ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Crop and Product Physiology
Interactive effects of irrigation and nitrogen management on greenhouse gas emissions and resource efficiency in alfalfa production
Provisionally accepted- College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, China
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Mitigating agricultural greenhouse gas (GHG) emissions while maintaining forage productivity is a key challenge under global carbon-neutrality goals. To evaluate the environmental and agronomic trade-offs of irrigation and nitrogen management, a field experiment was conducted in an arid region of Northwest China. Twelve irrigation–nitrogen treatment combinations were applied to alfalfa (Medicago sativa L.) to quantify N₂O, CO₂, and CH₄ fluxes, global warming potential (GWP), and resource-use efficiencies. Results showed that soil water-filled pore space and available nitrogen strongly regulated N₂O emissions, with peaks occurring within one week after irrigation or fertilization. Excessive water and nitrogen inputs significantly increased GHG emissions and reduced irrigation water productivity (IWP) and partial factor productivity of nitrogen (PFPN). Conversely, the high-water, moderate-nitrogen regime (300 mm irrigation + 120 kg N ha⁻¹) achieved a balanced outcome—sustaining high yield while reducing cumulative N₂O emissions by 29.5–93%, total GWP (Life Cycle Assessment, LCA-based) by 24.1%, and greenhouse gas emission intensity (GHGI) by 29.0% relative to conventional high-input management (reference treatment W2N3: 300 mm irrigation + 180 kg N ha⁻¹). These preliminary findings suggest a site-and year-specific water–nitrogen synergy zone that improved yield–GHG trade-offs under the semi-arid conditions of this study; they should be interpreted with caution and validated across additional years.
Keywords: crop yield, GHG emissions, Global warming potential, Medicago sativa L, Sustainable management, Water-nitrogen interactions
Received: 10 Nov 2025; Accepted: 19 Dec 2025.
Copyright: © 2025 Qu, Li, Song, Pang, Luan, Sun and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaobo Luan
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