Postharvest Hardness and Color Evolution of White Button Mushrooms (Agaricus bisporus)

Abstract

: The quality evaluation of mushrooms was studied by storing fresh white button mushrooms (Agaricus bisporus) for 6 to 8 d, at various controlled temperature conditions (3.5 to 15 °C) and measuring the instrumental textural hardness and color of the mushroom cap for different product batches. A nonlinear mixed effect Weibull model was used to describe mushroom cap texture and color kinetics during storage considering the batch variability into account. Storage temperature was found to play a significant role in controlling texture and color degradation. On lowering storage temperature (i) the extent of the final browning extent in the mushroom after storage was reduced and (ii) the rate textural hardness losses was slowed down. A linear dependence of the final browning index with temperature was found. An Arrhenius type relationship was found to exist between the temperature of storage and storage time with respect to textural hardness. The average batch energy of activation was calculated to be 207 ± 42kJ/mol in a temperature range of 3.5 to 20 °C. Practical Application: This article evaluates how temperature abuse affects mushroom texture and color, applying methods that allow for the consideration of the natural product variability that is inherent in mushrooms. Its results apply to mushroom producers, retail distribution, and supermarkets for effective storage management.

Colour Measurement and Analysis in Fresh and Processed Foods: A Review

“…Based on CIE L*a*b* coordinates, especially on the L* value, or on the CIE XYZ colour space, browning indicators in fruit have been developed (Lu et al 2007;Pristijono et al 2006). To capture this variation in a single index that would be related to a brown colour, the BI is calculated using the following expression (Maskan 2001;Mohapatra et al 2010):…”

Probabilistic shelf life assessment of white button mushrooms through sensorial properties analysis

“…On the other hand, multivariate data analysis takes care of number of variables affecting the acceptability, predicts the shelf life in a more meaningful way, but the inconsistent nature of the fresh product, owing to its biological variation itself poses a greater problem in estimation of shelf life in an effective way. A mixed effect model that addresses the internal as well as batch variation, is widely used by various researchers for modelling the quality evolution in fruits and vegetables during post harvest storage (Aguirre, Frias, Barry-Ryan, & Grogan, 2008;De Ketelaere, Stulens, Lammertyn, Cuong, & De Baerdemaeker, 2006;Fonseca, Oliveira, Frias, & Brecth, 2002;Hertog, Lammertyn, De Ketelaere, Scheerlinck, & Nicolaï, 2007;Mohapatra, Frias, Oliveira, Bira, & Kerry, 2008;Mohapatra, Bira, Kerry, Frias, & Oliveira, 2010;Montanez et al, 2002;Schouten, Jongbloed, Tijskens, & Kooten, 2004). The evolution of panel and panellists and sensory profiling representing the consumer liking while performing descriptive sensory analysis had also been addressed by mixed effect models (Chabanet & Pineau, 2006;Ortúzar, 2010;Pineau, Chabanet, & Schlich, 2007).…”

Breeding of a long shelf-life strain for commercial cultivation by mono–mono crossing in Pleurotus eryngii

“…This is an important factor in evaluating the shelf-life of mushrooms (Mohapatra et al, 2010;Singh et al, 2010). Although the shelflife of the hybrid strains showed a positive linear association with the middle hardness of the stipe, the bottom hardness showed a negative linear association with the shelf-life.…”