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首页> 外文期刊>Data in Brief >Nitrous oxide fluxes and soil nitrogen contents over eight years in four cropping systems designed to meet both environmental and production goals: A French field nitrogen data set
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Nitrous oxide fluxes and soil nitrogen contents over eight years in four cropping systems designed to meet both environmental and production goals: A French field nitrogen data set

机译:氧化二氮杂气和土壤氮含量超过八年的四种种植系统,旨在满足环境和生产目标:法国田间氮数据集

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With the development of agroecosystem approaches, new cropping systems have to be designed to deliver multiple ecosystem services. In this context, we assessed four innovative cropping systems, designed to reach multiple environmental and production goals, in a long-term field experiment (2009–2020) at Grignon (France, N 48.84°, E 1.95°). A wide range of measurements were made, for nutrient cycles and organic matter in particular, for an analysis of interactions occurring during the emissions of greenhouse gases. We focus here on nitrogen (N) data collected over eight years (2009–2016). The data include: nitrous oxide fluxes (N2O), soil N contents (NO3?and NH4+), aboveground plant N content and biomass at maturity, yield, agricultural practices including N spreading, and climate. The four systems differ in terms of tillage practices, N inputs, and species, which is likely to affect soil N. Field data were collected and N2O fluxes were calculated. These original new cropping systems are innovating, resulting in new combinations of agricultural practices. The data obtained could be used to improve models for parameterization and validation, and to increase the predictive accuracy of models of N losses in original conditions.
机译:随着农业系统方法的发展,必须设计新的裁剪系统来提供多个生态系统服务。在这方面,我们评估了四种创新的种植系统,旨在在格里尼翁(法国,N 48.84°,E 1.95°)的长期野外实验(2009-2020)中达到多种环境和生产目标。特别是对营养循环和有机物质进行了广泛的测量,用于分析温室气体排放期间发生的相互作用。我们专注于八年以上的氮气(n)数据(2009 - 2016年)。数据包括:氧化亚氮助熔剂(N2O),土壤N含量(NO 3?和NH4 +),成熟,产量,农业实践的地上植物N含量和生物质,包括N蔓延和气候。这四种系统在耕作实践,n个输入和物种方面不同,该输入和物种可能会影响土壤n。收集现场数据,计算N2O助熔剂。这些原创新型裁剪系统正在创新,导致新的农业实践组合。所获得的数据可用于改进参数化和验证的模型,并提高原始条件下的N损失模型的预测精度。

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