Abstract: Nearly half of the world cereal production comes from soils low or marginal in plant available zinc, leading to unsustainable and poor quality grain production. Therefore, the effects of nitrogen (N) rate and application time on zinc (Zn) and iron (Fe) concentration in wheat grain were investigated. Wheat (Triticum aestivum var. Krabat) was grown in a growth chamber with 8 and 16 h of day and night periods, respectively. The N rates were 29, 43, and 57 mg N kg(-1) soil, equivalent to 80, 120, and 160 kg N ha(-1). Zinc and Fe were applied at 10 mg kg(-1) growth media. In one of the N treatments, additional Zn and Fe through foliar spray (6 mg of Zn or Fe in 10 ml water / pot) was applied. Micro-analytical localization of Zn and Fe within grain was performed using scanning macro-X-ray fluorescence (MA-XRF) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). The following data were obtained: grain and straw yield pot 1, 1000 grains weight, number of grains pot 1, whole grain protein content, concentration of Zn and Fe in the grains. Grain yield increased from 80 to 120 kg N ha(-1) rates only and decreased at 160 kg N ha(-1) g. Relatively higher protein content and Zn and Fe concentration in the grain were recorded with the split N application of 160 kg N ha(-1). Soil and foliar supply of Zn and Fe (Zn + Fes+f), with a single application of 120 kg N ha(-1) N at sowing, increased the concentration of Zn by 46% and of Fe by 35%, as compared to their growth media application only. Line scans of freshly cut areas of sliced grains showed co-localization of Zn and Fe within germ, crease and aleurone. We thus conclude that split application of N at 160 kg ha(-1) at sowing and stem elongation, in combination with soil and foliar application of Zn and Fe, can be a good agricultural practice to enhance protein content and the Zn and Fe concentration in grain.

Abstract: Scanning electron microscopy coupled with microanalysis (SEM-EDX) is an important analytical tool for the morphological and chemical characterization of different types of materials. In many applications, SEM-EDX elemental maps are usually used and processed as images, thus flattening and reducing the spectroscopic information contained in EDX hyperspectral data cubes. The exploitation of the full hyperspectral dataset could be indeed very useful for the study of complex matrices like soil. In order to maximize the information attainable by SEM-EDX data cubes analysis, the software package “Datamuncher Gamma” was implemented and applied to study soil aggregates. By using this approach, different phases (silicates, aluminosilicates, Ca-carbonates, Ca-phosphates, organic matter, iron oxides) inside soil aggregates were successfully identified and segmented. The advantages of this method over the common ROI imaging approach are presented. Finally, this method was used to compare different aggregates in a Cr-polluted soil and understand their possible pedological history. The present method can be used for the analysis of every type of SEM-EDX data cubes, allowing its application to different types of samples and fields of study.