Shuanglei Song , Zhipeng Sha , Kaihong Zhang , Xuejun Liu
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引用次数: 0
Abstract
Enhanced-efficiency fertilisers are recognised methods of mitigating reactive nitrogen (Nr) release. Although previous data-driven studies have assessed the reductions in Nr emissions and increases in crop production and N utilisation from using urease inhibitors (UIs) and nitrification inhibitors (NIs), they have not determined whether dual inhibitors (DIs) outperform single inhibitors or identified the factors driving their efficacy. Therefore, we adopted a method that combines meta-analysis with a machine-learning model to determine the efficacy of DIs for emissions control and agronomic efficiency, clarify any differences with UIs or NIs, and identify the primary drivers. The results show that compared to urea, DI amendment significantly reduced NH3 volatilisation and N2O, NO, and CH4 emissions by 47.0 %, 36.9 %, 65.3 %, and 51.0 %, respectively, while increasing crop yield, N uptake, and N use efficiency by 5.6 %, 7.2 %, and 29.3 %, respectively. Moreover, its efficacy was mainly determined by soil pH and soil organic carbon. Compared with the UI alone, the DI significantly increased NH3 volatilisation, yield, and N uptake by 19.8 %, 2.0 % and 2.2 %, respectively, and decreased N2O and NO emissions by 23.9 % and 46.0 %, respectively. Compared with the NI alone, the DI significantly decreased NH3 volatilisation by 46.5 % and increased N2O emission, crop yield, NUE, and N uptake by 9.2 %, 2.6 %, 8.0 %, and 5.2 %, respectively. These results underscore the ability of DI-based fertiliser to mitigate environmental risks and enhance agronomic efficiency and revealed suitable application practices for avoiding the trade-offs associated with a single inhibitor. This study provides suggestions for the selection of mitigation options and promotes sustainable N management in the crop production sector.
期刊介绍:
Agriculture, Ecosystems and Environment publishes scientific articles dealing with the interface between agroecosystems and the natural environment, specifically how agriculture influences the environment and how changes in that environment impact agroecosystems. Preference is given to papers from experimental and observational research at the field, system or landscape level, from studies that enhance our understanding of processes using data-based biophysical modelling, and papers that bridge scientific disciplines and integrate knowledge. All papers should be placed in an international or wide comparative context.