Volume 17, Issue 98 (2020)                   FSCT 2020, 17(98): 109-119 | Back to browse issues page

‎ 10.29252/fsct.17.01.10

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Tabaei A, hazbavi I, Shahbazi F. Modeling and Optimization of Persimmon Drying Using Response Surface Methodology. FSCT 2020; 17 (98) :109-119
URL: http://fsct.modares.ac.ir/article-7-30018-en.html
Modeling and Optimization of Persimmon Drying Using Response Surface Methodology
Azadeh Tabaei1, Isa Hazbavi2, Feizollah Shahbazi3
1- Graduate Master, Biosystem Engineering, Lorestan University, Khorramabad, Iran
2- Assistant Professor, Biosystem Engineering, Lorestan University, Khorramabad, Iran , hazbavi2000@gmail.com
3- Associate Professor, Biosystem Engineering, Lorestan University, Khorramabad, Iran
Abstract:   (3030 Views)
Drying of food products using microwave can be a good replacement to hot air dryers. In this study, Response Surface Methodology (RSM) was used for optimization of the conditions for microwave drying of persimmon slices. The effects of microwave power (300, 500 and 700 W) and slice thickness (3, 5 and 7mm) as independent variables on shrinkage percentage, processing time and total color change of persimmon as dependent variables (responses) were evaluated. All process variables were statistically significant as quadratic regression models for all responses. As microwave power increased, the shrinkage percentage and total color change of persimmon slice increased but processing time decreased. As the thickness of persimmon slice increased, the processing time and total color change of persimmon slice increased but shrinkage percentage decreased. The optimum conditions obtained for minimum shrinkage percentage, processing time and total color change were 3 mm as slice thickness and the microwave power of 312 W. In optimized condition, the shrinkage percentage, processing time and total color change of dried persimmon slices were 72.5 %, 5.97 min and 15.2, respectively.
 
Keywords: Persimmon, Microwave, Quality, Response Surface Methodology
Full-Text [PDF 931 kb]   (479 Downloads)    
Article Type: Original Research | Subject: Statistics, modeling and response levels in the food industry
Received: 2019/02/1 | Accepted: 2020/02/1 | Published: 2020/03/29
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