Optimización de la extracción de glucosinolatos de maca (Lepidium meyenii) por superficie de respuesta y algoritmos genéticos

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Abstract
The aim this work was to compare the extraction process optimization of total glucosinolates of maca flour (Lepidium meyenii) (ETGMF) using RS for Box-Behnken (RSBB) Design with that of GA, according to x1: temperature (°C), x2: ethanol (%), x3: ratio solvent/raw material and x4: extraction time (min). TG were identified and quantified using HPLC. The variables (x1, x2, x3, x4) that influence their extraction were evaluated using a RSBB with the software Statistica and Wolfram Mathematica for the AG. From the development of the RSBB, a second order equation with R2 = 0.74794, p = 1.88248E-10 << 0.05 with 11% average absolute error was obtained; it showed the consistency of the model. It was not possible to obtain an optimal value of the ETGMF using RSBB because of the existence of two optimal zones due to the configuration of a chair surface. After 2000 iterations using GA, the maximum value of the function of 17.0986 μmol of TG/g of MF was obtained, which was reached with 69.9783 °C, 70.9540 ethanol%, 10.0488 ratio solvent/raw material in 90 min, which demonstrates the applicability of the GA.

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