Abstract
The present study aimed at determining the optimal conditions for extraction of total phenolic compounds from soybean (Glycine max) meal, a by-product of the soybean seeds industry, using a green protocol with microwave-assisted extraction (MAE). A face-centered composite design (FCCD) was used for optimization. Based on a screening aimed to determine the factors that significantly influenced the responses, a 50% hydro-ethanolic solution was used with solvent/dry matter ratio (60/1–110/1), power (120–270 W), and time (0–10 min) as factors, while the responses studied were total phenolic and flavonoid contents. FTIR, TLC, DPPH, and FRAP anti-oxidants tests were used to characterize the extracts obtained with optimum conditions. The factors that significantly influenced both responses were the individual effect of all factors, the interaction between solvent/dry matter ratio and extraction time, the quadratic effect of solvent/dry matter ratio, and power for total phenolic content, while only the quadratic effect of power significantly influenced the flavonoid content. The highest contents of phenols (13.09 mg GAE/g) and flavonoid (7.39 mg CE/g) were obtained at 120 W for 0.16 min with a solvent/dry matter ratio of 60/1. ATR-FTIR spectra indicated the presence of polyphenolic compounds in the extract, namely flavonoids. TLC indicated the presence of at least nine compounds in the extract, among which catechin and quercetin were identified with respective Rf of 0.98 and 0.93. DPPH assay showed the anti-oxidant capacity for the extract with an IC50 of 194.98 µg/ml. RSM permitted us to develop a green protocol for maximum extraction of polyphenols from soybean seeds waste using less solvent, low power, and a reduced time in MAE.
Highlights
Soybean meal is a by-product of the soybean seed industry, which is commonly used for animal feeding [1, 2] or rejected directly in nature, causing serious problems to municipalities and to the environment [3, 4]
The determination of experimental conditions for extraction of the highest polyphenolic content from soybean meal using a green protocol will be helpful, since these seeds are among the richest sources of the named compounds. is study aimed at determining the optimal conditions for extraction of phenolic compounds from soybean meal, a soybean seed industry waste product, using a face-centered composite design in the response surface methodology with microwave-assisted extraction (MAE)
Soybean meal extract was analyzed by a Fourier-transform infrared (FTIR) apparatus coupled with an attenuated total reflectance (ATR) accessory
Summary
Soybean meal is a by-product of the soybean seed industry, which is commonly used for animal feeding [1, 2] or rejected directly in nature, causing serious problems to municipalities and to the environment [3, 4]. Soybean waste and meal have not been exploited for the production of polyphenols. Soybean (Glycine max) seeds have been reported as one of the richest flavonoid legume sources known nowadays; with up to 3 mg/g dry weight [7], these compounds are not totally destroyed during the different treatments that seeds undergo and may find themselves in soybean meal discarded by industries. The determination of experimental conditions for extraction of the highest polyphenolic content from soybean meal using a green protocol will be helpful, since these seeds are among the richest sources of the named compounds. Is study aimed at determining the optimal conditions for extraction of phenolic compounds from soybean meal, a soybean seed industry waste product, using a face-centered composite design in the response surface methodology with MAE The determination of experimental conditions for extraction of the highest polyphenolic content from soybean meal using a green protocol will be helpful, since these seeds are among the richest sources of the named compounds. is study aimed at determining the optimal conditions for extraction of phenolic compounds from soybean meal, a soybean seed industry waste product, using a face-centered composite design in the response surface methodology with MAE
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