Storage time assessment and shelf-life prediction models for postharvest Agaricus bisporus

Rapid senescence and short shelf-life of fresh Agaricus bisporus can cause serious economic losses. Sometimes even illegal additives are used to maintain the freshness of A. bisporus. This misconduct can bring health risks to consumers. Therefore, it is meaningful to establish shelf-life prediction model for taking necessary measures to reduce the losses, and establish storage time assessment model to evaluate the true postharvest storage duration of A. bisporus to prevent commercial misconduct. We developed storage time assessment model and shelf-life prediction model based on mushroom texture (hardness, gumminess, chewiness), signal of water mobility and typical flavor. With the extension of storage time, all the qualities of A. bisporus showed a decreasing tendency at different temperatures. Quality decreases were proven suitable to the first-order kinetic model. Gumminess was a more accurate index to assess how long postharvest A. bisporus has already been stored (the storage time), whereas chewiness was a more precise index to predict how long postharvest A. bisporus can be stored (the shelf life). These mathematical models can be useful to assess the storage time and predict the shelf-life of fresh A. bisporus during distribution chain and storage under a temperature range of 4-20 degrees C.