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

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.