Compositional analysis of plant nutrients and soil P pools

目前的模型使用成分数据约束到一个单一的，如植物和土壤分析忽视了一个事实，即组件必须在一个封闭的信息空间内相互作用。由于在一个封闭系统中，一个成分的任何变化都必然伴随着其他成分的变化，因此系统的组织模式可能会被虚假的相关性所破坏。成分分析考虑了单纯形中成分之间所有可能的相互作用。成分数据分析已成功地应用于许多科学领域，最近，许多作物品种的营养诊断和解释土壤中的磷转化。作为偏离目标组成的量度，发现马氏距离将营养不平衡的玉米植物检测为“离群者”。 另一方面，土壤，作物残留物和有机产品的磷分馏程序允许区分不稳定和非不稳定的P池。P在不稳定和非不稳定池响应于驱动变量（时间，轮作，土壤保护措施，添加P）可以模拟成分分析使用的形式主义，如扰动向量，单纯度量，和马氏距离。土壤磷缓冲能力是一个重要的土壤功能，它可以保护土壤免受可溶性磷的损失，并控制磷供应到根系，可以与单纯度量或马氏距离。Mehlich-III磷饱和比是土壤磷缓冲能力的可靠指标。Mehlich-III指数与磷的活性库和非活性库之间的关系可以支持目前无机和有机土壤的环境阈值。我们的主要目标是建立土壤-植物系统中作物养分和土壤磷的组成模型。在这个项目中，我们将把Mahalanobis概念应用于魁北克和巴西的十种作物。此外，我们还将对土壤、有机投入物和作物残体中的磷进行分级，并使用成分分析和土壤磷缓冲能力指标来分析磷组分。从长远来看，我们将根据土壤和植物的成分模式对它们进行分类，以响应驱动变量。

Present models using compositional data constrained to a simplex such as plant and soil analyses disregard the fact that components must interact within a closed information space. Since any change in one constituent must be accompanied by a change in other constituents by resonance in a closed system, system patterns of organization may be spoiled by spurious correlations. Compositional analysis takes into account all possible interactions among components within a simplex. Compositional data analysis has been successfully applied in many scientific fields and, more recently, for nutrient diagnosis of many crop species and interpreting phosphorus transformations in soils. As a measure of deviation from targeted composition, the Mahalanobis distance was found to detect nutritionally imbalanced corn plants as 'outliers'. On the other hand, the phosphorus fractionation procedures for soils, crop residues, and organic products allow distinguishing between labile and non labile P pools. The P in labile and non labile pools in response to a driving variable (time, crop rotation, soil conservation practice, added P) can be modelled by compositional analysis using formalisms such as the perturbation vector, the simplicial metric, and the Mahalanobis distance. Soil P buffering capacity that protects the soil against soluble P loss and controls the P supply to roots is an important soil function that can be related to either the simplicial metric or the Mahalanobis distance. The Mehlich-III P saturation ratio proved to be a reliable indicator of soil P buffering capacity. The relationships between Mehlich-III indexes and labile and non labile pools of P could support the present environmental thresholds for both mineral and organic soils. Our main objective is to develop compositional models for crop nutrients and soil P in soil-plant systems. In this project, we will apply the compositional-Mahalanobis concept to ten crops in Quebec and Brazil. In addition, we will fractionate the P in soils, organic inputs, and crop residues and analyze P fractions using compositional analysis as well as indexes of soil P buffering capacity. On the long run, we will classify soils and plants according to their compositional patterns in response to driving variables.