Research Article | OPEN ACCESS
Multi-response Optimization of Pectinase Processing Conditions on Blueberry Juice Extraction by Desirability Function Methodology
Xueling Gao, Na Li, Jia Liu and Pengxiang Yue
School of Tea and Food Science, Anhui Agricultural University,
No. 130 West Changjiang Road, Hefei, Anhui, 230036, China
Advance Journal of Food Science and Technology 2014 5:647-654
Received: January 27, 2014 | Accepted: February 10, 2014 | Published: May 10, 2014
Abstract
Response Surface Methodology (RSM) was employed to analyze the effect of pectinase processing on Juice Yield (JY), Total Anthocyanin content (TA), Total Phenol content (TP) and Total Flavonoid content (TF) of blueberry juice. The processing conditions included enzyme dosage, hydrolysis temperature and hydrolysis time. For resolving multi-response optimization, desirability function method was used to integrate JY, TA, TP and TF into a new target D (Desirability value). Predicted values of JY, TA, TP, TF and D were found to be in good agreement with experimental values as indicated by the high R2 values of 0.9963, 0.9217, 0.9586, 0.9901 and 0.9933, respectively. The optimum conditions were: enzyme dosage of 0.6 mg/g, hydrolysis temperature of 51.6°C and hydrolysis time of 2.36 h. At this optimum point, JY, TA, TP, TF and D were 71.406%, 420.367 mg/L, 2.784 g/L, 3.121 g/L and 0.9206, respectively. The study showed that RSM was an effective technique to model the effect of pectinase processing on blueberry juice parameters and desirability function method could be used for multi- response optimization of blueberry juice extraction.
Keywords:
Blueberry, blueberry juice extraction, desirability function, muti-response optimization, pectinase, response surface methodology,
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Competing interests
The authors have no competing interests.
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