Hybrid Application of RSM and ANN to Optimize Natural Deep Eutectic Solvent-Based Distillation of Ocimum basilicum Essential Oil and Its Biological Activities

The extraction of essential oil from agricultural resources continues to be a challenge in the context of purity, the integrity of delicate compounds, and low yield. In the current study, a new distillation protocol, involving the use of Glucose–Citric Acid-based Natural Deep Eutectic Solvent (NaDES), has been developed and optimized through artificial intelligence (AI)-based models for enhanced recovery of Ocimum basilicum L. essential oil (OBEO). The NaDES mixture was prepared at various compositional ratios and customized through statistical tools of RSM as well as AI-based models (ANN) to optimize the recovery and chemical composition of OBEO. The physicochemical properties of the prepared NaDES were studied at 5–50% molar ratios of water, which revealed a pH drift of 1–2.5, a viscosity of 1244–5.21 mPa.s, and a density of 1.55–1.22 g/cm3. The maximum yield of OBEO (41.00 ± 0.27 mL/Kg of fresh aerial material) was obtained with the extracting solvent containing 31.6% NaDES applied with 7.18 mL/g solvent-to-solid ratio at 70 °C and 210 min of distillation time. Interestingly, the chemical composition of OBEO obtained through the test protocol was more diverse in chemical nature in comparison to the control (hydrodistillation) when studied through GC-MS analysis. Moreover, NaDES-based OBEO demonstrated potent broad-spectrum antimicrobial activity, antioxidant activity (90.36% inhibition of DPPH⸰), and notable mosquito repellent activity (RC50 = 407 µL). These findings indicate that Glucose–Citric Acid-based NaDES in combination with water can distill OBEO more efficiently for its application in food and pharmaceutical industries.