Nitrogen and organic matter managements improve rice yield and affect greenhouse gas emissions in China’s rice-wheat system

IF 5.6 1区 农林科学 Q1 AGRONOMY
Li Zhang , Feng Zhang , Kaiping Zhang , Yue Wang , Evgenios Agathokleous , Chao Fang , Zhike Zhang , Haiyan Wei , Zhongyang Huo
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引用次数: 0

Abstract

Context

Mineral nitrogen (N) management and organic matter management in the paddy fields directly affect yield and soil greenhouse gas (GHG) emissions in the rice-wheat rotation system of China. However, comprehensive research on the combined impacts of these two practices remains insufficient, and there is a lack of quantitative analyses on a large regional scale as well as identification of the main drivers.

Objective

This study aimed to elucidate the impact of mineral N management and organic matter management on rice yield and global warming potential (GWP) and their spatial distribution patterns, and to investigate influential factors.

Methods

We combined machine learning algorithms based on meta-analysis to assess the effect of mineral N management (synthetic N fertilizer, slow-/controlled- release fertilizer) and organic matter management (organic fertilizer, biochar amendment, and straw return) on rice yield and GHG in the rice-wheat system by compiling 163 peer-reviewed journal articles and high-resolution multi-source databases in China.

Results

Mineral N management significantly increased rice yield (412 %) and N2O (162.3 %), and reduced GHG emissions intensity (GHGI; 20.1 %). Organic matter management increased CH4, GWP, and GHGI by 74.4 %, 60.8 %, and 55.1 %, respectively. Machine learning (random forest (RF), support vector machine, multiple layer perceptron, and gradient boosting machine) suggested that RF was the optimal method for predicting rice yield and GHG (R2 = 0.43–0.90). The spatial distribution indicated that mineral N management boosted rice yield and N2O while reducing GHGI, especially in the Middle-lower Yangtze River (MLY) region, by 37.6 %, 277 %, and 25.2 %, respectively. Structural equation modeling and RF analysis revealed that field management practices and edaphic factors had major contributions to rice yield, while climatic factors were positively with CH4 and N2O emissions.

Implications

Our findings provide insights into the importance of inorganic and organic managements to ensure food security and environmental sustainability, thereby contributing to the promotion of sustainable rice production.
氮素和有机质管理提高了中国水稻-小麦系统的产量,并影响了温室气体排放
稻田矿质氮和有机质管理直接影响中国稻麦轮作系统的产量和土壤温室气体排放。然而,对这两种做法的综合影响的综合研究仍然不足,缺乏在大区域尺度上的定量分析和主要驱动因素的识别。目的研究矿质氮管理和有机质管理对水稻产量和全球变暖潜势(GWP)的影响及其空间分布规律,并探讨影响因素。方法采用基于meta分析的机器学习算法,通过编辑163篇同行评审期刊论文和高分辨率多源数据库,评估矿质氮管理(合成氮肥、缓释/控释氮肥)和有机质管理(有机肥、生物炭改良剂和秸秆还田)对水稻-小麦系统产量和温室气体的影响。结果矿质氮管理显著提高了水稻产量(412 %)和N2O(162.3 %),降低了温室气体排放强度(GHGI);20.1 %)。有机质管理使CH4、GWP和GHGI分别增加了74.4 %、60.8 %和55.1% %。机器学习(随机森林、支持向量机、多层感知机和梯度增强机)表明,随机森林是预测水稻产量和温室气体的最佳方法(R2 = 0.43 ~ 0.90)。空间分布表明,矿质氮管理提高了水稻产量和N2O,同时降低了GHGI,特别是在长江中下游地区,分别提高了37.6% %、277 %和25.2% %。结构方程模型和RF分析表明,田间管理方式和土壤因子对水稻产量的影响最大,而气候因子对CH4和N2O排放的影响正相关。研究结果揭示了无机和有机管理对确保粮食安全和环境可持续性的重要性,从而有助于促进可持续水稻生产。
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来源期刊
Field Crops Research
Field Crops Research 农林科学-农艺学
CiteScore
9.60
自引率
12.10%
发文量
307
审稿时长
46 days
期刊介绍: Field Crops Research is an international journal publishing scientific articles on: √ experimental and modelling research at field, farm and landscape levels on temperate and tropical crops and cropping systems, with a focus on crop ecology and physiology, agronomy, and plant genetics and breeding.
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