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Currently, there is almost no comprehensive mapping of agricultural cropland because of the lack of fast and affordable mapping methods for important soil properties. Arable land of some hectares in size show a broad range of different nutrient compositions. Because of this heterogeneity wrong fertilization can occur and can cause environmental pollution or lead to smaller harvests and this is simply a waste of resources. The goal of I4S (intelligence for soil) is to develop an integrated system for site-specific soil fertility management. The I4S consortium consists of 10 different institutions, which are testing various sensors for their suitability for the requested applications. Besides the preparation of reference materials, the main task of the Federal Institute for Materials Research and Testing (BAM) in this project is the method development for online-XRF (x-ray fluorescence spectroscopy) and for online-LIBS (laser-induced breakdown spectroscopy) sensor systems. Both methods have the advantage that there is no or only little sample preparation necessary. Each method provides a fast and simultaneous multi-element analysis. Both measurement setups can be utilized for a mobile application which is fundamental for reaching the goals of I4S. Having finally a set of some reference materials, further work will focus on the online-XRF and online-LIBS methods in order to obtain useable calibration models. The calibration models will then be tested using stationary and moving samples.
The preservation and the improvement of the fertility of soils by agricultural management measures requires carefully planned decisions which are based on a detailed capture of the soil qualities and a detailed understanding of soil processes. Profit losses can be caused on the one hand by conventional, surface-uniform managements (e.g., fertilization) by too low management intensity on one part of the surface, while other parts of the field receive too high doses and it thereby comes to environmental impacts or to waste of resources.
X-ray fluorescence analysis (XRF) and the Laser-induced Breakdown Spectroscopy (LIBS) are possible technologies which permit online analyses of the chemical composition.
New developments in spectroscopic techniques for process control are, in general, driven by shortcomings of existing technology, for example, when sensitivity, selectivity, robustness, and so forth do not meet the demands. The perfect process analytical method would be based on a robust and easy to handle customized technique operating in real time, come without any need for calibration, that is, be an absolute method, have a professional support, and be compliant to increasing regulatory requirements. However, there are at least trends toward such an all-in-one device suitable for every purpose.
Small, low-field NMR systems equipped with permanent magnet technology have been developed and allow for quantitative analysis as on-line instruments in a production environment. Quantitative high-resolution on-line NMR spectroscopy contributes to process understanding in pilot plant and research environments.
Laser spectroscopy is a promising field in process analysis owing to its sensitivity and selectivity. Laser-induced breakdown spectroscopy LIBS is a promising field for direct in situ analysis and remote sensing. Applications of quantum-cascade lasers for process analytical applications are a promising technique. Techniques such as cavity ring-down spectroscopy (CRDS), tunable diode laser absorption spectroscopy (TDLAS), and photothermal techniques are briefly introduced.
Recent developments of new detectors have improved X-ray fluorescence analysis (XRF) for qualitative and quantitative on-line evaluation of the elementary composition of liquid or solid samples, regardless of whether compact or bulk material.
The chapter also introduces miscellaneous techniques such as ion mobility spectroscopy (IMS), microwave and dielectric spectroscopy, terahertz spectroscopy, ultrasonic acoustic spectroscopy, and other methods.
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