Rice Yield Response Research Articles

Reduction of uncertainties in rice yield response to elevated CO2 by experiment-model integration: A case study in East China

Accurate prediction of future rice yield needs the precise estimations of rice yield response to climate change factors, of which the most important one is the increasing carbon dioxide (CO2) concentrations. Estimates of CO2 fertilization effect (CFE) on rice, however, still had large uncertainties. Therefore, using the rice planting areas in East China as the study area, we firstly compared the rice yields and CFE predicted by four state-of-the-art crop models, and found that the CFE predicted by these models had significant differences. We then quantified the CFE on rice yield using the field-controlled experiment conducted at Danyang site at Jiangsu province. Using CFE measurements from a field experiment as benchmark, we have developed an experiment–model integration approach aiming to reduce this variation. This study thus highlights the large CFE uncertainties of current crop models and provides us with a method to reduce this uncertainty, which is beneficial for the accurate prediction of future global rice yield in the context of climate change.

Response of rice yield, grain quality to chilling at grain filling stages.

This study aims to quantify the impacts of chilling at the grain filling stage on rice yield and grain quality. A factorial experiment with four levels of temperature and duration of chilling treatments at the early and late grain filling stages was conducted in 2017, 2018 and 2019. Per 10 °C·day increase in the accumulated cooling degree day at the early and late grain filling stages, the rice emergence-maturity duration was delayed by 0.8% (0.6%) and rice yield decreased by 2.2% (1.7%). Chilling at the early grain filling stage decreased the rice heading rate, while chilling at the late grain filling stage increased rice amylose but decreased protein content. For chilling treatment at the early grain filling stage, rice yield and grain quality were mainly correlated with seed-setting rate, whereas for chilling treatment at the late grain filling stage the rice yield and grain quality were mainly correlated with 1000-grain weight. This study improved the understanding of how chilling at the grain filling stages affects rice phenology, yield and grain quality, providing a theoretical basis for maintaining rice yield while ensuring grain quality. The results could be used to guide the rice-growing community in combating chilling at grain filling stages. © 2024 Society of Chemical Industry.

Responses of Rice Photosynthesis and Yield to Elevated CO2 Concentrations: A Quantitative Analysis via Chlorophyll Fluorescence Technology

Responses of Rice Photosynthesis and Yield to Elevated CO2 Concentrations: A Quantitative Analysis via Chlorophyll Fluorescence Technology

A Bayesian approach to assessing uncertainty in the effect of fertilization strategies on paddy rice yield via multiple on-farm experiments

ABSTRACT The surge in global agricultural input prices, particularly for nitrogen (N) fertilizers, has presented challenges for farmers facing stagnant crop prices and rising production costs. This study explored a system designed to sustain or enhance farmers’ income while reducing production costs, with a specific focus on implementing practices that involve cultivating crops with lower rates of fertilizer than conventional rates, particularly in smaller land settings, through on-farm experimentation (OFE). OFE was conducted over three years across 11 fields in Gifu, Japan, utilizing a strip trial design to investigate the effect of fertilizer input rates on rice yield. To collect yield data, unmanned aerial vehicle (UAV)-mounted multispectral cameras were deployed. A Gaussian process model was used to address the impact of fertilizer input rates on yield while accounting for spatial yield variation. The study further assessed the number of field trials achieving positive profits at certain probability levels by integrating outcomes from multiple OFEs. The results highlighted little rice yield response to fertilizer input in most of the fields, while several fields showed significant positive yield responses. Notably, the use of lower fertilizer input rates in certain fields proved to be more profitable whereas higher fertilizer input rates were less profitable in most fields. The results further emphasized the economic viability of lower rates, especially when fertilizer prices are high, thus contributing valuable insights for sustainable and profitable rice production in Japanese cultivation.

Optimal rainfall threshold for monsoon rice production in India varies across space and time

Climate change affects Indian agriculture, which depends heavily on the spatiotemporal distribution of monsoon rainfall. Despite the nonlinear relationship between crop yield and rainfall, little is known about the optimal rainfall threshold, particularly for monsoon rice. Here, we investigate the responses of rice yield to monsoon rainfall in India by analyzing historical rice production statistics and climate data from 1990 to 2017. Results show that excessive and deficit rainfall reduces rice yield by 33.7% and 19%, respectively. The overall optimal rainfall threshold nationwide is 1621 ± 34 mm beyond which rice yield declines by 6.4 kg per hectare per 100 mm of rainfall, while the identifiable thresholds vary spatially across 14 states. The temporal variations in rice yield are influenced by rainfall anomalies featured by El Niño-Southern Oscillation events.

Simulating the Responses of Rice Yield and Nitrogen Fates to the Ground Cover Rice Production System under Different Precipitation Year Types

The ground cover rice production system (GCRPS) has considerable potential for securing rice production in hilly mountainous areas. However, its impact on yields and N fates remains uncertain under varying rainfall conditions. A two-year field experiment (2021–2022) was carried out in Ziyang, Sichuan Province, located in the hilly mountains of southwest China. The experiment included two cultivation methods: conventional flooding paddy (Paddy, W1) and GCRPS (W2). These methods were combined with three N management practices: N1, no-N fertilizer; N2, 135 kg urea N per hm2 as a base fertilizer; and N3, 135 kg urea N per hm2 with split application for W1 and 67.5 kg N per hm2 of urea and chicken manure separately for W2. The WHCNS (soil water heat carbon nitrogen simulator) model was calibrated and validated to simulate ponding water depth, soil water storage, soil mineral N content, leaf area index, aboveground dry matter, crop N uptake, and rice yield. Subsequently, this model was used to simulate the responses of rice yield and N fates to GCRPS under different precipitation year types using meteorological data from 1980 to 2018. The results indicated that the WHCNS model performed well in simulating crop growth and N fates for both Paddy and GCRPS. Compared with Paddy, GCRPS reduced N leaching (35.1%–54.9%), ammonia volatilization (0.7%–13.6%), N runoff (71.1%–83.5%), denitrification (3.8%–6.7%), and total N loss (33.8%–56.9%) for all precipitation year types. However, GCRPS reduced crop N uptake and yield during wet years, while increasing crop N uptake and yield during dry and normal years. Fertilizer application reduced the stability and sustainability of rice yield in wet years, but increased the stability and sustainability of rice yield in dry and normal years. In conclusion, GCRPS is more suitable for normal and dry years in the study region with increasing rice yield and reducing N loss.

Evolution of Red Soil Fertility and Response of Rice Yield Under Long-Term Fertilization

Evolution of Red Soil Fertility and Response of Rice Yield Under Long-Term Fertilization

Optimal Soil, Climate, and Management Factors for Maximizing Crop Yield and Soil Nutrients in a Rice–Oilseed Rotation System with Straw Return

Straw return (SR) has been widely recommended as a conservation agricultural practice in China. However, the effects of SR on crop yield and soil properties are inconsistent across studies of rice–oilseed rape cropping systems in China. This study aimed to investigate the effects of SR on crop yield and soil nutrient content in a rice–oilseed rotation system, and to understand the mechanism of straw return on the difference in yield increases between rice and oilseed rape. Additionally, suitable climate factors, soil properties, and agricultural practices were identified to achieve maximum increases in yield and soil nutrients in a rice–oilseed rotation under SR. This paper is based on a meta-analysis of 1322 observations from 83 peer-reviewed studies to evaluate the effects of climate, initial soil conditions, and agricultural management practices on rice and oilseed rape yields and soil nutrients under SR. The results showed that the responses of oilseed rape and rice yield remained positive, with 12.37% and 6.54% increases, and were significantly higher under SR than the control (no SR). Moreover, SR significantly increased the contents of several soil nutrients (soil organic carbon (SOC), total nutrients, available nutrients) and microbial biomass carbon (MBC) and nitrogen (MBN). Interestingly, the increase in crop yields was attributed to the increase in SOC, total nitrogen, and available potassium. Additionally, the increase in yields was mainly affected by climate factors, initial soil properties, and agronomic practices. For example, both mean annual temperature (MAT) and mean annual precipitation (MAP) had a positive correlation with crop yield increases under SR (p < 0.01). Initial soil conditions such as low SOC and total nitrogen content were more suitable for increased rice yield under SR, while the opposite was true for increased oilseed rape yield. Without fertilization, the SR did not significantly improve crop yield and soil nutrients, while it was more pronounced with N fertilization at 150–180 kg hm−2. The positive effect of SR on crop yields is more evident with plowing tillage, whereas the SR caused the highest increase in soil nutrients with the no-tillage condition. These findings have important implications for further improving crop yield, SOC, and soil nutrients in the Chinese rice–oilseed cropping system through straw return.

Identifying Spatial Determinants of Rice Yields in Main Producing Areas of China Using Geospatial Machine Learning

Rice yield is essential to global food security under increasingly frequent and severe climate change events. Spatial analysis of rice yields becomes more critical for regional action to ensure yields and reduce climate impacts. However, the understanding of the spatially varied geographical, climate, soil, and environmental factors of rice yields needs to be improved, leading to potentially biased local rice yield prediction and responses to climate change. This study develops a spatial machine learning-based approach that integrates machine learning and spatial stratified heterogeneity models to identify the determinants and spatial interactions of rice yields in the main rice-producing areas of China, the world’s largest rice-producing nation. A series of satellite remote sensing-derived variables are collected to characterize varied geographical, climate, soil, and environmental conditions and explain the spatial disparities of rice yields. The first step is to explore the spatial clustering patterns of the rice yield distributions using spatially global and local autocorrelation models. Next, a Geographically Optimal Zones-based Heterogeneity (GOZH) model, which integrates spatial stratified heterogeneity models and machine learning, is employed to explore the power of determinants (PD) of individual spatial variables in influencing the spatial disparities of rice yields. Third, geographically optimal zones are identified with the machine learning-derived optimal spatial overlay of multiple geographical variables. Finally, the overall PD of various variables affecting rice yield distributions is calculated using the multiple variables-determined geographically optimal zones and the GOZH model. The comparison between the developed spatial machine learning-based approach and previous related models demonstrates that the GOZH model is an effective and robust approach for identifying the spatial determinants and their spatial interactions with rice yields. The identified spatial determinants and their interactions are essential for enhancing regional agricultural management practices and optimizing resource allocation within diverse main rice-producing regions. The comprehensive understanding of the spatial determinants and heterogeneity of rice yields of this study has a broad impact on agricultural strategies and food security.

Rice growth and yield responses to saline water irrigation are related to Na+/K+ratio in plants.

Rice growth and yield response to salinity can be influenced by the duration and the timing of salt stress. The present study tested the effects of saline water irrigation from vegetative growth to maturity on rice growth and yield and ion concentrations in the straw and root and related them to changes in soil salinity and soil solute potential. The treatments consisted of five levels of saline water irrigation (electrical conductivity ~0.25 (control), 4, 6, 8, and 10 dS m-1) with two rice cultivars (BRRI dhan67 and BRRI dhan99) grown in pots in a rain shelter. Grain weight per pot, dry straw weight, and root weight were significantly reduced with increasing water salinity, but BRRI dhan99 was less affected. With prolonged saline water irrigation, salt concentration increased in the soil and lowered the soil solute potential. Increased saline water induced higher concentrations of Na+ in the straw (527-1200 mmol kg-1 at 4-10 dS m-1) relative to the root. By contrast, higher Cl- concentrations accumulated in the root than in the straw. The decrease of K+ in the straw and root for increasing salinity was inconsistent, but the Na+/K+ ratio sharply increased in the straw with higher water salinity. The increased Na+/K+ explained most grain weight loss due to higher salinity (R2 = 0.93) followed by Na+ (R2 = 0.87) and Cl-1 (R2 = 0.53). We conclude that the prolonged saline water irrigation has a cumulative effect on root zone salinity and solute potential that depresses grain yield in rice by increasing the Na+/K+ ratio in plants.

Heterogenous response of rice yield to climate factors: a Just-Pope stochastic production function and quantile regression analysis

Heterogenous response of rice yield to climate factors: a Just-Pope stochastic production function and quantile regression analysis

Effect of Arbuscular Mycorrhizal Fungi on Lowland Rice Growth and Yield (Oryza sativa L.) under Different Farming Practices

In this study, a field experiment was conducted to evaluate the growth and yield responses of Sri Lankan lowland rice (Oryza sativa L.) with the application of beneficial Arbuscular mycorrhizal fungi (AMF) inoculum and intercropping with highly mycorrhizal-dependent vetiver grass (Chrysopogon zizanioides L.) under two different soil nutrient management systems (NMSs): conventional/chemical (CNMS) and organic (ONMS). The experiment was designed as a split plot with three blocks. Each CNMS and ONMS experiment included an untreated control (T0) and three treatments—AMF inoculation (T1), vetiver intercropping (T2), and the combination of AMF and vetiver (T3). According to the results, the colonization of rice roots with AMF was not affected significantly by the treatments and ranged from 0–15.8%. The effect was very low or absent in the early stage and then higher in the later stages of the rice plant. Furthermore, plant growth was not significantly different between the two NMSs, although grain yield was significantly higher (p < 0.05) in ONMS than for the respective controls (T0), with the order T1 (0.45 kg/m2) > T2 (0.42 kg/m2) > T3 (0.41 kg/m2) in CNMS and T2 (0.44 kg/m2) > T1 (0.41 kg/m2) > T3 (0.40 kg/m2), thus suggesting the utilization of AMF and vetiver in a lowland rice farming system is beneficial.

Enhancing physiological metrics, yield, zinc bioavailability, and economic viability of Basmati rice through nano zinc fertilization and summer green manuring in semi-arid South Asian ecosystem.

During the summer and rainy seasons (April-October) of 2020 and 2021, two consecutive field experiments were conducted at the research farm of the ICAR-Indian Agricultural Research Institute, New Delhi, India. In this study, we examined the effects of summer green manuring crops (GM) and a variety of zinc fertilizers (ZnF) on Basmati rice (Oryza sativa L.) growth, physiological development, yield response, zinc nutrition and economic returns. A combination of GM residues and nano zinc fertilization helped significantly enhancing Basmati rice's growth and its physiological development. Following the incorporation of Sesbania aculeata (Sesbania), successive Basmati rice physiological parameters were significantly improved, as well as grain, straw, biological yields, harvest index and economic returns. The highest Zn content of 15.1 mg kg -1 and the lowest of 11.8 mg kg -1 in milled rice grain were recorded in Sesbania green manuring (G2) and control i.e., in the fallow (G1), respectively. Coating onto urea with 0.2% nano zinc oxide (NZnCU) was observed to be more effective than other zinc sources in terms of growth parameters, yield attributes, zinc nutrition, grain and straw yields for succeeding Basmati rice crop; however, the effects were comparable to those of bulk zinc oxide-coated urea (BZnCU) of 1%. The highest Zn content of 15.1 mg kg -1 was recorded with the application of 1% BZnCU and the lowest of 11.96 mg kg -1 with the soil application of 5 kg Zn ha -1 through bulk ZnO in the milled rice grain. Application of 1% BZnCU led to a 26.25% increase in Zn content of milled rice grain compared to soil application of 5 kg Zn ha -1 through bulk ZnO. As a result, the combination of inclusion of Sesbania aculeata (Sesbania) residue and 0.2% NZnCU was identified as the most effective treatment, for Basmati rice growth and physiological development. A combination of nano Zn fertilization in conjunction with the incorporation of green manure can be advocated for better growth, physiological performance, zinc dense grains, and higher profitability of Basmati rice for farmers and consumers.

Nutrient use efficiency has decreased in southwest China since 2009 with increasing risk of nutrient excess

The optimal application of nutrients, such as nitrogen and phosphorus, to the soil is crucial for achieving high crop yields with minimal environmental impact. However, the effect of spatio-temporal changes in soil nutrient supply on crop yield is poorly understood in China. Here, we present a framework that combines environmental data, fertilizer field experiments, and machine learning to estimate the rice yield responses to different nutrient conditions and overall farmland nutrient sustainability in southwest China from 2009 to 2019. The results show that the fertilizer input has contributed to the long-term increase in rice yield over the past ten years. The fertilizer use has increased rice yield by 2.3–2.4 tons per hectare per year. However, the nutrient use efficiency decreased, with the fertilizer contribution ratio declining from 29.3% in 2009 to 27.5% in 2019. Further, 19% of the rice-growing farmlands are at risk of nutrient excess, and 36% are at risk of nutrient degradation. Controlling nitrogen and phosphorus input is key to nutrient regulation, and our approach may guide the sustainable use of nutrient resources on farmlands.

Rice yield response to climate variability diverges strongly among climate zones across China and is sensitive to trait variation

Rice yield response to climate variability diverges strongly among climate zones across China and is sensitive to trait variation

Integrated rice-aquatic animals culture systems promote the sustainable development of agriculture by improving soil fertility and reducing greenhouse gas emissions

Integrated rice–aquatic animals culture systems (RACSs) are of interest in sustainability research because they have been found to host diverse species and there is potential for positive synergistic effects between the plant (rice) and aquatic animal culture. However, their effect on soil fertility, rice productivity, and greenhouse gas (GHG) emissions, as well as the associations among them, remain unclear. A meta-analysis was conducted to systematically evaluate the sustainability of RACSs from the perspective of “rice productivity–GHG emissions–soil fertility” and their associations and to clarify how environmental factors and fertilizer-management practices affect responses of rice yield and GHG emissions to RACSs. We conducted a meta-analysis of 1807 paired observations collected from 78 published papers covering four countries that compared soil fertility, rice yield, and GHG emissions in a conventional rice monoculture system (CRMS) and in a RACS. Overall, the RACSs improved soil structure (soil bulk density declined by 5.8 % and total and capillary porosity increased by 6.4 % and 5.7 %, respectively), increased soil organic carbon (C, 7.9 %) and nitrogen (N, 6.6 %) storage, and reduced CH4 (9.2 %) and N2O (4.5 %) emissions; rice yield were little higher (by 2.0 %) than that of the CRMS. However, the effects varied under different RACS modes, environmental factors, and fertilizer-management practices. For instance, compared to CRMS, yields were 4.1 % higher in the rice–duck mode, 3.9 % lower in the rice–crayfish mode, and the no significantly change in the rice–fish system. The effects on GHG emissions and soil fertility were more pronounced in the rice–duck and rice–crayfish modes than in the rice–fish mode. Furthermore, paddy soils with low fertility (lower soil organic C and N) and less nutrient (nitrogen and phosphorus) input provide a higher rice yield and lower GHG emissions under RACSs. Overall, the RACSs stabilized rice productivity and reduced GHG emissions by improving the soil structure and increasing soil C and N sequestration; however, the effects varied by different RACS modes, initial soil properties, fertilizer input rate, and climate conditions. As such, environmental factors and nutrient management should be considered when designing and deciding what type of RACSs to employ. Our results also highlight the great potential of RACSs in the development of sustainable agriculture practices in the context of climate change. Future research and applications should consider the response of RACSs to climate and environmental factors and fertilizer-management practices, to achieve greater production and environmental benefits.

Grain quality and yield response of rice to application of plant growth-promoting bacteria and amino acids

To investigate the effects of foliar application of plant growth-promoting bacteria (PGPB) and amino acids (AAs) on grain yield, nutrient concentrations and protein content of rice grain, a field experiment was conducted as a split-plot in a randomized complete block design with three replications during 2019-2020. The experimental treatments included the PGPB at five levels (control, P. agglomerans strain O4 (PGPB1), P. putida strain P13 + P. agglomerans strain P5 (PGPB2), P. koreensis strain S14 + P. vancouverensis strain S19 (PGPB3), and PGPB1 + PGPB2 + PGPB3 (PGPB4) as main plots and AAs at four levels (control, methionine, lysine, and methionine + lysine) as sub-plots. The results indicated that PGPB significantly enhanced the grain yield, protein content and nutrient uptake in rice grains when compared with control plants. However, the plants treated with co-application of PGPB strains (PGPB4) showed higher yield, higher protein accumulation and greater nutrients uptake such as N, P, K and Fe compared with individual application of PGPB strains and untreated plants. Among the separate application of PGPB strains, rice plants treated with PGPB1 with capability to N-fixing had the potential for enhance yield and improve protein and nutrients accumulation. The combined foliar application of AAs had greatest impact in increasing yield and improving rice grain quality in terms of protein content and uptake of nutrients, especially N, Ca and Fe in grain. Overall, our results suggest that co-applications of PGPB strains (PGPB4) and using a mixture of two AAs (methionine + lysine) may find value as plant growth-promoting for increasing rice yield and quality.

Regional inequalities of future climate change impact on rice (Oryza sativa L.) yield in China

The implications of climate change for rice yield have significant repercussions for food security, particularly in China, where rice cultivation is diverse, involving various cropping intensities, management practices, and climate conditions across numerous regions. The regional discrepancies in the impact of climate change on rice yield in China, however, are yet to be fully understood. Using the ORYZA(v3) model and future climate data from 2025 to 2084, gathered from ten climate models and three climate change scenarios (RCP2.6, RCP4.5, and RCP8.5), we conducted an investigation into these regional discrepancies. Our findings suggest a projected average decline in rice yield ranging from 3.7 % to 16.4 % under both rainfed and fully irrigated conditions across different scenarios. Central, eastern, and northwestern China could face the most significant climate change impacts on both rainfed and irrigated rice, with yield reductions reaching 41.5 %. In contrast, low levels of climate change under the RCP2.6 scenario may benefit northeastern (2.4 %) and southern (1.0 %) regions for rainfed and irrigated rice, respectively. Fertilization effects from elevated CO2 could counterbalance climate change's negative impact, resulting in yield increases in all Chinese rice-growing regions, excluding the northwest. The primary factor influencing rice yield changes in all regions under the RCP4.5 and RCP8.5 scenarios was temperature. However, precipitation, solar radiation, and relative humidity had notable and sometimes dominant effects, especially under the RCP2.6 scenario. These results highlight the divergent, even contradictory, rice yield responses to climate change across China, underlining the need to account for regional differences in large-scale impact studies. The study's findings can inform future policy decisions regarding ensuring regional and national food security in China.

Reflectance Measurements from Aerial and Proximal Sensors Provide Similar Precision in Predicting the Rice Yield Response to Mid-Season N Applications.

Accurately detecting nitrogen (N) deficiency and determining the need for additional N fertilizer is a key challenge to achieving precise N management in many crops, including rice (Oryza sativa L.). Many remotely sensed vegetation indices (VIs) have shown promise in this regard; however, it is not well-known if VIs measured from different sensors can be used interchangeably. The objective of this study was to quantitatively test and compare the ability of VIs measured from an aerial and proximal sensor to predict the crop yield response to top-dress N fertilizer in rice. Nitrogen fertilizer response trials were established across two years (six site-years) throughout the Sacramento Valley rice-growing region of California. At panicle initiation (PI), unmanned aircraft system (UAS) Normalized Difference Red-Edge Index (NDREUAS) and GreenSeeker (GS) Normalized Difference Vegetation Index (NDVIGS) were measured and expressed as a sufficiency index (SI) (VI of N treatment divided by VI of adjacent N-enriched area). Following reflectance measurements, each plot was split into subplots with and without top-dress N fertilizer. All metrics evaluated in this study indicated that both NDREUAS and NDVIGS performed similarly with respect to predicting the rice yield response to top-dress N at PI. Utilizing SI measurements prior to top-dress N fertilizer application resulted in a 113% and 69% increase (for NDREUAS and NDVIGS, respectively) in the precision of the rice yield response differentiation compared to the effect of applying top-dress N without SI information considered. When the SI measured via NDREUAS and NDVIGS at PI was ≤0.97 and 0.96, top-dress N applications resulted in a significant (p < 0.05) increase in crop yield of 0.19 and 0.21 Mg ha-1, respectively. These results indicate that both aerial NDREUAS and proximal NDVIGS have the potential to accurately predict the rice yield response to PI top-dress N fertilizer in this system and could serve as the basis for developing a decision support tool for farmers that could potentially inform better N management and improve N use efficiency.

Responses of Rice Yield, N Uptake, NH3 and N2O Losses from Reclaimed Saline Soils to Varied N Inputs.

It is of agronomic importance to apply nitrogen (N), but it has high environmental risks in reclaimed saline soils. Therefore, we should apply N fertilizer at an appropriate rate to increase crop yield but decrease N losses. In this soil column experiment, rice yield, N uptake, and ammonia (NH3) and nitrous oxide (N2O) losses were measured in four treatments with no N application (control) and with N applications of 160, 200, and 240 kg/ha (N160, N200, and N240, respectively). The results show that grain yield, spike number, and thousand-kernel weight increased with increases in N application rate, but there was no significant difference in grain yield between N200 and N240. However, the kernels per spike increased first and then decreased with the increase in N application, of which N200 was recorded to have the highest kernels per spike value, which was 16.8 and 9.8% higher than those of N160 and N240, respectively. Total NH3 volatilization of the rice season increased with increasing N input, especially during the first and second supplementary fertilization stages. The NH4+-N concentration of overlying water was relatively lower under the N200 treatment in these two stages, and the yield-scaled NH3 volatilization and the emission factor were the lowest in N200, which were 26.2-27.8% and 4.0-21.0% lower than those of N160 and N240, respectively. Among the three N-applied treatments, N2O losses and the emission factor as well as the yield-scaled N2O emissions were the lowest under the N200 treatment, which had 34.7% and 78.9% lower N2O emissions and 57.8% and 83.5% lower emission factors than those of the N160 and N240 treatments, respectively. Moreover, the gene copies of AOA and AOB amoA, nirS, and nirK in cultivated layer soils all reached the minimum under the N200 treatment. According to the comprehensive effects of N fertilizer on rice grain yield and NH3 and N2O losses, we recommend applying 200 kg/ha to reclaimed saline soil to ensure crop yield and reduce N losses.