By gathering environmental data such as temperature or humidity in the direct environment of a plant during the production and/or distribution chain, a history can be build of the environmental conditions of the plant. These conditions are important predictors for the quality of the plant at different points in the chain. Using self-learning computer systems together with expert-knowledge we can predict the quality of the plant at these different points in the chain and ultimately at the retailer.
Using the predictions created by this app, a chain party may for instance decide to redirect specific (plants or trays of plants) to different retailers depending on whether a specific retailer needs either a longer or shorter chain. This will decrease loss.