Although there is an extensive set of literature on inventory management for perishable items, a majority of these operate at a higher level where all items are assumed to have a fixed shelf-life. However, depending on how they are handled in transit as well as during storage, the remaining shelf-life of perishable items can vary. We consider perishable inventory management with demand that is directly dependent on the amount of shelf-space allocated to the item of interest as well as its instantaneous quality. We assume the existence of detailed information at the item-level generated through auto-ID technology such as RFID with necessary sensors. Specifically, we extend the model in Bai and Kendall (2008) to incorporate item-level quality information and use Genetic Algorithms to solve our model. Our results show that the incorporation of item quality increases the resulting overall profit to the retailer.