Abstract
Green bell pepper was dried under vacuum-assisted microwave drying condition and the process was optimized using response surface methodology. The effect of microwave power (100–300 W) and vacuum level (200–600 mm Hg) were observed on the responses, viz. green color ratio, rehydration ratio, hardness, apparent density ratio, drying time and specific energy consumption. A central composite face-centered design was used to develop predictive regression models for the responses. Analysis of variance showed that quadratic model best fitted the experimental data. The microwave power level had greater effect on the quality attributes of green bell pepper; nevertheless at higher vacuum level the dried products had better quality. The optimum drying conditions were determined to be 284.4 W microwave power, 600 mm Hg vacuum level and the optimized value of the responses were obtained as green color ratio of 80.70%, rehydration ratio of 10.75, hardness of 152.98 N, apparent density ratio of 76.02%, drying time of 78 min, and specific energy consumption of 6.57 MJ/kg. Validation experiment was carried out at derived optimum condition to verify the prediction and adequacy of the models. Close agreement between experimental and predicted values was obtained.
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Abbreviations
- ADR:
-
Apparent density ratio (%)
- β :
-
Model coefficient
- D(x):
-
Desirability function
- g:
-
Gram
- GBP:
-
Green bell pepper
- GHz:
-
Gigahertz
- GR:
-
Green color ratio (%)
- kcal:
-
Kilocalorie
- M:
-
Microwave power, W
- MHz:
-
Megahertz
- RR:
-
Rehydration ratio
- RSM:
-
Response surface methodology
- SEC:
-
Specific energy consumption (MJkg-1)
- V:
-
Vacuum level, mm Hg
- VAM:
-
Vacuum-assisted microwave;
- W:
-
Watt
- X:
-
Code independent variable
- Y:
-
Code dependent variable
- i, j :
-
Indices of response variables
- k :
-
Indices of estimated model coefficient
- n :
-
Total number of responses
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Kumar, V., Shrivastava, S.L. Optimization of vacuum-assisted microwave drying parameters of green bell pepper using response surface methodology. Food Measure 11, 1761–1772 (2017). https://doi.org/10.1007/s11694-017-9557-7
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DOI: https://doi.org/10.1007/s11694-017-9557-7