increases in RS + CF and BC + CF occurred at 84 and 98 DAT, respectively. The cumulative NH₄⁺-N leaching differed among the treatments (Fig. 2 e). The RS + CF-treated soil had the greater cumulative NH 4 + -N loss (54 kg ha -1 ) (Fig. 2 e), accounting for 21% of the total N input (Fig. 3 ), whereas the control had the lowest (15 kg ha -1 ). Although cumulative NH 4 + -N leaching did not differ significantly between the CF and BC + CF treatments, that in the BC + CF treatment was numerically lower (28 kg ha -1 ; 14% of total N input) than CF (32 kg ha -1 ; 17% of total N input) (Fig. 2 e, 3 ). Correlation analyses showed significant negative correlations between the NH 4 + -N concentration in the leachate and the NO 3 - -N concentration in the soil solution ( r = -0.33; p < 0.05), TOC ( r = -0.31; p < 0.05), mineral N ( r = -0.31; p < 0.05), and exchangeable NO 3 - -N ( r = -0.29; p < 0.05). Conversely, the NH 4 + -N concentration in the leachate was strongly positively correlated with the NH 4 + -N concentration in the soil solution ( r = 0.82; p < 0.01) and soil Eh ( r = 0.37; p < 0.05) and exhibited a weaker positive correlation with the soil exchangeable NH 4 + -N ( r = 0.30; p < 0.05) (Table S2). The cumulative NO 3 - -N leaching was minor across the treatments (Fig. 2 f), with the lowest loss in the RS + CF treatment (1.3 kg ha -1 ; 0.5% of total N input), followed by the CF and control treatments (1.4 kg ha -1 ; 0.8% of total N input), and the greater loss occurred in the BC + CF-treated soil (1.5 kg ha -1 ; 0.7% of total N input) (Fig. 2 f, 3 ). Pearson correlation analysis indicated that the NO 3 - -N concentration in the leachate was positively correlated with total N ( r = 0.68; p < 0.01), organic N ( r = 0.68; p < 0.01), NO 3 - -N in soil solution ( r = 0.61; p < 0.01), exchangeable NH 4 + -N ( r = 0.39; p < 0.01), and mineral N ( r = 0.39; p < 0.01). Conversely, it was significantly negatively correlated with the soil Eh ( r = -0.45; p < 0.01) and the NH 4 + -N concentration in the soil solution ( r = -0.29; p < 0.05) (Table S2). NH 3 volatilization and N 2 O emission NH 3 volatilization fluxes presented broadly similar temporal patterns across the treatments (Fig. 4 a). After the first fertilization, BC + CF rapidly increase to 81 mg m -2 d -1 , whereas CF (100 mg m -2 d -1 ) and RS + CF (92 mg m -2 d -1 ) did not immediately increase. By 21 DAT, NH 3 volatilization declined to 23–24 mg m -2 d -1 in the CF and RS + CF treatments and to 20 mg m -2 d -1 in the BC + CF treatment. NH 3 volatilization increased again across treatments at 35 DAT (52–107 mg m -2 d -1 ) and then decreased by 56 DAT, stabilizing thereafter at 13–28 mg m -2 d -1 (Fig. 4 a). The cumulative NH 3 volatilization was highest under CF (44 kg ha -1 ; 23% of total N input), followed by the control and RS + CF (40 kg ha -1 each), and lowest under BC + CF (34 kg ha -1 ; 17% of total N input) (Fig. 4 b, 3 ). NH 3 volatilization was negatively correlated with total N and organic N (r = -0.42; p < 0.01 for both), mineral N and exchangeable NH₄⁺-N (r = -0.31; p < 0.05 for both), and CEC (r = -0.30; p < 0.05) (Table S2). N 2 O emission fluxes differed markedly among the treatments (Fig. 4 c). The CF and BC + CF treatments presented sharp peaks at 8 DAT (42 and 23 mg m -2 d -1 , respectively), whereas those of the control and RS + CF treatments remained relatively low and stable throughout the season (0.3–10 and 2.2–9 mg m -2 d -1 , respectively). Accordingly, cumulative N 2 O emissions were highest under CF (14 kg ha -1 ; 2.4% of total N input), followed by BC + CF (10 kg ha -1 ; 1.6% of total N input) and RS + CF (5.3 kg ha -1 ; 0.7% of total N input) (Fig. 4 d, 4 ). N 2 O emissions were positively correlated with soil mineral N and exchangeable NH 4 + -N ( r = 0.31; p < 0.05 for both) (Table S2). Nitrogen gas-related global warming potential and greenhouse gas intensity GWP N differed among the treatments (Fig. 5 a). CF presented the highest GWP N (247 kg CO 2 eq ha -1 ), whereas those of the control (196 kg CO 2 eq ha -1 ), RS + CF (193 kg CO 2 eq ha -1 ), and BS + CF (187 kg CO 2 eq ha -1 ) soils were not significantly different. However, BC + CF represented the lowest value. The GHGI decreased with increasing grain yield (R 2 = 0.88; p < 0.05) (Fig. 6 ). The control had the highest GHGI (122 kg CO 2 eq t -1 GY), followed by the CF (39 kg CO 2 eq t -1 GY), whereas the BC + CF achieved the lowest GHGI (16 kg CO 2 eq t -1 GY), which was 11% lower than that of the RS + CF (18 kg CO 2 eq t -1 GY) (Fig. 5 b). Discussion This study provides a system-level comparison of rice straw and rice straw–derived biochar as complementary amendments to chemical fertilizer in a continuously flooded tropical rice system, revealing distinct soil chemical properties, rice grain yields, N losses through leaching of NH 4 + -N and NO 3 − -N, NH 3 volatilization, and N 2 O emissions, as well as GWP N , GHGI, and NAE. Although both RS + CF and BC + CF improved soil fertility and reduced climate impacts compared with CF alone, the BC + CF amendment was the most effective at concurrently reducing N losses and increasing rice productivity. The incorporation of RS and biochar significantly improves soil chemistry by increasing soil organic matter and nutrient availability [ 13 , 16 , 24 ]. Compared with the CF treatment, the RS + CF and BC + CF amendments increased the soil TOC, CEC, total N, organic N, mineral N, exchangeable NH 4 + -N, and exchangeable NO 3 − -N contents during the rice growing season. These improvements were driven by the inherent properties of the RS and BC amendments, particularly their high TOC, CEC, and the carbon-to-nitrogen (C/N) ratio (Table 2 ), and by the greater total N inputs supplied by the combined treatments than those supplied by the CF treatment (Table 2 ). Overall, RS + CF and BC + CF enhanced total N and TOC, promoted N mineralization, and increased exchangeable NH 4 + -N and NO 3 − -N in soil [ 25 – 26 ]. Increased N availability during critical stages, especially tillering, was a key driver of grain yield, white rice grain yield, and husk biomass, and contributed to the significantly increased yields observed in the RS + CF- and BC + CF-treated soils ( p < 0.05). During tillering, the amount of exchangeable NH 4 + -N was greater in the RS + CF and BC + CF treatments than in the other treatments, sustaining the N supply essential for growth and productivity [ 27 ]. Moreover, the elevated CEC and exchangeable NH 4 + -N in BC + CF resulted in improved NH 4 + retention, resulting in the highest grain yield among the treatments (Table 1 ). Table 2 Mean values (n = 3) of the physicochemical properties of the initial soil, rice straw, and rice straw-derived biochar used in this study. Abbreviations: Ksat: saturated hydraulic conductivity; Exchangeable NH 4 + -N: exchangeable ammonium-nitrogen; Exchangeable NO 3 - -N: exchangeable nitrate-nitrogen. Initial soil Rice straw Rice straw-derived biochar Sand (g kg -1 ) 500 - - Silt (g kg -1 ) 340 - - Clay (g kg -1 ) 160 - - Soil texture Loam - - Bulk density, 0–20 cm (g cm -3 ) 1.5 - - Bulk density, 20–60 cm (g cm -3 ) 1.7 Ksat, 0–20 cm (cm s -1 ) 1.1×10 − 4 - - Ksat, 20–60 cm (cm s -1 ) 1.3×10 − 5 pH (H 2 O) 6.3 6.8 8.9 Total organic carbon (g kg -1 ) 4.1 347 469 Total nitrogen (g kg -1 ) 0.44 6.4 5.0 Carbon-to-nitrogen ratio - 54 94 Cation exchange capacity (cmol kg -1 ) 11 25 36 Exchangeable NH 4 + -N (mg kg -1 ) 4.5 - - Exchangeable NO 3 - -N (mg kg -1 ) 2.0 - - Mineral nitrogen (mg kg -1 ) 6.5 - - Organic nitrogen (mg kg -1 ) 434 - - NAE, defined as the increase in grain yield per unit of N applied, is a key indicator of N use efficiency with direct implications for both economic returns and environmental sustainability [ 28 – 30 ]. In our study, the RS + CF and BC + CF amendments significantly increased the NAE from 25 kg kg − 1 (CF) to 36 kg kg − 1 (RS + CF) and 50 kg kg − 1 (BC + CF) ( p < 0.01). These improvements were attributed to the high CEC and recalcitrant nature of the biochar, which enhanced nutrient retention, reduced N losses, and sustained plant-available N [ 18 , 20 , 29 ]. Consistent with this mechanism, the NAE was positively correlated with total N, mineral N, organic N, exchangeable NH 4 + -N, exchangeable NO 3 − -N, TOC, and CEC (Table S1 ). Collectively, these findings highlight the strategic advantage of using RS, particularly BC, in tropical flooded rice systems to optimize N cycling, increase soil fertility, and improve rice yield and agronomic performance. In flooded rice systems, more than 60% of applied N can be lost through multiple pathways, including mineral N leaching, NH 3 volatilization, and N 2 O emissions [ 5 – 8 ]. In the present study, CF alone resulted in the greatest total N loss, accounting for 43% of the total N input. In contrast, the incorporation of organic amendments reduced total N losses to 38% under RS + CF and 33% under BC + CF (Fig. 3 ), indicating improved system-level N retention, particularly with biochar application. Among the individual N loss pathways, cumulative NH 4 + -N leaching was greatest under RS + CF, accounting for 21% of the total N input, compared with 17% under CF and 14% under BC + CF (Fig. 3 ). The elevated NH 4 + -N leaching under RS + CF coincided with increased NH 4 + -N concentrations in soil solution during 21–35 DAT, which is consistent with the rapid anaerobic decomposition of rice straw [ 31 ]. In contrast, BC + CF amendment reduced cumulative NH 4 + -N leaching, reflecting the high CEC and enhanced nutrient adsorption of the biochar, which promoted NH 4 + retention in flooded soils [ 32 ]. Moderate cumulative NH 4 + -N leaching under CF (Fig. 2 e) resulted from rapid urea hydrolysis and limited soil retention capacity [ 18 , 33 ], whereas minimal leaching under the unfertilized control reflected the absence of external N input. In contrast, NO 3 − -N leaching contributed only 0.5–0.8% of the total N input across the treatments (Fig. 3 ), which is consistent with suppressed nitrification under continuously flooded conditions [ 33 – 34 ]. The lowest NO 3 − -N leaching occurred under RS + CF (0.5%), which coincided with elevated NH 4 + -N leaching and limited substrate availability for nitrification. These results highlight that shifts among N loss pathways can occur depending on the type of organic amendment type, even when total N losses are reduced. NH 3 ​ volatilization represented a major N loss pathway across fertilized treatments. Compared with CF alone, both RS + BC and BC + CF reduced cumulative NH 3 ​ volatilization, with the lowest losses observed under BC + CF. The negative correlations between NH 3 ​ volatilization and soil exchangeable NH 4 + -N and CEC (Table S2) suggest that increased NH 4 + retention reduced the conversion of NH 4 + to gaseous NH 3​ . The porous structure and surface functional groups of the biochar likely contributed to this effect by increasing its adsorption capacity and buffering the soil pH [ 21 , 35 ]. N 2 O emissions varied markedly among the treatments. CF alone produced the highest cumulative N 2 O emissions, corresponding to an emission factor of 2.4% of the total N input, substantially exceeding the IPCC Tier 1 default for continuously flooded rice systems [ 36 ]. In contrast, the incorporation of RS or BC reduced N 2 O emissions, with RS + CF resulting in the lowest emission factor (0.7%). The reduced N 2 O emissions under RS + CF were associated with low NO 3 − availability and high NH 4 + -N leaching, which constrained substrates for denitrification [ 30 ]. In contrast, BC + CF resulted in higher N 2 O emissions (1.6%) than did RS + CF, potentially reflecting increased retention of exchangeable NH 4 + , which may indirectly supply substrates for nitrification–denitrification processes [ 37 – 38 ]. Furthermore, the measured N loss pathways used to estimate indirect N 2​ O emissions also deviated from IPCC defaults. The fraction of applied N lost by leaching (Frac LEACH ​) ranges from 14.7–21.5% (Fig. 3 ), below the IPCC default of 30%, whereas FracGASF (the fraction of synthetic N volatilized as NH 3 ) is 16–23% (Fig. 3 ), which consistently exceeds the IPCC default of 10% [ 36 ]. Such departures are expected given the strong influence of local climate, soil properties, and fertilizer and amendment management (type, rate, and timing) [ 39 – 40 ]. Our measurements from continuously flooded tropical rice fields under contrasting N management practices provide site-specific evidence of substantial variability in these emission factors, offering valuable inputs for refining Thailand’s country-specific factors for both direct and indirect N 2​ O emissions in the national greenhouse gas inventory. Collectively, these results demonstrate that rice straw and biochar alter the relative importance of individual N loss pathways. While both amendments reduced total N losses, biochar was more effective at mitigating NH 4 + -N leaching and NH 3 ​ volatilization, whereas rice straw more strongly suppressed N 2​ O emissions. Evaluating N management strategies from a climate perspective requires the integration of both direct and indirect greenhouse gas emissions. GWP N accounts for direct N 2 O emissions as well as indirect emissions arising from NH 3 volatilization and subsequent deposition [ 41 ]. In this study, GWP N was significantly greater under CF alone than under RS + CF or BC + CF ( p < 0.05), reflecting the combined mitigation of NH 3 ​ volatilization and N 2 ​O emissions by organic amendments. No significant difference in GWP N was observed between RS + CF and BC + CF, indicating that both amendments comparably reduced the overall climate impact of N losses. However, the GHGI differed substantially among the treatments and declined strongly with increasing grain yield. Despite low absolute N inputs, the unfertilized control presented the highest GHGI due to poor yield performance, demonstrating that low-input rice cultivation is not inherently climate-efficient. The strong inverse relationship between the GHGI and grain yield (Fig. 6 ) underscores the importance of productivity gains in mitigating yield-scaled greenhouse gas emissions. By simultaneously reducing N losses and increasing grain yield, RS + CF and BC + CF achieved substantially lower GHGI than did CF alone. Among the treatments, BC + CF produced the lowest GHGI, reflecting its combined effects on N retention and crop productivity. In conclusion, while both rice straw and its derived biochar serve as effective complementary amendments to chemical fertilizers, they exert distinct regulatory control over N cycling in continuously flooded tropical paddy systems. Our system-level analysis reveals a strategic trade-off: rice straw application more effectively suppresses direct N 2 O emissions, whereas biochar provides a superior mechanism for mitigating NH₄⁺-N leaching and NH 3 volatilization. Crucially, the biochar-treated soil optimized the synergy between environmental mitigation and crop productivity, achieving the highest grain yield, agronomic efficiency of applied N, and N gas-related global warming potential. Furthermore, our findings challenge the assumption that low-input systems are environmentally superior; the poor productivity of unfertilized control resulted in the highest greenhouse gas intensity, indicating that no-input rice management is not inherently climate-efficient. Overall, integrating rice straw-derived biochar with chemical fertilizer represents a highly effective, scalable strategy for reducing nitrogen losses, sustaining rice productivity, and lowering yield-scaled climate impacts in flooded rice systems. Methods Site characteristics and experimental design The field experiment was conducted from July to November 2021 in Khon Kaen, Thailand (UTM: 48Q 265026E, 1825361N), which is located in a tropical savanna climate. During the experimental period, the average daily temperature was 29°C, and the cumulative rainfall was 645 mm (Fig. S1 ). The studied soil was classified as Aquic Haplustalfs [ 42 ], with a loam texture comprising 500, 340, and 160 g kg -1 of sand, silt, and clay, respectively (Table 2 ). The initial soil bulk density was 1.5 and 1.7 g cm -3 at the 0–20 and 20–30 cm depths, respectively. The saturated hydraulic conductivity (Ksat) was 1.1×10 − 4 cm s -1 (9.3 cm day -1 ) at 0–20 cm depth, and 1.3×10 − 5 cm s -1 (1.2 cm day -1 ) at the 20–60 cm depth. The initial soil pH (H 2 O) was 6.3, with a TOC of 4.1 g kg -1 , total N of 0.44 g kg -1 , CEC of 11 cmol kg -1 , exchangeable NH 4 + -N of 4.5 mg kg -1 , exchangeable NO 3 - -N of 2.0 mg kg -1 , mineral N of 6.5 mg kg -1 , and organic N of 434 mg kg -1 (Table 2 ). The experiment followed a randomized complete block design with four treatments and three replications (plot size: 5 m × 5 m). The treatments were as follows: (1) control (no fertilizer or organic application), (2) chemical fertilizer (CF), (3) rice straw combined with CF (RS + CF), and (4) rice straw-derived biochar combined with CF (BC + CF). RS was incorporated at a rate of 10 t ha − 1 (dry weight), following field-return estimates [ 43 ], whereas BC was applied at 3 t ha − 1 (dry weight). Both amendments were manually incorporated into topsoil 0–15 cm long via a hand hoe and incubated under field-moist conditions for 28 days before rice transplantation. CF application was targeted to achieve a yield of 6.25 t ha − 1 for RD6 rice ( Oryza sativa L.), following the recommendations of [ 44 ]. The chemical fertilizer supplied N, P 2 O 5 , and K 2 O at rates of 188, 38, and 132 kg ha − 1 , respectively, sourced from urea, diammonium phosphate, and muriate potash at rates of 376, 83, and 220 kg ha − 1 , respectively. Half of the N and the full doses of P 2 O 5 and K 2 O were applied at 7 days DAT, while the remaining N was applied at the early panicle initiation stage (42 DAT). The total N inputs were 188, 252, and 203 kg ha − 1 for CF, RS + CF, and BC + CF, respectively (Table 1 ). Irrigation was supplied via pumps from deep wells. The plots were submerged for 10 days before transplanting. RD6 rice seedlings (28 days old) were transplanted at 20 cm × 20 cm spacing (one seedling per hill). Continuous flooding (~ 5 cm depth) was maintained throughout the growing season, with drainage occurring 7 days before harvest. Weed, pest, and disease management adhered to the standard Thai Department of Agriculture guidelines. Material preparation and characterization RS was collected from the cultivated experimental field, air-dried, and cut into ~ 10 cm pieces. BC was produced from air-dried RS via a 200 L traditional drum kiln under oxygen-limited conditions at ~ 350°C for 2 h, which is consistent with farmer-operated production in Thailand [ 45 ]. The applied rate of 3 t ha -1 corresponded to that obtained from pyrolyzing 10 t ha -1 rice straw. Both the RS and BC samples were oven-dried (60°C), ground via a hammer mill and analyzed. The pH was measured in a 1:5 material-to-deionized water (DI water) suspension after 1.5 hours of shaking (HANNA HI8424) [ 46 ]. The CEC was determined using 1 M ammonium acetate (pH 7.0) [ 47 ]. The total N and TOC were measured via dry combustion (CN analyzer; Multi N/C 2100s, Analytik Jena, Germany), and the C/N ratio was calculated as TOC/total N. Compared with RS, BC presented a higher pH (8.9), TOC content (469 g kg − 1 ), C/N ratio (94), and CEC (36 cmol kg − 1 ), but a lower total N content (5.0 g kg − 1 ) (Table 2 ). Soil sampling and analysis Initial disturbed and undisturbed soil samples were collected at depths of 0–20 and 20–60 cm. Soil samples (0–20 cm) were collected during the growing season at 1 DAT (seedling), 56 DAT (maximum tillering), 105 DAT (panicle initiation), and 119 DAT (harvest). Five subsamples per plot (1 m × 1 m area) were composited, divided into field-moist subsamples stored at -4°C for mineral N, and air-dried subsamples were ground and sieved (< 2 mm) for chemical analyses. The physical properties of the initial soil samples were determined. The particle-size distribution was measured via the pipette method [ 48 ]. Bulk density and Ksat (0–20 and 20–60 cm) were measured using soil cores [ 49 – 50 ], with Ksat determined via the falling-head method [ 50 ]. The initial soil pH was measured in a 1:5 soil:DI water mixture. During the season, the field soil pH and Eh at 0–20 cm were monitored via a portable meter (HANNA HI8424). Soil TOC and total N contents were analyzed via dry combustion (Multi N/C 2100s, Analytik Jena, Germany). Exchangeable NH 4 + -N and NO 3 - -N were extracted with 2 M KCl and 0.5 M K 2 SO 4 , respectively. NH 4 + -N was determined colorimetrically via the salicylate‒sodium hypochlorite method [ 28 , 51 ], and NO 3 - -N was measured via the salicylic‒sodium hydroxide method [ 28 , 52 ], via a visible spectrophotometer (SP-UV300, PerkinElmer Inc., Waltham, MA, USA) at 650 and 410 nm, respectively. Mineral N was calculated as NH 4 + -N + NO 3 - -N, and organic N was calculated as total N − mineral N. Sampling and analyses of the soil solution and leachate The soil solution (0–20 cm) and leachate (20–60 cm) were collected via suction lysimeters installed at the center of each 1 m × 1 m subplot. Samples were drawn with a 100 mL syringe between 08:00 and 10:00, twice weekly throughout the season, and daily for 7 days following fertilizer application. The samples were stored at 4°C until NH₄⁺-N and NO₃⁻-N analyses were performed via the methods described above. The cumulative NH 4 + -N and NO 3 − -N leaching losses were calculated by multiplying the measured N concentrations by the corresponding daily leachate volume and summing over time. The daily leachate volume was estimated from depth-specific Ksat (9.3 cm day − 1 at 0–20 cm; 1.2 cm day − 1 at 20–60 cm) and converted to volumetric flux per hectare by multiplying by 1 ha area, yielding 9.3×10 5 and 1.2×10 5 L ha − 1 day − 1 for 0–20 and 20–60 cm, respectively, assuming vertical, unit-gradient flow. These fluxes were multiplied by the measured NH 4 + -N and NO 3 − -N concentrations to derive daily loads and cumulative losses. Measurements of soil NH 3 volatilization and N 2 O emission Gas sampling was conducted weekly alongside leachate sampling. When sampling coincided with fertilizer application, gas collection was performed 24 h after application to minimize interference [ 53 – 54 ]. NH 3 volatilization was measured via an adapted closed-chamber method with an H 2 SO 4 trap [ 55 ]. NH 3 was trapped twice per sampling day (08:00–12:00 and 12:00–16:00) [ 56 ], using 50 mL of 2 N H 2 SO 4 in an 80 mL glass jar placed inside a chamber (inner diameter 16 cm; height 29 cm). The trapped NH 3 -N was quantified via titration with 2 N NaOH: NH 3 -N (mg N) = (B − V) × N × 14 where “B” is the NaOH volume for the blank (mL), “V” is the NaOH volume for the sample (mL), “N” is NaOH normality, and “14” is the atomic weight of nitrogen. The NH 3 -N flux was calculated via a modified equation [ 57 ]: NH 3 -N (kg ha − 1 day − 1 ) = [2 × c(H 2 SO 4 ) × V(H 2 SO 4 ) × 10 − 3 × M(NH 3 ) × 10 − 3 ] / [4 × 24 / (π × R 2 × 10,000)] where “c(H 2 SO 4 )” is the acid concentration (mol L − 1 ), “V(H 2 SO 4 )” is the titrated acid volume (mL), “M(NH 3 )” is the molar mass of NH 3 (g mol − 1 ), “R” is the chamber radius (m), “4” is the trapping duration per event, and “24” is used to standardize the flux on a daily basis. The cumulative NH 3 -N volatilization (kg ha − 1 ) was obtained by summing the daily fluxes over the monitoring period. N 2 O emissions were measured via a closed-chamber method between 08:00 and 11:00. Chambers (60 cm × 60 cm × 80 cm) were placed on fixed frames, and gas samples were collected at 0, 10, 20, and 30 min via a 10 mL syringe and then transferred to 5 mL evacuated vials. The chamber air temperature and water level were recorded during sampling. N 2 O concentrations were analyzed via gas chromatography (Agilent 7890B, Agilent Technologies, USA) equipped with an electron capture detector (ECD) at 300°C and a HaySep Q packed column, with helium as the carrier gas at 20 mL min − 1 . N 2 O fluxes were calculated from the slope of the linear regression of concentration versus time, and cumulative emissions were calculated by summing daily fluxes. The cumulative N 2 O was converted to N 2 O-N via the molecular ratio of N in N 2 O and expressed as a percentage of the total N input to estimate N loss via N 2 O emissions. Measurements of rice yield and agronomic efficiency At harvest, aboveground biomass was determined by manually harvesting rice from a 1 m × 1 m area at the plot center (25 marked hills). The plants were separated into straw, white grains, and husks, and oven-dried at 70°C to a constant weight. The agronomic efficiency of applied N (NAE; kg kg -1 ) was calculated following Fageria and Barbosa [ 57 ]: NAE = (G f − G c )/N t where “G f ” is the grain yield in fertilized plots (kg ha -1 ), “G c ” is the grain yield in the unfertilized control (kg ha -1 ), and “N t ” is the total applied N (kg ha -1 ). Nitrogen gas-related global warming potential and greenhouse gas intensity The nitrogen gas-related global warming potential (GWP N ) was calculated in kg CO 2 eq ha -1 [ 58 ] via the following equation: GWP = 273 × (T + (T × 0.01)) × (44/28) where “273” is the GWP factor for N 2 O over a 100-year horizon, “T N2O ” is cumulative N 2 O emissions (kg N ha -1 ), “T NH3 ” is cumulative NH 3 volatilization (kg N ha -1 ), “0.01” is assumed to be 1% of emitted NH 3 deposited to land for subsequent conversion to N 2 O [ 59 ], and “44/28” is the ratio of the molecular weights of N 2 O to N. The greenhouse gas intensity (GHGI, kg CO 2 eq t -1 ) was calculated according to the methods of Zhao et al. [ 60 ]: GHGI = GWP/Y where “Y” is the sum of white grains and husks (t ha -1 ). Statistical analysis Statistical analyses were performed via Statistix 10 and IBM SPSS Statistics (version 28). Treatment effects were tested by analysis of variance, and mean comparisons were conducted via the least significant difference (LSD) test at p < 0.05. Pearson correlation was used to assess the relationships among soil N losses, soil properties, and rice yield components across treatments. The relationship between the GHGI and grain yield was evaluated via regression analysis at p < 0.05. Declarations Ethics statement This study does not include human or animal subjects. The plant collection and use procedures were in accordance with all the relevant guidelines. Additional Information Competing interests The authors declare that they have no competing interests. Funding Declaration This research was supported by the Fundamental Fund of Khon Kaen University (Grant Number: 49019) and the Thesis Support Scholarship from the Graduate School, Khon Kaen University (Grant Number: 641T217). Author Contribution S.S. (Somboon): data curation, formal analysis, investigation, conceptualization, visualization, writing – original draft, writing – review and editing; B.R. (Rossopa): methodology, writing – review and editing; S.Y. (Yodda): writing – review and editing; P.L. (Lawongsa): data curation, conceptualization, methodology, resources, validation, writing – review and editing; A.C. (Chidthaisong): methodology, writing – review and editing; T-S.S. (Sukitprapanon): data curation, conceptualization, visualization, methodology, resources, validation, supervision, project administration, funding acquisition, writing – review and editing. Acknowledgement The authors would like to acknowledge the staff from the Department of Soil Science and Environment for their support and the Integrated Soil and Organic Matter Management Research Group, Khon Kaen University for working on this field experiment. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request (T-S.S., [email protected] ). References Chivenge, P., Sharma, S., Bunquin, M. A. & Hellin, J. Improving nitrogen use efficiency—a key for sustainable rice production systems. Front. Sustain. Food Syst. 5 , 737412. 10.3389/fsufs.2021.737412 (2021). Omara, P., Aula, L., Oyebiyi, F. & Raun, W. R. World cereal nitrogen use efficiency trends: review and current knowledge. Agrosyst Geosci. Environ. 2 , 1–8. 10.2134/age2018.10.0045 (2019). 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Supplementary Files SupplementaryInformationTanabhatSakorn.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 04 May, 2026 Reviews received at journal 03 May, 2026 Reviewers agreed at journal 03 May, 2026 Reviews received at journal 15 Apr, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers invited by journal 28 Jan, 2026 Editor assigned by journal 23 Jan, 2026 Submission checks completed at journal 23 Jan, 2026 First submitted to journal 15 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8607079","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588059925,"identity":"3b81c5db-ecb1-4a3e-a755-cda9676f9b7b","order_by":0,"name":"Saowalak Somboon","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Saowalak","middleName":"","lastName":"Somboon","suffix":""},{"id":588059929,"identity":"a5d97bab-4ffb-4a8a-a5ac-9d8b6ccd7fae","order_by":1,"name":"Benjamas Rossopa","email":"","orcid":"","institution":"Ministry of Agriculture and Cooperatives","correspondingAuthor":false,"prefix":"","firstName":"Benjamas","middleName":"","lastName":"Rossopa","suffix":""},{"id":588059930,"identity":"3f20b204-7d0a-4a8d-ac54-765eb05c8e9b","order_by":2,"name":"Sujitra Yodda","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Sujitra","middleName":"","lastName":"Yodda","suffix":""},{"id":588059931,"identity":"2ac432af-7d4c-4dd1-b635-d76bfc5dd5ab","order_by":3,"name":"Phrueksa Lawongsa","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Phrueksa","middleName":"","lastName":"Lawongsa","suffix":""},{"id":588059941,"identity":"9aa789e3-a65e-40b8-b76c-0accc071b6db","order_by":4,"name":"Amnat Chidthaisong","email":"","orcid":"","institution":"King Mongkut's University of Technology Thonburi","correspondingAuthor":false,"prefix":"","firstName":"Amnat","middleName":"","lastName":"Chidthaisong","suffix":""},{"id":588059942,"identity":"e4b5b7e6-28e7-45f8-9e6e-2ba30e7f2120","order_by":5,"name":"Tanabhat-Sakorn Sukitprapanon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYPCCBDkJHijTgJBaqMIEY5gWCaK1JM4gWos9+9mDH3+2paXP7DljwPCjhqHOnKAtPHnJ0rxtObmzeXsMGHuOMUhYNhB0WI6BNGNbRe48fh4DBt4GoMMOENLC/8b458+2inQ5oBbGv0RpkcgxkwA6LEEa6DBm4my58cbMmudcmuHMnmMFh2WOSUhuIKSFvT/H+OaPsmR5iTPJGx++qbHhJ2gLCgAqliBF/SgYBaNgFIwCXAAAYgo3dSFOyeEAAAAASUVORK5CYII=","orcid":"","institution":"Khon Kaen University","correspondingAuthor":true,"prefix":"","firstName":"Tanabhat-Sakorn","middleName":"","lastName":"Sukitprapanon","suffix":""}],"badges":[],"createdAt":"2026-01-15 05:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8607079/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8607079/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102846367,"identity":"c46ed88e-e82c-467d-9938-dc5055f65139","added_by":"auto","created_at":"2026-02-17 13:22:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35193,"visible":true,"origin":"","legend":"\u003cp\u003eMeans and standard deviations (bars) of field soil pH (a), field soil redox potential (field soil Eh) (b), total organic carbon (TOC) (c), cation exchange capacity (CEC) (d), total N (e), organic N (f), mineral N (g), exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (h), and exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N (i) concentrations under different treatments at the seedling, tillering, panicle initiation, and harvest stages. Different letters indicate significant differences among treatments according to the LSD test with \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/d78ff3b902c0fa8f212db35a.png"},{"id":102846366,"identity":"da3e0071-987c-43f5-ba18-6afe8403bda8","added_by":"auto","created_at":"2026-02-17 13:22:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":74962,"visible":true,"origin":"","legend":"\u003cp\u003eMeans and standard deviations (bars) of the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (a) and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N (b) concentrations in the soil solution at the 0–20 cm soil depth; the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (c) and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N (d) concentrations in the leachate; and the cumulative leaching of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (e) and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N (f) at the 20–60 cm soil depth under the control, chemical fertilizer (CF), rice straw and chemical fertilizer (RS+CF), rice straw-derived biochar and chemical fertilizer (BC+CF) treatments during rice cultivation.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/8b048e9302f0e32086fe1a61.png"},{"id":102846368,"identity":"c36a4f9e-b313-43f1-92c2-767e5c65508c","added_by":"auto","created_at":"2026-02-17 13:22:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17093,"visible":true,"origin":"","legend":"\u003cp\u003eMeans and standard deviations (bars) of the relative fractions of N losses from paddy soils treated with different treatments, including chemical fertilizer (CF), rice straw and chemical fertilizer (RS+CF), and rice straw-derived biochar and chemical fertilizer (BC+CF). Different letters indicate significant differences among treatments according to the LSD test, with \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/87dfe97cf38f9e1e1a7a66c1.png"},{"id":102846372,"identity":"394ece44-f3c6-4508-8c07-f4e07288c8e2","added_by":"auto","created_at":"2026-02-17 13:22:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":43905,"visible":true,"origin":"","legend":"\u003cp\u003eMeans and standard deviations (bars) of NH\u003csub\u003e3\u003c/sub\u003e volatilization (a) and N\u003csub\u003e2\u003c/sub\u003eO emission (b), cumulative NH\u003csub\u003e3 \u003c/sub\u003evolatilization (c), and cumulative N\u003csub\u003e2\u003c/sub\u003eO emission (d) in paddy soils treated with different treatments, including the control, chemical fertilizer (CF), rice straw and chemical fertilizer (RS+CF), and rice straw-derived biochar and chemical fertilizer (BC+CF) treatments, during the rice growing season.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/80d3b64e8f548c2697da582f.png"},{"id":102846369,"identity":"96d35d7b-2bfe-4c4a-87b0-2cf8b920796f","added_by":"auto","created_at":"2026-02-17 13:22:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":14857,"visible":true,"origin":"","legend":"\u003cp\u003eMeans and standard deviations (bars) of nitrogen gas-related global warming potential (GWP\u003csub\u003eN\u003c/sub\u003e) (a) and greenhouse gas intensity (GHGI) (b) from paddy soils treated with different treatments, including the control, chemical fertilizer (CF), rice straw with chemical fertilizer (RS+CF), and rice straw-derived biochar with chemical fertilizer (BC+CF) treatments. Different letters indicate significant differences among treatments according to the LSD test, with p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/66f22c95edf805aea257659f.png"},{"id":102963594,"identity":"8f300639-ea33-4d90-932d-e88dc4546dee","added_by":"auto","created_at":"2026-02-19 04:19:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":13480,"visible":true,"origin":"","legend":"\u003cp\u003eLinear regression analysis between greenhouse gas intensity (GHGI) (kg CO\u003csub\u003e2\u003c/sub\u003e eq t\u003csup\u003e-1\u003c/sup\u003e GY) and rice grain yield (kg ha\u003csup\u003e-1\u003c/sup\u003e). * indicates significance at the level of \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/6c7cd0ec09f748f4b126eed6.png"},{"id":102965329,"identity":"ce28d0d7-38b7-4ce9-a399-b3043987543c","added_by":"auto","created_at":"2026-02-19 04:31:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1667521,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/8748b656-62bd-482a-bb78-17421ceb77c0.pdf"},{"id":102846371,"identity":"9ed26d1d-62f2-45ff-9466-a6de4e710810","added_by":"auto","created_at":"2026-02-17 13:22:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":360504,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformationTanabhatSakorn.docx","url":"https://assets-eu.researchsquare.com/files/rs-8607079/v1/a703c9fa7308c9c7ba6f1048.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rice straw-derived biochar reduces nitrogen losses and greenhouse gas emissions while improving rice productivity and agronomic efficiency in a tropical paddy soil","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNitrogen (N) is an essential nutrient for plant growth and a major determinant of crop productivity and food security. To achieve high yields, N fertilizer is often applied in excess of crop demand, increasing production costs, whereas the global N use efficiency typically remains below 40% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Inefficient N use leads to substantial losses to the environment, accelerating soil acidification, eutrophication, groundwater contamination, air pollution, and greenhouse gas (GHG) emissions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Rice is a staple food for more than half of the world\u0026rsquo;s population and dominates cultivated areas in Asia, with approximately 165\u0026nbsp;million hectares globally [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. N management in flooded rice systems is particularly challenging because more than 60% of applied N can be lost via multiple pathways, including mineral N leaching (ammonium-nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N), and nitrate-nitrogen (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N); 0.1\u0026ndash;33%), ammonia (NH\u003csub\u003e3\u003c/sub\u003e) volatilization (10\u0026ndash;60%), and nitrous oxide (N\u003csub\u003e2\u003c/sub\u003eO) emissions (5\u0026ndash;35%) [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Among these, N₂O is a potent GHG with a global warming potential (GWP) that is 273 times greater than that of carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], underscoring the urgency of integrated N management strategies that reduce losses while sustaining yield.\u003c/p\u003e \u003cp\u003eRice straw (RS) management offers both opportunities and trade-offs for mitigating N losses in paddy soils [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The incorporation of RS can increase soil total organic carbon (TOC) and total N, improving soil fertility and rice yield [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Several studies have reported reduced mineral N leaching following RS incorporation, attributed to the immobilization of inorganic N into organic pools and improved N sequestration, which limits N mobility [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. For example, RS incorporation decreased NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N in leachate from saline\u0026ndash;sodic paddy soils [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and Yang et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] reported 13% mitigation of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e leaching in a temperate arid region. RS can also reduce NH\u003csub\u003e3\u003c/sub\u003e volatilization and N\u003csub\u003e2\u003c/sub\u003eO emissions by lowering NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N in floodwater and promoting N immobilization, including a reported 41% reduction in NH\u003csub\u003e3\u003c/sub\u003e volatilization under subtropical monsoon conditions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, rapid RS decomposition increases NH\u003csub\u003e3\u003c/sub\u003e volatilization [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and elevates N\u003csub\u003e2\u003c/sub\u003eO emissions by supplying labile carbon for denitrification [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These contrasting outcomes highlight the need for system-level evaluation of RS effects across all major N loss pathways.\u003c/p\u003e \u003cp\u003eBiochar, which is produced by the pyrolysis of crop residues under limited oxygen, is widely proposed as a complementary strategy for improving soil fertility and mitigating N losses. Biochar can increase TOC and total N, enhance nutrient retention, improve yield, and reduce N losses through both leaching and gaseous pathways [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Its high carbon stability, porosity, and cation exchange capacity (CEC) support the adsorption and retention of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N and can influence microbial immobilization and soil buffering [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Field evidence indicates that rice straw-derived biochar (BC) reduces NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N leaching (30\u0026ndash;38.6%) and total N leaching (12.8\u0026ndash;13.4%) and decreases NH\u003csub\u003e3\u003c/sub\u003e volatilization and N\u003csub\u003e2\u003c/sub\u003eO emissions by 11.5\u0026ndash;17.8% in subtropical monsoon climates [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Selvarajh et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] further reported that enriched BC (5\u0026ndash;10 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) reduced NH\u003csub\u003e3\u003c/sub\u003e volatilization by increasing the adsorption capacity and buffering pH, whereas Yang et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] reported 45.1\u0026ndash;74% reductions in cumulative N\u003csub\u003e2\u003c/sub\u003eO emissions (1\u0026ndash;5% w/w) linked to increased soil pH and reduced NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e reductase activity. Nonetheless, biochar application increases NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching when nitrification is suppressed, as retained NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e can accumulate in the soil solution [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Thus, the effects of biochar should be assessed together with other N-loss pathways and agronomic outcomes.\u003c/p\u003e \u003cp\u003eDespite extensive studies on RS and BC, direct comparisons that quantify all major N loss pathways within a single flooded rice system remain limited. Many studies emphasize one pathway (e.g., NH\u003csub\u003e3\u003c/sub\u003e or N\u003csub\u003e2\u003c/sub\u003eO) without integrating mineral N leaching, agronomic efficiency, and climate metrics. In particular, GHGI is often reported without system-level indices such as nitrogen gas-related global warming potential (GWP\u003csub\u003eN\u003c/sub\u003e), which requires concurrent quantification of NH\u003csub\u003e3\u003c/sub\u003e volatilization and N\u003csub\u003e2\u003c/sub\u003eO emissions. These knowledge gaps preclude a comprehensive evaluation of the net environmental benefits and inherent biogeochemical trade-offs between rice straw and biochar amendments. Here, we conduct a comparative, system-level assessment of RS and BC applications in tropical flooded paddy soil by linking mineral N leaching (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N), NH\u003csub\u003e3\u003c/sub\u003e volatilization, and N\u003csub\u003e2\u003c/sub\u003eO emissions with rice yield, the agronomic efficiency of applied N (NAE), and climate-relevant indices (GWP\u003csub\u003eN\u003c/sub\u003e and GHGI). We hypothesized that both RS and BC enhance soil fertility and rice productivity, but the greater stability and CEC of BC would result in greater reductions in total N losses across the leaching and gaseous pathways, resulting in lower GWP\u003csub\u003eN\u003c/sub\u003e and GHGI. Our objectives were to (1) quantify N losses via NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N leaching, NH\u003csub\u003e3\u003c/sub\u003e volatilization, and N\u003csub\u003e2\u003c/sub\u003eO emissions, (2) evaluate rice grain yield and NAE, and (3) assess GWP\u003csub\u003eN\u003c/sub\u003e and GHGI under RS combined with chemical fertilizer (CF), BC combined with CF, and CF in a tropical paddy soil system.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eSoil chemical properties during rice cultivation\u003c/b\u003e The soil chemical dynamics under the control, chemical fertilizer (CF), rice straw combined with CF (RS\u0026thinsp;+\u0026thinsp;CF), and rice straw-derived biochar combined with CF (BC\u0026thinsp;+\u0026thinsp;CF) treatments are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The soil pH remained nearly neutral (6.5\u0026ndash;7.3) across the treatments during the season (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Across treatments, the mean redox potential (Eh) decreased from \u0026minus;\u0026thinsp;86 mV (seedling) to -324 mV (panicle initiation) and then increased to 166 mV at harvest (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). TOC was consistently greater in the RS\u0026thinsp;+\u0026thinsp;CF (3,367\u0026ndash;6,133 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and BC\u0026thinsp;+\u0026thinsp;CF (3,667\u0026ndash;5,668 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatments than in the CF (2,367\u0026ndash;4,467 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and the control (2,933\u0026ndash;4,200 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Cation exchange capacity (CEC) increased at the seedling stage under RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF (13 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) but converged among treatments from tillering to panicle initiation (10\u0026ndash;12 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e); at harvest, BC\u0026thinsp;+\u0026thinsp;CF remained higher (11 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than the RS\u0026thinsp;+\u0026thinsp;CF, CF, and control (10 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe seasonal dynamics of total N, organic N, mineral N, and exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N followed similar patterns across treatments, peaking at the tillering stage and gradually decreasing thereafter (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee\u0026ndash;h). The total N content was significantly greater in the RS\u0026thinsp;+\u0026thinsp;CF (167\u0026ndash;2,167 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and BC\u0026thinsp;+\u0026thinsp;CF (170\u0026ndash;2,213 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatments than in the CF (94\u0026ndash;692 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatments and control (92\u0026ndash;621 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). The peak total N at tillering reached 2,167 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (RS\u0026thinsp;+\u0026thinsp;CF) and 2,213 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (BC\u0026thinsp;+\u0026thinsp;CF), and at harvest, BC\u0026thinsp;+\u0026thinsp;CF presented the highest total N (1,070 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), followed by RS\u0026thinsp;+\u0026thinsp;CF (786 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), whereas the CF (128 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and the control (97 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) presented the lowest total N. Organic N dominated total N (88\u0026ndash;2,171 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), whereas mineral N was relatively low (1.5\u0026ndash;43 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef\u0026ndash;g). Exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N increased from seedling (13\u0026ndash;15 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF) to tillering (35\u0026ndash;43 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and remained higher at harvest (25\u0026ndash;36 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than in the CF and the control (0.25\u0026ndash;3.3 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh). Unlike other N components, exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N remained low (0\u0026ndash;0.95 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and presented stage-dependent peaks, particularly at panicle initiation (0.69 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in RS\u0026thinsp;+\u0026thinsp;CF and 0.95 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in BC\u0026thinsp;+\u0026thinsp;CF) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRice yield and agronomic efficiency\u003c/b\u003e The organic amendments significantly increased the rice yield and NAE (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). BC\u0026thinsp;+\u0026thinsp;CF produced the highest grain yield (11,823 kg ha\u003csup\u003e-1\u003c/sup\u003e), significantly outperforming RS\u0026thinsp;+\u0026thinsp;CF (10,577 kg ha\u003csup\u003e-1\u003c/sup\u003e) and CF (6,333 kg ha\u003csup\u003e-1\u003c/sup\u003e), whereas the control yielded 1,609 kg ha\u003csup\u003e-1\u003c/sup\u003e. BC\u0026thinsp;+\u0026thinsp;CF also produced the highest white grain (7,331 kg ha\u003csup\u003e-1\u003c/sup\u003e) and husk (4,492 kg ha\u003csup\u003e-1\u003c/sup\u003e) yields. The straw biomass was greatest in BC\u0026thinsp;+\u0026thinsp;CF (17,600 kg ha\u003csup\u003e-1\u003c/sup\u003e), but was not significantly different from that in RS\u0026thinsp;+\u0026thinsp;CF (14,726 kg ha\u003csup\u003e-1\u003c/sup\u003e) or CF (15,962 kg ha\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRice yield and agronomic efficiency under different treatments. Abbreviations: NAE: agronomic efficiency of applied nitrogen; Control: no fertilizer or organic application; CF: soil treated with chemical fertilizer; RS\u0026thinsp;+\u0026thinsp;CF: soil treated with rice straw and chemical fertilizer; BC\u0026thinsp;+\u0026thinsp;CF: soil treated with rice straw-derived biochar and chemical fertilizer. Lowercase letters in the same column represent significant differences among treatments according to the LSD test, with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal N input\u003c/p\u003e \u003cp\u003e(kg ha\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eYield (kg ha\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNAE\u003c/p\u003e \u003cp\u003e(kg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStraw\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWhite rice grain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHusk\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,100c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,609d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e913d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e696d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,962ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,333c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,855c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,479c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRS\u0026thinsp;+\u0026thinsp;CF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,726b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,577b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,466b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,112b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC\u0026thinsp;+\u0026thinsp;CF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17,600a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,823a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,331a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,492a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePearson correlation analysis (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) revealed a strong positive correlation between rice grains and white grains and husks (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.00 for both; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Additionally, grain yield was positively correlated with TOC (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.91), soil total N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.91), organic N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.91), exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89), exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.86), and the mineral N content (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eBoth the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF amendments significantly enhanced NAE (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The NAE increased from 25 kg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (CF) to 36 kg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (RS\u0026thinsp;+\u0026thinsp;CF) and 50 kg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (BC\u0026thinsp;+\u0026thinsp;CF), and was strongly correlated with grain yield, white grains, and husks (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.98 for all) and with straw biomass (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.73) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSoil nitrogen losses\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNH\u003c/b\u003e \u003csub\u003e \u003cb\u003e4\u003c/b\u003e \u003c/sub\u003e \u003csup\u003e \u003cb\u003e+\u003c/b\u003e \u003c/sup\u003e \u003cb\u003e-N and NO\u003c/b\u003e \u003csub\u003e \u003cb\u003e3\u003c/b\u003e \u003c/sub\u003e \u003csup\u003e \u003cb\u003e-\u003c/b\u003e \u003c/sup\u003e \u003cb\u003e-N concentrations in the soil solution at 0\u0026ndash;20 cm depth\u003c/b\u003e Across the fertilized treatments, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N dominated the soil solution (0.16\u0026ndash;17 mg L\u003csup\u003e-1\u003c/sup\u003e), whereas NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N remained low (0.01\u0026ndash;0.20 mg L\u003csup\u003e-1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026ndash;b). In contrast, the control had a lower NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration (0.12\u0026ndash;2.39 mg L\u003csup\u003e-1\u003c/sup\u003e), while the NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N concentration ranged from 0.06\u0026ndash;0.16 mg L\u003csup\u003e-1\u003c/sup\u003e.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration in the soil solution exhibited similar dynamics under the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF treatments but differed from those under the control and CF treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). After the first fertilization at 7 days after transplanting (DAT), the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration peaked at 8 DAT in RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF (16 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and at 9 DAT in CF (14 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). RS\u0026thinsp;+\u0026thinsp;CF (4.9˗14 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The BC\u0026thinsp;+\u0026thinsp;CF (1.9\u0026ndash;8.7 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) amendments resulted in higher NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentrations than did the CF and control treatments from 35\u0026ndash;46 DAT. After the second fertilization, the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration in the CF treatment increased again to 4.4 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 43 DAT and then gradually declined (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N concentrations differed among the treatments throughout the season, ranging from 0.01 to 0.20 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N concentrations generally peaked approximately 7 DAT (0.18\u0026ndash;0.20 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and then declined; by 112 DAT, the NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N concentration was lower in the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF treatments (0.04 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than in the CF (0.10 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and control (0.11 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) treatments.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNH\u003c/b\u003e \u003csub\u003e \u003cb\u003e4\u003c/b\u003e \u003c/sub\u003e \u003csup\u003e \u003cb\u003e+\u003c/b\u003e \u003c/sup\u003e \u003cb\u003e-N and NO\u003c/b\u003e \u003csub\u003e \u003cb\u003e3\u003c/b\u003e \u003c/sub\u003e \u003csup\u003e \u003cb\u003e-\u003c/b\u003e \u003c/sup\u003e \u003cb\u003e-N leaching at 20\u0026ndash;60 cm depth\u003c/b\u003e NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N was the predominant mineral N in the leachate (0\u0026ndash;11 mg L\u003csup\u003e-1\u003c/sup\u003e), whereas NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N in the leachate was lower (0\u0026ndash;0.22 mg L\u003csup\u003e-1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec\u0026ndash;d). The leachate NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N dynamics were similar in the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), with peaks at 8 DAT after the first fertilization (8.6 and 6.2 mg L\u003csup\u003e-1\u003c/sup\u003e, respectively). A second elevated period occurred at 21\u0026ndash;35 DAT, during which RS\u0026thinsp;+\u0026thinsp;CF reached 10.7\u0026ndash;11.0 mg L\u003csup\u003e-1\u003c/sup\u003e and BC\u0026thinsp;+\u0026thinsp;CF reached 3.2\u0026ndash;6.1 mg L\u003csup\u003e-1\u003c/sup\u003e. In contrast, the CF peaked earlier at 9 DAT (8.4 mg L\u003csup\u003e-1\u003c/sup\u003e), whereas that of the control remained low and relatively stable (0\u0026ndash;2.1 mg L\u003csup\u003e-1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N concentrations in the leachate in the CF and control treatments were relatively stable (0.07\u0026ndash;0.16 and 0.08\u0026ndash;0.18 mg L\u003csup\u003e-1\u003c/sup\u003e), whereas those in the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF treatments were more variable (0\u0026ndash;0.19 and 0\u0026ndash;0.22 mg L\u003csup\u003e-1\u003c/sup\u003e, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF peaked at 7 DAT (0.14 and 0.22 mg L\u003csup\u003e-1\u003c/sup\u003e, respectively) and declined rapidly by 8 DAT. During the first 7 days after each fertilization, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N in the leachate was generally greater in the CF and control treatments than in the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF treatments. Later-season increases in RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF occurred at 84 and 98 DAT, respectively.\u003c/p\u003e \u003cp\u003eThe cumulative NH₄⁺-N leaching differed among the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). The RS\u0026thinsp;+\u0026thinsp;CF-treated soil had the greater cumulative NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N loss (54 kg ha\u003csup\u003e-1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), accounting for 21% of the total N input (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), whereas the control had the lowest (15 kg ha\u003csup\u003e-1\u003c/sup\u003e). Although cumulative NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching did not differ significantly between the CF and BC\u0026thinsp;+\u0026thinsp;CF treatments, that in the BC\u0026thinsp;+\u0026thinsp;CF treatment was numerically lower (28 kg ha\u003csup\u003e-1\u003c/sup\u003e; 14% of total N input) than CF (32 kg ha\u003csup\u003e-1\u003c/sup\u003e; 17% of total N input) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Correlation analyses showed significant negative correlations between the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration in the leachate and the NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N concentration in the soil solution (\u003cem\u003er\u003c/em\u003e = -0.33; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), TOC (\u003cem\u003er\u003c/em\u003e = -0.31; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), mineral N (\u003cem\u003er\u003c/em\u003e = -0.31; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N (\u003cem\u003er\u003c/em\u003e = -0.29; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration in the leachate was strongly positively correlated with the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration in the soil solution (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.82; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and soil Eh (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and exhibited a weaker positive correlation with the soil exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.30; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table S2).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe cumulative NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N leaching was minor across the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef), with the lowest loss in the RS\u0026thinsp;+\u0026thinsp;CF treatment (1.3 kg ha\u003csup\u003e-1\u003c/sup\u003e; 0.5% of total N input), followed by the CF and control treatments (1.4 kg ha\u003csup\u003e-1\u003c/sup\u003e; 0.8% of total N input), and the greater loss occurred in the BC\u0026thinsp;+\u0026thinsp;CF-treated soil (1.5 kg ha\u003csup\u003e-1\u003c/sup\u003e; 0.7% of total N input) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Pearson correlation analysis indicated that the NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N concentration in the leachate was positively correlated with total N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.68; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), organic N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.68; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N in soil solution (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.61; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.39; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and mineral N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.39; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Conversely, it was significantly negatively correlated with the soil Eh (\u003cem\u003er\u003c/em\u003e = -0.45; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentration in the soil solution (\u003cem\u003er\u003c/em\u003e = -0.29; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table S2).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNH\u003c/b\u003e \u003csub\u003e \u003cb\u003e3\u003c/b\u003e \u003c/sub\u003e \u003cb\u003evolatilization and N\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO emission\u003c/b\u003e NH\u003csub\u003e3\u003c/sub\u003e volatilization fluxes presented broadly similar temporal patterns across the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). After the first fertilization, BC\u0026thinsp;+\u0026thinsp;CF rapidly increase to 81 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e, whereas CF (100 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e) and RS\u0026thinsp;+\u0026thinsp;CF (92 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e) did not immediately increase. By 21 DAT, NH\u003csub\u003e3\u003c/sub\u003e volatilization declined to 23\u0026ndash;24 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e in the CF and RS\u0026thinsp;+\u0026thinsp;CF treatments and to 20 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e in the BC\u0026thinsp;+\u0026thinsp;CF treatment. NH\u003csub\u003e3\u003c/sub\u003e volatilization increased again across treatments at 35 DAT (52\u0026ndash;107 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e) and then decreased by 56 DAT, stabilizing thereafter at 13\u0026ndash;28 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The cumulative NH\u003csub\u003e3\u003c/sub\u003e volatilization was highest under CF (44 kg ha\u003csup\u003e-1\u003c/sup\u003e; 23% of total N input), followed by the control and RS\u0026thinsp;+\u0026thinsp;CF (40 kg ha\u003csup\u003e-1\u003c/sup\u003e each), and lowest under BC\u0026thinsp;+\u0026thinsp;CF (34 kg ha\u003csup\u003e-1\u003c/sup\u003e; 17% of total N input) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). NH\u003csub\u003e3\u003c/sub\u003e volatilization was negatively correlated with total N and organic N (r = -0.42; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for both), mineral N and exchangeable NH₄⁺-N (r = -0.31; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for both), and CEC (r = -0.30; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table S2).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eN\u003csub\u003e2\u003c/sub\u003eO emission fluxes differed markedly among the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The CF and BC\u0026thinsp;+\u0026thinsp;CF treatments presented sharp peaks at 8 DAT (42 and 23 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e, respectively), whereas those of the control and RS\u0026thinsp;+\u0026thinsp;CF treatments remained relatively low and stable throughout the season (0.3\u0026ndash;10 and 2.2\u0026ndash;9 mg m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e, respectively). Accordingly, cumulative N\u003csub\u003e2\u003c/sub\u003eO emissions were highest under CF (14 kg ha\u003csup\u003e-1\u003c/sup\u003e; 2.4% of total N input), followed by BC\u0026thinsp;+\u0026thinsp;CF (10 kg ha\u003csup\u003e-1\u003c/sup\u003e; 1.6% of total N input) and RS\u0026thinsp;+\u0026thinsp;CF (5.3 kg ha\u003csup\u003e-1\u003c/sup\u003e; 0.7% of total N input) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). N\u003csub\u003e2\u003c/sub\u003eO emissions were positively correlated with soil mineral N and exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.31; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for both) (Table S2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eNitrogen gas-related global warming potential and greenhouse gas intensity\u003c/b\u003e GWP\u003csub\u003eN\u003c/sub\u003e differed among the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). CF presented the highest GWP\u003csub\u003eN\u003c/sub\u003e (247 kg CO\u003csub\u003e2\u003c/sub\u003e eq ha\u003csup\u003e-1\u003c/sup\u003e), whereas those of the control (196 kg CO\u003csub\u003e2\u003c/sub\u003e eq ha\u003csup\u003e-1\u003c/sup\u003e), RS\u0026thinsp;+\u0026thinsp;CF (193 kg CO\u003csub\u003e2\u003c/sub\u003e eq ha\u003csup\u003e-1\u003c/sup\u003e), and BS\u0026thinsp;+\u0026thinsp;CF (187 kg CO\u003csub\u003e2\u003c/sub\u003e eq ha\u003csup\u003e-1\u003c/sup\u003e) soils were not significantly different. However, BC\u0026thinsp;+\u0026thinsp;CF represented the lowest value. The GHGI decreased with increasing grain yield (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.88; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The control had the highest GHGI (122 kg CO\u003csub\u003e2\u003c/sub\u003e eq t\u003csup\u003e-1\u003c/sup\u003e GY), followed by the CF (39 kg CO\u003csub\u003e2\u003c/sub\u003e eq t\u003csup\u003e-1\u003c/sup\u003e GY), whereas the BC\u0026thinsp;+\u0026thinsp;CF achieved the lowest GHGI (16 kg CO\u003csub\u003e2\u003c/sub\u003e eq t\u003csup\u003e-1\u003c/sup\u003e GY), which was 11% lower than that of the RS\u0026thinsp;+\u0026thinsp;CF (18 kg CO\u003csub\u003e2\u003c/sub\u003e eq t\u003csup\u003e-1\u003c/sup\u003e GY) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a system-level comparison of rice straw and rice straw\u0026ndash;derived biochar as complementary amendments to chemical fertilizer in a continuously flooded tropical rice system, revealing distinct soil chemical properties, rice grain yields, N losses through leaching of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, NH\u003csub\u003e3\u003c/sub\u003e volatilization, and N\u003csub\u003e2\u003c/sub\u003eO emissions, as well as GWP\u003csub\u003eN\u003c/sub\u003e, GHGI, and NAE. Although both RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF improved soil fertility and reduced climate impacts compared with CF alone, the BC\u0026thinsp;+\u0026thinsp;CF amendment was the most effective at concurrently reducing N losses and increasing rice productivity.\u003c/p\u003e \u003cp\u003eThe incorporation of RS and biochar significantly improves soil chemistry by increasing soil organic matter and nutrient availability [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Compared with the CF treatment, the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF amendments increased the soil TOC, CEC, total N, organic N, mineral N, exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, and exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N contents during the rice growing season. These improvements were driven by the inherent properties of the RS and BC amendments, particularly their high TOC, CEC, and the carbon-to-nitrogen (C/N) ratio (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and by the greater total N inputs supplied by the combined treatments than those supplied by the CF treatment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF enhanced total N and TOC, promoted N mineralization, and increased exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N in soil [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Increased N availability during critical stages, especially tillering, was a key driver of grain yield, white rice grain yield, and husk biomass, and contributed to the significantly increased yields observed in the RS\u0026thinsp;+\u0026thinsp;CF- and BC\u0026thinsp;+\u0026thinsp;CF-treated soils (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). During tillering, the amount of exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N was greater in the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF treatments than in the other treatments, sustaining the N supply essential for growth and productivity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Moreover, the elevated CEC and exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N in BC\u0026thinsp;+\u0026thinsp;CF resulted in improved NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e retention, resulting in the highest grain yield among the treatments (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean values (n\u0026thinsp;=\u0026thinsp;3) of the physicochemical properties of the initial soil, rice straw, and rice straw-derived biochar used in this study. Abbreviations: Ksat: saturated hydraulic conductivity; Exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N: exchangeable ammonium-nitrogen; Exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N: exchangeable nitrate-nitrogen.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial soil\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRice straw\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRice straw-derived biochar\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSand (g kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilt (g kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClay (g kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil texture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulk density, 0\u0026ndash;20 cm (g cm\u003csup\u003e-3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulk density, 20\u0026ndash;60 cm (g cm\u003csup\u003e-3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKsat, 0\u0026ndash;20 cm (cm s\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKsat, 20\u0026ndash;60 cm (cm s\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH (H\u003csub\u003e2\u003c/sub\u003eO)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal organic carbon (g kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e469\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal nitrogen (g kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbon-to-nitrogen ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCation exchange capacity (cmol kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N (mg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N (mg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMineral nitrogen (mg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganic nitrogen (mg kg\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNAE, defined as the increase in grain yield per unit of N applied, is a key indicator of N use efficiency with direct implications for both economic returns and environmental sustainability [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our study, the RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF amendments significantly increased the NAE from 25 kg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (CF) to 36 kg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (RS\u0026thinsp;+\u0026thinsp;CF) and 50 kg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (BC\u0026thinsp;+\u0026thinsp;CF) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These improvements were attributed to the high CEC and recalcitrant nature of the biochar, which enhanced nutrient retention, reduced N losses, and sustained plant-available N [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Consistent with this mechanism, the NAE was positively correlated with total N, mineral N, organic N, exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, TOC, and CEC (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Collectively, these findings highlight the strategic advantage of using RS, particularly BC, in tropical flooded rice systems to optimize N cycling, increase soil fertility, and improve rice yield and agronomic performance.\u003c/p\u003e \u003cp\u003eIn flooded rice systems, more than 60% of applied N can be lost through multiple pathways, including mineral N leaching, NH\u003csub\u003e3\u003c/sub\u003e volatilization, and N\u003csub\u003e2\u003c/sub\u003eO emissions [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the present study, CF alone resulted in the greatest total N loss, accounting for 43% of the total N input. In contrast, the incorporation of organic amendments reduced total N losses to 38% under RS\u0026thinsp;+\u0026thinsp;CF and 33% under BC\u0026thinsp;+\u0026thinsp;CF (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), indicating improved system-level N retention, particularly with biochar application.\u003c/p\u003e \u003cp\u003eAmong the individual N loss pathways, cumulative NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching was greatest under RS\u0026thinsp;+\u0026thinsp;CF, accounting for 21% of the total N input, compared with 17% under CF and 14% under BC\u0026thinsp;+\u0026thinsp;CF (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The elevated NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching under RS\u0026thinsp;+\u0026thinsp;CF coincided with increased NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N concentrations in soil solution during 21\u0026ndash;35 DAT, which is consistent with the rapid anaerobic decomposition of rice straw [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In contrast, BC\u0026thinsp;+\u0026thinsp;CF amendment reduced cumulative NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching, reflecting the high CEC and enhanced nutrient adsorption of the biochar, which promoted NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e retention in flooded soils [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Moderate cumulative NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching under CF (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee) resulted from rapid urea hydrolysis and limited soil retention capacity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], whereas minimal leaching under the unfertilized control reflected the absence of external N input. In contrast, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N leaching contributed only 0.5\u0026ndash;0.8% of the total N input across the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which is consistent with suppressed nitrification under continuously flooded conditions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The lowest NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N leaching occurred under RS\u0026thinsp;+\u0026thinsp;CF (0.5%), which coincided with elevated NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching and limited substrate availability for nitrification. These results highlight that shifts among N loss pathways can occur depending on the type of organic amendment type, even when total N losses are reduced.\u003c/p\u003e \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e​ volatilization represented a major N loss pathway across fertilized treatments. Compared with CF alone, both RS\u0026thinsp;+\u0026thinsp;BC and BC\u0026thinsp;+\u0026thinsp;CF reduced cumulative NH\u003csub\u003e3\u003c/sub\u003e​ volatilization, with the lowest losses observed under BC\u0026thinsp;+\u0026thinsp;CF. The negative correlations between NH\u003csub\u003e3\u003c/sub\u003e​ volatilization and soil exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and CEC (Table S2) suggest that increased NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e retention reduced the conversion of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e to gaseous NH\u003csub\u003e3​\u003c/sub\u003e. The porous structure and surface functional groups of the biochar likely contributed to this effect by increasing its adsorption capacity and buffering the soil pH [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eN\u003csub\u003e2\u003c/sub\u003eO emissions varied markedly among the treatments. CF alone produced the highest cumulative N\u003csub\u003e2\u003c/sub\u003eO emissions, corresponding to an emission factor of 2.4% of the total N input, substantially exceeding the IPCC Tier 1 default for continuously flooded rice systems [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In contrast, the incorporation of RS or BC reduced N\u003csub\u003e2\u003c/sub\u003eO emissions, with RS\u0026thinsp;+\u0026thinsp;CF resulting in the lowest emission factor (0.7%). The reduced N\u003csub\u003e2\u003c/sub\u003eO emissions under RS\u0026thinsp;+\u0026thinsp;CF were associated with low NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e availability and high NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching, which constrained substrates for denitrification [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In contrast, BC\u0026thinsp;+\u0026thinsp;CF resulted in higher N\u003csub\u003e2\u003c/sub\u003eO emissions (1.6%) than did RS\u0026thinsp;+\u0026thinsp;CF, potentially reflecting increased retention of exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, which may indirectly supply substrates for nitrification\u0026ndash;denitrification processes [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, the measured N loss pathways used to estimate indirect N\u003csub\u003e2​\u003c/sub\u003eO emissions also deviated from IPCC defaults. The fraction of applied N lost by leaching (Frac\u003csub\u003eLEACH\u003c/sub\u003e​) ranges from 14.7\u0026ndash;21.5% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), below the IPCC default of 30%, whereas FracGASF (the fraction of synthetic N volatilized as NH\u003csub\u003e3\u003c/sub\u003e) is 16\u0026ndash;23% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which consistently exceeds the IPCC default of 10% [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Such departures are expected given the strong influence of local climate, soil properties, and fertilizer and amendment management (type, rate, and timing) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Our measurements from continuously flooded tropical rice fields under contrasting N management practices provide site-specific evidence of substantial variability in these emission factors, offering valuable inputs for refining Thailand\u0026rsquo;s country-specific factors for both direct and indirect N\u003csub\u003e2​\u003c/sub\u003eO emissions in the national greenhouse gas inventory.\u003c/p\u003e \u003cp\u003eCollectively, these results demonstrate that rice straw and biochar alter the relative importance of individual N loss pathways. While both amendments reduced total N losses, biochar was more effective at mitigating NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching and NH\u003csub\u003e3\u003c/sub\u003e​ volatilization, whereas rice straw more strongly suppressed N\u003csub\u003e2​\u003c/sub\u003eO emissions.\u003c/p\u003e \u003cp\u003eEvaluating N management strategies from a climate perspective requires the integration of both direct and indirect greenhouse gas emissions. GWP\u003csub\u003eN\u003c/sub\u003e accounts for direct N\u003csub\u003e2\u003c/sub\u003eO emissions as well as indirect emissions arising from NH\u003csub\u003e3\u003c/sub\u003e volatilization and subsequent deposition [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In this study, GWP\u003csub\u003eN\u003c/sub\u003e was significantly greater under CF alone than under RS\u0026thinsp;+\u0026thinsp;CF or BC\u0026thinsp;+\u0026thinsp;CF (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), reflecting the combined mitigation of NH\u003csub\u003e3\u003c/sub\u003e​ volatilization and N\u003csub\u003e2\u003c/sub\u003e​O emissions by organic amendments. No significant difference in GWP\u003csub\u003eN\u003c/sub\u003e was observed between RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF, indicating that both amendments comparably reduced the overall climate impact of N losses. However, the GHGI differed substantially among the treatments and declined strongly with increasing grain yield. Despite low absolute N inputs, the unfertilized control presented the highest GHGI due to poor yield performance, demonstrating that low-input rice cultivation is not inherently climate-efficient. The strong inverse relationship between the GHGI and grain yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) underscores the importance of productivity gains in mitigating yield-scaled greenhouse gas emissions. By simultaneously reducing N losses and increasing grain yield, RS\u0026thinsp;+\u0026thinsp;CF and BC\u0026thinsp;+\u0026thinsp;CF achieved substantially lower GHGI than did CF alone. Among the treatments, BC\u0026thinsp;+\u0026thinsp;CF produced the lowest GHGI, reflecting its combined effects on N retention and crop productivity.\u003c/p\u003e \u003cp\u003eIn conclusion, while both rice straw and its derived biochar serve as effective complementary amendments to chemical fertilizers, they exert distinct regulatory control over N cycling in continuously flooded tropical paddy systems. Our system-level analysis reveals a strategic trade-off: rice straw application more effectively suppresses direct N\u003csub\u003e2\u003c/sub\u003eO emissions, whereas biochar provides a superior mechanism for mitigating NH₄⁺-N leaching and NH\u003csub\u003e3\u003c/sub\u003e volatilization. Crucially, the biochar-treated soil optimized the synergy between environmental mitigation and crop productivity, achieving the highest grain yield, agronomic efficiency of applied N, and N gas-related global warming potential. Furthermore, our findings challenge the assumption that low-input systems are environmentally superior; the poor productivity of unfertilized control resulted in the highest greenhouse gas intensity, indicating that no-input rice management is not inherently climate-efficient. Overall, integrating rice straw-derived biochar with chemical fertilizer represents a highly effective, scalable strategy for reducing nitrogen losses, sustaining rice productivity, and lowering yield-scaled climate impacts in flooded rice systems.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eSite characteristics and experimental design\u003c/b\u003e The field experiment was conducted from July to November 2021 in Khon Kaen, Thailand (UTM: 48Q 265026E, 1825361N), which is located in a tropical savanna climate. During the experimental period, the average daily temperature was 29\u0026deg;C, and the cumulative rainfall was 645 mm (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The studied soil was classified as Aquic Haplustalfs [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], with a loam texture comprising 500, 340, and 160 g kg\u003csup\u003e-1\u003c/sup\u003e of sand, silt, and clay, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The initial soil bulk density was 1.5 and 1.7 g cm\u003csup\u003e-3\u003c/sup\u003e at the 0\u0026ndash;20 and 20\u0026ndash;30 cm depths, respectively. The saturated hydraulic conductivity (Ksat) was 1.1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e cm s\u003csup\u003e-1\u003c/sup\u003e (9.3 cm day\u003csup\u003e-1\u003c/sup\u003e) at 0\u0026ndash;20 cm depth, and 1.3\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e cm s\u003csup\u003e-1\u003c/sup\u003e (1.2 cm day\u003csup\u003e-1\u003c/sup\u003e) at the 20\u0026ndash;60 cm depth. The initial soil pH (H\u003csub\u003e2\u003c/sub\u003eO) was 6.3, with a TOC of 4.1 g kg\u003csup\u003e-1\u003c/sup\u003e, total N of 0.44 g kg\u003csup\u003e-1\u003c/sup\u003e, CEC of 11 cmol kg\u003csup\u003e-1\u003c/sup\u003e, exchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N of 4.5 mg kg\u003csup\u003e-1\u003c/sup\u003e, exchangeable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N of 2.0 mg kg\u003csup\u003e-1\u003c/sup\u003e, mineral N of 6.5 mg kg\u003csup\u003e-1\u003c/sup\u003e, and organic N of 434 mg kg\u003csup\u003e-1\u003c/sup\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe experiment followed a randomized complete block design with four treatments and three replications (plot size: 5 m \u0026times; 5 m). The treatments were as follows: (1) control (no fertilizer or organic application), (2) chemical fertilizer (CF), (3) rice straw combined with CF (RS\u0026thinsp;+\u0026thinsp;CF), and (4) rice straw-derived biochar combined with CF (BC\u0026thinsp;+\u0026thinsp;CF). RS was incorporated at a rate of 10 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (dry weight), following field-return estimates [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], whereas BC was applied at 3 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (dry weight). Both amendments were manually incorporated into topsoil 0\u0026ndash;15 cm long via a hand hoe and incubated under field-moist conditions for 28 days before rice transplantation.\u003c/p\u003e \u003cp\u003eCF application was targeted to achieve a yield of 6.25 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for RD6 rice (\u003cem\u003eOryza sativa\u003c/em\u003e L.), following the recommendations of [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The chemical fertilizer supplied N, P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e, and K\u003csub\u003e2\u003c/sub\u003eO at rates of 188, 38, and 132 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively, sourced from urea, diammonium phosphate, and muriate potash at rates of 376, 83, and 220 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively. Half of the N and the full doses of P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e and K\u003csub\u003e2\u003c/sub\u003eO were applied at 7 days DAT, while the remaining N was applied at the early panicle initiation stage (42 DAT). The total N inputs were 188, 252, and 203 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for CF, RS\u0026thinsp;+\u0026thinsp;CF, and BC\u0026thinsp;+\u0026thinsp;CF, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIrrigation was supplied via pumps from deep wells. The plots were submerged for 10 days before transplanting. RD6 rice seedlings (28 days old) were transplanted at 20 cm \u0026times; 20 cm spacing (one seedling per hill). Continuous flooding (~\u0026thinsp;5 cm depth) was maintained throughout the growing season, with drainage occurring 7 days before harvest. Weed, pest, and disease management adhered to the standard Thai Department of Agriculture guidelines.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMaterial preparation and characterization\u003c/b\u003e RS was collected from the cultivated experimental field, air-dried, and cut into ~\u0026thinsp;10 cm pieces. BC was produced from air-dried RS via a 200 L traditional drum kiln under oxygen-limited conditions at ~\u0026thinsp;350\u0026deg;C for 2 h, which is consistent with farmer-operated production in Thailand [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The applied rate of 3 t ha\u003csup\u003e-1\u003c/sup\u003e corresponded to that obtained from pyrolyzing 10 t ha\u003csup\u003e-1\u003c/sup\u003e rice straw.\u003c/p\u003e \u003cp\u003eBoth the RS and BC samples were oven-dried (60\u0026deg;C), ground via a hammer mill and analyzed. The pH was measured in a 1:5 material-to-deionized water (DI water) suspension after 1.5 hours of shaking (HANNA HI8424) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The CEC was determined using 1 M ammonium acetate (pH 7.0) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The total N and TOC were measured via dry combustion (CN analyzer; Multi N/C 2100s, Analytik Jena, Germany), and the C/N ratio was calculated as TOC/total N. Compared with RS, BC presented a higher pH (8.9), TOC content (469 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), C/N ratio (94), and CEC (36 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), but a lower total N content (5.0 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSoil sampling and analysis\u003c/b\u003e Initial disturbed and undisturbed soil samples were collected at depths of 0\u0026ndash;20 and 20\u0026ndash;60 cm. Soil samples (0\u0026ndash;20 cm) were collected during the growing season at 1 DAT (seedling), 56 DAT (maximum tillering), 105 DAT (panicle initiation), and 119 DAT (harvest). Five subsamples per plot (1 m \u0026times; 1 m area) were composited, divided into field-moist subsamples stored at -4\u0026deg;C for mineral N, and air-dried subsamples were ground and sieved (\u0026lt;\u0026thinsp;2 mm) for chemical analyses.\u003c/p\u003e \u003cp\u003eThe physical properties of the initial soil samples were determined. The particle-size distribution was measured via the pipette method [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Bulk density and Ksat (0\u0026ndash;20 and 20\u0026ndash;60 cm) were measured using soil cores [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], with Ksat determined via the falling-head method [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The initial soil pH was measured in a 1:5 soil:DI water mixture. During the season, the field soil pH and Eh at 0\u0026ndash;20 cm were monitored via a portable meter (HANNA HI8424). Soil TOC and total N contents were analyzed via dry combustion (Multi N/C 2100s, Analytik Jena, Germany).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eExchangeable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N were extracted with 2 M KCl and 0.5 M K\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, respectively. NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N was determined colorimetrically via the salicylate‒sodium hypochlorite method [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N was measured via the salicylic‒sodium hydroxide method [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], via a visible spectrophotometer (SP-UV300, PerkinElmer Inc., Waltham, MA, USA) at 650 and 410 nm, respectively. Mineral N was calculated as NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N\u0026thinsp;+\u0026thinsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N, and organic N was calculated as total N\u0026thinsp;\u0026minus;\u0026thinsp;mineral N.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling and analyses of the soil solution and leachate\u003c/b\u003e The soil solution (0\u0026ndash;20 cm) and leachate (20\u0026ndash;60 cm) were collected via suction lysimeters installed at the center of each 1 m \u0026times; 1 m subplot. Samples were drawn with a 100 mL syringe between 08:00 and 10:00, twice weekly throughout the season, and daily for 7 days following fertilizer application. The samples were stored at 4\u0026deg;C until NH₄⁺-N and NO₃⁻-N analyses were performed via the methods described above.\u003c/p\u003e \u003cp\u003eThe cumulative NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N leaching losses were calculated by multiplying the measured N concentrations by the corresponding daily leachate volume and summing over time. The daily leachate volume was estimated from depth-specific Ksat (9.3 cm day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 0\u0026ndash;20 cm; 1.2 cm day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 20\u0026ndash;60 cm) and converted to volumetric flux per hectare by multiplying by 1 ha area, yielding 9.3\u0026times;10\u003csup\u003e5\u003c/sup\u003e and 1.2\u0026times;10\u003csup\u003e5\u003c/sup\u003e L ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for 0\u0026ndash;20 and 20\u0026ndash;60 cm, respectively, assuming vertical, unit-gradient flow. These fluxes were multiplied by the measured NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N concentrations to derive daily loads and cumulative losses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasurements of soil NH\u003c/b\u003e \u003csub\u003e \u003cb\u003e3\u003c/b\u003e \u003c/sub\u003e \u003cb\u003evolatilization and N\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO emission\u003c/b\u003e Gas sampling was conducted weekly alongside leachate sampling. When sampling coincided with fertilizer application, gas collection was performed 24 h after application to minimize interference [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e volatilization was measured via an adapted closed-chamber method with an H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e trap [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. NH\u003csub\u003e3\u003c/sub\u003e was trapped twice per sampling day (08:00\u0026ndash;12:00 and 12:00\u0026ndash;16:00) [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], using 50 mL of 2 N H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e in an 80 mL glass jar placed inside a chamber (inner diameter 16 cm; height 29 cm). The trapped NH\u003csub\u003e3\u003c/sub\u003e-N was quantified via titration with 2 N NaOH:\u003c/p\u003e \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e-N (mg N) = (B\u0026thinsp;\u0026minus;\u0026thinsp;V) \u0026times; N \u0026times; 14\u003c/p\u003e \u003cp\u003ewhere \u0026ldquo;B\u0026rdquo; is the NaOH volume for the blank (mL), \u0026ldquo;V\u0026rdquo; is the NaOH volume for the sample (mL), \u0026ldquo;N\u0026rdquo; is NaOH normality, and \u0026ldquo;14\u0026rdquo; is the atomic weight of nitrogen.\u003c/p\u003e \u003cp\u003eThe NH\u003csub\u003e3\u003c/sub\u003e-N flux was calculated via a modified equation [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e-N (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) = [2 \u0026times; c(H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e) \u0026times; V(H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e) \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e \u0026times; M(NH\u003csub\u003e3\u003c/sub\u003e) \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e] / [4 \u0026times; 24 / (π\u0026thinsp;\u0026times;\u0026thinsp;R\u003csup\u003e2\u003c/sup\u003e \u0026times; 10,000)]\u003c/p\u003e \u003cp\u003ewhere \u0026ldquo;c(H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e)\u0026rdquo; is the acid concentration (mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), \u0026ldquo;V(H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e)\u0026rdquo; is the titrated acid volume (mL), \u0026ldquo;M(NH\u003csub\u003e3\u003c/sub\u003e)\u0026rdquo; is the molar mass of NH\u003csub\u003e3\u003c/sub\u003e (g mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), \u0026ldquo;R\u0026rdquo; is the chamber radius (m), \u0026ldquo;4\u0026rdquo; is the trapping duration per event, and \u0026ldquo;24\u0026rdquo; is used to standardize the flux on a daily basis.\u003c/p\u003e \u003cp\u003eThe cumulative NH\u003csub\u003e3\u003c/sub\u003e-N volatilization (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was obtained by summing the daily fluxes over the monitoring period.\u003c/p\u003e \u003cp\u003eN\u003csub\u003e2\u003c/sub\u003eO emissions were measured via a closed-chamber method between 08:00 and 11:00. Chambers (60 cm \u0026times; 60 cm \u0026times; 80 cm) were placed on fixed frames, and gas samples were collected at 0, 10, 20, and 30 min via a 10 mL syringe and then transferred to 5 mL evacuated vials. The chamber air temperature and water level were recorded during sampling. N\u003csub\u003e2\u003c/sub\u003eO concentrations were analyzed via gas chromatography (Agilent 7890B, Agilent Technologies, USA) equipped with an electron capture detector (ECD) at 300\u0026deg;C and a HaySep Q packed column, with helium as the carrier gas at 20 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. N\u003csub\u003e2\u003c/sub\u003eO fluxes were calculated from the slope of the linear regression of concentration versus time, and cumulative emissions were calculated by summing daily fluxes. The cumulative N\u003csub\u003e2\u003c/sub\u003eO was converted to N\u003csub\u003e2\u003c/sub\u003eO-N via the molecular ratio of N in N\u003csub\u003e2\u003c/sub\u003eO and expressed as a percentage of the total N input to estimate N loss via N\u003csub\u003e2\u003c/sub\u003eO emissions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasurements of rice yield and agronomic efficiency\u003c/b\u003e At harvest, aboveground biomass was determined by manually harvesting rice from a 1 m \u0026times; 1 m area at the plot center (25 marked hills). The plants were separated into straw, white grains, and husks, and oven-dried at 70\u0026deg;C to a constant weight.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe agronomic efficiency of applied N (NAE; kg kg\u003csup\u003e-1\u003c/sup\u003e) was calculated following Fageria and Barbosa [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003eNAE = (G\u003csub\u003ef\u003c/sub\u003e \u0026minus; G\u003csub\u003ec\u003c/sub\u003e)/N\u003csub\u003et\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ewhere \u0026ldquo;G\u003csub\u003ef\u003c/sub\u003e\u0026rdquo; is the grain yield in fertilized plots (kg ha\u003csup\u003e-1\u003c/sup\u003e), \u0026ldquo;G\u003csub\u003ec\u003c/sub\u003e\u0026rdquo; is the grain yield in the unfertilized control (kg ha\u003csup\u003e-1\u003c/sup\u003e), and \u0026ldquo;N\u003csub\u003et\u003c/sub\u003e\u0026rdquo; is the total applied N (kg ha\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNitrogen gas-related global warming potential and greenhouse gas intensity\u003c/b\u003e The nitrogen gas-related global warming potential (GWP\u003csub\u003eN\u003c/sub\u003e) was calculated in kg CO\u003csub\u003e2\u003c/sub\u003e eq ha\u003csup\u003e-1\u003c/sup\u003e [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] via the following equation:\u003c/p\u003e \n\u003ch3\u003eGWP = 273 × (T + (T × 0.01)) × (44/28)\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ewhere \u0026ldquo;273\u0026rdquo; is the GWP factor for N\u003csub\u003e2\u003c/sub\u003eO over a 100-year horizon, \u0026ldquo;T\u003csub\u003eN2O\u003c/sub\u003e\u0026rdquo; is cumulative N\u003csub\u003e2\u003c/sub\u003eO emissions (kg N ha\u003csup\u003e-1\u003c/sup\u003e), \u0026ldquo;T\u003csub\u003eNH3\u003c/sub\u003e\u0026rdquo; is cumulative NH\u003csub\u003e3\u003c/sub\u003e volatilization (kg N ha\u003csup\u003e-1\u003c/sup\u003e), \u0026ldquo;0.01\u0026rdquo; is assumed to be 1% of emitted NH\u003csub\u003e3\u003c/sub\u003e deposited to land for subsequent conversion to N\u003csub\u003e2\u003c/sub\u003eO [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], and \u0026ldquo;44/28\u0026rdquo; is the ratio of the molecular weights of N\u003csub\u003e2\u003c/sub\u003eO to N.\u003c/p\u003e \u003cp\u003eThe greenhouse gas intensity (GHGI, kg CO\u003csub\u003e2\u003c/sub\u003e eq t\u003csup\u003e-1\u003c/sup\u003e) was calculated according to the methods of Zhao et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGHGI = GWP/Y\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ewhere \u0026ldquo;Y\u0026rdquo; is the sum of white grains and husks (t ha\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical analysis\u003c/b\u003e Statistical analyses were performed via Statistix 10 and IBM SPSS Statistics (version 28). Treatment effects were tested by analysis of variance, and mean comparisons were conducted via the least significant difference (LSD) test at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Pearson correlation was used to assess the relationships among soil N losses, soil properties, and rice yield components across treatments. The relationship between the GHGI and grain yield was evaluated via regression analysis at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003cb\u003eEthics statement\u003c/b\u003e This study does not include human or animal subjects. The plant collection and use procedures were in accordance with all the relevant guidelines.\u003c/p\u003e\u003ch2\u003e \u003cb\u003eAdditional Information\u003c/b\u003e \u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding Declaration\u003c/h2\u003e \u003cp\u003eThis research was supported by the Fundamental Fund of Khon Kaen University (Grant Number: 49019) and the Thesis Support Scholarship from the Graduate School, Khon Kaen University (Grant Number: 641T217).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.S. (Somboon): data curation, formal analysis, investigation, conceptualization, visualization, writing \u0026ndash; original draft, writing \u0026ndash; review and editing; B.R. (Rossopa): methodology, writing \u0026ndash; review and editing; S.Y. (Yodda): writing \u0026ndash; review and editing; P.L. (Lawongsa): data curation, conceptualization, methodology, resources, validation, writing \u0026ndash; review and editing; A.C. (Chidthaisong): methodology, writing \u0026ndash; review and editing; T-S.S. (Sukitprapanon): data curation, conceptualization, visualization, methodology, resources, validation, supervision, project administration, funding acquisition, writing \u0026ndash; review and editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eThe authors would like to acknowledge the staff from the Department of Soil Science and Environment for their support and the Integrated Soil and Organic Matter Management Research Group, Khon Kaen University for working on this field experiment.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request (T-S.S., [email protected]).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChivenge, P., Sharma, S., Bunquin, M. A. \u0026amp; Hellin, J. 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Total Environ.\u003c/em\u003e \u003cb\u003e904\u003c/b\u003e, 166279. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2023.166279\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2023.166279\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Agricultural wastes, Nitrogen losses, Rice production, Greenhouse gas emissions, Climate change","lastPublishedDoi":"10.21203/rs.3.rs-8607079/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8607079/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBalancing nitrogen (N) productivity with environmental sustainability is critical in flooded rice systems, where N losses by leaching and gaseous emissions are substantial. This study conducted a system-level comparison of four treatments in a continuously flooded tropical paddy field: an unfertilized control, chemical fertilizer (CF), rice straw with CF (RS\u0026thinsp;+\u0026thinsp;CF), and rice straw-derived biochar with CF (BC\u0026thinsp;+\u0026thinsp;CF). We quantified major N-loss pathways, agronomic efficiency of applied N (NAE), and N gas-related global warming potential (GWP\u003csub\u003eN\u003c/sub\u003e). The results indicate that BC\u0026thinsp;+\u0026thinsp;CF minimized total N loss to 33% of total N input, compared to 38% under RS\u0026thinsp;+\u0026thinsp;CF and 43% under CF. Compared with CF, BC\u0026thinsp;+\u0026thinsp;CF significantly reduced NH\u003csub\u003e3\u003c/sub\u003e volatilization and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching, driven by increased soil cation exchange capacity and mineral N retention. While RS\u0026thinsp;+\u0026thinsp;CF yielded the lowest N\u003csub\u003e2\u003c/sub\u003eO emissions, it presented greater NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N leaching than BC\u0026thinsp;+\u0026thinsp;CF. Both organic amendments reduced GWP\u003csub\u003eN\u003c/sub\u003e and greenhouse gas intensity (GHGI) compared to CF; however, BC\u0026thinsp;+\u0026thinsp;CF resulted in superior grain yield and NAE. Conversely, the unfertilized control produced the highest GHGI due to low productivity. These findings demonstrate that integrating rice straw-derived biochar with chemical fertilizer represents an optimal system-level strategy for mitigating N losses, enhancing agronomic efficiency, and lowering climate impacts of flooded rice production.\u003c/p\u003e","manuscriptTitle":"Rice straw-derived biochar reduces nitrogen losses and greenhouse gas emissions while improving rice productivity and agronomic efficiency in a tropical paddy soil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-17 13:22:40","doi":"10.21203/rs.3.rs-8607079/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-04T13:34:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-03T08:24:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282599274913454949113211335874567110822","date":"2026-05-03T06:27:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-15T05:52:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259122787778543285347305347299491533755","date":"2026-02-02T13:58:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282599274913454949113211335874567110822","date":"2026-01-28T16:26:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-28T10:52:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-23T05:29:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-23T05:27:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-01-15T05:11:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8ac1e69d-b3e1-4081-a4e1-a9487fc4906d","owner":[],"postedDate":"February 17th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-04T13:34:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-03T08:24:40+00:00","index":32,"fulltext":""},{"type":"reviewerAgreed","content":"282599274913454949113211335874567110822","date":"2026-05-03T06:27:14+00:00","index":31,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":62556434,"name":"Earth and environmental sciences/Climate sciences"},{"id":62556435,"name":"Biological sciences/Ecology"},{"id":62556436,"name":"Earth and environmental sciences/Ecology"},{"id":62556437,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-05-04T13:39:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-17 13:22:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8607079","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8607079","identity":"rs-8607079","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}