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- Feature selection (1)
- Gold nanoparticles (1)
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- Precision agriculture (1)
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A facile approach for the synthesis of monodisperse gold nanoparticles with radii in the range of 7 to 20 nm is presented. Starting from monodisperse seeds with radii of 7 nm, produced in the first step, the addition of a defined amount of additional precursor material permits distinct size regulation and the realization of predicted nanoparticle sizes. These information were derived from ex- and in situ investigations by comprehensive small angle X-ray scattering (SAXS), X-ray absorption near edge structure (XANES) and UV-Vis data to obtain information on the physicochemical mechanisms. The obtained mechanisms can be transferred to other seeded growth processes. Compared to similar approaches, the presented synthesis route circumvents the use of different reducing or stabilizing agents. The size of resulting nanoparticles can be varied over a large size range presented for the first time without a measurable change in the shape, polydispersity or surface chemistry. Thus, the resulting nanoparticles are ideal candidates for size dependence investigations.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer.
The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements