Optimization of extraction in supercritical fluids in obtaining Pouteria lucuma seed oil by response surface methodology and artificial neuronal network coupled with a genetic algorithm - Chauca-Cerrutti, Alex; Inga, Marianela; Pasquel-Reátegui, José Luis; Betalleluz-Pallardel, Indira; Puma-Isuiza, Gustavo (Frontiers in Chemistry, 2024)
In processing lucuma (Pouteria lucuma), waste such as shells and seeds is generated, which is a source of bioactive compounds. Recently, lucuma seed (LS), especially its oily fraction, has been studied for containing phytosterols and tocopherols, powerful antioxidants with health benefits. This research proposes to extract lucuma seed oil (LSO) using supercritical fluid (SCF) to improve the quality of the extract and minimize the environmental impact. LS was previously characterized, and then the extraction parameters were optimized using a Box-Behnken design, considering temperature (40-60°C), pressure (100-300 bar), and CO2 flow rate (3-7 mL/min), applying the response surface methodology (RSM) and neural networks with genetic algorithm (ANN+GA). The results indicated optimal parameters of 45°C, 300 bar, and 6 mL/min, obtaining a yield of 97.35% of the total oil. The RSM and ANN+GA models showed a R2 values of 0.9891 and 0.9999 respectively, showing that both models present a good fit to the experimental data. However, ANN+GA provides a greater proportion of the total variability, which facilitates the identification of the optimal parameters for the extraction of oil from lucuma seeds. Compared to the Soxhlet method, the LSO obtained by SCF presented better acidity (4.13 mg KOH/g), iodine (100.3 cg I/g), and refraction (1.47) indices, as well as to a higher content of mono- and polyunsaturated fatty acids. Supercritical CO2 extraction is presented as a sustainable green alternative to Soxhlet extraction in extracting oil from lucuma seed due to its high extraction efficiency and similar fatty acid profile.