PREDICTING ROSE VASE LIFE IN A SUPPLY CHAIN

Abstract

An important quality attribute of cut flowers is their vase life. With increasing market globalization, the vase life is more and more affected by transport and storage. However, techniques to measure the potential vase life at the point of sale in the chain are not available at this moment. Therefore, simulation models that can predict vase life based on temperature and time, as measured by data loggers, could be very valuable. Moreover, such simulation models could be used for scenario studies to investigate quality critical control points. A previously published simulation model, based on data from literature, was validated for cut rose flowers using data of a vase life experiment with flowers stored at 1, 5, 8 and 12°C for periods varying between 2 and 39 days. The experimental setup was designed to exclude the occurrence of Botrytis and water uptake problems due to bacteria as much as possible. The experimentally obtained vase life data confirmed that the relationship between temperature and loss of vase life during storage could very well be described by a sigmoidal curve. The predicted vase life applying the simulation model correlated very well to the measured vase life. However, the vase life after long storage was underestimated; this could be improved by adapting only one parameter of the model for the specific cultivar calculated from the vase life of fresh cut flowers without storage. Also a linear temperature sum model was tested. The temperature sum-model gave acceptable outcomes within narrow temperature and storage period ranges, but largely overestimated vase life of flowers with short remaining vase lives. Besides non-linear effects of temperature on the rate of vase life-loss, this was largely due to the non-linear effect of the length of the storage period.