Development of novel fast screening methods to predict cadmium concentrations in cacao beans

The cacao from South-America contains high concentrations of cadmium (Cd) that originates from the high natural Cd background concentration in soils of that region. The 2019 regulations by the European Union have set a stringent limit for Cd in chocolate. Nearly half of the South-American production exceeds this limit. Farmers are currently faced with lower prices for their products. The low quality of the local laboratories also brings a large uncertainty, because the low limits require methods detecting trace quantities. There is a need for better quality control on the laboratories and a sound sampling strategy. Along the same lines, cacao expansion areas need a predictive tool to assess the likelihood that new plantations yield products that are below the limits. This proposed PhD addresses these issues by developing and comparing three fast screening methods. The first is based on MIR (Mid Infra Red) analysis of beans and soils. The MIR is a lab-based system that is not very expensive and that delivers a result within seconds. It can not directly detect Cd, but the very data-rich MIR signal can contain signals that correlate with Cd provided sufficient calibration and advanced data-analysis, e.g. with Artificial Intelligence. The research group of the applicant has > 500 soil and bean samples which will be used to test the approach and, if successful, it will be applied at field scale in South-America. Secondly, this applicant will evaluate portable XRF equipment which can detect Cd at and around the limits. It will be tested if plant leaf Cd signals with XRF (higher than bean Cd and likely above detection limits) are predictive for bean Cd. Finally, novel GIS based data analysis of existing data (bean survey plus soil maps and climate data) will be evaluated as a predictive tool. This PhD will provide novel insights in analytical methods and will provide data useful for the local cacao industry in South America.