Do you want to keep up to date? Subscribe to our newsletter. 1mail every 2months! |
 |
Cerdanyola del Vallès (Barcelona, Spain), 13th of April, 2022. The Lleida-based company Altinco, specialized in sustainable agrochemical products, has developed a formula to optimize the pruning process in fields and thus achieve a significant reduction in crop management costs. The product consists of a complexed copper solution whereby the greater the amount of complex, the more effective the application will be.
After obtaining promising results in the formulation phase and in field trials, Altinco used synchrotron light to determine the content and composition of its product. At the ALBA Synchrotron, the spectral data and analytical information were obtained to verify the identity and composition of the substance. This is one of the most important phases of the project since the characterization tests are necessary to register the product under the ECHA (European Chemicals Agency).
Using the X-ray absorption spectroscopy technique at the CLAESS beamline, the composition and amount of copper complex in four different formulations of the agricultural product could be verified. It was concluded that the variability in the amount of complexed copper was due to slight differences in the pH of the solutions and the concentration of copper and ligand. It was also observed that the four formulations contained only copper complexed or bound to ligands or compounds, with an oxidation state of +2. No reduced copper, Cu(I) ions or Cu(0) metallic copper were detected in any sample.
Figure 1. X-ray absorption spectra of different copper standards
Figure 2. X-ray absorption spectra of the different analyzed formulations
These measures were funded by the TamaTA program, which is part of the European CALIPSOplus project (grant 730872) in which ALBA participates. This program provides small and medium-sized companies access to European synchrotron facilities for the improvement of their research and industrial developments.
This project has received funding from the European Union's Horizon 2020 Research and Innovation program under Grant Agreement No. 730872.
