Increasing the Efficiency of Gac (Momordica cochinchinensis Spreng) Aril Oil Extraction by Commercial Pectinase Pretreatment and Microwave Dehydration

Autor: Suthida Akkarachaneeyakorn, Amornrat Artwichai, Sudaporn Maingam, Kittiyaporn Kinmonta
Rok vydání: 2022
Předmět:
Zdroj: Applied Science and Engineering Progress.
ISSN: 2673-0421
2672-9156
DOI: 10.14416/j.asep.2022.02.007
Popis: The objectives of this research were to determine the optimal conditions for using commercial pectinase (Pectinex® Ultra SP-L) and microwave dehydration to increase the efficiency of gac (Momordica cochinchinensis Spreng) aril oil extraction by using a screw press, to find mathematical models to predict the yields, extraction efficiencies, and β-carotene and lycopene contents in gac aril oil that varied with the enzyme concentrations, enzyme incubation temperatures, and microwave drying powers, and to validate the mathematical models. A Box-Behnken experimental design for three factors, including enzyme concentrations (0.01, 0.11, and 0.21% w/w), enzyme incubation temperatures (30, 45, and 60 °C), and microwave drying powers and times (450 W for 28 min, 600 W for 20 min, and 800 W for 14 min), was applied to determine the optimal conditions for increasing the efficiency of gac (Momordica cochinchinensis Spreng) aril oil extraction using commercial pectinase and microwave dehydration pretreatments before pressing with a screw press. It was found that the optimal conditions for extracting oil from gac aril based on the highest values of yield (12.14%), extraction efficiency (72.92%), and β-carotene and lycopene contents (104.64, and 27.90 mg/100 g oil, respectively) and the lowest of microwave energy consumption (720 kJ) were an enzyme concentration of 0.13% (w/w), enzyme incubation temperature of 45 °C and microwave drying power of 600 W for 20 min. To validate the mathematical models, the predicted yields, extraction efficiencies, and β-carotene and lycopene contents were compared to the experimental data and the deviants were less than 10%, which indicated that the model predictions were reliable.
Databáze: OpenAIRE
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