Currently, quality assurance in the food supply chain is predominantly conducted manually with traditional destructive methods. Best before date forecasts depend mainly on time of arrival without including weather or cold chain. Measured data within the food supply chain is not digitized and can therefore not be aggregated for analysis. We propose a new architecture for improving sustainability of the food supply by combining innovative measurement techniques with a trusted cloud edge infrastructure. Forecasts based on digital twins and a shared federated data space for freshness data serve to optimize supply chain processes and reduce the loss of fresh produce along the supply chain. In this paper, we present a suitable system architecture with independent data spaces and flexible implementations for trusted local deployments.