Optimized water management in intelligent cultivation systems mitigates greenhouse gas emissions and energy demand while ensuring rice yield sustainability - Wenan Weng; Ping Liao; Xiuli Li; Minmin Sun; Yufei Ling; Zhipeng Xing; Jiwei Qu; Juan Chen; Haiyan Wei; Hui Gao; Hongcheng Zhang (Agricultural Water Management)
Achieving simultaneous improvements in rice yield, reductions in greenhouse gas (GHG) emissions, and enhanced energy efficiency represents a critical challenge for sustainable food production. Currently, Eastern China is actively promoting intelligent rice cultivation technologies, including intelligent precision dry direct-seeding (IDS), unmanned aerial vehicle sowing (UAS), and intelligent mechanical transplanting (IMT). Comprehensive assessments of yield, GHG emissions, and energy consumption under these patterns are currently lacking, thereby limiting technological optimization and dissemination decisions. Here, we carried out field trials in 2022–2023 to systematically evaluate these cultivation patterns. The results showed that IMT achieved the highest mean yield (11.1 t ha-¹), exceeding IDS (10.5 t ha-¹) and UAS (10.2 t ha-¹) due to greater sink capacity. IDS reduced global warming potential (GWP) and greenhouse gas intensity (GHGI) by 53.7 % and 50.3 %, respectively, compared to IMT, and by 22.0 % and 23.2 % compared to UAS. This reduction stemmed primarily from lower methane (CH4) emissions, despite higher nitrous oxide (N₂O) emissions, which were largely associated with changes in microbial gene abundance (e.g., lower mcrA/pmoA ratio, higher AOA-amoA and narG). IDS also demonstrated excellent energy efficiency, boosted energy use efficiency by 9.7 % and 3.4 % over UAS and IMT, respectively, with total energy input of 43,171.7, 46,113.5, and 46,311.4 MJ ha−1. Our results suggest that IDS can achieve acceptable yields in rural areas with significant reductions in greenhouse gas emissions and energy consumption.