Multi-objective optimization of drying conditions for the Olea europaea L. leaves with NSGA-Ⅱ

摘要

Phenolic compounds from olive leaves, which attract great attention with their highphenolic content and high antioxidant activity, need to be dried to increase the extractionefficiency before extraction. For this purpose, it is aimed to obtain optimaldrying conditions of hot air inlet temperature (Tg), orifice inlet air flow rate (ν), dryingtime (t), and rehydration ratio (RR) for moisture removal of olive leaves. For thispurpose, final moisture content (MC) and moisture loss (ML) were modeled and optimizedby using soft computing methods. Pareto sets were obtained from predictedquadratic linear models using the least-squares(LS) approach. The nondominatedsorting genetic algorithm-Ⅱ (NSGA-Ⅱ)was used for optimization. The compromisesolution was obtained using the fuzzy c-meansclustering algorithm (FCM) algorithm,one of the multicriteria decision-makingmethods. When the olive leaf is dried underoptimum conditions determined by FCM (Tg = 63.84°C, v = 1.700 m/s, t = 997 s,RR = 2.21%), the experimental values for total phenolic content (TPC) and oleuropeinamount were (20.07 ± 1.01) mg GAE/g dw and (7.30 ± 0.71) mg/g dw, respectively. Itwas found that drying olive leaves under low airflow rate and low hot air input temperatureresulted in less alteration of TPC and oleuropein amount.