Analyzing quality and modelling mass loss of onions during drying and storage

MN Islam, O Körner, JS Pedersen, JN Sørensen… - … and electronics in …, 2019 - Elsevier
MN Islam, O Körner, JS Pedersen, JN Sørensen, M Edelenbos
Computers and electronics in agriculture, 2019Elsevier
Minimizing mass loss during drying and storage without compromising quality is crucial for
the onion industry. An experiment was carried out to monitor the quality changes related to
mass loss and to develop a robust mechanistic model to predict mass loss of onion bulbs
during drying and storage. Bulbs were dried for 14 days at 20° C or 35° C followed by 232
days storage at 4° C and 75% relative humidity (RH) or 4° C and 95% RH. The developed
model described the dynamic behavior of mass loss of onion bulbs taking into account mass …
Abstract
Minimizing mass loss during drying and storage without compromising quality is crucial for the onion industry. An experiment was carried out to monitor the quality changes related to mass loss and to develop a robust mechanistic model to predict mass loss of onion bulbs during drying and storage. Bulbs were dried for 14 days at 20 °C or 35 °C followed by 232 days storage at 4 °C and 75% relative humidity (RH) or 4 °C and 95% RH. The developed model described the dynamic behavior of mass loss of onion bulbs taking into account mass loss in transpiration and mass loss in respiration. The input data were temperature, RH, air velocity and respiration. Drying at 35 °C influenced mass loss and skin quality more than drying at 20 °C. Bulbs were drier and had more white scales seen through cracked skin. High RH (95%) in storage reduced mass loss more than low RH (75%) but partially increased rooting. The developed model in its simplest form showed good prediction of mass loss during drying (R2 = 99.9) and storage (R2 = 99.0). Moreover, validation with external data showed robustness in modeling. Further refinements of the model e.g. amendment of the model by including more factors that are directly involved in transpiration may reduce the uncertainties of the developed model and improve its future value for the onion industry.
Elsevier
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