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Temporal and spatial variation in soil nitrate acquisition by maize as influenced by nitrate depth distribution

机译:硝酸盐深度分布的玉米土壤硝酸盐采集的时间和空间变化

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Residual soil nitrate-N (RSN) is a principal determinant used across the northcentral region of the USA to adjust fertilizer N application rates to maize (Zea mays L.). Preplant soil sampling is usually performed to depths as deep as 120 cm to assess RSN. It is important to understand the temporal and spatial (depth) variation in RSN acquisition by maize to improve N fertilization strategies especially given the investment in soil analysis required for variable rate technologies (VRT). Research wasinitiated in 1994 to assess the effects of concentration and depth distribution of RSN as will as soil, crop and N fertilization management impacts on RSN use efficiency. Bromide was used as an RSN tracer and depth injected (at 20, 60 and 80 cm ) in contiguous microplots within a broad range of RSN depth and concentration distributions. Covariance analysis of 72 RSN profiles during a 2-year period resulted in our ability to account for 97% of the variation in grain yield and N uptake by including a description of RSN profile distribution in our analysis of variance. Variation in the depth of maize RSN acquisition was significantly influenced by year and attributed to differences in plant N demand (annual variation) as well as N fertilization and croprotation. These results imply that the use of technologies that assess real-time plant N demand will improve variable rate technologies and most likely improve our ability to increase N use efficiency. Delaying the time of N fertilization also improvesthe acquisition of deep RSN.
机译:残留的土壤硝酸盐-N(RSN)是在美国的北部中央地区使用的主要决定因素,以调整肥料对玉米的施肥率(ZEA Mays L.)。预膜土壤采样通常进行深度为120厘米的深度,以评估RSN。重要的是要了解玉米RSN采集中的时间和空间(深度)变化,以提高施肥策略,特别是考虑到可变率技术(VRT)所需的土壤分析的投资。 1994年的研究缺乏,评估RSN的浓度和深度分布的影响,因为土壤,作物和N施肥管理对RSN使用效率的影响。在宽范围的RSN深度和浓度分布中,使用溴化物作为RSN示踪剂和深度注入(在20,60和80cm)中,在宽范围的RSN深度和浓度分布。在2年期间,72 RSN概况的协方差分析导致我们能够通过在我们对方差分析中,包括对RSN型材分布的描述来占粮食产量和N吸收的97%。玉米RSN采集深度的变化受到一年的显着影响,并归因于植物N需求(年度变异)以及N施肥和裂隙的差异。这些结果意味着使用评估实时工厂N需求的技术将改善可变速率技术,最有可能提高我们提高N使用效率的能力。延迟N施肥的时间也增加了收购深度RSN。

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