4.5 Article

Effects of aerosolized citric acid-radio frequency as a pretreatment on hot-air drying characteristics of banana

Journal

FOOD SCIENCE & NUTRITION
Volume 9, Issue 11, Pages 6382-6388

Publisher

WILEY
DOI: 10.1002/fsn3.2610

Keywords

aerosolized citric acid; banana; drying; radiofrequency

Funding

  1. Agricultural Sciences and the Natural Resources University of Khuzestan

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The study evaluated the effects of aerosolized citric acid-RF pretreatment on the quality characteristics of hot air-dried banana. Results showed that this treatment increased total phenolic content, shrinkage, and color changes, while decreasing rehydration ratio and firmness. The combination of citric acid aerosolization and RF treatment showed promise for preserving phenolic compounds and affecting various quality parameters of the banana samples.
The effects of aerosolized citric acid-radio frequency (RF) pretreatment were evaluated on the quality characteristics of hot air-dried banana. The results showed that increasing the RF intensity elevated the total phenolic content (TPC), shrinkage, and color changes, while the TPC and color changes decreased with increasing the RF exposure duration. A rise in the RF intensity reduced the rehydration ratio (RR) and firmness of the samples. Aerosolization of citric acid rendered the preservation of the phenolic compounds of the samples to a higher extent, and TPC decreased from 311 +/- 3.4 mg/g in fresh banana to 252.1 +/- 4.24 mg/g in the samples treated with a RF of 27.12 Hz for 40 min, 280.5 +/- 8.1 mg/g in the ones treated with 1% aerosolized citric acid for 40 min, and 162.5 +/- 10.8 mg/g in the ones with no pretreatment. According to scanning electron microscopy (SEM), the application of aerosolized citric acid pretreatment caused tissue softening and the formation of cell holes in the samples. Cell wall collapse and damage were severe when RF was in use, which caused the blockage of some microchannels within the tissue. The Page model with the highest determination coefficient (R-2) and the lowest root-mean-squared error (RMSE) and chi-square (chi(2)) was selected as the best model.

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