Hyperspectral Spectroscopy Analysis

Research- objects	Year	Model	Output
Analysis of (hyper-) spectral signatures with double Weibull functions, NIRS analysis, ongoing projects with various objectives concerning agricultural research, plant breeding, trait recognition and precision farming, and other topic as meat quality survey or medical diagnostics.	2010 - 2017	An universal model for the analysis of hyperspectral reflectance signals with respect to qualitative and quantitative traits. Uses the complete technical sensor information of the device (no reduction to some few domains) for the analysis. Applicable in high-throughput phenotyping systems, plant breeding, precision farming, early results of field, greenhouse and lab experiments with respect to quantitative phenology, breeding traits, pathogen diagnosis, abiotic stresses and many more by the use of multivariate methods. Technique is not limited to green leaves, but also applicable for plant organs of different colour (i.e. tomato), classification and determination of common objects in remote sensing and medicine. Method is competitive with PLS (Partial least squares) and Support Vector Machines (SVM) procedures. Also suitable in NIRS analysis techniques to estimate substances and concentrations on a quantitative level.	Patent.pdf (in German only) Analyse hyperspektraler Signaturen mit doppelten Weibull-Funktionen, PFG Photogrammetrie, Fernerkundung, Geoinformation Jahrgang 2011 Heft 5 (2011), p. 349 - 359. DOI (proposed citation)