巴西中西部大豆-玉米继代作物氮利用效率的可持续性分析

Nitrogen Pub Date : 2024-03-12 DOI:10.3390/nitrogen5010016
Francisco Gilberto Erthal Risi, C. M. Hüther, C. Righi, R. C. Umburanas, T. Tezotto, D. Dourado Neto, Klaus Reichardt, Carlos Rodrigues Pereira
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摘要

氮(N)在大气中以 N2 的形式大量存在,并转化为活性形式(Nr)供植物同化。在前工业时代,大气中 N2 向 Nr 的转化与 Nr 向 N2 的再转化相平衡,但 20 世纪的人类活动通过合成肥料、生物 N2 固定和化石燃料燃烧加强了这种转化。过剩的 Nr 对生态系统和人类福祉产生了不利影响。本研究旨在评估巴西中西部马托格罗索州和南马托格罗索州大豆-玉米演替(SPSS,C)土壤-植物系统中氮的利用效率。我们估算了 SPSS,C 中的氮大流量,并确定了关键的农业环境指标。从 2008 年到 2020 年,SPSS,C 的年播种面积增加了 3.3 倍(目前为 730 万公顷)。据估计,SPSS,C 的年均人为净氮输入量、年均氮平衡量和氮损失量分别为约 204 千克 [N] ha-1、57 千克 [N] ha-1 和 30 千克 [N] ha-1,表明氮的累积和损失持续存在。在 SPSS,C 中,农艺效率和氮保持率指标的平均结果分别为 0.71 和 0.90。氮利用效率结果不高,反映了氮损失效应。尽管存在这些局限性,SPSS,C 中仍有机会制定管理策略,以减少氮损失并提高效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sustainability Analysis of Nitrogen Use Efficiency in Soybean-Corn Succession Crops of Midwest Brazil
Nitrogen (N) is abundant in the atmosphere as N2, which is converted into reactive forms (Nr) for plant assimilation. In pre-industrial times, atmospheric N2 conversion to Nr balanced Nr reconversion to N2, but 20th-century human activity intensified this conversion via synthetic fertilizers, biological N2 fixation, and fossil fuel burning. The surplus of Nr detrimentally impacts ecosystems and human well-being. This study aimed to assess the N use efficiency in the soil–plant system of the soybean-corn succession (SPSS,C) in Mato Grosso and Mato Grosso do Sul, Brazil’s midwest. We estimated N macrofluxes in SPSS,C and identified key agro-environmental indicators. Between 2008 and 2020, the yearly sowed area for the SPSS,C increased by 3.3-fold (currently 7.3 million ha). The average annual input of net anthropogenic Nr, average annual N balance, and N loss in SPSS,C was estimated to be ~204 kg [N] ha−1, 57 kg [N] ha−1, and 30 kg [N] ha−1, respectively, indicating persistent N accumulation and loss. The average results of the agronomic efficiency and N retention indicator in the SPSS,C was 0.71 and 0.90, respectively. Modest N use efficiency results reflect N loss effects. Despite these limitations, there are opportunities in SPSS,C for management strategies to reduce N loss and enhance efficiency.
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