Effect of long term fertilization management strategies on methane emissions and rice yield

Utilizing machine learning to optimize agricultural inputs for improved rice production benefits

Lower efficiency of agricultural inputs in the four conventional rice planting methods limits productivity and environmental benefits in Southwest China. Thus, we developed a machine-learning-based decision-making system for achieving optimal comprehensive benefits during rice production. Based on conventional benefits for achieving optimal benefits, implemented strategies in these planting methods: reducing N fertilizer by 16% while increasing seed inputs by 9% in mechanical transplanting (MT) method improved yield and environmental benefits; reducing N fertilizer and seed inputs by 10-12% in mechanical direct seeding (MD) method decreased environmental impacts; increasing N-K fertilizers and seed inputs by 15-33% in manual transplanting (MAT) method improved its comprehensive benefits by 7-14%; applying N-P-K fertilizer ratio of 2:1:2 in manual direct seeding (MAD) method enhanced yield. Our study provides strategies for improving benefits in these planting methods, with MT method being more beneficial for optimizing comprehensive benefits, especially in yield and environmental impacts, in Southwest China.

Comprehensive assessment of straw returning with organic fertilizer on paddy ecosystems: A study based on greenhouse gas emissions, C/N sequestration, and risk health

High greenhouse gas emissions and soil deterioration are caused by the overuse of chemical fertilizers. To improve soil quality and crop productivity, it is necessary to utilize fewer chemical fertilizers to achieve sustainable agriculture. Organic substitution is a scientific fertilization strategy that will benefit future agricultural productivity development, little is known about how it affects the heavy metal content and trace gas emissions in rice grains. A field experiment using straw return to the field (SRF), organic fertilizer application (OFA), and their combination (SRF/OFA) fertilization strategies. The results demonstrated that SRF, OFA, and SRF/OFA increased the yield by 19.40%, 22.39%, and 28.36% than the natural growth control group (NG). The OFA has the highest STN stock and SRF/OFA has the highest STN sequestration rate, while SRF achieved the highest SOC stock and sequestration rate. The OFA reduced CO2, CH4, and N2O emissions by 17.73%, 71.87%, and 86.06%, resulting in a minimum global warming potential and greenhouse gas intensity yield among these strategies. Cumulative seasonal CO2 and CH4 emissions were negatively correlated with soil paddy soil C/N and C/P (P < 0.05). Moreover, Cu, Cd, and Pb contents in grain were reduced by 66.18%-70.31%, 35.45%-40.91%, and 76.62%-77.92%, respectively. The health risk evaluation revealed that all metals had a target hazard quotient of <1, except for NG. The hazard index (0.42-0.53), which measures the additive effects of contaminants, exceeded the threshold. The implementation of the organic alternative strategy can reduce the trend of increasing surface pollution, slow down the excessive utilization intensity of agricultural resources, and encourage the development of a greener, more sustainable agricultural way.

Soil pH Determines Nitrogen Effects on Methane Emissions From Rice Paddies

Rice paddies account for approximately 9% of human-induced methane (CH4) emissions. Nitrogen (N) fertilization affects CH4 emissions from paddy soils through several mechanisms, leading to conflicting results in field experiments. The primary drivers of these N-related effects remain unclear and the contribution of N fertilization to CH4 emissions from the rice paddies has not yet been quantified for global area. This uncertainty contributes to significant challenges in projecting global CH4 emissions and hinders the development of effective local mitigation strategies. Here, we show through a meta-analysis and experiments that the impact of N fertilization on CH4 emissions from rice paddies can be largely predicted by soil pH. Specifically, N fertilization stimulates CH4 emissions most strongly in acidic soils by accelerating organic matter decomposition and increasing the activities of methanogens. Accounting for the interactions between soil pH and N fertilization, we estimate that N fertilization has raised current area-scaled and yield-scaled CH4 emissions across the total global paddy area by 52% and 8.2%, respectively. Our results emphasize the importance of alleviating soil acidification and sound N management practices to mitigate global warming.

Towards climate neutrality in the Spanish N-fertilizer sector: A study based on radiative forcing

Agricultural systems in the 21st Century face the double challenge of achieving climate neutrality while maintaining food security. Synthetic fertilizers rich in nitrogen (N-fertilizers) boost agricultural production at the expense of increasing climate impact. Public policies, such as the Farm-to-Fork (F2F) Strategy, aim to reduce the extensive use of N-fertilizers with the ultimate goal of achieving a climate neutral European Union (EU). However, the strong link between N-fertilizers and GHG emissions (i.e., CO2, CH4 and, especially, N2O) highlights the need to better understand the climate impact of this sector. The present study conducts a climate impact analysis of Spanish N-fertilizer sector for two periods: (i) from 1960 to 2020 using real data and (ii) from 2021 to 2100 considering five forecasted scenarios. The scenarios range from business-as-usual practices to a full accomplishment of the goals pursued by the EU's F2F strategy. The system's climate stability and neutrality are analysed for the different scenarios based on radiative forcing (RF) metrics. Additionally, the study evaluates the short-term impact of the EU decarbonization goals on the climate impact of the Spanish N-fertilizer sector. The results of the study illustrate that the long-lasting climate impact of N2O and CO2 emissions compromise the capacity of N-fertilizer sector to achieve climate stability and approach climate neutrality. However, the decarbonisation of transport and N-fertilizer production activities is an important driver to substantially reduce the life cycle CH4 and CO2 emissions in the Spanish N-fertilizer sector. The results also highlight that more severe reductions on N-cycles than those suggested by the EU's F2F are required, especially to reduce the long-lasting N2O emissions in the N-fertilizer sector. Overall, the study concludes that using RF-based metrics increases robustness and transparency of climate assessments, which is necessary for a higher integration of climate science within public policymaking.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables

Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.

A low-methane rice with high-yield potential realized via optimized carbon partitioning

Global rice cultivation significantly contributes to anthropogenic methane emissions. The methane emissions are caused by methane-producing microorganisms (methanogenic archaea) that are favoured by the anoxic conditions of paddy soils and small carbon molecules released from rice roots. However, different rice cultivars are associated with differences in methane emission rates suggesting that there is a considerable natural variation in this trait. Starting from the hypothesis that sugar allocation within a plant is an important factor influencing both yields and methane emissions, the aim of this study was to produce high-yielding rice lines associated with low methane emissions. In this study, the offspring (here termed progeny lines) of crosses between a newly characterized low-methane rice variety, Heijing 5, and three high-yielding elite varieties, Xiushui, Huayu and Jiahua, were selected for combined low-methane and high-yield properties. Analyses of total organic carbon and carbohydrates showed that the progeny lines stored more carbon in above-ground tissues than the maternal elite varieties. Also, metabolomic analysis of rhizospheric soil surrounding the progeny lines showed reduced levels of glucose and other carbohydrates. The carbon allocation, from roots to shoots, was further supported by a transcriptome analysis using massively parallel sequencing of mRNAs that demonstrated elevated expression of the sugar transporters SUT-C and SWEET in the progeny lines as compared to the parental varieties. Furthermore, measurement of methane emissions from plants, grown in greenhouse as well as outdoor rice paddies, showed a reduction in methane emissions by approximately 70 % in the progeny lines compared to the maternal elite varieties. Taken together, we report here on three independent low-methane-emission rice lines with high yield potential. We also provide a first molecular characterisation of the progeny lines that can serve as a foundation for further studies of candidate genes involved in sugar allocation and reduced methane emissions from rice cultivation.

Long-term non-phosphorus application increased paddy methane emission by promoting organic acid and methanogen abundance in Tai Lake region, China

Rice paddy is a significant source of atmospheric methane (CH₄), a major global warming source. CH₄ emission from paddy fields is greatly influenced by phosphorus (P) management, especially the long-term non-P application on CH₄ emission is largely unexplored. In the present study, long-term non-P application (NK) and P application (NPK) treatments of two paddy fields in Suzhou (from 1980) and Yixing (from 2009), Tai Lake region was done. The effect of P application on CH₄ emissions and related microorganisms (i.e., methanogens and methanotrophs) from 2019 to 2020 was analyzed. Results revealed that long-term NK treatment didn't alter the seasonal trend of CH₄ flux, but significantly promoted CH₄ emissions at the tillering stage. The non-P application for >12 years caused the cumulative CH₄ emissions of NK treatment in the whole rice season significantly increased by 41.9-221 % in two fields compared to NPK treatment in 2019 and 2020. NK treatment increased the abundance and diversity of methanogens, while reducing the abundance and diversity of methanotrophs. Community composition of soil pmoA gene differed in two experiment sites. Correlation analysis revealed that the CH₄ emission was significant and positively related to soil mcrA gene and C/P while negatively related to soil pmoA gene and P. Structure equation model analysis show the low soil available P content was the dominant driving factor for the high CH₄ emission under long-term non-P application through its direct impact on soil mcrA and pmoA genes. The increased soil organic acid content was another driver which was positively related to soil mcrA gene and negatively to soil pmoA gene. Our findings demonstrate the important role of soil P in regulating CH₄ emissions from paddy fields in the Tai Lake region, China, and suitable P application is necessary for ensuring the yield while reducing CH₄ emission.

Fertilization and Global Warming Impact on Paddy CH4 Emissions

INTRODUCTION

This study aimed to assess the influence of experimental warming and fertilization on rice yield and paddy methane emissions.

METHODS

A free-air temperature increase system was used for the experimental warming treatment (ET), while the control treatment used ambient temperature (AC). Each treatment contained two fertilization strategies, (i) normal fertilization with N, P and K fertilizers (CN) and (ii) without N fertilizer input (CK).

RESULTS

The yield was remarkably dictated by fertilization (p < 0.01), but not warming. Its value with CN treatment increased by 76.24% compared to CK. Also, the interactive effect of warming and fertilization on CH₄ emissions was insignificant. The seasonal emissions from warming increased by 36.93% compared to AC, while the values under CN treatment increased by 79.92% compared to CK. Accordingly, the ET-CN treatment obtained the highest CH₄ emissions (178.08 kg ha^-1), notably higher than the other treatments. Also, the results showed that soil fertility is the main driver affecting CH₄ emissions rather than soil microorganisms.

CONCLUSIONS

Fertilization aggravates the increasing effect of warming on paddy methane emissions. It is a daunting task to optimize fertilization to ensure yield and reduce methane emissions amid global warming.

Changes in Soil Chemical Properties Due to Long-Term Compost Fertilization Regulate Methane Turnover Related Gene Abundances in Rice Paddy

Maintaining rice yield, soil function, and fertility are essential components of long-term compost fertilization. However, paddy fields are major sources of anthropogenic methane emissions. The aim of the study is to evaluate the changes in soil chemical properties and their concurrent impact on the abundance of methanogenesis (mcrA) and methane oxidation (pmoA) related genes among compost (Com), NPK+Compost (NPKCom), and unfertilized (NF) fallow paddy fields under long-term compost fertilization. Results showed that compost and NPK+Compost fertilization altered the soil chemical properties of paddy fields with a significant increase in the functional gene abundance potentially associated with Methanobacteriaceae for mcrA (1.23 × 106 to 3.84 × 106 copy number g−1 dry soil) and methane oxidizing bacteria such as Methylomonas and Methylobacter for pmoA (1.65 × 106 to 4.3 × 106 copy number g−1 dry soil). Ordination plots visualized these changes, where treatments clustered distinctly indicating that Com and NPKCom treatments were characterized by paddy soils with elevated OM, TN, K and P content and higher abundances of methanogenesis and methane oxidation related genes. The study showed that long-term compost fertilization resulted in paddy fields with high nutrient content and high gene abundance, attributed to methanogens and methane oxidizing bacteria that responded well with compost fertilization. These results indicated the potential of these fallow paddy fields for methane emission and methane oxidation and that they are ‘primed’, potentially influencing subsequent paddy field responses to long-term compost application.

Effect of fertilization on nitrogen losses through surface runoffs in Chinese farmlands: A meta-analysis

Surface runoff is the main cause of farmland nitrogen (N) losses in plain areas, which adversely affect water quality. The impact of fertilization on N runoff loss often varies. A meta-analysis was performed using 245 observations from 31 studies in China, to estimate the response of N loss in both paddy and upland fields subjected to different fertilization strategies, and investigate the link between N runoffs, soil properties, as well as precipitation in the planting season. The results showed that compared to the control (without fertilization), N losses subjected to fertilization increased from 3.31 kg/ha to 10.03 kg/ha and from 3.00 kg/ha to 11.24 kg/ha in paddy and upland fields respectively. Importantly, paddy N loss was significantly correlated with fertilizer type and N application rate (predictors); in upland fields N application rate and seasonal precipitation were the main driving factors. For the N application rate, N loss increased with increase in rates for both paddies and upland fields. Moreover, the N loss from upland fields increased with the precipitation during planting season. Between the three fertilizers used in paddies, the increase in loss of CRF (controlled release fertilizer) or OF (organic fertilizer) was lower than that of CF (inorganic chemical fertilizer) with the lowest value in CRF. Subset analysis showed that the effect of CRF and OF in paddies was not affected by the predictors, revealing the steadily controlling property of CRF and OF in paddies. Also, all the predictors had an insignificant impact to N loss risk in paddies during the high application rate. Overall, the results confirm the importance of N dosage in N runoff loss from farmland. Fertilizer type is a key consideration for N loss control in paddies, while the seasonal precipitation should not be ignored in upland fields.