Optimization of simultaneous recovery of oil and protein from sesame (Sesamum indicum) seed

Abstract

This study investigated the simultaneous recovery of oil and protein from sesame seeds using aqueous extraction technique by the application of factorial design and central composite design.Solid-to-solvent ratio and pH were identified to have the highest significant (p < .05) effects on both oil and protein recovery. High solvent volume and extration temperature favored protein yield. Solvent volume had more influence on the protein yield than the extraction temperature.The significant effect of the extraction temperature was quadratic in nature while solid-to-solvent ratio was both linear and quadratic. Optimization of the extraction process showed that the optimal conditions for the process were found to be solid-to-solvent ratio, 1:3 (w/v); pH, 11; extraction temperature, 47 8C and surfactant concentration, 0.1 M NaCl with predicted oil and protein recovery of 73.60% and 75.12%, respectively. The validated values for oil and protein recoveries were 75.02% and 73.10%, respectively. The processing steps are readily scalable. Practical applicationsSesame is an oilseed that contains edible and odorless oil, and with good source of protein for man. The mechanical method of extracting edible oil from oilseeds gives low yield while n-hexane is flammability, explosiveness, and mild toxicity. Simultaneous recovery of oil and protein from sesame seeds using aqueous extraction technique will reduce production cost and time while maintaining high oil and protein yields. The oil can be used for both domestic and industrial purposes, and the protein in food formulation to combat malnutrition. K E Y W O R D Saqueous extraction, central composite design, factorial design, oil and protein recovery, optimization, simultaneous recovery

Characterization of protein isolate from Sesamum indicum seed: In vitro protein digestibility, amino acid profile, and some functional properties

“…The aqueous extraction technique described by Fasuan et al. () and Gbadamosi, Fasuan, and Omobuwajo () was employed. Fifty grams of ground sesame powder was weighed and suspended in 150 ml of 0.1 M NaCl at 47°C and homogenized for 30 min in a thermostat water bath (Julabo, model SW22, Germany).…”

“…Preliminary experiments were conducted to identify the optimal conditions for the independent variables used in this research. The aqueous extraction technique described by Fasuan et al (2018) and Gbadamosi, Fasuan, and Omobuwajo (2017) was employed.…”

“…Previous works on aqueous extraction process involved the use of enzymes, whereas the application of sodium chloride (NaCl) as surface active agent in collaboration with optimal conditions of pH, temperature, solid‐to‐solvent ratio has not been studied. In the previous parts of this study, oil and protein were simultaneously extracted and the process parameters were optimized (Fasuan, Omobuwajo, & Gbadamosi, ). However, in this study, the impacts of pH and ionic power on emulsion activity index and foam capacity, solubility, in vitro protein digestibility, and amino acid profile of the isolated sesame protein through simultaneous recovery of protein and oil (aqueous technique) were discussed.…”

Sesame Seeds: A Nutrient-Rich Superfood

“…The circumstances mentioned earlier have led to an extraction efficiency of 82.49%. The optimization of the method by Fasuan et al [273] resulted in improved outcomes, with oil and protein recoveries of 73.60% and 75.12%, respectively. This was achieved using a solid-to-solvent ratio of 1:3 (m/V), a pH of 11, an extraction temperature of 47 • C, and a surfactant concentration of 0.1 mol/L NaCl.…”

Oxidation ofAmaranthus viridisstarch: Amylose content evaluation

“…Central composite design response surface methodology (CCD-RSM) is a widely used optimization tool in food research (Betiku & Adesina, 2013;Betiku & Taiwo, 2015;Chen, Chen, & Lin, 2005;Dhillon, Brar, Verma, & Tyagi, 2011;Emeko, Olugbogi, & Betiku, 2015;Fasuan, Gbadamosi, & Akanbi, 2018;Fasuan, Omobuwajo, & Gbadamosi, 2017;Naveena, Altaf, Bhadraya, Madhavenda, & Reddy, 2005). Artificial neural network (ANN) is a technique that has ability to imitate the neurological processing skill of the human brain; and has been used in modeling of some food processing studies.…”