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首页> 外文期刊>Australian Journal of Soil Research >Potentially mineralisable nitrogen: relationship to crop production and spatial mapping using infrared reflectance spectroscopy
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Potentially mineralisable nitrogen: relationship to crop production and spatial mapping using infrared reflectance spectroscopy

机译：潜在可矿化的氮：与作物产量和使用红外反射光谱法进行空间制图的关系

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Accurate and rapid prediction of the spatial structure of soil nitrogen (N) supply would have both economic and environmental benefits with respect to improved inorganic N fertiliser management. Yet traditional biochemical indices of soil N supply have not been widely incorporated into fertiliser decision support systems or environmental risk monitoring programs. Here we illustrate that in a low-input, semi-arid environment, potentially mineralisable N (PMN, as determined by anaerobic incubation) explained 21% of wheat grain yield (P=0.003), whereas there was no significant relationship between wheat grain yield and inorganic N fertiliser application. We also assessed the spatial pattern of PMN using a structured grid soil sampling strategy over a 10-ha area (180 separate samples, 0-0.1m). PMN in each soil sample was determined by standard biochemical analysis and also predicted using a fourier transform infrared spectrometer (FTIR). Findings illustrate that FTIR was able to significantly predict (P<0.001) PMN values in soil and has the advantage of enabling high sample throughput and rapid (within minutes) soil analysis. Given the relatively low cost of FTIR machines and ease of use, such an approach has practical application in situations where analysis cost or access to equipped laboratories has hindered the measurement and monitoring of soil N supply within paddocks and across regions.
机译：准确，快速地预测土壤氮素供应的空间结构，对于改善无机氮肥的管理具有经济和环境效益。然而，土壤氮供应的传统生化指标尚未广泛纳入肥料决策支持系统或环境风险监测计划中。在此我们说明，在低投入，半干旱的环境中，潜在可矿化氮（PMN，通过厌氧培养确定）解释了小麦籽粒产量的21％（P = 0.003），而小麦籽粒产量之间没有显着关系和无机氮肥的应用。我们还使用结构化的网格土壤采样策略在10公顷的区域（180个单独的样本，0-0.1m）上评估了PMN的空间格局。通过标准生化分析确定每种土壤样品中的PMN，并使用傅立叶变换红外光谱仪（FTIR）进行预测。结果表明，FTIR能够显着预测土壤中的PMN值（P <0.001），并且具有实现高样品通量和快速（几分钟内）土壤分析的优势。鉴于FTIR机器的成本相对较低且易于使用，因此这种方法在分析成本或无法访问配备完善的实验室阻碍了围场内和跨区域土壤氮供应的测量和监控的情况下具有实际应用价值。

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