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Collaborative project: Using multiple sensors to optimize rating in crop production – Subproject 2
Project
Project code: 2815405810
Contract period: 01.09.2011
- 31.12.2014
Budget: 20,471 Euro
Purpose of research: Experimental development
The use of hyperspectral measurement technology in plant breeding showed following results: Accurate predictive models for the non-destructive detection of the crop parameters (a) biomass fresh, (b) biomass dry, (c) leaf area index, (d) pigment contents: chlorophyll a and b, and carotenoids; and (e) the total nitrogen content have been developed successfully, based on spectral reflectance measurements. The adoption of the models to the low-cost TriSpek system could be implemented well for pigment determination. Predicting the parameters biomass, leaf area index and the total nitrogen content showed some influence of the ambient temperatures, which produced sensor noise in the near infrared. The availability of new spectrometers with CMOS technology reduces these problems significantly. By connecting the spectral data with the digital field maps, monitoring can be dynamically performed also in a spatial context. It is possible to detect heterogeneities within breeding nurseries indirectly by identifying growth differences in the hyperspectral data and take the affected parcel into account when evaluating the breeding experiments.
Section overview
Subjects
- Agricultural Engineering Plant Production
