Volume 17 Part 1 Article 10: Quality Prediction of Agaricus bisporus Mushrooms by Gene Expression

Volume 17 Part 1 Article 10
Year 2008
Title: Quality Prediction of Agaricus bisporus Mushrooms by Gene Expression
Authors: J.J. Mes, E.A. Hendrix, H. Harkema, J. Amsing, J. Peters, S. Bastiaan-Net and A.S.M. Sonnenberg

Abstract:

Button mushrooms (Agaricus bisporus) have a limited shelf life. An optimal time of harvest, quick cooling and short transport time to selling points are needed to ensure a good quality. Even if these conditions are optimal, large variations can be seen in quality of different mushroom batches. A cause of this variation in quality is not always evident.

There is, in principle, for each quality grade a suitable market. However, the unpredictable postharvest quality development makes it difficult to match quality and market type. It is estimated that this leads to an economic loss of 5–10% of crop value.

Tools to predict postharvest quality can help to improve matching of quality and market type. One of the possible tools is based on gene expression analysis. A prerequisite for this approach is the availability of molecular indicator genes and a fast method to assess gene expression. We have used dedicated microarrays containing over 700 spotted unique genes to identify genes whose activity is correlated with postharvest quality development. For this, a small-scale microarray hybridisation experiment was used to analyse the expression of these genes in batches of button mushrooms that showed different degree of browning after a cold postharvest period of 7 days. These analyses have generated a list of putative indicator genes. Ongoing research, using real-time polymerase chain reaction will reveal if these putative indicators can be used for quality prediction of mushrooms in the production chain. Although real-time-based gene-expression analysis is a reliable way to assess gene expression, the method is probably too costly and time consuming (taking at least one day) for practical ‘in-chain’ application. We will therefore develop with additional partners new and faster types of sampling, and RNA isolation and detection methods.

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