Green add-in of agricultural wastes through NADES-based ultrasound and microwave extraction methods: Optimization and greenness assessment

Abstract

The increasing volume of agricultural wastes presents both an environmental burden and a potential resource for circular economy applications. Green extraction technologies offer a viable route to recover valuable bioactive compounds from these residues while reducing reliance on hazardous solvents and energy-intensive processes. This review examines recent developments in Natural Deep Eutectic Solvents (NADES) coupled with Ultrasound-Assisted Extraction (UAE) and Microwave-Assisted Extraction (MAE), with particular focus on their combined contributions to efficiency, selectivity, and process sustainability. The mechanistic roles of cavitation-driven cell disruption and dielectric heating are discussed in relation to mass transfer enhancement and solvent–matrix interactions. Optimization strategies, including Taguchi designs, response surface methodology, artificial neural networks, and multi-response desirability models, are evaluated for their effectiveness in refining extraction conditions. Greenness assessment tools such as Analytical Greenness (AGREE), Green Analytical Procedure Index (GAPI), and the Analytical Eco-Scale are also reviewed to highlight inconsistencies in current sustainability evaluations and to identify opportunities for more comprehensive benchmarking. By integrating solvent innovation, process intensification, and environmental metrics, this review situates NADES-based UAE/MAE as emerging platforms for the valorization of agricultural wastes within a sustainable circular economy framework. Key research gaps and future directions are identified, including the need for standardized greenness metrics, improved understanding of synergistic mechanisms, and assessment of solvent recyclability for future scale-up.

Keywords

natural deep eutectic solvents (NADES)ultrasound-assisted extraction (UAE)microwave-assisted extraction (MAE)agricultural waste optimization strategies greenness assessment

Introduction

The rapid expansion of global agriculture has led to the generation of enormous amounts of biomass residues. These include husks, peels, bagasse, straw, and fruit pomace, which are produced during harvesting and processing stages. A large fraction of these residues is burned, landfilled, or left to decompose, contributing to greenhouse gas emissions, soil and water pollution, and the inefficient use of resources.¹ Such practices contradict global sustainability goals and highlight the urgent need for more sustainable waste management strategies. Therefore, the concept of waste valorization has emerged as a central theme in sustainable resource management. This term refers to the process of converting waste materials into higher-value products such as biofuels, platform chemicals, dietary fibers, phenolic extracts, and nutraceutical ingredients.² This approach not only reduces environmental burdens but also supports the transition to a sustainable bioeconomy, enhancing circular resource use.³

The circular economy paradigm is also closely linked to this concept. Unlike the linear model of “take-make-dispose,” the circular economy emphasizes the continuous circulation of resources through reuse, recycling, and upcycling. They are reintegrated as raw materials, contributing to sustainable material cycles,⁴ supporting the United Nations Sustainable Development Goals, particularly SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action).

Another key framework underpinning waste valorization is green chemistry, which focuses on designing chemical processes to prevent pollution at the molecular level by minimizing or eliminating the use and generation of hazardous substances. This approach, defined by Paul Anastas and John Warner in the 1990s, guides the entire lifecycle of chemical products, from design and manufacture to use and disposal. Green chemistry aims to use safer solvents, renewable materials, save energy, and reduce waste. Conventional methods for extracting bioactive compounds often use harmful solvents like methanol, acetone, or chloroform, which can harm the environment and our health. To address this issue, researchers have turned to safer alternatives called Natural Deep Eutectic Solvents (NADES). One of the main benefits of NADES is their low toxicity, making them suitable for use in food, animal feed, cosmetics, pharmaceuticals, and agrochemicals.⁵

NADES are mixtures of natural compounds (e.g., organic acids, sugars, amino acids) that form eutectic liquids through hydrogen bonding. These solvents combine high solubilization power, tunable polarity, low volatility, and biodegradability, making them promising alternatives to conventional solvents.^6,7 Research demonstrates their effectiveness in extracting polyphenols, flavonoids, alkaloids, and other bioactives from diverse plant materials.⁸

In addition to solvent innovation, process intensification techniques such as Ultrasound-Assisted Extraction (UAE) and Microwave-Assisted Extraction (MAE) have shown great promise. UAE employs acoustic cavitation to disrupt plant cell walls, enhancing solvent penetration and release of intracellular compounds. It reduces extraction time, solvent use, and energy consumption while improving yields.⁹ On the other hand, MAE uses dielectric heating to accelerate solvent and solute interactions, enabling rapid, efficient recovery of bioactives with reduced thermal degradation.¹⁰

Combining NADES with green extraction methods like UAE or MAE creates a synergistic process that is more efficient than traditional methods.^11–14 The UAE uses ultrasound to create cavitation bubbles that disrupt cell walls, improving solvent penetration, while MAE uses microwave energy to heat the solvent and rapidly accelerate molecular interactions. These hybrid approaches offer advantages of enhanced mass transfer, reduced solvent use, and lower energy demand compared to conventional techniques.

Despite progress, several gaps remain. First, research often prioritizes yield maximization while overlooking other critical objectives, such as solvent recyclability and energy efficiency. Second, tools such as Taguchi design, response surface methodology, artificial neural networks, and desirability functions have been applied in extraction research, but rarely combined with greenness metrics.^15,16 Third, comprehensive greenness assessments remain scarce. Metrics such as the Analytical Greenness (AGREE) tool, the Green Analytical Procedure Index (GAPI), and Eco-Scale provide structured ways to evaluate environmental sustainability, but are seldom integrated into biomass extraction studies.¹⁷

Therefore, this review aims to provide a comprehensive synthesis of recent advances in NADES-based ultrasound and microwave extractions of antioxidants from agro-residues. The review not only summarizes current progress but also identifies critical research gaps and future directions necessary for advancing sustainable extraction technologies in the context of the circular bioeconomy.

Green solvents and extraction methods

Natural deep eutectic solvents (NADES)

The term “eutectic,” derived from the Greek meaning “easy melting,” was introduced by British physicist Frederick Guthrie in 1884 to describe a mixture with a lower liquefaction temperature than any of its individual components. However, not all eutectic mixtures qualify as Deep Eutectic Solvents (DES), as many immiscible solid-phase mixtures exhibit a eutectic point.¹⁸ The term “deep” lacks a universally accepted definition, but it generally refers to mixtures with a eutectic temperature significantly lower than an ideal liquid mixture. Despite variations in terminology, the classification principles of DES remain consistent, and the acronym is increasingly applied in a broader context.

Abbott and his colleagues in 2003 created the first Deep Eutectic Solvent by combining choline chloride and urea in a 1:2 molar ratio (also referred to as reline). This solvent has a melting point (MP) of 12 °C, which is lower than the MPs of ChCl (302 °C) and Ur (133 °C).¹⁹ The substantial MP depression of eutectic mixtures is believed to be the result of charge delocalization, which is the process by which halide anion (HBA) converts to halide base dielectric (HBD) through hydrogen bond formation.²⁰ Deep Eutectic Solvents (DESs) are primarily classified into four categories: organic salts combined with metal salts (type 1), organic salts combined with metal hydrates (type 2), organic salts combined with hydrogen bond donors (HBD) (type 3), and metal chlorides combined with HBD (type 4).²¹

In 2011, Choi et al.²² defined ‘Natural Deep Eutectic Solvents’ (NADESs) as quaternary ammonium salts and natural compounds such as amino acids, polyols, sugars, organic acids, amides, amines, and diols. NADES exhibit superior extraction properties compared to DESs, effectively solubilizing both polar and non-polar compounds. This enhancement is primarily due to their unique physicochemical properties, such as adjustable viscosity, tunable polarity, and the capacity for strong intermolecular hydrogen bonding interactions.²³ Therefore, varying the HBA/HBD composition and molar ratio of the solvent to optimize for each type of target compound. In addition, their role as a stabilizing medium for oxidation-sensitive substances makes them very valuable in many scientific and industrial applications.²⁴ Some types of NADES in the extraction of bioactive compounds are presented in Table 1.

Table 1.

Some types of NADES in the extraction of bioactive compounds.

Matrix	HBA	HBD	Molar ratio	Water content (%, v/v)	Target compounds	Ref.
Blueberry pomace	Choline chloride	1,4-butanediol	1:3	20	Anthocyanins polyphenols	²⁵
Curcuma longa L.	Choline chloride	Lactic acid	1:1	20	Curcuminoids	²⁶
Melia azedarach	Choline chloride	Glycerol	2:1	_	Total phenolic content Total flavonoid content	²⁷
Rubia truppeliana and R. cordifolia fruit	Choline chloride	Lactic acid	1:1	10	Flavonoids	²⁸
Lemon peel wastes	Choline chloride	Acetic acid	1:2	15	Flavonoids	²⁹
Orange pomace	Choline chloride	Lactic acid	1:3	20	Hydroxycinnamic acids, flavanones, flavones, flavonols, and limonoids	³⁰
Vitis davidii Foex. pomace	Choline chloride	Glycerol	1:2	35	Anthocyanins	³¹
Black mulberry fruit	Choline chloride	Lactic acid	1:2	40	Phenolics and flavonoids	³²
Date palm seeds	Choline chloride	Lactic acid	1:2	20	Polyphenols	³³
Moringa oleifera L. leaves	L-Proline	Glycerol	2:5	30	Total phenolic content Total flavonoid content	³⁴
Gentiana asclepiadea L. biowaste	Choline chloride	1,2-propanediol	1:3	20	Gentiopicroside, isovitexin, and isogentisin	¹³
Javanese turmeric (Curcuma xanthorrhiza Roxb.)	Choline chloride	Malic acid	1:1	25	Curcuminoids and xanthorrhizol	¹⁴
Codonopsis pilosula Franch	Lactic acid	d-Glucose	2:1	20	Phenolics, flavonoids, and terpenoids	³⁵

Composition of NADES

The composition of NADES is one crucial aspect. It depends on selecting HBDs and hydrogen bond acceptors (HBAs). The combination of these components determines the solvent's polarity, hydrogen bonding capacity, and chemical compatibility with target compounds, which are critical for efficient extraction. Studies have shown that the viscosity of NADES can vary significantly based on the specific HBDs used and their respective concentrations. Higher concentrations of HBDs tend to increase viscosity, which can adversely affect the extraction efficiency of bioactive compounds.³⁶

Molar ratio of HBD to HBA

The molar ratio of HBD to HBA is another factor that directly affects the physical and chemical properties of NADES. Adjusting this ratio alters the solvent's hydrogen-bonding capacity and polarity, thereby influencing its selectivity toward specific compounds. An inappropriate ratio can result in an unstable solvent or reduced solubilizing power, leading to poor extraction efficiency.³⁷

Water content in NADES

Another critical factor is the water content in NADES. Water significantly affects viscosity and solubility. While a small amount of water can lower viscosity and improve mass transfer, enhancing solubility and extraction efficiency, excessive water may dilute the eutectic characteristics of NADES, reducing its effectiveness.³⁸

Ultrasound-assisted extraction (UAE)

UAE is a technique that utilizes ultrasonic waves to enhance the extraction of bioactive compounds from plant materials. This method primarily operates through three mechanisms: cavitation, cell disruption, and enhanced mass transfer. When ultrasonic waves are applied, gel-like cavitation occurs, leading to the formation, growth, and eventual collapse of bubbles within the liquid medium. This process disrupts plant cell structures and facilitates the release of intracellular compounds into the solvent, thus enhancing extraction yields while preserving bioactivity.^39,40

Compared with conventional extraction approaches, UAE offers several advantages, including shorter extraction times, reduced solvent consumption, improved extraction efficiency, and reduced thermal degradation at lower operating temperatures.^9,41 However, significant limitations are associated with its implementation, particularly regarding temperature control during high-power ultrasound operations. High-frequency ultrasound generates localized heating, which can lead to the decomposition of sensitive bioactive compounds. Therefore, optimizing operating factors such as power, time, solid-to-liquid ratio, and pulse cycle is essential to achieve high efficiency without compromising biological activity.⁴² Some combined extraction processes of UAE and NADES are presented in Table 2.

Table 2.

Some combined extraction processes of UAE and NADES.

Matrix	UAE	Time (minutes)	Power	SLR (mL:g)	Pulse cycle	Target compounds	Ref.
Spent coffee grounds	An ultrasonic probe	30	90 W	20:1	-	Caffeine	⁴³
Orange pomace	An ultrasound probe	5	130 W; 30% amplitude	2:0.76	-	Hydroxycinnamic acids, flavanones, flavones, flavonols, and limonoids	³⁰
Melia azedarach	An ultrasound probe	20	130 W	50:1	-	Total phenolic content Total flavonoid content	²⁷
Lemon peel wastes	An ultrasonic probe	5	320 W	20:1	-	Flavonoids	²⁹
Gardenia fruits	An ultrasonic probe	2	400 W	40:1	50%	Crocins	⁴⁴
Vitis davidii Foex. pomace	An ultrasonic probe	40	420 W	30:1	-	Anthocyanins	³¹
Vegetable oil	An ultrasonic probe	2.5	150 W; 20 kHz	9:1	83.3%	Biodiesel	⁴⁵
Carobs	An ultrasonic probe	10	500 W; 20 kHz	25:1	50%	Total phenolic content	⁴⁶
Pomegranate peel	An ultrasonic probe	8	The intensity level of 59.2 W/cm²	50:1	50%	Total phenolic content	⁴⁷
Grapefruit peel	An ultrasonic probe	51.8	800 W; 20 kHz	50:1	50%	Pectin	⁴⁸
Curcuma longa	An ultrasonic probe	20	The intensity level of 70.8 W/cm²	20:1	60%	Curcuminoids	²⁶
Glycyrrhizaglabra	An ultrasonic probe	15	2.66 W/cm³ acoustic density	30:1	50%	Glycyrrhizic Acid	⁴⁹
Gentiana asclepiadea L. biowaste	An ultrasonic bath	40	320 W; 35 kHz	10:1	-	Gentiopicroside, isovitexin, and isogentisin	¹³
Black mulberry fruit	An ultrasonic bath	15	300 W	60:1	-	Phenolics and flavonoids	³²
Javanese turmeric (Curcuma xanthorrhiza Roxb.)	An ultrasonic bath	20	170 W; 60 kHz	15:1	-	Curcuminoids and xanthorrhizol	¹⁴
Rubia truppeliana and R. cordifolia fruit	An ultrasonic cleaner	20	600 W; 40 kHz	30:1	-	Flavonoids	²⁸
Blueberry pomace	An ultrasonic cleaner	30	700 W; 40 kHz	25:1	-	Anthocyanins Polyphenols	²⁵
Date palm seeds	The ultrasound bath	30	-	10:1	-	Polyphenols	³³
Moringa oleifera L. leaves	An ultrasonic bath	30	320 W	10:1	-	Total phenolic content Total flavonoid content	³⁴

Ultrasonic power

The power of the ultrasound waves is a critical factor influencing extraction efficiency. Higher ultrasonic power levels can enhance the mechanical forces acting on the plant matrix, leading to more effective cell disruption and increased extraction rates.⁵⁰ However, there is a threshold beyond which further increases in power may not yield proportional increases in extraction efficiency and may instead cause detrimental effects on the extracted compounds.⁵¹ Ultrasonic extraction methods, particularly those using ultrasonic baths and probes, have attracted considerable attention in contemporary research due to their significant impact on extraction efficiency. The differences in ultrasonic energy output between these systems significantly affects the extraction efficiency. The ultrasonic probe, which emits higher intensity ultrasonic waves than the ultrasonic bath, plays an important role in improving the extraction efficiency.⁵² Higher intensity triggers stronger cavitation, characterized by the formation and collapse of microbubbles, facilitating the disruption of cell structure. This disruption increases the contact area between the solvent and the target compound, thereby improving mass transfer and extraction efficiency. In an ultrasonic bath, cavitation occurs indirectly and is often less intense, creating favorable conditions to prevent thermal decomposition of thermosensitive compounds, but may not achieve the same extraction efficiency as direct sonication from an ultrasonic probe. Hassan et al. demonstrated that extraction by an ultrasonic probe achieved higher efficiency than extraction by an ultrasonic bath.⁴³ This observation was also confirmed by Jana Šic Žlabur et al. when extracting nettle.⁵³ Table 2 shows that the optimal power varies depending on the matrix properties, solvents, and target compounds profile.

Ultrasonic time

Ultrasonic time plays a crucial role in the extraction process. Long-term sonication time enhances the release of target compounds by facilitating greater disruption of plant cells, thereby increasing yield.⁵⁴ However, prolonged exposure may also result in the degradation of thermolabile bioactive compounds due to excessive heat generation and the formation of free radicals. Consequently, optimizing the extraction time is essential to maximize yield while preserving the structural stability and functional properties of the extracted compounds.⁵⁵ As shown in Table 2, the optimal UAE durations were generally short (2–40 min), reflecting the strong enhancing effect of the UAE system in reducing extraction time compared to conventional methods.

Solid-to-liquid ratio (SLR)

The solid-to-liquid ratio is a vital variable that significantly impacts the extraction efficiency of UAE. Various studies highlight the interplay between solid-to-liquid ratio and extraction yield, indicating optimal ranges for achieving maximum efficiency. A study by Tan et al. emphasized that a solid-to-liquid ratio of 1:10 was optimal for the extraction of paclitaxel, as higher ratios (1:5) did not enhance yield, and lower ratios led to inefficient energy dispersion, affecting cavitation and consequently the extraction process.⁵⁶ This finding is supported by the work of Omar et al., which suggests that while a larger solvent-to-solid ratio generally favors mass transfer due to a concentration gradient, excessive solvent relative to solid can lead to diminishing returns in extracting efficacy.⁵⁷ However, black mulberry fruit was optimally extracted at an SLR value of 1:60,³² melia azedarach at 1:50,²⁷ gardenia fruits at 1:40,⁴⁴ and grape pomace at 1:30.³¹ This highlights the need to adjust the SLR value according to plant morphology and solvent properties.

Pulse cycle

Pulse duration is the time the ultrasound probe remains in the “on” state while pulse interval is the time the ultrasound probe remains in the “off” state. The use of pulsed ultrasound, as opposed to continuous exposure, has been shown to provide additional control over temperature fluctuations, thereby improving extraction efficiency and preserving bioactive compound integrity.^45,46 This approach minimizes the erosion of ultrasound probe tips and allows for better temperature control, which is particularly advantageous for heat-sensitive compounds that may decompose or lose their antioxidant capacity under prolonged or elevated temperatures.⁴⁶ Moreover, the duty cycle of ultrasound application can be optimized to further enhance extraction outcomes. Duty cycle adjustments effectively regulate exposure time to sonication, leading to improved extraction efficiencies while also mitigating possible damage to delicate compounds.^45,52 It can be seen from Table 2 that the ultrasonic pulse parameter at 50% usually gives the optimum extraction value.

Microwave-assisted extraction (MAE)

MAE utilizes microwave energy to enhance the extraction of bioactive compounds from plant materials. The fundamental mechanism of MAE is based on dielectric heating, which occurs when microwave radiation interacts with polar molecules in both the solvent and the plant matrix. This interaction leads to rapid heating, resulting in the disruption of cell walls and the release of bioactive compounds into the solvent, thus accelerating the extraction process.⁵⁸ MAE offers several advantages over conventional methodologies, enhancing the efficiency and effectiveness of extraction processes. The foremost benefits include significantly shorter extraction times, direct and uniform heating, and reduced energy and solvent consumption.^59,60 However, the technique also entails challenges, particularly the risk of thermal degradation of thermo-sensitive compounds.⁶¹ Critical parameters that must be optimized include microwave power, extraction time, and solvent to solid ratio.⁶² Some combined extraction processes of MAE and NADES are presented in Table 3.

Table 3.

Some combined extraction processes of MAE and NADES.

Matrix	Time	Power	SLR (mL : g)	Target compounds	Ref.
Blueberry by-products	30 minutes	800 W	20:1	Anthocyanins polyphenols	¹²
Centella asiatica (L.) Urb. (CA)	30 seconds	300 W	20:1	Madecassoside Asiaticoside	¹¹
Mitragyna speciosa (Korth.) Havil leaves	20 minutes	60% W microwave power	20:1	Total polyphenol content	⁶³
Urtica dioica	10 minutes	300 W	13:1	Total polyphenol content & Total flavonoid content	⁶⁴
Brewer'sSpent Grains	13.30 minutes	700 W	10:1	Total polyphenol content	⁶⁵
Eleutherine bulbose (Mill.) Bulb	15 minutes	270 W	8: 1	Total polyphenol content	⁶⁶
Olive pomace	30 minutes	200 W	12.5: 1	Total polyphenol content	⁶⁷

Microwave power

Microwave power plays a crucial role in the extraction of bioactive compounds, significantly influencing both the efficiency of extraction and the integrity of thermolabile compounds. Higher microwave power enhances the heating rate, which accelerates the disruption of cellular structures, thereby improving extraction efficiency.⁶⁸ However, while higher microwave power can enhance extraction efficiency, it also poses risks of degrading sensitive compounds due to overheating.⁶⁹

Microwave time

The duration of microwave exposure is a critical factor influencing both the yield and integrity of bioactive compounds extracted from various plant materials. Research indicates that while prolonged microwave exposure can enhance the extraction efficiency of these compounds, excessive exposure may lead to thermal degradation and alterations in their chemical composition.⁷⁰

Solid-to-liquid ratio

The solid-to-liquid ratio is a critical factor affecting the efficiency of microwave-assisted extraction (MAE) of active compounds from plant materials. The impact of SLR on extraction efficiency is primarily attributable to changes in the concentration gradient between the solid material and solvent, which enhances mass transfer and elution of specific compounds.⁷¹ As indicated by Dinardo et al., a higher SLR increases the total phenolic content in various plant materials by increasing the concentration gradient, further accelerating mass transfer.⁷² This phenomenon suggests that optimal extraction efficiency is closely tied to the careful selection of SLR.

Hybrid and sequential approaches (UAE + MAE)

The interaction between UAE and microwave-assisted extraction (MAE) in conjunction with NADES represents a growing area of study, remarkably as preliminary results suggest that their complementarity can yield significantly higher extraction efficiencies compared to each method executed in isolation.^73–77 A better understanding of the synergistic mechanism is critical for optimizing extraction efficiencies and enhancing the overall sustainability of extraction processes.

Central to the combination between the UAE and MAE is the phenomenon of cavitation, which is primarily associated with ultrasound. During UAE, cavitation leads to the formation of microbubbles that collapse violently, generating intense local heating and high shear forces, which can disrupt plant matrices and enhance mass transfer.⁷⁸ This energy input is compounded when integrated with MAE, which provides a uniform heating mechanism that promotes solute dissolution into the solvent at elevated temperatures. The structural properties of NADES, positively influenced by the cavitation effect, enhance the solvent's capacity to penetrate and extract phenolic compounds from plant materials.³²

The interplay between viscosity and microwave heating necessitates further investigation. The viscous nature of concentrated NADES might inhibit the diffusion of solutes under microwave assistance; however, the application of UAE could enhance penetration and reduce effective viscosity, thereby enabling more efficient extraction.^26,79 This highlights the importance of fine-tuning the ratio of NADES constituents and water content to maximize the efficacy of both extraction techniques.⁷⁴ Some extraction processes combine UAE and MAE sequentially with NADES are presented in Table 4.

Table 4.

Some extraction processes combine UAE and MAE sequentially with NADES.

Matrix	Solvent	UAE system	MAE system	Key findings	Ref.
Date seed	Choline chloride and ethylene glycol (1:2)	An ultrasonic bath; SLR: 1/30 (w/v); T: 50 °C; t: 50 mins; amplitude: 80%	SLR: 1/30 (w/v); T: 50 °C; t:10 mins; P: 600 W	Sequential hybridization techniques enhance the extraction efficiency of bioactive compounds more efficiently than single green techniques	⁷⁶
Codonopsis pilosula	Lactic acid and glucose (2:1)	SLR: 1/80 (w/v); T: 30 °C; t: 10 mins; P: 300 W	SLR: 1/50 (w/v); P: 240 W; t: 4 mins	UMAE increased the extraction efficiency of bioactive compounds with an SLR of 1/40 (w/v), sonication time of 5 min, and microwave time of 4 min	³⁵
Abelmoschus sagittifolius (Kurz) Merr roots	Citric acid and glucose (2:1)	SLR: 1/40 (w/v); T: 30 °C; t: 5 mins; P: 150 W	SLR: 1/50 (w/v); t: 2 mins; P: 400 W	Highest phenolic content when SLR was 1/40 with 5 min ultrasound and 4 min microwave	⁷⁴

Optimization in NADES-UAE/MAE

Optimization is a crucial step in ensuring high performance and environmental sustainability of NADES assisted ultrasonic and microwave extraction (UAE/MAE) processes. The complexity of these systems arises from multiple interdependent factors, such as solvent composition, solid-to-liquid ratio, temperature, extraction time, and applied power, which influence process performance, selectivity, and environmental friendliness. Over the past decade, optimization strategies have evolved dramatically from traditional approaches to advanced hybrid and multi-objective models.

Classical approaches: One-factor-at-a-time, Taguchi, RSM

The one-factor-at-a-time (OFAT) method has long been the basis for optimization studies in many extraction processes, including those using NADES. However, the inefficiency of this method and its failure to account for multi-factor interactions have made it less popular in modern optimization practices. To address these challenges, more sophisticated methods such as the Design of Experiments (DoE) framework have gained attention. Among them, the Taguchi method and Response Surface Methodology (RSM) are particularly notable for their ability to streamline experimental design, increase efficiency, and improve the robustness of the optimization process.

The Taguchi method uses orthogonal arrays to dramatically reduce the number of experimental runs required while allowing researchers to identify the most influential parameters with increased statistical power.⁸⁰ Several studies have showcased the effectiveness of Taguchi designs in optimizing extraction processes.^81–83 In contrast, RSM offers a more complex approach by developing predictive polynomial models that capture interactions among variables, as illustrated by contour plots. This method has been widely used to optimize extraction parameters affecting total phenolic content (TPC) and total flavonoid content (TFC) in studies involving NADES.^25,32,34 Additionally, RSM's interactive modeling capabilities enable a deeper understanding of how multifactorial changes affect extraction efficiency. Together, the Taguchi method and RSM establish a robust statistical framework for NADES-based extraction optimization, allowing them to leverage their unique properties to enhance mass transfer and extraction efficiencies. These optimizations not only improve efficiency but also support environmentally sustainable extraction methods in food and pharmaceuticals, providing a comprehensive approach to modern extraction.

Advanced approaches: ANN, machine learning, hybrid Taguchi Grey, desirability function

As NADES systems become increasingly complex, researchers have turned to advanced computational approaches. Artificial neural networks (ANNs) and broader machine learning algorithms can capture highly nonlinear and multidimensional relationships between process variables and responses, often outperforming traditional regression models in predictive accuracy. ANNS operate under a framework that involves processing elements, or neurons, that excel at approximating any function. This enables them to model complex phenomena and relationships without presuppositions about the underlying data distributions or the nature of the phenomena involved.⁸⁴

Hybrid methods, such as Taguchi Grey relational analysis, have also been adopted to integrate the efficiency of Taguchi screening with the ability of Grey analysis to rank multiple responses simultaneously.⁸⁵ Additionally, the desirability function approach enables researchers to convert multiple response variables into a single composite score, facilitating simultaneous optimization of yield, antioxidant activity, and other targets. This methodology, originating in the foundational work of Harrington and further refined by Derringer and Suich, facilitates the simultaneous optimization of multiple performance metrics, including yield and antioxidant activity.⁸⁶ By transforming quantitative responses into desirability scores, researchers can effectively evaluate and compare the effectiveness of their experimental outcomes, ensuring that each response variable is considered within the optimization framework. These advanced approaches reflect a shift from experimental trial-and-error toward data-driven, predictive optimization.

Integrating greenness assessment into optimization is another emerging trend. For example, Georgia D. Ioannou et al.⁸⁷ combined RSM with AGREE metrics to evaluate the NADES-UAE of phenolic extraction from prickly pear peels, demonstrating that optimal conditions should consider not only yield but also solvent biodegradability and process eco-efficiency.⁸⁷ Such approaches shift optimization from purely technical outcomes toward frameworks that address real-world constraints and sustainability goals.

Green assessment tools

The application of environmentally friendly solvents and energy-efficient extraction technologies, such as NADES combined with Ultrasound- and Microwave-Assisted Extraction (UAE and MAE), requires a systematic “green” assessment. Green assessment tools provide quantitative or semi-quantitative metrics that translate the twelve principles of Green Analytical Chemistry (GAC) into operational indicators of environmental performance. These metrics allow researchers to balance efficiency (yield, selectivity, and activity) with sustainability (energy use, toxicity, waste generation, and recyclability). Among the many methods proposed over the past decade, the Analytical Eco-Scale, the GAPI, and the Analytical Greenness Index (AGREE) have become the most widely adopted frameworks for evaluating green extraction and analytical processes.

Analytical Eco-Scale

The Analytical Eco-Scale is a semi-quantitative tool developed by Gałuszka et al.⁸⁸ to estimate the overall environmental impact of an analytical or extraction method. The system assumes an ideal score of 100 points for a completely environmentally friendly process, then subtracts “penalty points” for each environmentally unfriendly feature, such as the use of toxic reagents, excessive solvents, high energy consumption, or waste generation. The Eco-Scale score is thus expressed as:

Eco - scale score = 100 - \sum p e n a l t y p o i n t s

⁸⁸

If the score is greater than 75, it is considered an excellent green method. If the score is between 50 and 75, it is regarded as an acceptable green method. If the score is below 50, it is considered inadequate greenness.⁸⁸

Eco-Scale provides a simple, reproducible, and transparent scoring system suitable for comparing extraction conditions or solvent types.⁸⁹ However, the system remains semi-quantitative and somewhat subjective, as penalty values depend on expert judgment. It also does not take into account life-cycle aspects (e.g., solvent recovery, equipment manufacturing) or multi-criteria trade-offs between productivity and environmental friendliness.⁹⁰

Green analytical procedure index (GAPI)

GAPI was proposed by Płotka-Wasylka in 2018.¹⁷ It provides a comprehensive visual assessment of the greenness of the entire workflow, from sampling and sample preparation to analysis and waste management. GAPI uses a chart divided into five zones (sample collection, solvent/reagent type, equipment, energy consumption and waste), each zone coded with three colors (green = low impact, yellow = medium, red = high impact). The end result is a pentagonal color scheme that summarizes the overall sustainability profile.

GAPI provides a visual representation of which process stages are environmentally critical, helping researchers identify “red zones” for improvement.⁹¹ Unlike Eco-Scale, GAPI does not provide a single score, which can complicate ranking across multiple methods. Furthermore, because GAPI was originally designed for analytical processes rather than extraction processes, certain criteria (e.g., solvent recyclability, solvent viscosity, or recovery) must be adjusted when applied to NADES-based extraction methods.

Analytical GREEnness metric (AGREE)

AGREE, developed by Pena-Pereira et al.,⁹² is a software-assisted tool that translates the twelve principles of Green Analytical Chemistry into twelve quantitative indicators (each ranging from 0 to 1). The program calculates an overall AGREE score (0–1) and generates a radar-like pie chart, where each segment corresponds to a GAC principle. Colors range from red (low compliance) to green (high compliance), providing a visual assessment of sustainability.

The AGREE method has emerged as a useful tool for quantitative assessment and comparison of green analysis, especially when compared with existing indices such as GAPI and Ecoscale. One of the main advantages of this method is its ability to provide numerical scores along with graphical representations, which enhances the reproducibility of comparisons between different analysis methods, making it easier for users to identify specific weaknesses, such as excessive energy use and poor waste management practices.⁹³ However, the AGREE metric is based on a comprehensive input dataset, requiring extensive data collection, which may not always be feasible under all laboratory conditions.⁹⁴ To address this limitation, AGREEprep (2022) was introduced for green sample preparation, which includes ten specialized principles such as miniaturization, automation, and matrix simplification. This version is particularly suitable for evaluating extraction stages before instrumental analysis.⁹⁵

Future perspectives

The rapid growth of research on NADES-based ultrasound- and microwave-assisted extraction (USAE) systems has highlighted their great potential as an environmentally friendly, energy-efficient, and tunable alternative to conventional organic solvent techniques. There is growing evidence that combining NADES with UAE or microwave-assisted extraction (MAE) can significantly improve the recovery of phenolics, flavonoids, terpenoids, and other bioactive molecules from plant-derived extraction platforms. Despite these advances, the transition of NADES-UAE/MAE from laboratory-scale demonstration models to standardized, industry-ready green extraction platforms remains challenging due to several unaddressed methodological and conceptual gaps that require systematic attention.

A key priority for future research is the harmonization and standardization of greenness assessment indicators. Although existing studies use a variety of assessment frameworks, such as the Analytical Greenness Index (AGREE), the GAPI, and the Ecoscale, these tools are often applied inconsistently across experimental settings, with significant differences in scoring criteria, reporting formats, and assessment depth. This heterogeneity reduces comparability across studies and makes it difficult to assess the environmental performance of the UAE/MAE based on NADES compared to traditional extraction methods. To overcome this limitation, an integrated, widely applicable greenness assessment protocol that synthesizes multiple indicators into a unified composite index is urgently needed. Such a standardized framework would allow for transparent quantification of solvent biodegradability, energy consumption, carbon emissions, solvent recovery efficiency, and waste generation. Doing so would not only enhance reproducibility in academic research but also strengthen the reliability and regulatory acceptability of NADES-enabled technologies in industrial settings.

A second important future direction involves mechanistic elucidation of synergistic effects in hybrid or sequential UAE–MAE extraction systems. Experimental evidence consistently shows that combining ultrasonic cavitation with microwave dielectric heating can improve mass transfer, reduce solvent viscosity, accelerate cell wall disruption, and significantly shorten extraction times. However, the fundamental physicochemical interactions responsible for these synergistic effects, especially in the presence of the highly structured NADES hydrogen-bonded network, remain poorly understood. Improving this understanding will require a combination of experimental techniques with computational modeling. Molecular dynamics simulations, quantum chemical calculations, and mesoscale modeling can clarify how microwave cavitation, localized hot spots, and microwave polarization fields perturb the NADES molecular architecture and facilitate matrix–solvent interactions. At the same time, in situ and real-time monitoring methods, such as acoustic pore mapping, infrared thermography, high-speed optical imaging, dielectric profiling, and dynamic viscosity measurements, will enable direct observation of energy dissipation pathways and solvent-matrix interactions during the extraction process. The integration of these methods has the potential to shift the field from empirical parameter tuning to predictive, mechanism-based process design, thus enabling rational optimization of NADES-UAE/MAE for a wide range of biomass feedstocks.

Conclusion

The evolution from classical approaches, such as Taguchi orthogonal arrays and RSM, toward more sophisticated, data-driven computational tools. While traditional designs remain effective for preliminary screening, the field is increasingly leveraging advanced analytics, including Artificial Neural Networks (ANN), hybrid Taguchi-Grey relational analysis, and desire-function-based models, to capture non-linear interactions and optimize complex matrices with greater precision. This methodological evolution is increasingly coupled with the rigorous application of standardized green metrics, such as the Analytical Greenness metric (AGREE), the GAPI, and the Eco-scale. The integration of these multi-objective optimization frameworks will address the essential dual task of maximizing mining productivity and performance while balancing energy efficiency and environmental impact. By embedding these comprehensive, sustainability-oriented principles into the early stages of process design, researchers provide a clear, evidence-based pathway for upscaling Natural Deep Eutectic Solvent-based Ultrasound/Microwave-Assisted Extraction (NADES-UAE/MAE) technologies from laboratory-scale proofs of concept to economically viable, industry-relevant solutions.

Footnotes

Acknowledgments

The authors gratefully acknowledge financial support from the National Science and Technology Council in Taiwan and the research infrastructure support for this work from National Chi Nan University.

ORCID iDs

Quang-Chi Bui

Chih-Chi Yang

Yung-Pin Tsai

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The data is available upon request.

Footnote

Declaration of generative AI and AI-assisted technologies in the writing process. During the preparation of this work, the author(s) used ChatGPT to improve the readability of certain sections. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the publication.

References

Mishra

Siwal

Nayaka

, et al. Waste-to-chemicals: green solutions for bioeconomy markets. Sci Total Environ 2023; 887: 164006.

Capanoglu

Nemli

Tomas-Barberan

. Novel approaches in the valorization of agricultural wastes and their applications. J Agric Food Chem 2022; 70: 6787–6804.

Sharma

Sridhar

Gupta

, et al. Greener technologies in agri-food wastes valorization for plant pigments: step towards circular economy. Curr Res Green Sustain Chem 2022; 5: 100340.

Geissdoerfer

Savaget

Bocken

NMP

, et al.

The circular economy – a new sustainability paradigm?

J Cleaner Prod 2017; 143: 757–768.

Choi

Verpoorte

. Green solvents for the extraction of bioactive compounds from natural products using ionic liquids and deep eutectic solvents. Curr Opin Food Sci 2019; 26: 87–93.

Dai

van Spronsen

Witkamp

G-J

, et al. Natural deep eutectic solvents as new potential media for green technology. Anal Chim Acta 2013; 766: 61–68.

Liu

Friesen

McAlpine

, et al. Natural deep eutectic solvents: properties, applications, and perspectives. J Nat Prod 2018; 81: 679–690.

Ruesgas-Ramón

Figueroa-Espinoza

Durand

. Application of deep eutectic solvents (DES) for phenolic compounds extraction: overview, challenges, and opportunities. J Agric Food Chem 2017; 65: 3591–3601.

Chémat

Zill-e-Huma Khan

. Applications of ultrasound in food technology: processing, preservation and extraction. Ultrason Sonochem 2011; 18: 813–835.

10.

Chy

MWR

Ahmed

Iftekhar

, et al. Optimization of microwave-assisted polyphenol extraction and antioxidant activity from papaya peel using response surface methodology and artificial neural network. Appl Food Res 2024; 4: 100591.

11.

Phaisan

Makkliang

Putalun

, et al. Development of a colorless Centella asiatica (L.) Urb. extract using a natural deep eutectic solvent (NADES) and microwave-assisted extraction (MAE) optimized by response surface methodology. RSC Adv 2021; 11: 8741–8750.

12.

Alchera

Ginepro

Giacalone

. Microwave-assisted extraction (MAE) of bioactive compounds from blueberry by-products using a sugar-based NADES: a novelty in green chemistry. LWT 2024; 192: 115642.

13.

Jovanović

Milutinović

Radan

, et al. Ultrasound-assisted natural deep eutectic solvents (NaDES) extraction of gentiopicroside, isovitexin, and isogentisin from Gentiana asclepiadea L. biowaste. Sustain Chem Pharm 2024; 42: 101808.

14.

Ariestanti

Mun’im

Hartrianti

, et al. Ultrasonic-assisted extraction (UAE) of Javanese turmeric rhizomes using natural deep eutectic solvents (NADES): screening, optimization, and in vitro cytotoxicity evaluation. Ultrason Sonochem 2025; 114: 107271.

15.

Ahmed

Yub Harun

Waqas

, et al. Optimization of operational parameters using artificial neural network and support vector machine for bio-oil extracted from rice husk. ACS Omega 2024; 9: 26540–26548.

16.

Puma-Isuiza

García-Chacón

Osorio

, et al. Extraction of phenolic compounds from lucuma (Pouteria lucuma) seeds with natural deep eutectic solvents: modelling using response surface methodology and artificial neural networks. Front Sustain Food Syst 2024; 8: 1401825.

17.

Płotka-Wasylka

. A new tool for the evaluation of the analytical procedure: Green Analytical Procedure Index. Talanta 2018; 181: 204–209.

18.

Martins

MAR

Pinho

Coutinho

JAP

. Insights into the nature of eutectic and deep eutectic mixtures. J Solution Chem 2019; 48: 962–982.

19.

Abbott

Capper

Davies

, et al. Novel solvent properties of choline chloride/urea mixtures electronic supplementary information (ESI) available: spectroscopic data. Chem Commun 2003; 1: 70–71.

20.

Kalhor

Ghandi

. Deep eutectic solvents for pretreatment, extraction, and catalysis of biomass and food waste. Molecules 2019; 24: 4012.

21.

Zdanowicz

Wilpiszewska

Spychaj

. Deep eutectic solvents for polysaccharides processing. A review. Carbohydr Polym 2018; 200: 361–380.

22.

Choi

van Spronsen

Dai

, et al.

Are natural deep eutectic solvents the missing link in understanding cellular metabolism and physiology?

Plant Physiol 2011; 156: 1701–1705.

23.

Paiva

Craveiro

Aroso

, et al. Natural deep eutectic solvents – solvents for the 21st century. ACS Sustain Chem Eng 2014; 2: 1063–1071.

24.

Bener

Şen

Önem

, et al. Microwave-assisted extraction of antioxidant compounds from by-products of Turkish hazelnut (Corylus avellana L.) using natural deep eutectic solvents: modeling, optimization and phenolic characterization. Food Chem 2022; 385: 132633.

25.

Zhang

X-J

Liu

Z-T

Chen

X-Q

, et al. Deep eutectic solvent combined with ultrasound technology: a promising integrated extraction strategy for anthocyanins and polyphenols from blueberry pomace. Food Chem 2023; 422: 136224.

26.

Patil

Pathak

Rathod

. Optimization and kinetic study of ultrasound assisted deep eutectic solvent based extraction: a greener route for extraction of curcuminoids from Curcuma longa. Ultrason Sonochem 2021; 70: 105267.

27.

Jamshaid

Ahmed

. Optimization of ultrasound-assisted extraction of valuable compounds from fruit of Melia azedarach with glycerol-choline chloride deep eutectic solvent. Sustain Chem Pharm 2022; 29: 100827.

28.

Chen

X-Q

Z-H

Liu

L-L

, et al. Green extraction using deep eutectic solvents and antioxidant activities of flavonoids from two fruits of Rubia species. LWT 2021; 148: 111708.

29.

Chaves

de Souza Mesquita

Strieder

, et al. Eco-friendly and high-performance extraction of flavonoids from lemon peel wastes by applying ultrasound-assisted extraction and eutectic solvents. Sustain Chem Pharm 2024; 39: 101558.

30.

Plaza

Marina

. Natural deep eutectic solvents and ultrasound-assisted extraction for the recovery of antioxidant phenolic compounds from orange pomace. Microchem J 2025; 212: 113366.

31.

Zhang

Lin

Zhang

, et al. Ultrasound-assisted natural deep eutectic solvent extraction of anthocyanin from Vitis davidii Foex. Pomace: optimization, identification, antioxidant activity and stability. Heliyon 2024; 10: e33066.

32.

Pham

Weina

, et al. Green extraction of phenolics and flavonoids from black mulberry fruit using natural deep eutectic solvents: optimization and surface morphology. BMC Chem 2023; 17: 119.

33.

Alfaleh

Sindi

. Systematic study on date palm seeds (Phoenix dactylifera L.) extraction optimisation using natural deep eutectic solvents and ultrasound technique. Sci Rep 2024; 14: 16622.

34.

Chen

, et al. Deep eutectic solvent-based ultrasonic-assisted extraction of phenolic compounds from Moringa oleifera L. leaves: optimization, comparison and antioxidant activity. Sep Purif Technol 2020; 247: 117014.

35.

Nguyen Nguyen

, et al. Extracting phenolics, flavonoids, and terpenoids from Codonopsis pilosula using green solvents. Sustain Chem Pharm 2024; 37: 101395.

36.

Tian

Row

. Evaluation of alcohol-based deep eutectic solvent in extraction and determination of flavonoids with response surface methodology optimization. J Chromatogr, A 2013; 1285: 22–30.

37.

Altamash

Atilhan

Aliyan

, et al. Rheological, thermodynamic, and gas solubility properties of phenylacetic acid-based deep eutectic solvents. Chem Eng Technol 2017; 40: 778–790.

38.

Dai

Witkamp

G-J

Verpoorte

, et al. Tailoring properties of natural deep eutectic solvents with water to facilitate their applications. Food Chem 2015; 187: 14–19.

39.

Azmir

Zaidul

ISM

Rahman

, et al. Techniques for extraction of bioactive compounds from plant materials: a review. J Food Eng 2013; 117: 426–436.

40.

Ashokkumar

. Applications of ultrasound in food and bioprocessing. Ultrason Sonochem 2015; 25: 17–23.

41.

Ötleş

. Handbook of food analysis instruments. Boca Raton (FL): CRC press, 2009.

42.

Turksever

Benzer Gurel

Sahiner

, et al. Effects of green extraction methods on antioxidant and antimicrobial properties of artichoke (Cynara scolymus L.) leaves. Food Technol Biotechnol 2024; 62: 279–291.

43.

Hassan

Al Yaqoobi

. Assessment of ultrasound-assisted extraction of caffeine and its bioactivity. J Ecol Eng 2023; 24: 126–133.

44.

Huang

Zhu

, et al. Integrated natural deep eutectic solvent and pulse-ultrasonication for efficient extraction of crocins from gardenia fruits (Gardenia jasminoides Ellis) and its bioactivities. Food Chem 2022; 380: 132216.

45.

Martinez-Guerra

Gude

. Continuous and pulse sonication effects on transesterification of used vegetable oil. Energy Convers Manage 2015; 96: 268–276.

46.

Christou

Stavrou

Kapnissi-Christodoulou

. Continuous and pulsed ultrasound-assisted extraction of carob’s antioxidants: processing parameters optimization and identification of polyphenolic composition. Ultrason Sonochem 2021; 76: 105630.

47.

Pan

, et al. Continuous and pulsed ultrasound-assisted extractions of antioxidants from pomegranate peel. Ultrason Sonochem 2012; 19: 365–372.

48.

Zhang

Bailina

, et al. Effects of ultrasound and/or heating on the extraction of pectin from grapefruit peel. J Food Eng 2014; 126: 72–81.

49.

Lanjekar

Rathod

. Application of ultrasound and natural deep eutectic solvent for the extraction of glycyrrhizic acid from Glycyrrhiza glabra : optimization and kinetic evaluation. Ind Eng Chem Res 2021; 60: 9532–9538.

50.

Rodríguez-Pérez

Gilbert-López

Mendiola

, et al. Optimization of microwave-assisted extraction and pressurized liquid extraction of phenolic compounds from Moringa oleifera leaves by multiresponse surface methodology. Electrophoresis 2016; 37: 1938–1946.

51.

Linares

Rojas

. Ultrasound-assisted extraction of natural pigments from food processing by-products: a review. Front Nutr 2022; 9: 891462.

52.

Kumar

Srivastav

Sharanagat

. Ultrasound assisted extraction (UAE) of bioactive compounds from fruit and vegetable processing by-products: a review. Ultrason Sonochem 2021; 70: 105325.

53.

Šic Žlabur

Radman

Opačić

, et al. Application of ultrasound as clean technology for extraction of specialized metabolites from stinging nettle (Urtica dioica L.). Front Nutr 2022; 9: 870923.

54.

Lou

Wang

Zhang

, et al. Improved extraction of oil from chickpea under ultrasound in a dynamic system. J Food Eng 2010; 98: 13–18.

55.

Anaya-Esparza

Ramos-Aguirre

Zamora-Gasga

, et al. Optimization of ultrasonic-assisted extraction of phenolic compounds from Justicia spicigera leaves. Food Sci Biotechnol 2018; 27: 1093–1102.

56.

Tan

Wang

, et al. Ultrasonic assisted extraction of paclitaxel from Taxus x media using ionic liquids as adjuvants: optimization of the process by response surface methodology. Molecules 2017; 22: 1483.

57.

Omar

Liu

Wang

. Effects of ultrasound-assisted extraction on yield of flaxseed oil, β- and γ- tocopherols optimized by orthogonal array design. Eur J Lipid Sci Technol 2014; 116: 1412–1420.

58.

Belwal

Ezzat

Rastrelli

, et al. A critical analysis of extraction techniques used for botanicals: trends, priorities, industrial uses and optimization strategies. TrAC, Trends Anal Chem 2018; 100: 82–102.

59.

Longarespatron

Canizaresmacias

. Focused microwaves-assisted extraction and simultaneous spectrophotometric determination of vanillin and p-hydroxybenzaldehyde from vanilla fragans. Talanta 2006; 69: 882–887.

60.

Lovrić

Putnik

Bursać Kovačević

, et al. The effect of microwave-assisted extraction on the phenolic compounds and antioxidant capacity of blackthorn flowers. Food Technol Biotechnol 2017; 55. DOI: 10.17113/ftb.55.02.17.4687.

61.

Crescente

Cascone

Sorrentino

, et al. Influence of extraction techniques on chemical composition, antioxidant and antifungal activities of Mentha spicata L. essential oil: a comparative study of microwave-assisted hydrodistillation and steam distillation. Food Biosci 2025; 69: 106939.

62.

Kheyar

Amiali

, et al. Impacts of microwave-assisted extraction parameters on total phenolic compounds yield from Algerian Moringa oleifera leaves, using response surface methodology. Nat Prod Res 2025; 39: 4126–4134.

63.

Prabowo

Agustina

Nur

, et al. Green and optimum extraction of total polyphenols content from Mitragyna speciosa Korth. Havil leaves using microwave- assisted natural deep eutectic solvent extraction. Phcog J 2022; 14: 29–38.

64.

Sahal

Hussain

Mishra

, et al. Microwave-assisted extraction of bioactive compounds from Urtica dioica using solvent-based process optimization and characterization. Sci Rep 2025; 15: 25375.

65.

López-Linares

Campillo

Coca

, et al. Microwave-assisted deep eutectic solvent extraction of phenolic compounds from brewer’s spent grain. J Chem Technol Biotechnol 2021; 96: 481–490.

66.

Yusuf

Astati

Ardana

, et al. Optimizing natural deep eutectic solvent citric acid-glucose based microwave-assisted extraction of total polyphenols content from Eleutherine bulbosa (Mill.) bulb. Indonesian Journal of Chemistry 2021; 21: 797.

67.

Chanioti

Tzia

. Extraction of phenolic compounds from olive pomace by using natural deep eutectic solvents and innovative extraction techniques. Innovative Food Sci Emerging Technol 2018; 48: 228–239.

68.

Dahmoune

Nayak

Moussi

, et al. Optimization of microwave-assisted extraction of polyphenols from Myrtus communis L. leaves. Food Chem 2015; 166: 585–595.

69.

Cui

Kakuda

. Extraction, fractionation, structural and physical characterization of wheat β-d-glucans. Carbohydr Polym 2006; 63: 408–416.

70.

Doulabi

Golmakani

Ansari

. Evaluation and optimization of microwave-assisted extraction of bioactive compounds from eggplant peel by-product. J Food Process Preserv 2020; 44. DOI: 10.1111/jfpp.14853.

71.

Cacace

Mazza

. Mass transfer process during extraction of phenolic compounds from milled berries. J Food Eng 2003; 59: 379–389.

72.

DiNardo

Brar

Subramanian

, et al. Optimization of microwave-assisted extraction parameters and characterization of phenolic compounds in Yellow European Plums. Can J Chem Eng 2018; 97: 256–267.

73.

Muñoz-Almagro

Morales-Soriano

Villamiel

, et al. Hybrid high-intensity ultrasound and microwave treatment: a review on its effect on quality and bioactivity of foods. Ultrason Sonochem 2021; 80: 105835.

74.

Pham

Tran

TNH

, et al. Ultrasonic-assisted and microwave-assisted extraction of phenolics and terpenoids from Abelmoschus sagittifolius (Kurz) Merr roots using natural deep eutectic solvents. ACS Omega 2023; 8: 29704–29716.

75.

Del Amo-Mateos

Cáceres

Coca

, et al. Recovering rhamnogalacturonan-I pectin from sugar beet pulp using a sequential ultrasound and microwave-assisted extraction: study on extraction optimization and membrane purification. Bioresour Technol 2024; 394: 130263.

76.

Osamede Airouyuwa

Khan

Mostafa

, et al. A comparative study on sequential green hybrid techniques (ultrasonication, microwave and high shear homogenization) for the extraction of date seed bioactive compounds and its application as an additive for shelf-life extension of Oreochromis niloticus. Ultrason Sonochem 2024; 111: 107094.

77.

Safitra

Muharam

Farizal , et al. Solanesol sequential extraction from tobacco leaves using microwave-ultrasound-assisted extraction (MUAE): MAE optimization. Curr Res Green Sustain Chem 2024; 8: 100393.

78.

Chémat

Rombaut

Meullemiestre

, et al. Review of Green Food Processing techniques. Preservation, transformation, and extraction. Innovative Food Sci Emerging Technol 2017; 41: 357–377.

79.

Liu

J-Z

Lin

Z-X

Kong

W-H

, et al. Ultrasonic-assisted extraction-synergistic deep eutectic solvents for green and efficient incremental extraction of Paris polyphylla saponins. J Mol Liq 2022; 368: 120644.

80.

Güldane

Cingöz

. Extraction of bioactive compounds from yellow onion peels: taguchi-SAW hybrid optimization. TURJAF 2023; 11: 2589–2594.

81.

Idris

Nadzir

Abd Shukor

. Optimization of solvent-free microwave extraction of Centella asiatica using Taguchi method. J Environ Chem Eng 2020; 8: 103766.

82.

Ramezani

Raji

Rezakazemi

, et al. Juglone extraction from walnut (Juglans regia L.) green husk by supercritical CO2: process optimization using Taguchi method. J Environ Chem Eng 2020; 8: 103776.

83.

Shu

Annamalai

Idris

, et al. Dataset of ultrasound-assisted extraction of anthocyanin from the petals of Clitoria ternatea using Taguchi method and effect of storage conditions on the anthocyanin stability. Data Brief 2022; 40: 107803.

84.

Filippis

LACD

Serio

Facchini

, et al. ANN modelling to optimize manufacturing process. In: El-Shahat A (ed) Advanced applications for artificial neural networks. InTech, 2018. DOI: 10.5772/intechopen.71237.

85.

Abifarin

Olubiyi

, et al. Taguchi grey relational optimization of the multi-mechanical characteristics of Kaolin reinforced hydroxyapatite: effect of fabrication parameters. Int J Grey Syst 2021; 1: 20–32.

86.

Zakir Hossain

Sultana

Hossain

, et al. Optimization of microalgal biomass and lipid productivities for bioenergy production using central composite design with desirability function. Int J Energy Res 2021; 45: 17342–17357.

87.

Ioannou

Christodoulou

Sofroniou

, et al. Phenolic extraction from prickly pear peels using deep eutectic solvents with macrocyclic enhancers. Food Chem 2025; 492: 145275.

88.

Gałuszka

Migaszewski

Konieczka

, et al. Analytical Eco-Scale for assessing the greenness of analytical procedures. TrAC, Trends Anal Chem 2012; 37: 61–72.

89.

Derayea

Elhamdy

Badr El-Din

, et al. Novel spectrofluorometric approach for assessing vilazodone by blocking photoinduced electron transfer: analytical performance, and greenness–blueness evaluation. RSC Adv 2024; 14: 4065–4073.

90.

Essam

Saad

Elzanfaly

, et al. Optimization and validation of eco-friendly RP-HPLC and univariate spectrophotometric methods for the simultaneous determination of Fluorometholone and Tetrahydrozoline hydrochloride. Acta Chromatogr 2021; 33: 216–227.

91.

Płotka-Wasylka

Wojnowski

. Complementary green analytical procedure index (ComplexGAPI) and software. Green Chem 2021; 23: 8657–8665.

92.

Pena-Pereira

Wojnowski

Tobiszewski

. AGREE—Analytical GREEnness metric approach and software. Anal Chem 2020; 92: 10076–10082.

93.

Fares

Hegazy

El-Sayed

, et al. Quality by design approach for green HPLC method development for simultaneous analysis of two thalassemia drugs in biological fluid with pharmacokinetic study. RSC Adv 2022; 12: 13896–13916.

94.

Makwakwa

Moema

Msagati

TAM

. Multi-criteria decision analysis: technique for order of preference by similarity to ideal solution for selecting greener analytical method in the determination of mifepristone in environmental water samples. Environ Sci Pollut Res 2024; 31: 29460–29471.

95.

Wojnowski

Tobiszewski

Pena-Pereira

, et al. AGREEprep – analytical greenness metric for sample preparation. TrAC, Trends Anal Chem 2022; 149: 116553.