Journal of Food Measurement and Characterization

, Volume 11, Issue 4, pp 1761–1772 | Cite as

Optimization of vacuum-assisted microwave drying parameters of green bell pepper using response surface methodology

  • Vivek KumarEmail author
  • Shanker Lal Shrivastava
Original Paper


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.


Green bell pepper Optimization Vacuum-assisted microwave drying Response surface methodology Specific energy consumption 

List of symbols


Apparent density ratio (%)


Model coefficient


Desirability function




Green bell pepper




Green color ratio (%)




Microwave power, W




Rehydration ratio


Response surface methodology


Specific energy consumption (MJkg-1)


Vacuum level, mm Hg


Vacuum-assisted microwave;




Code independent variable


Code dependent variable


i, j

Indices of response variables


Indices of estimated model coefficient


Total number of responses


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Agricultural and Food EngineeringIndian Institute of TechnologyKharagpurIndia

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