Influence of vacuum impregnation pretreatment combined with IR drying on quince quality with shrinkage modeling by ANN

Abstract

The effects of infrared power on drying behavior of quince slice were investigated. The samples were pretreated under vacuum impregnation (VI) and atmospheric pressure with sucrose sirup. The quality attributes measured included moisture content, bulk density rehydration, water loss, solid gain, texture, porosity, color, non-enzymatic browning, and effective moisture diffusivity. In addition, the modeling of shrinkage by ANN. VI increased the effective moisture diffusivity, bulk density, and softening of the dried fruit tissues while decreasing the time of drying (p < 0.05). The highest porosity was observed for the control samples treated under VI and dried at 1200 W. The desired color was achieved in the osmotic samples treated under atmospheric conditions and dried at 800 W. The rate of rehydration was reduced in the osmotic samples under vacuum. MLP neural network was used to model the shrinkage of the best topology 3-3-1 by LM learning algorithm and threshold function of Tangent sigmoid function, with a correlation coefficient of 0.9963 and the error MSE of 0.000340.

Keywords:

• Drying
• infrared
• neural network
• osmotic dehydration
• quince

Disclosure statement

No potential conflict of interest was reported by the authors.