Journal
INDUSTRIAL CROPS AND PRODUCTS
Volume 150, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.indcrop.2020.112395
Keywords
Cynaropicrin; Ultrasound assisted extraction; Pulse mode; Response surface methodology; Cynara cardunculus
Categories
Funding
- Regional Development European Foundation [ALT20-03-0145-FEDER-000038]
- Alentejo Region Operational Program (ALENTEJO 2020) [ALT20-03-0145-FEDER-000038]
- Fundacao para a Ciencia e a Tecnologia [SFRH/BD/110969/2015, IF/00505/2014/CP1224/CT0004]
- Associate Laboratory for Green Chemistry - LAQV - national funds from FCT/MCTES [UIDB/50006/2020]
- FCT/MCTES [UIDB/05183/2020]
- Fundação para a Ciência e a Tecnologia [IF/00505/2014/CP1224/CT0004, SFRH/BD/110969/2015] Funding Source: FCT
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In this study, conditions for ultrasound assisted extraction (UAE) of cynaropicrin from Cynara cardunculus leaves by assessing the effect of pulsed mode and different duty cycles were optimized. Pulse mode presented a reduction of 45 % on energy consumption/g cynaropicrin extracted, comparatively to continuous mode, and a duty cycle of 25 % presented the highest kinetic rate between the duty cycles under study, with a lower number of pulse repetitions necessary to reach a steady state conditions. The extraction methodology was further optimized by response surface methodology (RSM), using a Box-Bhenken design with 3 factors (solid/liquid ratio, amplitude and temperature), and 3 levels for correlation of independent variables with the extraction yield (mg of cynaropicrin/g dry weight) and cynaropicrin concentration (mg cynaropicrin /g extract). Experimental results were fitted to a second order polynomial model, using multiple regression and analysis of variance to determine the fitness of the model. Optimal conditions were found for a solid/liquid ratio of 1/27, amplitude of 67 % and temperature of 44 degrees C, with a predicted value of 23.99 mg/g DW and 192.23 mg/g extract for extraction yield and cynaropicrin concentration, respectively. The predicted values fit the experimental ones, with a 95 % confidence level showing the accuracy of the model. The results obtained suggest the applicability of the UAE optimization methodologies described, for cynaropicrin extraction from Cynara cardunculus leaves, illustrating its potential application on biotechnological and agro food industries.
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