Articles
Respiratory gas and RQ analysis of different pear cultivars during RQ-DCA storage
Article number
1386_10
Pages
73 – 78
Language
English
Abstract
Nowadays, new innovative storage techniques are being developed to better maintain the quality of pome fruit during long-term storage.
With respiratory quotient-based dynamic controlled atmosphere (RQ-DCA) storage, the gas concentrations are continuously adapted according to the needs of the fruit, improving storability and quality significantly with respect to conventional CA storage.
In RQ-DCA, the O2 concentration is regulated to maintain a low enough RQ value (CO2 production rate/O2 consumption rate). Below a critical O2 concentration, the RQ value exponentially increases, indicating hypoxia and the onset of fermentative breakdown in the fruit that is to be avoided.
Due to the large variability both within and between different cultivars, the individual fruit response might differ significantly.
In this work, we apply a physics-based, stochastic diffusion-reaction model to pear fruit to compute gas transport within pears of two different cultivars, taking into account biological variability in material properties and variations in cool room conditions.
The goal is to quantify the effect of the observed variability on the RQ within the pear and that determined from gas levels of the surrounding air.
Results show that the RQ of the air always underestimates the RQ inside the pears, indicating the importance of the internal gas gradients in the fruit.
At low oxygen concentrations in the cool room, the RQ of both the air and the fruit is strongly impacted by biological variability of pear respiration properties.
The RQ is also very sensitive to temperature variations, but due to proper air circulation in the cool room, the temperature gradients are limited.
Despite large variations in the RQ, making the measured RQ in the room less representative for the batch of fruit, the simulations reveal that the variability of minimal fruit O2 concentration remains low.
As a result, the results of this work indicate the robustness of the RQ-DCA technique.
Eventually, these statistics will be used to help optimize the RQ-DCA implementation for large cool rooms of different pear cultivars such that the occurrence of hypoxia is prevented.
With respiratory quotient-based dynamic controlled atmosphere (RQ-DCA) storage, the gas concentrations are continuously adapted according to the needs of the fruit, improving storability and quality significantly with respect to conventional CA storage.
In RQ-DCA, the O2 concentration is regulated to maintain a low enough RQ value (CO2 production rate/O2 consumption rate). Below a critical O2 concentration, the RQ value exponentially increases, indicating hypoxia and the onset of fermentative breakdown in the fruit that is to be avoided.
Due to the large variability both within and between different cultivars, the individual fruit response might differ significantly.
In this work, we apply a physics-based, stochastic diffusion-reaction model to pear fruit to compute gas transport within pears of two different cultivars, taking into account biological variability in material properties and variations in cool room conditions.
The goal is to quantify the effect of the observed variability on the RQ within the pear and that determined from gas levels of the surrounding air.
Results show that the RQ of the air always underestimates the RQ inside the pears, indicating the importance of the internal gas gradients in the fruit.
At low oxygen concentrations in the cool room, the RQ of both the air and the fruit is strongly impacted by biological variability of pear respiration properties.
The RQ is also very sensitive to temperature variations, but due to proper air circulation in the cool room, the temperature gradients are limited.
Despite large variations in the RQ, making the measured RQ in the room less representative for the batch of fruit, the simulations reveal that the variability of minimal fruit O2 concentration remains low.
As a result, the results of this work indicate the robustness of the RQ-DCA technique.
Eventually, these statistics will be used to help optimize the RQ-DCA implementation for large cool rooms of different pear cultivars such that the occurrence of hypoxia is prevented.
Authors
C. Verreydt, P. Verboven, T. Defraeye, B.M. Nicolaï
Keywords
numerical modeling, stochastic simulations, tissue microstructure, fruit respiration, hypoxia
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