Pectin extraction from Helianthus annuus (sunflower) heads using RSM and ANN modelling by a genetic algorithm approach.
作者： Shanmugaprakash Muthusamy , Lakshmi Priya Manickam , Venkateshprabhu Murugesan , Chandrasekaran Muthukumaran , Arivalagan Pugazhendhi
DOI: 10.1016/J.IJBIOMAC.2018.11.036
关键词:
摘要: Abstract In this work, Response Surface Methodology (RSM) and Artificial Neural Network coupled with genetic algorithm (ANN-GA) have been used to develop a model optimise the conditions for extraction of pectin from sunflower heads. Input parameters were time (10–20 min), temperature (40–60 °C), frequency (30–60 Hz), solid/liquid ratio (S/L) (1:20–1:40 g/mL) while yield (PY%) was output. Results showed that ANN-GA had higher prediction efficiency than RSM. Using ANN as fitness function, maximum 29.1 ± 0.07% searched by at 10 min, 59.9 °C, 30 Hz, solid liquid 1:29.9 g/mL experimental value found be 29.5 ± 0.7%. Extracted characterised FTIR 13C NMR. Thus, GA has proved effective method optimization process
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