Extraction and characterization of bioactive compounds from coffee by-products: physicochemical and LC-MS analysis

Extraction and characterization of bioactive compounds from coffee by-products: physicochemical and LC-MS analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Extraction and characterization of bioactive compounds from coffee by-products: physicochemical and LC-MS analysis Rabita Mohd Firdaus Achutan, Nurul Atiqah Izzati Md Ishak, Mohamed Kheireddine Aroua, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7024028/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Spent coffee grounds (SCGs), an abundant byproduct of Coffea arabica L., hold significant potential as a renewable resource for bioactive compounds. This study explores ultrasound-assisted extraction (UAE) as a sustainable approach to enhance the recovery of phenolic-rich metabolites using seven solvents with varying polarity. The optimized glycerol/methanol co-solvent system achieved the highest extraction efficiency, with a total phenolic content (TPC) of 6.059 ± 0.089 mg GAE/g and a total flavonoid content (TFC) of 8.549 ± 0.010 mg QE/g. Comprehensive liquid chromatography − mass spectrometry (LC-MS) analysis identified key secondary metabolites, including caffeine, chlorogenic acids (CGAs), and phenolic compounds which contribute to diverse functional properties such as antioxidant, antimicrobial, UV-protective, anti-inflammatory, and anti-cellulite activities. These bioactive components have substantial applications in industrial crop-based pharmaceuticals, cosmetics, and bio-based materials. By integrating UAE with environmentally friendly co-solvents, this study presents a scalable and sustainable extraction strategy, reducing reliance on conventional solvents while maximizing yield and purity. Additionally, the findings support waste valorization and circular economy principles, positioning SCGs as a viable industrial crop resource with significant implications for biorefinery processes, bio-based product development, and sustainable cropping systems. This research provides a systematic framework for solvent selection in metabolite extraction, reinforcing its relevance to industrial crop management and sustainable bioactive compound production. The demonstrated efficacy of UAE establishes SCGs as an untapped industrial crop derivative, contributing to the advancement of green extraction technologies and industrial applications. Spent coffee grounds bioactive compounds extraction solvent industrial crop Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Coffee is among the most widely consumed beverages globally, generating vast quantities of organic waste. Spent coffee grounds (SCGs), a major byproduct of coffee production, are typically discarded post-brewing, contributing to significant environmental concerns. According to the International Coffee Organization, global coffee production reached approximately 169 million 60 kg bags in the 2020/2021 season, underscoring the massive volume of SCGs generated annually (Mitraka et al., 2021 ). Improper disposal through landfilling or incineration will not only escalates soil and air pollution but also contradicts sustainability efforts such as United Nations Sustainable Development Goal (SDG) 12: Responsible Consumption and Production. Given their widespread availability and rich bioactive composition, SCGs present an opportunity for waste valorisation, particularly in industrial crop-based bioactive compound extraction (Abubakar et al., 2022 ). SCGs contain alkaloids like caffeine and trigonelline, chlorogenic acids (CGAs), phenolic acids, and other polyphenols (Hewage et al., 2022 ; Sánchez-Camargo et al., 2020 ), all of which are well-documented for antioxidant (Andrade et al., 2022 ), UV protection (Choi et al., 2016 ), anti-bacterial (Calheiros et al., 2023 ), anti-inflammatory (Angeloni et al., 2021 ), and anticellulite effects (Ribeiro et al., 2013 ). These properties make SCGs an attractive resource for pharmaceutical, cosmetic, and nutraceutical industries while supporting the demand for eco-conscious formulations and green chemistry approaches. Consequently, sustainable extraction methodologies are vital to unlocking the full potential of SCGs while minimizing environmental impact and aligning with bio-based industrial applications. Several extraction techniques have been explored for the recovery of these bioactive, including Soxhlet extraction, microwave-assisted extraction, hydrothermal processing, and ultrasound-assisted extraction (UAE) (Bouhzam et al., 2023 ; Chatzimitakos et al., 2023 ). Among these, UAE has emerged as a promising technology due to its energy efficiency, shorter processing time, and enhanced extraction yield (Ghenabzi̇A et al., 2023 ; Patrice Didion et al., 2023 ). However, the choice of solvent significantly impacts extraction efficiency and metabolite composition. Traditional solvents such as methanol and acetone, though effective, raise concerns regarding toxicity and environmental sustainability. In contrast, green solvents like ethanol, water, and glycerol are increasingly favoured for their biodegradability, low toxicity, and eco-friendly profile (Brglez Mojzer et al., 2016 ). Glycerol (1,2,3-propanetriol), a naturally occurring biocompatible polyol, has received attention for its low volatility, high solubility, and suitability for bioactive compound extraction (Joshi and Adhikari, 2019 ). Recognized as a preferred green solvent under Pfizer’s solvent selection guide, glycerol's ability to dissolve organic and inorganic compounds makes it a viable alternative for extracting phenolic compounds and alkaloids from SCGs (Rodrigues et al., 2017 ). Besides, in the food and beverage industry, it serves as a solvent, sweetener, and preservative, while in cosmetics, it functions as an emollient and carrier. Given its biocompatibility and safety, glycerol presents a viable alternative to conventional solvents for extracting bioactive compounds (Chilakamarry et al., 2021 ; Fluhr et al., 2008 ). To complement extraction methods, advanced analytical techniques play a crucial role in identifying and quantifying the diverse array of compounds present in natural matrices. Among these, liquid chromatography–mass spectrometry (LC-MS) is a widely recognized tool for detailed chemical profiling, frequently applied to natural products, biological samples, pharmaceuticals, and environmental matrices (Alqarni, 2024 ). While prior research has largely focused on quantifying individual metabolites, few studies have integrated metabolite profiling with biosynthetic pathway analysis or linked such findings to potential applications. For example, CGAs are synthesized through the phenylpropanoid pathway, initiating from phenylalanine and progressing through enzymatic transformations to generate functional derivatives such as trans -cinnamic acid, 4-coumarate, and 4-coumaroyl-CoA (Grohar et al., 2021 ; Li et al., 2022 ). This study systematically examines seven distinct solvent systems, including ethanol, methanol, water, and glycerol-based co-solvent mixtures (glycerol-methanol, glycerol-ethanol, glycerol-water) for SCG metabolite extraction and characterization. Total phenolic content (TPC) and total flavonoid content (TFC) assessments, coupled with LC-MS chemical profiling, provide a comprehensive framework for sustainable extraction methodologies in industrial crop applications. Additionally, this study explores biosynthetic pathways, particularly the phenylpropanoid pathway involved in CGA synthesis, revealing insights into metabolite bioavailability and potential functionality. To the best of our knowledge, this is the first comprehensive study to integrate green solvent extraction, LC-MS profiling, and metabolic pathway analysis for SCGs, thereby advancing their potential for sustainable bioactive compound extraction and industrial product development. Materials and Methods SCGs pre-treatment The pristine SCGs ( Coffea arabica L.) was collected from the Starbuck at Sunway University, Selangor. The collected SCGs was dried in the oven at 373.15 K until it reached a moisture value of < 10%. The dried SCGs obtained were kept in airtight containers at ambient and dark rooms until the extraction process. Preparation of solvents and extraction of bioactive compounds To extract bioactive compounds from SCGs, various solvents were utilized, including water, ethanol, methanol, glycerol, and glycerol-based mixtures comprising glycerol/water (G/W, 1:1 v/v), glycerol/ethanol (G/E, 1:1 v/v), and glycerol/methanol (G/M, 1:1 v/v). These glycerol-based mixtures were prepared in advance to ensure consistency before the extraction process. Figure 1 provides an overview of the extraction workflow, illustrating the step-by-step process employed in obtaining bioactive compounds from SCGs. The procedure begin with the addition of 0.5 g of dried SCGs to 10 mL of the respective solvent, followed by mechanical processing involving grinding with a pestle and mortar, vortex mixing, and sonication for 30 minutes. To enhance the efficiency of extraction, the sonication process was repeated every 24 hours over a 72-hour incubation period while maintaining a constant temperature of 300.15 K. After the incubation period, the SCG suspensions underwent centrifugation at 2000 rpm for 15 minutes to separate the liquid extracts from the solid residues. The resulting supernatants were then subjected to filtration to remove any remaining particulates. Different filtration methods were applied based on the solvent used: ethanol, methanol, and water extracts were filtered sequentially using mixed cellulose ester (MCE) syringe membrane filters with 0.45 µm and 0.22 µm pore sizes, while glycerol-based extracts were filtered using nylon syringe membrane filters with the same pore sizes. Once filtered, all extracts were transferred into 50 mL centrifuge tubes and stored under refrigerated conditions at 277.15 K to maintain their chemical stability until further analysis. Each extract was labelled based on the solvent used: Water (W), Ethanol (E), Methanol (M), Glycerol (G), Glycerol/Water (G/W), Glycerol/Ethanol (G/E), and Glycerol/Methanol (G/M). To ensure accuracy and reproducibility, the entire extraction procedure was conducted in triplicate. Morphological and surface characterization of SCGs extracts Scanning electron microscopy (SEM) The surface morphology and elemental composition of the pristine SCGs was investigated utilizing SEM coupled with Energy Dispersive X-ray Spectroscopy (EDX) instrumentation (Model: Tescan VEGA-3). Phytochemical assays of SCGs extracts Total phenolic content (TPC) The TPC of the SCG extracts was determined following a modified version of the method described by Lim et al. (Lim et al., 2024 ). To ensure accuracy, a calibration curve was established using gallic acid (GA) as the standard, prepared in concentrations ranging from 0 to 1000 µ g/mL. The reaction mixture for the TPC assay was prepared by combining 5 µL of the extract sample (10 mg/mL) or GA standard with 25 µ L of Folin–Ciocalteu reagent, 350 µ L of deionized distilled water (ddH₂O), and 75 µ L of 20% sodium carbonate solution. An additional 45 µ L of ddH₂O was added to complete the reaction volume. The mixture was thoroughly homogenized within 10 minutes and subsequently incubated in complete darkness for 60 minutes to facilitate the reaction. Following incubation, the absorbance of each sample was measured at 750 nm using a UV-visible spectrophotometer microplate reader. A standard curve was generated by plotting the absorbance values at 750 nm against the corresponding concentrations of GA standards (Fig. S1 ). The linear regression equation obtained from the calibration curve was used to determine the TPC of the SCG extracts. The results were expressed in milligrams (mg) of gallic acid equivalents (GAE) per gram (g) of extract (mg GAE/g). Total flavonoid content (TFC) TFC of the SCG extracts was determined using a modified version of the method outlined by Lim et al. (2023) (Lim et al., 2024 ). To ensure accuracy in quantification, a calibration curve was constructed using quercetin as the reference standard, with concentrations ranging from 0 to 1000 µ g /mL. The assay was conducted by preparing reaction mixtures in which 10 mg/mL of SCG extract or quercetin standard was combined with 250 µ L of 2% aluminum chloride (AlCl₃) solution, 250 µ L of 1 M sodium acetate (CH₃COONa), and 490 µ L of deionized distilled water (ddH₂O). The mixture was thoroughly homogenized and incubated for 15 minutes to allow the reaction to proceed. Following the incubation, absorbance readings were recorded at 425 nm using a UV-visible spectrophotometer microplate reader (TECAN, Infinite M200 PRO). The standard curve was established by plotting the absorbance values at 425 nm against the corresponding quercetin concentrations. (Fig. S2). The linear regression equation obtained from this calibration curve was then used to calculate the TFC in the SCG extracts. The results were expressed in milligrams of quercetin equivalent (QE) per gram of extract (mg QE/g). 2,2-Diphenyl-1-picrylhydrazyl (DPPH) The antioxidant activity of the SCG extracts was evaluated using the DPPH radical scavenging assay, following a standardized protocol. Ascorbic acid was utilized as the positive control, prepared in a series of concentrations ranging from 0 to 100 µ g. The prepared solutions were carefully transferred into individual wells of sterile 96-well microplates, ensuring consistency across all replicates (n = 4). To initiate the reaction, a 0.2 mM DPPH solution was added to each well, covering both the test samples and the ascorbic acid standard. After gentle mixing for approximately five seconds, the plates were incubated in a dark environment at room temperature for 15 minutes to allow the reaction to proceed. Once the incubation period was completed, absorbance measurements were recorded at 517 nm using a UV-visible spectrophotometer microplate reader. The antioxidant capacity of the extracts was quantified based on their ability to scavenge DPPH free radicals, with results expressed in terms of IC₅₀ values. These IC₅₀ values, representing the concentration required to inhibit 50% of the free radicals, were then compared to the ascorbic acid standard to assess the relative antioxidant potency of the SCG extracts. Physicochemical characterization of SCGs extracts Liquid chromatography-mass spectrometry (LC-MS) The identification and characterization of secondary metabolites in SCG extracts were conducted using an Agilent 1290 Infinity LC system, coupled with an Agilent 6520 Accurate-Mass Quadrupole Time-of-Flight (Q-TOF) mass spectrometer. This setup, equipped with a dual-electron spray ionization (ESI) source, enabled analysis in both positive and negative ionization modes. To optimize performance, the experimental procedure was adapted from established methodologies by Lim et al. and Thiyagarasaiyar et al., with minor modifications (Lim et al., 2024 ; Thiyagarasaiyar et al., 2021 ). Chromatographic separation was performed using an Agilent Zorbax Eclipse XDB-C18 Narrow-Bore column (2.1 mm × 150 mm, 3.5 µm), maintained at 25°C, while the autosampler was kept at 4°C. The mobile phase, consisting of a 60:40 water-acetonitrile mixture, was delivered at a constant flow rate of 0.5 mL/min. SCG extract samples (3.0 µL) were injected into the system and analysed under both ionization polarities. Mass spectra were recorded within an m/z range of 100 to 3200, with a fragmentor voltage of 125 V. Nitrogen gas was used as the collision gas to facilitate ion fragmentation. Data acquisition in positive-ion ESI mode was performed at a scan rate of 1.03 s per scan. The resulting chromatographic and spectral data were processed using Agilent MassHunter Qualitative Analysis software (version B.05.00). Compound identification and characterization were achieved by comparing LC-MS spectral data with entries in the METLIN database, enabling precise identification of bioactive metabolites in the SCG extracts. Fourier Transform Infrared (FTIR) analysis The identification of functional groups present in the SCG extracts was conducted using FTIR spectroscopy, utilizing a Bruker VERTEX 70v spectrometer (Rosenheim, Germany). The analysis was performed with an attenuated total reflectance (ATR) technique to facilitate direct measurement of the samples without extensive preparation. Prior to sample analysis, a baseline scan was performed by collecting spectra without any sample in contact with the ATR crystal to ensure accuracy and eliminate background interference. Once the baseline scan was established, a few drops of each SCG extract were carefully placed onto the ATR crystal window. The sample was then brought into direct contact with the crystal, and the spectral data acquisition commenced. The FTIR spectra were recorded over a broad wavenumber range of 4000–400 cm⁻¹, capturing characteristic absorption bands corresponding to different functional groups within the extracts. The absorbance values obtained provided insights into the molecular composition of the SCG extracts, enabling the identification of key functional groups associated with bioactive compounds. Results and Discussion Morphological and surface characterization of SCGs extracts Scanning Electron Microscopy (SEM) The surface morphology of SCGs was analysed using SEM to gain insights into their structural characteristics. SEM imaging was conducted at different magnification levels to observe the microstructural details of the untreated SCGs particles. The micrographs obtained at magnifications of 300× and 1000× are illustrated in Fig. 2 (a) and Fig. 2 (b). At 300× magnification, the SEM images show a heterogeneous distribution of particle sizes, indicating the irregular nature of dry SCG particles. When observed at a higher magnification of 1000×, the SCG particles exhibit a distinctive "sponge-like" structure with flake-like formations. The pore sizes measured within the SCGs structure were found to range from 10 to 18 µm. This observation aligns with previous studies, which have reported that untreated biowaste materials, including SCGs, typically feature irregular pores, resulting in a loosely packed and coarse porous network (Mariana et al., 2018 ; Wang et al., 2017 ). Similarly, Bejenari et al. examined pristine SCGs and reported pore sizes between 8 and 17 µm, with the majority of SCGs particles measuring approximately 389.48 ± 19.47 µm in size (Bejenari et al., 2022 ). These findings are consistent with reports by Zein et al. and Lee et al., who documented dry SCG pore sizes extending up to 30 µm (Zein et al., 2017 ). To further investigate the elemental composition of SCGs, energy-dispersive X-ray (EDX) spectroscopy (Fig. 2 c) (EDX) mapping (Fig. 2 d-f) was performed. The EDX results confirm that carbon is the predominant element, accounting for 90.85% of the total atomic composition. Oxygen follows as the second most abundant element at 8.37%, with trace amounts of potassium (0.45%), magnesium (0.21%), and sulfur (0.32%). These elemental distributions provide valuable insights into the composition of SCGs, which may influence their potential applications in various fields. In-vitro antioxidant activities TPC and TFC of SCGS extracts Phenolic compounds are a diverse group of secondary metabolites synthesized by plants in response to various environmental stressors, including exposure to ultraviolet (UV) radiation and pathogenic attacks (Yang et al., 2018 ). These bioactive compounds play a crucial role in plant defence mechanisms and exhibit strong antioxidant properties due to their ability to donate hydrogen atoms, reduce oxidative species, chelate metal ions, and quench singlet oxygen. Through these mechanisms, phenolic compounds effectively neutralize free radicals, thereby mitigating oxidative damage (Mathew et al., 2015 ). Furthermore, they disrupt the chain reaction of free radical formation by stabilizing as phenoxy radicals, which are relatively less reactive, thus preventing further oxidative stress (Leopoldini et al., 2004 ). In this study, the TPC of SCG extracts was analysed, and the results are summarized in Table 1 . The findings indicate notable variations in TPC among different solvent extractions. Among the tested extracts, the glycerol/methanol (G/M) extract exhibited the highest phenolic content, reaching 6.059 mg of gallic acid equivalents per gram (mg GAE g⁻¹) of extract. This was followed by the glycerol/water (G/W) extract, which contained 4.352 mg GAE g⁻¹, and the glycerol/ethanol (G/E) extract with 3.305 mg GAE g⁻¹. The water extract demonstrated a slightly lower phenolic content at 3.607 mg GAE g⁻¹, while the methanol extract contained 3.382 mg GAE g⁻¹. The ethanol extract exhibited a further reduction in phenolic concentration, with a recorded value of 2.529 mg GAE g⁻¹. Notably, the pure glycerol extract displayed the lowest TPC among all tested solvents, with a value of 1.442 mg GAE g⁻¹. These variations highlight the influence of solvent polarity on phenolic compound extraction, suggesting that mixed solvent systems, particularly those incorporating glycerol and methanol, enhance the solubilization and recovery of phenolic constituents from SCGs. Table 1 Phytochemical Contents of the SCGs Extract Solvent TPC (mg GAE/g) TFC (mg QE/g) DPPH IC 50 (mg/ml) Glycerol 1.442 ± 0.003 0.104 ± 0.001 - Ethanol 2.529 ± 0.007 3.474 ± 0.005 - Methanol 3.382 ± 0.014 4.146 ± 0.004 - Water 3.607 ± 0.022 0.284 ± 0.001 - G/E 3.304 ± 0.019 6.665 ± 0.016 1.713 G/W 4.352 ± 0.047 3.490 ± 0.009 1.590 G/M 6.059 ± 0.089 8.549 ± 0.010 1.552 Among the pure solvents, methanol proved to be the most effective for extracting phenolic compounds, followed by water, ethanol, and glycerol. This is in agreement with Musatto et al., who optimized phenolic extraction from SCGs using a conventional solid–liquid extraction method with 60% methanol at a solvent-to-solid ratio of 40 mL/g SCGs over 90 minutes, obtaining a TPC of 16 mg GAE g⁻¹ (Mussatto et al., 2011 ). Comparisons with other studies also highlight ethanol and methanol as optimal solvents for phenolic extraction due to their high polarity (Calle Chumo et al., 2022 ). Furthermore, research indicates that ultrasonic-assisted extraction can significantly enhance phenolic yields. Gigliobianco et al. employed subcritical water extraction at 179°C for 36 minutes and reported substantial TPC improvements (Gigliobianco et al., 2020 ). Water, often considered the most environmentally friendly solvent due to its low toxicity, non-flammability, cost-effectiveness, and ease of separation (Zhou et al., 2019 ), does not always provide the most efficient extraction. Several studies have demonstrated that the addition of co-solvents, such as methanol, ethanol, or glycerol, enhances polyphenol solubility by increasing the polarity of the extraction medium(Awad et al., 2021 ; Bouhzam et al., 2023 ; Da Porto et al., n.d.; Panzella et al., 2020 ). Thouri et al. confirmed that solvent polarity plays a crucial role in the yield of extracted polyphenols, as polar solvents effectively solubilize antioxidant compounds through hydrogen bonding interactions between the solvent and polyphenolic hydroxyl groups (Thouri et al., 2017 ). Consistent with these observations, the findings of this study highlight that the inclusion of co-solvents can significantly improve polyphenol extraction efficiency. Flavonoids, a major subclass of polyphenolic compounds, have been widely studied for their bioactive properties. Structurally, flavonoids are characterized by two aromatic rings connected by a three-carbon bridge, forming an oxygenated heterocyclic system. The experimental results presented in Table 1 indicate considerable variation in TFC across different extracts. The G/M extract exhibited the highest TFC at 8.549 mg quercetin equivalents per gram (mg QE g⁻¹), followed by the G/E extract (6.665 mg QE g⁻¹), methanol extract (4.146 mg QE g⁻¹), G/W extract (3.490 mg QE g⁻¹), ethanol extract (3.474 mg QE g⁻¹), water extract (0.284 mg QE g⁻¹), and the glycerol extract (0.104 mg QE g⁻¹). Similar to the TPC results, the G/M extract demonstrated superior flavonoid extraction efficiency, likely due to methanol’s strong polarity, which facilitates the solubilization of both polar and semi-polar compounds. These findings align with those reported by Chen et al., who observed TFC values ranging from 5.6 to 25.1 mg QE g⁻¹ in coffee pulp extracts obtained using ethanol concentrations between 0% and 99.5% (Chen et al., 2021 ). Furthermore, Alkaltham et al. found that methanol and ethyl acetate extractions yielded TFC values of 8.02 mg QE g⁻¹ and 0.787 mg QE g⁻¹, respectively, in coffee pulp extracts (Alkaltham et al., 2020 ). According to Huaman et al., glycerol, when used in combination with methanol, ethanol, or water, significantly improved polyphenol extraction efficiency (Huamán-Castilla et al., 2020 ). This enhancement is attributed to flavonoids being predominantly polar compounds due to their unsubstituted hydroxyl groups, making polar solvents like ethanol, methanol, and ethyl acetate more suitable for their extraction from plant matrices (Etika and Iryani, 2019 ). Conversely, less polar flavonoids such as isoflavones, flavanones, flavones, and flavanols exhibit better solubility in less polar solvents like glycerol, hexane, dichloromethane, and diethyl ether (Chaves et al., 2020 ). The results of this study further support the use of solvent combinations rather than single solvents to selectively enhance the extraction of specific bioactive compounds based on their polarity. Tailoring the extraction process in this way maximizes the efficiency and yield of target compounds. Moreover, combining alcohol-based solvents such as methanol and ethanol with glycerol not only enhances extraction efficiency but also mitigates health and safety risks associated with the use of methanol and ethanol alone. Additionally, the biodegradable and eco-friendly nature of glycerol contributes to the sustainability of the extraction process, making it a viable option for future green extraction methodologies. Antioxidant Activity of SCGs Extracts The phenolic content of substances is closely associated with their ability to neutralize free radicals, which is a key determinant of their antioxidant potential. In this study, the free radical scavenging activity of SCGs extracts was evaluated using the DPPH assay, a widely recognized method for measuring antioxidant activity. The assay is based on the ability of antioxidants to reduce the stable, purple-coloured DPPH radical (DPPH•) into a yellow hydrazine molecule by donating electrons or hydrogen atoms. This reaction effectively neutralizes the radical, leading to a loss of colour intensity, which can be quantitatively measured using spectrophotometry (Munteanu and Apetrei, 2021 ). The extent of this reduction is directly proportional to the availability of hydroxyl groups within the antioxidant compounds present in the extract (Baliyan et al., 2022 ). Furthermore, the antioxidant efficacy of SCGs extracts was assessed using the half-maximal inhibitory concentration (IC 50 ) value, which represents the concentration of extract required to reduce the initial DPPH• concentration by 50%. A lower IC 50 value indicates stronger antioxidant capacity (Rivero-Cruz et al., 2020 ). The results of the DPPH scavenging assays for all tested extracts, as presented in Table 1 , reveal significant variations in antioxidant activity based on the extraction solvent used. Notably, extracts obtained using single solvents such as ethanol, methanol, water, and glycerol exhibited negative IC 50 values, suggesting an absence of significant antioxidant activity. In contrast, extracts prepared using binary solvent systems, specifically glycerol/methanol (G/M), glycerol/water (G/W), and glycerol/ethanol (G/E), demonstrated notable antioxidant activity. Among these, the G/M extract exhibited the lowest IC 50 value (1.552 mg/ml), indicating the highest scavenging efficiency compared to the G/W and G/E extracts. These results are consistent with the TPC and TFC findings, reinforcing the correlation between phenolic and flavonoid content and antioxidant activity. The observed antioxidant activity of SCGs extracts aligns with findings reported in previous studies. Kusumocahyo et al. investigated the extraction efficiency of coffee pulp using a semi-polar ethanol-water mixture, concluding that a 50:50 solvent ratio yielded an extract with higher antioxidant activity (IC50 = 487.96 ± 5.94 mg/ml) compared to pure water extraction. Their findings further emphasized the importance of solvent polarity in maximizing phenolic compound recovery and antioxidant activity (Kusumocahyo et al., 2020 ). Similarly, Shang et al. analysed the antioxidant potential of SCGs from ten different sources using pressurized liquid extraction (PLE) with an ethanol-water solvent system. Their results showed substantial variation in the content of active compounds, including 5-caffeoylquinic acid (5-CQA) at levels ranging from 51 to 201 mg/g DW, total phenolics (TP) between 19 and 26 mg GAE/g DW, and caffeine concentrations of 3 to 9 mg/g DW. Antioxidant activity, assessed using both DPPH and ABTS assays, ranged from 16 to 38 mg VE/g DW and 10 to 28 mg VE/g DW, respectively, suggesting that SCGs are a promising source of bioactive polyphenols (Shang et al., 2017 ). The impact of pre-treatment methods on phytochemical retention was also highlighted by Kieu Tran et al., who demonstrated that drying conditions significantly influence the antioxidant potential of coffee pulp. Their study utilized a methanol-water solvent mixture (1:1, v/v) to extract secondary metabolites, revealing that vacuum drying at 90°C or 110°C yielded the highest DPPH radical scavenging capacity (2.24 mg TE/g DW) (Kieu Tran et al., 2020 ). Additionally, research by Ansori et al. examined the antioxidant potential of SCGs from different coffee varieties, namely Robusta, Liberica, and Arabica. Using ultrasonic-assisted extraction with 60% ethanol, they found that Robusta SCGs exhibited the highest antioxidant capacity. Their findings suggest that SCGs contain potent electron-donating compounds that effectively inhibit oxidation chain reactions by stabilizing free radicals. Furthermore, skincare formulations enriched with SCGs extract exhibited 10 to 100 times higher antioxidant activity than formulations without the extract, underscoring the potential of SCGs as a valuable ingredient for functional applications (Universiti Malaysia Terengganu et al., 2021 ). Identification of metabolites profiling involved in SCGs extraction LC-MS Analysis Plant secondary metabolites constitute a diverse class of bioactive compounds synthesized by plants in response to various environmental stimuli, including biotic and abiotic stresses. These compounds, while not directly involved in essential physiological functions such as growth and reproduction, play crucial roles in plant defence and interaction with their environment. In this study, LC-MS analysis was conducted to identify the secondary metabolites present in SCGs extracts obtained using different solvent systems. The results, summarized in Table 2 , provide a detailed account of the major active secondary metabolites, including their retention time (RT), classification, molecular formula, and structure. The identified metabolites primarily fall into three distinct categories: alkaloids, phenolic compounds, and diterpenes. One of the predominant alkaloids detected in the SCGs extract was caffeine (1,3,7-trimethylxanthine), a bioactive compound widely recognized for its stimulant properties and potential health benefits (DePaula and Farah, 2019 ). Caffeine has been extensively studied for its physiological effects, including its ability to enhance cognitive function and reduce the risk of neurodegenerative diseases such as Parkinson’s and Alzheimer’s (Kolahdouzan and Hamadeh, 2017 ). Furthermore, a study by Venkata Charan Tej et al. demonstrated that caffeine inhibited tumour growth in a carcinogen-induced fibrosarcoma model after 250 days of exposure to 3-MCA. In this study, caffeine was identified in extracts obtained using ethanol, methanol, water, and glycerol/methanol (G/M) as a positive ion with a mass-to-charge ratio (m/z) of 195.0876 at a retention time of 7.7 minutes (Venkata Charan Tej et al., 2019). This aligns with findings by Tahrim et al., who employed HPLC analysis to identify caffeine at a retention time of 7.71 minutes with an m/z of 195 (Tahrim et al., 2013 ). By comparing retention times with reference standards and utilizing accurate mass measurements from TOF-MS, they confirmed the presence of caffeine in real samples. In addition to caffeine, its metabolic derivatives—paraxanthine, theobromine, and theophylline were identified, with paraxanthine exhibiting a retention time of 0.733 minutes and an m/z of 179.0569. Previous research suggests that both caffeine and paraxanthine exert neuroprotective effects, with paraxanthine specifically demonstrating the ability to protect dopaminergic neurons against neurodegeneration and synaptic loss (Okuro et al., 2010 ). Apart from alkaloids, phenolic compounds represent another major class of secondary metabolites present in SCGs. These compounds are biosynthesized through the shikimic acid and pentose phosphate pathways, and their prevalence in coffee by-products is well-documented. One of the most significant phenolic compounds found in coffee is chlorogenic acid (CGAs), which constitutes between 4% and 8.4% of the dry matter content in Coffea Arabica and 7–14.4% in Coffea Canephora, with hybrid species exhibiting intermediate levels (Gichimu et al., 2014 ). CGAs are esters formed through the conjugation of Quinic acid with trans -cinnamic acids, including caffeic acid, p-coumaric acid, and ferulic acid. These compounds are primarily present as simple esters of hydroxycarboxylic acids or glucose (Rojas-González et al., 2022 ). Numerous studies have demonstrated the strong antioxidant and anti-inflammatory properties of caffeic acid and ferulic acid, which contribute to their protective effects against oxidative stress (Chaudhary et al., 2023 ; Liang and Kitts, 2015 ). Additionally, Quinic acid has been identified for its antimicrobial activity, suggesting its potential role in inhibiting bacterial infections (Andrade et al., 2022 ; Ramón-Gonçalves et al., 2019 ). The LC-MS analysis further confirmed the presence of Quinic acid and trans-cinnamic acid (ferulic acid) in the SCGs extracts. Quinic acid was detected at a retention time of 0.747 minutes with an m/z of 193.0696, while trans -cinnamic acid was identified at 9.141 minutes with an m/z of 193.0506 (Moeenfard et al., 2014 ). In addition, three CGAs isomers— cis -5-CQA, 3-O-feruloylquinic acid, and 4-caffeoyl-1,5-quinolactone were detected, suggesting the potential isomerization of CGAs during extraction. These compounds exhibit multiple biological activities, including antioxidant, hepatoprotective, hypoglycaemic, and antiviral effects (Rojas-González et al., 2022 ). CGAs serve as crucial defence compounds in plants against environmental stressors, while in humans, they offer significant therapeutic benefits (Alcázar Magaña et al., 2021 ). Research conducted by Andrade et al. identified caffeine and 5-CQA as the primary bioactive compounds in SCGs sourced from Guatemala, Brazil, Timor, and Ethiopia, using methanol/water solvent mixtures (Andrade et al., 2022 ). Their findings were validated through the µ-speed/UHPLC-PDA method, confirming the presence of additional bioactive compounds such as 3-CQA, caffeic acid, 4,5-diCQA, 1,5-diCQA, and 3,4-diCQA. These metabolites have been extensively documented for their biological activities, making them valuable for pharmaceutical, cosmetic, and food industry applications. The extraction efficiency of polyphenols, particularly CGAs and p-coumaric acids, was further validated by Gonçalves et al., who reported concentrations ranging from 0.02 to 4.8 mg/g and 0.173 to 0.50 mg/g, respectively, when water was used as the primary solvent (Ramón-Gonçalves et al., 2019 ). The present study corroborates these findings, highlighting the effectiveness of polar solvent mixtures in isolating phytoconstituents such as polyphenols (Badr et al., 2022 ). In agreement with these results, Badr et al. identified rosmarinic acid and syringic acid as predominant phenolic acids in SCGs, while flavonoids such as apigenin-7-glucoside, naringin, epicatechin, and catechin were also detected. The use of isopropanol as an extraction solvent in their study demonstrated an eco-friendly approach to bioactive compound isolation. Furthermore, cytotoxicity assays on liver cancer cells (Hep-G2) revealed moderate activity with selective toxicity over healthy oral epithelial cell lines (OEC), though less potent than cisplatin, the positive control. The findings of this study emphasize the potential of SCGs as a valuable source of bioactive secondary metabolites with diverse applications in nutraceuticals, pharmaceuticals, and functional foods. The use of solvent mixtures in extraction significantly enhances the recovery of key metabolites, aligning with existing literature and demonstrating the feasibility of green and sustainable extraction methodologies for polyphenol-rich extracts. The diverse bioactivities exhibited by these compounds further support the exploration of SCGs-derived metabolites for health-promoting applications. FTIR Analysis LC-MS serves as a powerful analytical tool for the identification and quantification of a wide range of organic compounds in complex mixtures. However, in addition to LC-MS, FTIR spectroscopy was performed to obtain crucial information regarding the functional groups associated with active metabolites, which play a significant role in the extraction of SCGs. The TPC and TFC results indicated that co-solvent extractions yielded higher phenolic and flavonoid content compared to single solvent extractions. As a result, pristine SCGs extraction samples, along with co-solvent extraction samples, were subjected to FTIR analysis to elucidate the functional groups present. The FTIR spectra of pristine SCGs and SCGs extracts obtained using ethanol, water, and methanol solvents were shown in Fig. 3 and Table S1 . All spectra displayed broad absorption bands in the 3308–3311 cm⁻¹ region, corresponding to O-H stretching vibrations. The O-H stretching band in the observed IR spectrum peaked at approximately 3311 cm⁻¹, with a slight shoulder around 3250 cm⁻¹. According to Dai et al., free O-H stretching vibrations without hydrogen bonding typically appear between 3700 and 3600 cm⁻¹, whereas hydrogen bonding formation shifts the O-H stretching frequency to lower wavenumbers. A reduction in frequency is indicative of higher O-H content, suggesting the presence of hydroxyl groups associated with polyphenolic compounds (Dai et al., 2023 ). Furthermore, two distinct bands were observed in the 2900 − 2800 cm⁻¹ region, where a peak at 2936 cm⁻¹ was attributed to asymmetric stretching and another at 2834 cm⁻¹ was associated with symmetric stretching of C-H bonds within methylene groups. The intensity of these bands correlates with the quantity of methyl groups in the compound and suggests strong inter- and intra-molecular hydrogen bonding, characteristic of polyhydroxy polyphenolic structures (Kanazawa et al., 2021 ). Li et al. have linked these stretching phenomena specifically to aliphatic bonds present in compounds such as caffeine and lipids (Li et al., 2014 ). Conversely, Ravindran et al. have associated the peak at 2920 cm⁻¹ with hydrogen bonding in cellulose, further highlighting the diverse composition of SCGs (Ravindran et al., 2017 ). Additionally, the presence of a moderate absorption peak at 1736 cm⁻¹ confirmed the existence of carbonyl functional groups, specifically C = O stretching vibrations. This observation aligns with the findings of Saeed et al., who noted that functional groups containing carbonyl moieties, such as ketones, aldehydes, and carboxylic acids, exhibit strong IR absorption bands within the 1700–1750 cm⁻¹ range (Saeed et al., 2023 ). Spectral peaks between 1750 cm⁻¹ and 1730 cm⁻¹ corresponded to ester groups within the hemicellulose fraction, indicative of interactions between lignin and polysaccharides (Ravindran et al., 2017 ). The signal at 1610 cm⁻¹ was assigned to C = C stretching vibrations and asymmetric C = OH stretching in the aromatic ring, primarily associated with lignin, cellulose, and hemicellulose components (Huang et al., 2012 ). At 1414 cm⁻¹, the skeletal C-H stretching vibration of the aromatic ring was identified. However, overlapping bands at 1415 cm⁻¹ and 1412 cm⁻¹, primarily due to the symmetric stretching of C = OH, have been highlighted in prior studies by Li et al. (Li et al., 2018 ). Furthermore, a moderate peak at 1325 cm⁻¹ was linked to C-N stretching vibrations, with Marjanović et al. suggesting that a medium peak at 1365 cm⁻¹ corresponds to stretching vibrations in phenazine-type rings or C-N stretching vibrations, further supported by a shoulder at 1337 cm⁻¹ associated with C-N bonding (Marjanović et al., 2011 ). The spectral region between 1020 and 1158 cm⁻¹ exhibited C-O stretching vibrations characteristic of the phenolic hydroxyl group, with greater intensity observed in all extraction samples compared to pristine SCGs powder. Lower wavenumber absorptions were also detected, including C = C and C-C out-of-plane bending vibrations at 833 cm⁻¹ and 518 cm⁻¹, respectively. These findings indicate the presence of complex organic structures, particularly polyphenols and related secondary metabolites, contributing to the bioactivity of SCGs extracts. As part of the LC-MS and FTIR analyses, secondary metabolites were identified and classified based on their functional groups, as detailed in Table 3 . The LC-MS results using various solvents identified seven primary functional groups, encompassing ketones, carboxylic acids, lactones, esters, aldehydes, furans, and phenols. This classification provides a comprehensive understanding of the diverse array of bioactive compounds present in SCGs extracts, reinforcing their potential applications in pharmaceuticals, nutraceuticals, and cosmetics. The identification of these compounds through complementary analytical techniques such as LC-MS and FTIR further validates the chemical complexity and functional properties of SCGs, highlighting their role as a valuable resource for bioactive metabolites. Chemical composition of SCGs and possible pathway of profiling metabolites from SCGs Possible pathway for profiling metabolites extracted from SCGs are purposed in Fig. 4 , highlighting the transformation of bioactive compounds within the lignocellulosic matrix. SCGs primarily comprise hemicellulose, cellulose, and lignin which each contributing uniquely to metabolite formation. Hemicellulose, composed of 1,4-glycosidic linkages, facilitates polysaccharide hydrolysis (Álvarez-Martínez and Pfrengle, 2025 ). Cellulose, a polymer of glucose units connected by β-1,4-glycosidic bonds and rich in hydroxyl functional groups, influences degradation and conversion processes (Zeng and Pan, 2022 ). Lignin, constructed from p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol, provides structural rigidity but undergoes selective depolymerization during extraction (Jiang et al., 2023 ). Quantitative analyses by Santos et al. revealed notable concentrations of phenolic compounds (12.0 mg/g), caffeine (14.5 µg/g), and CGAs (31.8 µg/g) in SCGs. Carbohydrates, including cellulose and hemicellulose are abundant. Cellulose’s structural integrity and biocompatibility make it a valuable material across various industries (Bhatia et al., 2019 ). Hemicellulose, a heteropolysaccharide, contains diverse sugar units such as arabinose, xylose, glucose, galactose, mannose, glucuronic acid, and methylglucuronic acid. These can be efficiently extracted via physical, chemical, or enzymatic methods. For instance, Ballesteros et al. reported that alkali treatment of SCGs yielded polysaccharides rich in arabinose, mannose, galactose, and glucose (Ballesteros et al., 2015 ). Similarly, Coelho et al. identified high carbohydrate content in SCGs, comprising mannose (48.4 mol%), galactose (22.5 mol%), and glucose (17.1 mol%) (Coelho et al., 2021 ). In addition to carbohydrates, SCGs contain significant protein content (13–17 wt.% of dry mass), rendering them a valuable nutrient source for the food industry and a promising substrate for biotechnological applications (Ballesteros et al., 2015 ; Kovalcik et al., 2018 ). Lignin, another major constituent, is rich in functional groups including phenolic, aliphatic hydroxyl, methoxyl, carbonyl, and aldehyde moieties, with their abundance depending on the feedstock source (J. Cerino-Córdova et al., 2020 ). Metabolite profiling in SCGs primarily involves dehydration and depolymerization reactions, which facilitate the breakdown of macromolecular structures into bioactive intermediates. Hydrolysis further improves extraction efficiency by enhancing metabolite bioavailability. Coffee plants contain two principal classes of nucleotide-derived alkaloids: purine alkaloids (e.g., caffeine, 1,3,7-N-trimethylxanthine) and pyridine alkaloids (e.g., trigonelline). Caffeine and trigonelline typically comprise 1–2% of the coffee bean's dry weight. LC-MS analyses have confirmed the presence of caffeine in SCG extracts obtained using ethanol, methanol, water, and glycerol/methanol mixtures. Caffeine, a methylated purine derivative, is biosynthesized via methylation of xanthine skeletons, beginning with the conversion of xanthosine to 7-methylxanthosine (Ashihara, 2016 ). Furthermore, paraxanthine (1,7-dimethylxanthine), a caffeine metabolite, was detected in methanolic and aqueous SCG extracts. Caffeine undergoes enzymatic modifications to form biologically active derivatives such as paraxanthine, theobromine, and theophylline. Phenolic compounds present in SCGs such as quinic acid and trans-cinnamic acid undergo enzymatic transformation into caffeic acid, p-coumaric acid, and ferulic acid. These intermediates contribute to the synthesis of CGAs including caffeoylquinic acids (CQAs), feruloylquinic acids (FQAs), and p-coumaroylquinic acids (p-CoQAs), which exhibit well-documented antioxidant and anti-inflammatory properties (Valanciene and Malys, 2022 ). Additionally, diterpenes such as gibberellin A15 play regulatory roles in plant biochemistry. The biosynthesis of CGAs in SCGs proceeds via the phenylpropanoid metabolic pathway, which generates hydroxycinnamic acids as precursors. The process initiates with the deamination of phenylalanine to cinnamic acid by phenylalanine ammonia-lyase (PAL), a key regulatory enzyme (Taofiq et al., 2017 ). Cinnamic acid undergoes hydroxylation, catalysed by cinnamate-4-hydroxylase (C 4 H), to yield hydroxycinnamic acids such as caffeic acid, p-coumaric acid, and ferulic acid (Feduraev et al., 2020 ). These acids subsequently esterify with quinic acid through the action of hydroxycinnamoyltransferase (HCT), forming various CGA isomers (Habtemariam, 2019 ). For instance, caffeic acid forms CQAs, ferulic acid forms FQAs, and p-coumaric acid forms p-CoQAs. Comprehensive profiling of these isomers via LC-MS facilitates their exploitation in industrial applications and functional food development (Rojas-González et al., 2022 ). The biosynthetic pathway of diterpenes in SCGs involves the generation of gibberellin A15 through a series of enzymatic steps. Isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP) serve as five-carbon precursors for isoprenoid synthesis (Chaves et al., 2016 ). These condense to form geranylgeranyl diphosphate (GGDP) via geranylgeranyl diphosphate synthase (GGPPS) (Haney et al., 2017 ), which is subsequently converted to copalyl diphosphate (CDP) by ent-copalyl diphosphate synthase (CPS) (Sun et al., 2021 ). CDP then undergoes multiple transformations such cyclization, oxidation, and rearrangement which mediated by cytochrome P450 monooxygenases (CYPs) and other enzymes, ultimately yielding gibberellin A15. In conclusion, the detailed characterization of SCG metabolites via advanced analytical techniques such as LC-MS provides critical insights into their chemical complexity and application potential. By employing sustainable extraction methods and elucidating biosynthetic pathways, this study advances the valorisation of SCGs in alignment with circular economy principles and environmental sustainability goals within the coffee industry. Bioactive secondary metabolite and the properties The profiling of metabolites from SCGs has been extensively studied, revealing the presence of secondary metabolites with substantial potential as value-added products in pharmaceutical and cosmetic applications. Table 4 categorizes the primary secondary metabolites identified through LC-MS analysis, illustrating their diverse functionalities, including antioxidant properties, UV radiation protection, antibacterial effects, anti-inflammatory activity, and anti-cellulite benefits. These compounds have been extensively documented, demonstrating their efficacy across various applications. Table 4 Use of main secondary metabolites in SCGs for different purposes. Potential Secondary metabolite Antioxidant properties Caffeic acid (Purushothaman et al., 2022 ) CGAs (Liang and Kitts, 2015 ; Wang et al., 2022 ) Protection against UV radiation Caffeine (Conney et al., 2013 ) Phenolic compound including flavonoids, Quinic acids, ferulic acid) (Ghazi, 2022 ) CGAs (Bhattacharyya et al., 2014 ; Xue et al., 2022 ) Anti-bacterial properties Caffeine (Almeida et al., 2006 ; Woziwodzka et al., 2022 ) Anti-inflammatory properties Caffeine (Castaldo et al., 2021 ; Eichwald et al., 2023 ) CGAs (Huang et al., 2023 ) Caffeic acid (Zielińska et al., 2021 ) Anti-cellulite properties Caffeine (Herman and Herman, 2013 ; Vogel et al., 2022 ) A review by Espíndola et al. emphasized the significance of caffeic acid in hepatocarcinoma, a form of liver cancer. Research suggests that caffeic acid exerts potent anticancer effects by modulating key signalling pathways involved in cell growth, proliferation, and apoptosis. Its chemical structure facilitates interactions with specific molecular targets within hepatocarcinoma cells, influencing cancer-related cellular mechanisms (Sun et al., 2021 ). Liang et al. further classified CGAs into subcategories such as CQAs, p-CoQAs and FQAs (Liang and Kitts, 2015 ). Epidemiological studies indicate a correlation between coffee consumption and a reduced risk of chronic diseases, suggesting that CGAs mitigate oxidative stress by regulating intracellular redox balance. Additionally, these compounds exhibit anti-inflammatory effects through modulation of metabolic pathways (Liang and Kitts, 2015 ). Conney et al. demonstrated caffeine’s protective role against UVB-induced skin cancer, proposing mechanisms that include its function as a natural sunscreen and its ability to induce apoptosis in precancerous and cancerous lesions via p53-dependent and independent pathways (Conney et al., 2013 ). Similarly, Ghazi et al. reported that polyphenolic compounds, particularly flavonoids derived from plant and algal extracts which provide photoprotection against ultraviolet radiation. These compounds serve as effective UV filters due to their antioxidant and anti-inflammatory properties, offering a promising natural alternative to synthetic UV blockers in skincare formulations (Ghazi, 2022 ). In line with these findings, Xue et al. investigated CGAs’ protective role against UVA-induced skin photoaging, revealing their regulation of collagen metabolism and apoptosis in human dermal fibroblasts. These properties suggest their potential for integration into photoprotective and anti-aging cosmetic formulations (Xue et al., 2022 ). Additionally, Bhattacharyya et al. demonstrated that CGA-phospholipid complexes provided enhanced protection against UVA-induced oxidative stress compared to conventional formulations. Notably, the protective effects were most pronounced when UVA irradiation occurred four hours post-application, indicating sustained photoprotection (Bhattacharyya et al., 2014 ). Beyond photoprotection, caffeine has been shown to enhance the antibacterial efficacy of widely used antibiotics. Woziwodzka et al. investigated caffeine’s effect on 30 antibiotics against Staphylococcus aureus, finding that it potentiated the antibacterial activity of specific antibiotics, particularly ciprofloxacin and tetracycline, against Gram-negative pathogens (Woziwodzka et al., 2022 ). Similarly, Almeida et al. examined the antimicrobial effects of coffee extracts and their chemical constituents against nine enterobacteria strains. Their results indicated that caffeine, CGAs, and protocatechuic acid exhibited potent antimicrobial effects, with caffeine and protocatechuic acid demonstrating significant activity against Salmonella enterica. Importantly, the caffeine concentration in coffee extracts was sufficient to exert meaningful antimicrobial effects, reinforcing its relevance in food safety applications (Almeida et al., 2006 ). Secondary metabolites in SCGs also exhibit anti-inflammatory and anti-cellulite properties. Eichwald et al. explored caffeine’s influence on gene expression related to inflammation, adenosine receptors, epigenetics, and oxidative metabolism in mouse vastus lateralis muscle subjected to lipopolysaccharide (LPS)-induced inflammation. The findings suggest that caffeine pre-treatment reduced pro-inflammatory biomarker expression, fostering an anti-inflammatory environment. Additionally, the modulation of adenosine receptors and epigenetic mechanisms implies that caffeine’s anti-inflammatory effects may be mediated through epigenetic alterations (Eichwald et al., 2023 ). Castaldo et al. investigated the antioxidant and anti-inflammatory properties of coffee compounds, demonstrating that digestion may enhance their bioactivity. These findings contribute to understanding coffee’s health benefits, particularly regarding its potential post-simulated gastrointestinal digestion (Castaldo et al., 2021 ). The dermatological applications of caffeine have been validated through scientific studies, particularly in cellulite treatment. Vogel et al. assessed the quality of caffeine-containing cosmetic formulations for cellulite reduction (Vogel et al., 2022 ). Their study examined microbiological safety, pH stability, colour retention, caffeine concentration, and viscosity. While caffeine content and viscosity remained stable, microbiological analysis revealed that mold and yeast concentrations exceeded permissible thresholds set by the Brazilian pharmacopoeia, and pH levels declined over time, increasing acidity. Despite these challenges, the study affirmed caffeine’s viability as an active ingredient in anti-cellulite treatments, reinforcing its relevance in cosmetic dermatology. Conclusion This study underscores the potential of SCGs as a valuable derivative of industrial crops, contributing to the sustainable extraction of bioactive compounds. The application of UAE combined with a glycerol/methanol co-solvent system demonstrated enhanced efficiency in recovering phenolic-rich metabolites, with optimized yields of TPC and TFC. Comparative evaluation of seven solvents highlights the critical role of solvent polarity in influencing extraction outcomes, with glycerol/methanol providing superior performance. Comprehensive LC-MS profiling identified a wide spectrum of bioactive, including caffeine, CGAs, and phenolic compounds, renowned for their multifunctional applications. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7024028","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":481257290,"identity":"e538d166-5322-4479-8ec0-0938def0d7a7","order_by":0,"name":"Rabita Mohd Firdaus Achutan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYFACHoYDDAxycgiBA8RoOcBgbEyaFqAi48QGorWYt589ePhDjUH6/Bm5xyR+tjHI8d1IYN3Mg0eLzJm8hAMHjhnkbriRlybZ28ZgLHkjge02Pi0SDDkGBw6w/cndIJFjdoO3jSFxA0Et/G+AWv4ZpMvPyDG7+beNoZ6wFgmgLQfbDBIYbuSY3QbakmBAWMu7hANn+wwMN5x5Y/5b5pyE4cwzD9tuzsHrsNzDHyq+GcjLt+cYG74ps5HnO5587MYbPFpQASObBIhsYMLnMDTwB6r1B/FaRsEoGAWjYPgDAP73VZvU3VmLAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0003-6557-8065","institution":"Sunway University","correspondingAuthor":true,"prefix":"","firstName":"Rabita","middleName":"Mohd Firdaus","lastName":"Achutan","suffix":""},{"id":481257291,"identity":"627cd230-cd9e-4e56-a8fd-1c322d42c012","order_by":1,"name":"Nurul Atiqah Izzati Md Ishak","email":"","orcid":"","institution":"Sunway University","correspondingAuthor":false,"prefix":"","firstName":"Nurul","middleName":"Atiqah Izzati Md","lastName":"Is","suffix":"Md"},{"id":481257292,"identity":"0a96cd8e-40cb-4b15-8578-daaefa1b2f6e","order_by":2,"name":"Mohamed Kheireddine Aroua","email":"","orcid":"","institution":"Sunway University","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"Kheireddine","lastName":"Aroua","suffix":""},{"id":481257293,"identity":"a02ab851-a20d-4f1a-810e-ff96cc909445","order_by":3,"name":"Lai Ti Gew","email":"","orcid":"","institution":"Sunway University","correspondingAuthor":false,"prefix":"","firstName":"Lai","middleName":"Ti","lastName":"Gew","suffix":""}],"badges":[],"createdAt":"2025-07-02 01:16:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7024028/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7024028/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86538015,"identity":"036a5b53-0bcc-490a-9385-680fdd301685","added_by":"auto","created_at":"2025-07-11 19:12:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45522,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of extraction of SCGs using different solvents.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/11db37214d71e56a24718edb.jpg"},{"id":86538016,"identity":"620bca38-1f46-41f3-8a4c-389f49b0a373","added_by":"auto","created_at":"2025-07-11 19:12:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96643,"visible":true,"origin":"","legend":"\u003cp\u003eSEM was performed to portray the morphological characterisation of SCG at (a) magnification: 300x; (b) magnification: 1000x; (c) EDX spectrum (d-h) EDX mapping.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/d618d1604a8f209917d739f8.jpg"},{"id":86538329,"identity":"ef9fe866-bfa3-471e-8c01-030bd406fada","added_by":"auto","created_at":"2025-07-11 19:20:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":100757,"visible":true,"origin":"","legend":"\u003cp\u003eFTIR spectra of (a) SCGs, extract using (b) G/E; (c) G/W; (d) G/M.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/5f4510ceaa0025032c2bff43.jpg"},{"id":86538020,"identity":"2b66d22b-1c75-4db4-8812-c3a86ee03228","added_by":"auto","created_at":"2025-07-11 19:12:59","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":80234,"visible":true,"origin":"","legend":"\u003cp\u003ePossible pathway of profiling metabolites from SCGs.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/57e2bcda120838035e2d741e.jpg"},{"id":87645375,"identity":"d1fdd077-df5b-4e8a-b5de-181d6bf73171","added_by":"auto","created_at":"2025-07-26 17:53:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1317617,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/e4874d66-31ef-47e6-8b3e-b639032870aa.pdf"},{"id":86538660,"identity":"35e2c7c3-63a2-48f9-bde1-c7ec0753dde8","added_by":"auto","created_at":"2025-07-11 19:28:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14135,"visible":true,"origin":"","legend":"","description":"","filename":"Int.J.Environ.Res.Highlight.docx","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/58a4644479b1d791e83e0b80.docx"},{"id":86538028,"identity":"3526a10f-6606-417d-ad53-f76b671811f7","added_by":"auto","created_at":"2025-07-11 19:13:00","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":148893,"visible":true,"origin":"","legend":"","description":"","filename":"Int.J.Environ.Res.SI.docx","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/c46d53eda11bced752be62bc.docx"},{"id":86538661,"identity":"6bb1a5a9-bd67-447f-907d-ad7b5015a158","added_by":"auto","created_at":"2025-07-11 19:29:00","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":417465,"visible":true,"origin":"","legend":"","description":"","filename":"Table2and3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7024028/v1/586a3f2f3f42c890c36ebd74.docx"}],"financialInterests":"","formattedTitle":"Extraction and characterization of bioactive compounds from coffee by-products: physicochemical and LC-MS analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoffee is among the most widely consumed beverages globally, generating vast quantities of organic waste. Spent coffee grounds (SCGs), a major byproduct of coffee production, are typically discarded post-brewing, contributing to significant environmental concerns. According to the International Coffee Organization, global coffee production reached approximately 169\u0026nbsp;million 60 kg bags in the 2020/2021 season, underscoring the massive volume of SCGs generated annually (Mitraka et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Improper disposal through landfilling or incineration will not only escalates soil and air pollution but also contradicts sustainability efforts such as United Nations Sustainable Development Goal (SDG) 12: Responsible Consumption and Production. Given their widespread availability and rich bioactive composition, SCGs present an opportunity for waste valorisation, particularly in industrial crop-based bioactive compound extraction (Abubakar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSCGs contain alkaloids like caffeine and trigonelline, chlorogenic acids (CGAs), phenolic acids, and other polyphenols (Hewage et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; S\u0026aacute;nchez-Camargo et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), all of which are well-documented for antioxidant (Andrade et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), UV protection (Choi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), anti-bacterial (Calheiros et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), anti-inflammatory (Angeloni et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and anticellulite effects (Ribeiro et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These properties make SCGs an attractive resource for pharmaceutical, cosmetic, and nutraceutical industries while supporting the demand for eco-conscious formulations and green chemistry approaches. Consequently, sustainable extraction methodologies are vital to unlocking the full potential of SCGs while minimizing environmental impact and aligning with bio-based industrial applications. Several extraction techniques have been explored for the recovery of these bioactive, including Soxhlet extraction, microwave-assisted extraction, hydrothermal processing, and ultrasound-assisted extraction (UAE) (Bouhzam et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chatzimitakos et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among these, UAE has emerged as a promising technology due to its energy efficiency, shorter processing time, and enhanced extraction yield (Ghenabzi̇A et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Patrice Didion et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the choice of solvent significantly impacts extraction efficiency and metabolite composition. Traditional solvents such as methanol and acetone, though effective, raise concerns regarding toxicity and environmental sustainability. In contrast, green solvents like ethanol, water, and glycerol are increasingly favoured for their biodegradability, low toxicity, and eco-friendly profile (Brglez Mojzer et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGlycerol (1,2,3-propanetriol), a naturally occurring biocompatible polyol, has received attention for its low volatility, high solubility, and suitability for bioactive compound extraction (Joshi and Adhikari, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Recognized as a preferred green solvent under Pfizer\u0026rsquo;s solvent selection guide, glycerol's ability to dissolve organic and inorganic compounds makes it a viable alternative for extracting phenolic compounds and alkaloids from SCGs (Rodrigues et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Besides, in the food and beverage industry, it serves as a solvent, sweetener, and preservative, while in cosmetics, it functions as an emollient and carrier. Given its biocompatibility and safety, glycerol presents a viable alternative to conventional solvents for extracting bioactive compounds (Chilakamarry et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fluhr et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo complement extraction methods, advanced analytical techniques play a crucial role in identifying and quantifying the diverse array of compounds present in natural matrices. Among these, liquid chromatography\u0026ndash;mass spectrometry (LC-MS) is a widely recognized tool for detailed chemical profiling, frequently applied to natural products, biological samples, pharmaceuticals, and environmental matrices (Alqarni, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). While prior research has largely focused on quantifying individual metabolites, few studies have integrated metabolite profiling with biosynthetic pathway analysis or linked such findings to potential applications. For example, CGAs are synthesized through the phenylpropanoid pathway, initiating from phenylalanine and progressing through enzymatic transformations to generate functional derivatives such as \u003cem\u003etrans\u003c/em\u003e-cinnamic acid, 4-coumarate, and 4-coumaroyl-CoA (Grohar et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study systematically examines seven distinct solvent systems, including ethanol, methanol, water, and glycerol-based co-solvent mixtures (glycerol-methanol, glycerol-ethanol, glycerol-water) for SCG metabolite extraction and characterization. Total phenolic content (TPC) and total flavonoid content (TFC) assessments, coupled with LC-MS chemical profiling, provide a comprehensive framework for sustainable extraction methodologies in industrial crop applications. Additionally, this study explores biosynthetic pathways, particularly the phenylpropanoid pathway involved in CGA synthesis, revealing insights into metabolite bioavailability and potential functionality. To the best of our knowledge, this is the first comprehensive study to integrate green solvent extraction, LC-MS profiling, and metabolic pathway analysis for SCGs, thereby advancing their potential for sustainable bioactive compound extraction and industrial product development.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eSCGs pre-treatment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe pristine SCGs (\u003cem\u003eCoffea arabica\u003c/em\u003e L.) was collected from the Starbuck at Sunway University, Selangor. The collected SCGs was dried in the oven at 373.15 K until it reached a moisture value of \u0026lt;\u0026thinsp;10%. The dried SCGs obtained were kept in airtight containers at ambient and dark rooms until the extraction process.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePreparation of solvents and extraction of bioactive compounds\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo extract bioactive compounds from SCGs, various solvents were utilized, including water, ethanol, methanol, glycerol, and glycerol-based mixtures comprising glycerol/water (G/W, 1:1 v/v), glycerol/ethanol (G/E, 1:1 v/v), and glycerol/methanol (G/M, 1:1 v/v). These glycerol-based mixtures were prepared in advance to ensure consistency before the extraction process. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides an overview of the extraction workflow, illustrating the step-by-step process employed in obtaining bioactive compounds from SCGs. The procedure begin with the addition of 0.5 g of dried SCGs to 10 mL of the respective solvent, followed by mechanical processing involving grinding with a pestle and mortar, vortex mixing, and sonication for 30 minutes. To enhance the efficiency of extraction, the sonication process was repeated every 24 hours over a 72-hour incubation period while maintaining a constant temperature of 300.15 K. After the incubation period, the SCG suspensions underwent centrifugation at 2000 rpm for 15 minutes to separate the liquid extracts from the solid residues. The resulting supernatants were then subjected to filtration to remove any remaining particulates. Different filtration methods were applied based on the solvent used: ethanol, methanol, and water extracts were filtered sequentially using mixed cellulose ester (MCE) syringe membrane filters with 0.45 \u0026micro;m and 0.22 \u0026micro;m pore sizes, while glycerol-based extracts were filtered using nylon syringe membrane filters with the same pore sizes. Once filtered, all extracts were transferred into 50 mL centrifuge tubes and stored under refrigerated conditions at 277.15 K to maintain their chemical stability until further analysis.\u003c/p\u003e\u003cp\u003eEach extract was labelled based on the solvent used: Water (W), Ethanol (E), Methanol (M), Glycerol (G), Glycerol/Water (G/W), Glycerol/Ethanol (G/E), and Glycerol/Methanol (G/M). To ensure accuracy and reproducibility, the entire extraction procedure was conducted in triplicate.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMorphological and surface characterization of SCGs extracts\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eScanning electron microscopy (SEM)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe surface morphology and elemental composition of the pristine SCGs was investigated utilizing SEM coupled with Energy Dispersive X-ray Spectroscopy (EDX) instrumentation (Model: Tescan VEGA-3).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhytochemical assays of SCGs extracts\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTotal phenolic content (TPC)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe TPC of the SCG extracts was determined following a modified version of the method described by Lim et al. (Lim et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To ensure accuracy, a calibration curve was established using gallic acid (GA) as the standard, prepared in concentrations ranging from 0 to 1000 \u003cem\u003e\u0026micro;\u003c/em\u003eg/mL. The reaction mixture for the TPC assay was prepared by combining 5 \u0026micro;L of the extract sample (10 mg/mL) or GA standard with 25 \u003cem\u003e\u0026micro;\u003c/em\u003eL of Folin\u0026ndash;Ciocalteu reagent, 350 \u003cem\u003e\u0026micro;\u003c/em\u003eL of deionized distilled water (ddH₂O), and 75 \u003cem\u003e\u0026micro;\u003c/em\u003eL of 20% sodium carbonate solution. An additional 45 \u003cem\u003e\u0026micro;\u003c/em\u003eL of ddH₂O was added to complete the reaction volume. The mixture was thoroughly homogenized within 10 minutes and subsequently incubated in complete darkness for 60 minutes to facilitate the reaction. Following incubation, the absorbance of each sample was measured at 750 nm using a UV-visible spectrophotometer microplate reader. A standard curve was generated by plotting the absorbance values at 750 nm against the corresponding concentrations of GA standards (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The linear regression equation obtained from the calibration curve was used to determine the TPC of the SCG extracts. The results were expressed in milligrams (mg) of gallic acid equivalents (GAE) per gram (g) of extract (mg GAE/g).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTotal flavonoid content (TFC)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTFC of the SCG extracts was determined using a modified version of the method outlined by Lim et al. (2023) (Lim et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To ensure accuracy in quantification, a calibration curve was constructed using quercetin as the reference standard, with concentrations ranging from 0 to 1000 \u003cem\u003e\u0026micro;\u003c/em\u003eg /mL. The assay was conducted by preparing reaction mixtures in which 10 mg/mL of SCG extract or quercetin standard was combined with 250 \u003cem\u003e\u0026micro;\u003c/em\u003eL of 2% aluminum chloride (AlCl₃) solution, 250 \u003cem\u003e\u0026micro;\u003c/em\u003eL of 1 M sodium acetate (CH₃COONa), and 490 \u003cem\u003e\u0026micro;\u003c/em\u003eL of deionized distilled water (ddH₂O). The mixture was thoroughly homogenized and incubated for 15 minutes to allow the reaction to proceed. Following the incubation, absorbance readings were recorded at 425 nm using a UV-visible spectrophotometer microplate reader (TECAN, Infinite M200 PRO). The standard curve was established by plotting the absorbance values at 425 nm against the corresponding quercetin concentrations. (Fig. S2). The linear regression equation obtained from this calibration curve was then used to calculate the TFC in the SCG extracts. The results were expressed in milligrams of quercetin equivalent (QE) per gram of extract (mg QE/g).\u003c/p\u003e\u003cp\u003e\u003cb\u003e2,2-Diphenyl-1-picrylhydrazyl (DPPH)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe antioxidant activity of the SCG extracts was evaluated using the DPPH radical scavenging assay, following a standardized protocol. Ascorbic acid was utilized as the positive control, prepared in a series of concentrations ranging from 0 to 100 \u003cem\u003e\u0026micro;\u003c/em\u003eg. The prepared solutions were carefully transferred into individual wells of sterile 96-well microplates, ensuring consistency across all replicates (n\u0026thinsp;=\u0026thinsp;4). To initiate the reaction, a 0.2 mM DPPH solution was added to each well, covering both the test samples and the ascorbic acid standard. After gentle mixing for approximately five seconds, the plates were incubated in a dark environment at room temperature for 15 minutes to allow the reaction to proceed. Once the incubation period was completed, absorbance measurements were recorded at 517 nm using a UV-visible spectrophotometer microplate reader. The antioxidant capacity of the extracts was quantified based on their ability to scavenge DPPH free radicals, with results expressed in terms of IC₅₀ values. These IC₅₀ values, representing the concentration required to inhibit 50% of the free radicals, were then compared to the ascorbic acid standard to assess the relative antioxidant potency of the SCG extracts.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhysicochemical characterization of SCGs extracts\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLiquid chromatography-mass spectrometry (LC-MS)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe identification and characterization of secondary metabolites in SCG extracts were conducted using an Agilent 1290 Infinity LC system, coupled with an Agilent 6520 Accurate-Mass Quadrupole Time-of-Flight (Q-TOF) mass spectrometer. This setup, equipped with a dual-electron spray ionization (ESI) source, enabled analysis in both positive and negative ionization modes. To optimize performance, the experimental procedure was adapted from established methodologies by Lim et al. and Thiyagarasaiyar et al., with minor modifications (Lim et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Thiyagarasaiyar et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Chromatographic separation was performed using an Agilent Zorbax Eclipse XDB-C18 Narrow-Bore column (2.1 mm \u0026times; 150 mm, 3.5 \u0026micro;m), maintained at 25\u0026deg;C, while the autosampler was kept at 4\u0026deg;C. The mobile phase, consisting of a 60:40 water-acetonitrile mixture, was delivered at a constant flow rate of 0.5 mL/min. SCG extract samples (3.0 \u0026micro;L) were injected into the system and analysed under both ionization polarities. Mass spectra were recorded within an m/z range of 100 to 3200, with a fragmentor voltage of 125 V. Nitrogen gas was used as the collision gas to facilitate ion fragmentation. Data acquisition in positive-ion ESI mode was performed at a scan rate of 1.03 s per scan. The resulting chromatographic and spectral data were processed using Agilent MassHunter Qualitative Analysis software (version B.05.00). Compound identification and characterization were achieved by comparing LC-MS spectral data with entries in the METLIN database, enabling precise identification of bioactive metabolites in the SCG extracts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFourier Transform Infrared (FTIR) analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe identification of functional groups present in the SCG extracts was conducted using FTIR spectroscopy, utilizing a Bruker VERTEX 70v spectrometer (Rosenheim, Germany). The analysis was performed with an attenuated total reflectance (ATR) technique to facilitate direct measurement of the samples without extensive preparation. Prior to sample analysis, a baseline scan was performed by collecting spectra without any sample in contact with the ATR crystal to ensure accuracy and eliminate background interference. Once the baseline scan was established, a few drops of each SCG extract were carefully placed onto the ATR crystal window. The sample was then brought into direct contact with the crystal, and the spectral data acquisition commenced. The FTIR spectra were recorded over a broad wavenumber range of 4000\u0026ndash;400 cm⁻\u0026sup1;, capturing characteristic absorption bands corresponding to different functional groups within the extracts. The absorbance values obtained provided insights into the molecular composition of the SCG extracts, enabling the identification of key functional groups associated with bioactive compounds.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e\u003cstrong\u003eMorphological and surface characterization of SCGs extracts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScanning Electron Microscopy (SEM)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe surface morphology of SCGs was analysed using SEM to gain insights into their structural characteristics. SEM imaging was conducted at different magnification levels to observe the microstructural details of the untreated SCGs particles. The micrographs obtained at magnifications of 300\u0026times; and 1000\u0026times; are illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e (a) and Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e (b). At 300\u0026times; magnification, the SEM images show a heterogeneous distribution of particle sizes, indicating the irregular nature of dry SCG particles. When observed at a higher magnification of 1000\u0026times;, the SCG particles exhibit a distinctive \u0026quot;sponge-like\u0026quot; structure with flake-like formations. The pore sizes measured within the SCGs structure were found to range from 10 to 18 \u0026micro;m. This observation aligns with previous studies, which have reported that untreated biowaste materials, including SCGs, typically feature irregular pores, resulting in a loosely packed and coarse porous network (Mariana et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Similarly, Bejenari et al. examined pristine SCGs and reported pore sizes between 8 and 17 \u0026micro;m, with the majority of SCGs particles measuring approximately 389.48\u0026thinsp;\u0026plusmn;\u0026thinsp;19.47 \u0026micro;m in size (Bejenari et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). These findings are consistent with reports by Zein et al. and Lee et al., who documented dry SCG pore sizes extending up to 30 \u0026micro;m (Zein et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eTo further investigate the elemental composition of SCGs, energy-dispersive X-ray (EDX) spectroscopy (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec) (EDX) mapping (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed-f) was performed. The EDX results confirm that carbon is the predominant element, accounting for 90.85% of the total atomic composition. Oxygen follows as the second most abundant element at 8.37%, with trace amounts of potassium (0.45%), magnesium (0.21%), and sulfur (0.32%). These elemental distributions provide valuable insights into the composition of SCGs, which may influence their potential applications in various fields.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn-vitro antioxidant activities\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTPC and TFC of SCGS extracts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhenolic compounds are a diverse group of secondary metabolites synthesized by plants in response to various environmental stressors, including exposure to ultraviolet (UV) radiation and pathogenic attacks (Yang et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). These bioactive compounds play a crucial role in plant defence mechanisms and exhibit strong antioxidant properties due to their ability to donate hydrogen atoms, reduce oxidative species, chelate metal ions, and quench singlet oxygen. Through these mechanisms, phenolic compounds effectively neutralize free radicals, thereby mitigating oxidative damage (Mathew et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Furthermore, they disrupt the chain reaction of free radical formation by stabilizing as phenoxy radicals, which are relatively less reactive, thus preventing further oxidative stress (Leopoldini et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn this study, the TPC of SCG extracts was analysed, and the results are summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The findings indicate notable variations in TPC among different solvent extractions. Among the tested extracts, the glycerol/methanol (G/M) extract exhibited the highest phenolic content, reaching 6.059 mg of gallic acid equivalents per gram (mg GAE g⁻\u0026sup1;) of extract. This was followed by the glycerol/water (G/W) extract, which contained 4.352 mg GAE g⁻\u0026sup1;, and the glycerol/ethanol (G/E) extract with 3.305 mg GAE g⁻\u0026sup1;. The water extract demonstrated a slightly lower phenolic content at 3.607 mg GAE g⁻\u0026sup1;, while the methanol extract contained 3.382 mg GAE g⁻\u0026sup1;. The ethanol extract exhibited a further reduction in phenolic concentration, with a recorded value of 2.529 mg GAE g⁻\u0026sup1;. Notably, the pure glycerol extract displayed the lowest TPC among all tested solvents, with a value of 1.442 mg GAE g⁻\u0026sup1;. These variations highlight the influence of solvent polarity on phenolic compound extraction, suggesting that mixed solvent systems, particularly those incorporating glycerol and methanol, enhance the solubilization and recovery of phenolic constituents from SCGs.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePhytochemical Contents of the SCGs Extract\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSolvent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTPC\u003c/p\u003e\n \u003cp\u003e(mg GAE/g)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTFC\u003c/p\u003e\n \u003cp\u003e(mg QE/g)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDPPH IC\u003csub\u003e50\u003c/sub\u003e (mg/ml)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlycerol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.442\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.104\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.529\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.474\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.382\u0026thinsp;\u0026plusmn;\u0026thinsp;0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.146\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.607\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.284\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG/E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.304\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.665\u0026thinsp;\u0026plusmn;\u0026thinsp;0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.713\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG/W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.352\u0026thinsp;\u0026plusmn;\u0026thinsp;0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.490\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG/M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.059\u0026thinsp;\u0026plusmn;\u0026thinsp;0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.549\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.552\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong the pure solvents, methanol proved to be the most effective for extracting phenolic compounds, followed by water, ethanol, and glycerol. This is in agreement with Musatto et al., who optimized phenolic extraction from SCGs using a conventional solid\u0026ndash;liquid extraction method with 60% methanol at a solvent-to-solid ratio of 40 mL/g SCGs over 90 minutes, obtaining a TPC of 16 mg GAE g⁻\u0026sup1; (Mussatto et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Comparisons with other studies also highlight ethanol and methanol as optimal solvents for phenolic extraction due to their high polarity (Calle Chumo et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, research indicates that ultrasonic-assisted extraction can significantly enhance phenolic yields. Gigliobianco et al. employed subcritical water extraction at 179\u0026deg;C for 36 minutes and reported substantial TPC improvements (Gigliobianco et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Water, often considered the most environmentally friendly solvent due to its low toxicity, non-flammability, cost-effectiveness, and ease of separation (Zhou et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), does not always provide the most efficient extraction. Several studies have demonstrated that the addition of co-solvents, such as methanol, ethanol, or glycerol, enhances polyphenol solubility by increasing the polarity of the extraction medium(Awad et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bouhzam et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Da Porto et al., n.d.; Panzella et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Thouri et al. confirmed that solvent polarity plays a crucial role in the yield of extracted polyphenols, as polar solvents effectively solubilize antioxidant compounds through hydrogen bonding interactions between the solvent and polyphenolic hydroxyl groups (Thouri et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Consistent with these observations, the findings of this study highlight that the inclusion of co-solvents can significantly improve polyphenol extraction efficiency.\u003c/p\u003e\n\u003cp\u003eFlavonoids, a major subclass of polyphenolic compounds, have been widely studied for their bioactive properties. Structurally, flavonoids are characterized by two aromatic rings connected by a three-carbon bridge, forming an oxygenated heterocyclic system. The experimental results presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e indicate considerable variation in TFC across different extracts. The G/M extract exhibited the highest TFC at 8.549 mg quercetin equivalents per gram (mg QE g⁻\u0026sup1;), followed by the G/E extract (6.665 mg QE g⁻\u0026sup1;), methanol extract (4.146 mg QE g⁻\u0026sup1;), G/W extract (3.490 mg QE g⁻\u0026sup1;), ethanol extract (3.474 mg QE g⁻\u0026sup1;), water extract (0.284 mg QE g⁻\u0026sup1;), and the glycerol extract (0.104 mg QE g⁻\u0026sup1;). Similar to the TPC results, the G/M extract demonstrated superior flavonoid extraction efficiency, likely due to methanol\u0026rsquo;s strong polarity, which facilitates the solubilization of both polar and semi-polar compounds.\u003c/p\u003e\n\u003cp\u003eThese findings align with those reported by Chen et al., who observed TFC values ranging from 5.6 to 25.1 mg QE g⁻\u0026sup1; in coffee pulp extracts obtained using ethanol concentrations between 0% and 99.5% (Chen et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, Alkaltham et al. found that methanol and ethyl acetate extractions yielded TFC values of 8.02 mg QE g⁻\u0026sup1; and 0.787 mg QE g⁻\u0026sup1;, respectively, in coffee pulp extracts (Alkaltham et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to Huaman et al., glycerol, when used in combination with methanol, ethanol, or water, significantly improved polyphenol extraction efficiency (Huam\u0026aacute;n-Castilla et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). This enhancement is attributed to flavonoids being predominantly polar compounds due to their unsubstituted hydroxyl groups, making polar solvents like ethanol, methanol, and ethyl acetate more suitable for their extraction from plant matrices (Etika and Iryani, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Conversely, less polar flavonoids such as isoflavones, flavanones, flavones, and flavanols exhibit better solubility in less polar solvents like glycerol, hexane, dichloromethane, and diethyl ether (Chaves et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). The results of this study further support the use of solvent combinations rather than single solvents to selectively enhance the extraction of specific bioactive compounds based on their polarity. Tailoring the extraction process in this way maximizes the efficiency and yield of target compounds. Moreover, combining alcohol-based solvents such as methanol and ethanol with glycerol not only enhances extraction efficiency but also mitigates health and safety risks associated with the use of methanol and ethanol alone. Additionally, the biodegradable and eco-friendly nature of glycerol contributes to the sustainability of the extraction process, making it a viable option for future green extraction methodologies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntioxidant Activity of SCGs Extracts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe phenolic content of substances is closely associated with their ability to neutralize free radicals, which is a key determinant of their antioxidant potential. In this study, the free radical scavenging activity of SCGs extracts was evaluated using the DPPH assay, a widely recognized method for measuring antioxidant activity. The assay is based on the ability of antioxidants to reduce the stable, purple-coloured DPPH radical (DPPH\u0026bull;) into a yellow hydrazine molecule by donating electrons or hydrogen atoms. This reaction effectively neutralizes the radical, leading to a loss of colour intensity, which can be quantitatively measured using spectrophotometry (Munteanu and Apetrei, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The extent of this reduction is directly proportional to the availability of hydroxyl groups within the antioxidant compounds present in the extract (Baliyan et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, the antioxidant efficacy of SCGs extracts was assessed using the half-maximal inhibitory concentration (IC\u003csub\u003e50\u003c/sub\u003e) value, which represents the concentration of extract required to reduce the initial DPPH\u0026bull; concentration by 50%. A lower IC\u003csub\u003e50\u003c/sub\u003e value indicates stronger antioxidant capacity (Rivero-Cruz et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe results of the DPPH scavenging assays for all tested extracts, as presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, reveal significant variations in antioxidant activity based on the extraction solvent used. Notably, extracts obtained using single solvents such as ethanol, methanol, water, and glycerol exhibited negative IC\u003csub\u003e50\u003c/sub\u003e values, suggesting an absence of significant antioxidant activity. In contrast, extracts prepared using binary solvent systems, specifically glycerol/methanol (G/M), glycerol/water (G/W), and glycerol/ethanol (G/E), demonstrated notable antioxidant activity. Among these, the G/M extract exhibited the lowest IC\u003csub\u003e50\u003c/sub\u003e value (1.552 mg/ml), indicating the highest scavenging efficiency compared to the G/W and G/E extracts. These results are consistent with the TPC and TFC findings, reinforcing the correlation between phenolic and flavonoid content and antioxidant activity.\u003c/p\u003e\n\u003cp\u003eThe observed antioxidant activity of SCGs extracts aligns with findings reported in previous studies. Kusumocahyo et al. investigated the extraction efficiency of coffee pulp using a semi-polar ethanol-water mixture, concluding that a 50:50 solvent ratio yielded an extract with higher antioxidant activity (IC50\u0026thinsp;=\u0026thinsp;487.96\u0026thinsp;\u0026plusmn;\u0026thinsp;5.94 mg/ml) compared to pure water extraction. Their findings further emphasized the importance of solvent polarity in maximizing phenolic compound recovery and antioxidant activity (Kusumocahyo et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, Shang et al. analysed the antioxidant potential of SCGs from ten different sources using pressurized liquid extraction (PLE) with an ethanol-water solvent system. Their results showed substantial variation in the content of active compounds, including 5-caffeoylquinic acid (5-CQA) at levels ranging from 51 to 201 mg/g DW, total phenolics (TP) between 19 and 26 mg GAE/g DW, and caffeine concentrations of 3 to 9 mg/g DW. Antioxidant activity, assessed using both DPPH and ABTS assays, ranged from 16 to 38 mg VE/g DW and 10 to 28 mg VE/g DW, respectively, suggesting that SCGs are a promising source of bioactive polyphenols (Shang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe impact of pre-treatment methods on phytochemical retention was also highlighted by Kieu Tran et al., who demonstrated that drying conditions significantly influence the antioxidant potential of coffee pulp. Their study utilized a methanol-water solvent mixture (1:1, v/v) to extract secondary metabolites, revealing that vacuum drying at 90\u0026deg;C or 110\u0026deg;C yielded the highest DPPH radical scavenging capacity (2.24 mg TE/g DW) (Kieu Tran et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, research by Ansori et al. examined the antioxidant potential of SCGs from different coffee varieties, namely Robusta, Liberica, and Arabica. Using ultrasonic-assisted extraction with 60% ethanol, they found that Robusta SCGs exhibited the highest antioxidant capacity. Their findings suggest that SCGs contain potent electron-donating compounds that effectively inhibit oxidation chain reactions by stabilizing free radicals. Furthermore, skincare formulations enriched with SCGs extract exhibited 10 to 100 times higher antioxidant activity than formulations without the extract, underscoring the potential of SCGs as a valuable ingredient for functional applications (Universiti Malaysia Terengganu et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of metabolites profiling involved in SCGs extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLC-MS Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlant secondary metabolites constitute a diverse class of bioactive compounds synthesized by plants in response to various environmental stimuli, including biotic and abiotic stresses. These compounds, while not directly involved in essential physiological functions such as growth and reproduction, play crucial roles in plant defence and interaction with their environment. In this study, LC-MS analysis was conducted to identify the secondary metabolites present in SCGs extracts obtained using different solvent systems. The results, summarized in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, provide a detailed account of the major active secondary metabolites, including their retention time (RT), classification, molecular formula, and structure. The identified metabolites primarily fall into three distinct categories: alkaloids, phenolic compounds, and diterpenes.\u003c/p\u003e\n\u003cp\u003eOne of the predominant alkaloids detected in the SCGs extract was caffeine (1,3,7-trimethylxanthine), a bioactive compound widely recognized for its stimulant properties and potential health benefits (DePaula and Farah, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Caffeine has been extensively studied for its physiological effects, including its ability to enhance cognitive function and reduce the risk of neurodegenerative diseases such as Parkinson\u0026rsquo;s and Alzheimer\u0026rsquo;s (Kolahdouzan and Hamadeh, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, a study by Venkata Charan Tej et al. demonstrated that caffeine inhibited tumour growth in a carcinogen-induced fibrosarcoma model after 250 days of exposure to 3-MCA. In this study, caffeine was identified in extracts obtained using ethanol, methanol, water, and glycerol/methanol (G/M) as a positive ion with a mass-to-charge ratio (m/z) of 195.0876 at a retention time of 7.7 minutes (Venkata Charan Tej et al., 2019). This aligns with findings by Tahrim et al., who employed HPLC analysis to identify caffeine at a retention time of 7.71 minutes with an m/z of 195 (Tahrim et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). By comparing retention times with reference standards and utilizing accurate mass measurements from TOF-MS, they confirmed the presence of caffeine in real samples. In addition to caffeine, its metabolic derivatives\u0026mdash;paraxanthine, theobromine, and theophylline were identified, with paraxanthine exhibiting a retention time of 0.733 minutes and an m/z of 179.0569. Previous research suggests that both caffeine and paraxanthine exert neuroprotective effects, with paraxanthine specifically demonstrating the ability to protect dopaminergic neurons against neurodegeneration and synaptic loss (Okuro et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eApart from alkaloids, phenolic compounds represent another major class of secondary metabolites present in SCGs. These compounds are biosynthesized through the shikimic acid and pentose phosphate pathways, and their prevalence in coffee by-products is well-documented. One of the most significant phenolic compounds found in coffee is chlorogenic acid (CGAs), which constitutes between 4% and 8.4% of the dry matter content in Coffea Arabica and 7\u0026ndash;14.4% in Coffea Canephora, with hybrid species exhibiting intermediate levels (Gichimu et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). CGAs are esters formed through the conjugation of Quinic acid with \u003cem\u003etrans\u003c/em\u003e-cinnamic acids, including caffeic acid, p-coumaric acid, and ferulic acid. These compounds are primarily present as simple esters of hydroxycarboxylic acids or glucose (Rojas-Gonz\u0026aacute;lez et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Numerous studies have demonstrated the strong antioxidant and anti-inflammatory properties of caffeic acid and ferulic acid, which contribute to their protective effects against oxidative stress (Chaudhary et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liang and Kitts, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Additionally, Quinic acid has been identified for its antimicrobial activity, suggesting its potential role in inhibiting bacterial infections (Andrade et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ram\u0026oacute;n-Gon\u0026ccedil;alves et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe LC-MS analysis further confirmed the presence of Quinic acid and trans-cinnamic acid (ferulic acid) in the SCGs extracts. Quinic acid was detected at a retention time of 0.747 minutes with an m/z of 193.0696, while \u003cem\u003etrans\u003c/em\u003e-cinnamic acid was identified at 9.141 minutes with an m/z of 193.0506 (Moeenfard et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). In addition, three CGAs isomers\u0026mdash;\u003cem\u003ecis\u003c/em\u003e-5-CQA, 3-O-feruloylquinic acid, and 4-caffeoyl-1,5-quinolactone were detected, suggesting the potential isomerization of CGAs during extraction. These compounds exhibit multiple biological activities, including antioxidant, hepatoprotective, hypoglycaemic, and antiviral effects (Rojas-Gonz\u0026aacute;lez et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). CGAs serve as crucial defence compounds in plants against environmental stressors, while in humans, they offer significant therapeutic benefits (Alc\u0026aacute;zar Maga\u0026ntilde;a et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Research conducted by Andrade et al. identified caffeine and 5-CQA as the primary bioactive compounds in SCGs sourced from Guatemala, Brazil, Timor, and Ethiopia, using methanol/water solvent mixtures (Andrade et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Their findings were validated through the \u0026micro;-speed/UHPLC-PDA method, confirming the presence of additional bioactive compounds such as 3-CQA, caffeic acid, 4,5-diCQA, 1,5-diCQA, and 3,4-diCQA. These metabolites have been extensively documented for their biological activities, making them valuable for pharmaceutical, cosmetic, and food industry applications.\u003c/p\u003e\n\u003cp\u003eThe extraction efficiency of polyphenols, particularly CGAs and p-coumaric acids, was further validated by Gon\u0026ccedil;alves et al., who reported concentrations ranging from 0.02 to 4.8 mg/g and 0.173 to 0.50 mg/g, respectively, when water was used as the primary solvent (Ram\u0026oacute;n-Gon\u0026ccedil;alves et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The present study corroborates these findings, highlighting the effectiveness of polar solvent mixtures in isolating phytoconstituents such as polyphenols (Badr et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). In agreement with these results, Badr et al. identified rosmarinic acid and syringic acid as predominant phenolic acids in SCGs, while flavonoids such as apigenin-7-glucoside, naringin, epicatechin, and catechin were also detected. The use of isopropanol as an extraction solvent in their study demonstrated an eco-friendly approach to bioactive compound isolation. Furthermore, cytotoxicity assays on liver cancer cells (Hep-G2) revealed moderate activity with selective toxicity over healthy oral epithelial cell lines (OEC), though less potent than cisplatin, the positive control. The findings of this study emphasize the potential of SCGs as a valuable source of bioactive secondary metabolites with diverse applications in nutraceuticals, pharmaceuticals, and functional foods. The use of solvent mixtures in extraction significantly enhances the recovery of key metabolites, aligning with existing literature and demonstrating the feasibility of green and sustainable extraction methodologies for polyphenol-rich extracts. The diverse bioactivities exhibited by these compounds further support the exploration of SCGs-derived metabolites for health-promoting applications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFTIR Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLC-MS serves as a powerful analytical tool for the identification and quantification of a wide range of organic compounds in complex mixtures. However, in addition to LC-MS, FTIR spectroscopy was performed to obtain crucial information regarding the functional groups associated with active metabolites, which play a significant role in the extraction of SCGs. The TPC and TFC results indicated that co-solvent extractions yielded higher phenolic and flavonoid content compared to single solvent extractions. As a result, pristine SCGs extraction samples, along with co-solvent extraction samples, were subjected to FTIR analysis to elucidate the functional groups present. The FTIR spectra of pristine SCGs and SCGs extracts obtained using ethanol, water, and methanol solvents were shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e. All spectra displayed broad absorption bands in the 3308\u0026ndash;3311 cm⁻\u0026sup1; region, corresponding to O-H stretching vibrations. The O-H stretching band in the observed IR spectrum peaked at approximately 3311 cm⁻\u0026sup1;, with a slight shoulder around 3250 cm⁻\u0026sup1;. According to Dai et al., free O-H stretching vibrations without hydrogen bonding typically appear between 3700 and 3600 cm⁻\u0026sup1;, whereas hydrogen bonding formation shifts the O-H stretching frequency to lower wavenumbers. A reduction in frequency is indicative of higher O-H content, suggesting the presence of hydroxyl groups associated with polyphenolic compounds (Dai et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eFurthermore, two distinct bands were observed in the 2900\u0026thinsp;\u0026minus;\u0026thinsp;2800 cm⁻\u0026sup1; region, where a peak at 2936 cm⁻\u0026sup1; was attributed to asymmetric stretching and another at 2834 cm⁻\u0026sup1; was associated with symmetric stretching of C-H bonds within methylene groups. The intensity of these bands correlates with the quantity of methyl groups in the compound and suggests strong inter- and intra-molecular hydrogen bonding, characteristic of polyhydroxy polyphenolic structures (Kanazawa et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Li et al. have linked these stretching phenomena specifically to aliphatic bonds present in compounds such as caffeine and lipids (Li et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Conversely, Ravindran et al. have associated the peak at 2920 cm⁻\u0026sup1; with hydrogen bonding in cellulose, further highlighting the diverse composition of SCGs (Ravindran et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAdditionally, the presence of a moderate absorption peak at 1736 cm⁻\u0026sup1; confirmed the existence of carbonyl functional groups, specifically C\u0026thinsp;=\u0026thinsp;O stretching vibrations. This observation aligns with the findings of Saeed et al., who noted that functional groups containing carbonyl moieties, such as ketones, aldehydes, and carboxylic acids, exhibit strong IR absorption bands within the 1700\u0026ndash;1750 cm⁻\u0026sup1; range (Saeed et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Spectral peaks between 1750 cm⁻\u0026sup1; and 1730 cm⁻\u0026sup1; corresponded to ester groups within the hemicellulose fraction, indicative of interactions between lignin and polysaccharides (Ravindran et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). The signal at 1610 cm⁻\u0026sup1; was assigned to C\u0026thinsp;=\u0026thinsp;C stretching vibrations and asymmetric C\u0026thinsp;=\u0026thinsp;OH stretching in the aromatic ring, primarily associated with lignin, cellulose, and hemicellulose components (Huang et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAt 1414 cm⁻\u0026sup1;, the skeletal C-H stretching vibration of the aromatic ring was identified. However, overlapping bands at 1415 cm⁻\u0026sup1; and 1412 cm⁻\u0026sup1;, primarily due to the symmetric stretching of C\u0026thinsp;=\u0026thinsp;OH, have been highlighted in prior studies by Li et al. (Li et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, a moderate peak at 1325 cm⁻\u0026sup1; was linked to C-N stretching vibrations, with Marjanović et al. suggesting that a medium peak at 1365 cm⁻\u0026sup1; corresponds to stretching vibrations in phenazine-type rings or C-N stretching vibrations, further supported by a shoulder at 1337 cm⁻\u0026sup1; associated with C-N bonding (Marjanović et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe spectral region between 1020 and 1158 cm⁻\u0026sup1; exhibited C-O stretching vibrations characteristic of the phenolic hydroxyl group, with greater intensity observed in all extraction samples compared to pristine SCGs powder. Lower wavenumber absorptions were also detected, including C\u0026thinsp;=\u0026thinsp;C and C-C out-of-plane bending vibrations at 833 cm⁻\u0026sup1; and 518 cm⁻\u0026sup1;, respectively. These findings indicate the presence of complex organic structures, particularly polyphenols and related secondary metabolites, contributing to the bioactivity of SCGs extracts.\u003c/p\u003e\n\u003cp\u003eAs part of the LC-MS and FTIR analyses, secondary metabolites were identified and classified based on their functional groups, as detailed in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The LC-MS results using various solvents identified seven primary functional groups, encompassing ketones, carboxylic acids, lactones, esters, aldehydes, furans, and phenols. This classification provides a comprehensive understanding of the diverse array of bioactive compounds present in SCGs extracts, reinforcing their potential applications in pharmaceuticals, nutraceuticals, and cosmetics. The identification of these compounds through complementary analytical techniques such as LC-MS and FTIR further validates the chemical complexity and functional properties of SCGs, highlighting their role as a valuable resource for bioactive metabolites.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChemical composition of SCGs and possible pathway of profiling metabolites from SCGs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePossible pathway for profiling metabolites extracted from SCGs are purposed in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, highlighting the transformation of bioactive compounds within the lignocellulosic matrix. SCGs primarily comprise hemicellulose, cellulose, and lignin which each contributing uniquely to metabolite formation. Hemicellulose, composed of 1,4-glycosidic linkages, facilitates polysaccharide hydrolysis (\u0026Aacute;lvarez-Mart\u0026iacute;nez and Pfrengle, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Cellulose, a polymer of glucose units connected by \u0026beta;-1,4-glycosidic bonds and rich in hydroxyl functional groups, influences degradation and conversion processes (Zeng and Pan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Lignin, constructed from p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol, provides structural rigidity but undergoes selective depolymerization during extraction (Jiang et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Quantitative analyses by Santos et al. revealed notable concentrations of phenolic compounds (12.0 mg/g), caffeine (14.5 \u0026micro;g/g), and CGAs (31.8 \u0026micro;g/g) in SCGs. Carbohydrates, including cellulose and hemicellulose are abundant. Cellulose\u0026rsquo;s structural integrity and biocompatibility make it a valuable material across various industries (Bhatia et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hemicellulose, a heteropolysaccharide, contains diverse sugar units such as arabinose, xylose, glucose, galactose, mannose, glucuronic acid, and methylglucuronic acid. These can be efficiently extracted via physical, chemical, or enzymatic methods. For instance, Ballesteros et al. reported that alkali treatment of SCGs yielded polysaccharides rich in arabinose, mannose, galactose, and glucose (Ballesteros et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Similarly, Coelho et al. identified high carbohydrate content in SCGs, comprising mannose (48.4 mol%), galactose (22.5 mol%), and glucose (17.1 mol%) (Coelho et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). In addition to carbohydrates, SCGs contain significant protein content (13\u0026ndash;17 wt.% of dry mass), rendering them a valuable nutrient source for the food industry and a promising substrate for biotechnological applications (Ballesteros et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kovalcik et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Lignin, another major constituent, is rich in functional groups including phenolic, aliphatic hydroxyl, methoxyl, carbonyl, and aldehyde moieties, with their abundance depending on the feedstock source (J. Cerino-C\u0026oacute;rdova et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eMetabolite profiling in SCGs primarily involves dehydration and depolymerization reactions, which facilitate the breakdown of macromolecular structures into bioactive intermediates. Hydrolysis further improves extraction efficiency by enhancing metabolite bioavailability. Coffee plants contain two principal classes of nucleotide-derived alkaloids: purine alkaloids (e.g., caffeine, 1,3,7-N-trimethylxanthine) and pyridine alkaloids (e.g., trigonelline). Caffeine and trigonelline typically comprise 1\u0026ndash;2% of the coffee bean\u0026apos;s dry weight. LC-MS analyses have confirmed the presence of caffeine in SCG extracts obtained using ethanol, methanol, water, and glycerol/methanol mixtures. Caffeine, a methylated purine derivative, is biosynthesized via methylation of xanthine skeletons, beginning with the conversion of xanthosine to 7-methylxanthosine (Ashihara, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, paraxanthine (1,7-dimethylxanthine), a caffeine metabolite, was detected in methanolic and aqueous SCG extracts. Caffeine undergoes enzymatic modifications to form biologically active derivatives such as paraxanthine, theobromine, and theophylline.\u003c/p\u003e\n\u003cp\u003ePhenolic compounds present in SCGs such as quinic acid and trans-cinnamic acid undergo enzymatic transformation into caffeic acid, p-coumaric acid, and ferulic acid. These intermediates contribute to the synthesis of CGAs including caffeoylquinic acids (CQAs), feruloylquinic acids (FQAs), and p-coumaroylquinic acids (p-CoQAs), which exhibit well-documented antioxidant and anti-inflammatory properties (Valanciene and Malys, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, diterpenes such as gibberellin A15 play regulatory roles in plant biochemistry. The biosynthesis of CGAs in SCGs proceeds via the phenylpropanoid metabolic pathway, which generates hydroxycinnamic acids as precursors. The process initiates with the deamination of phenylalanine to cinnamic acid by phenylalanine ammonia-lyase (PAL), a key regulatory enzyme (Taofiq et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Cinnamic acid undergoes hydroxylation, catalysed by cinnamate-4-hydroxylase (C\u003csub\u003e4\u003c/sub\u003eH), to yield hydroxycinnamic acids such as caffeic acid, p-coumaric acid, and ferulic acid (Feduraev et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). These acids subsequently esterify with quinic acid through the action of hydroxycinnamoyltransferase (HCT), forming various CGA isomers (Habtemariam, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). For instance, caffeic acid forms CQAs, ferulic acid forms FQAs, and p-coumaric acid forms p-CoQAs. Comprehensive profiling of these isomers via LC-MS facilitates their exploitation in industrial applications and functional food development (Rojas-Gonz\u0026aacute;lez et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe biosynthetic pathway of diterpenes in SCGs involves the generation of gibberellin A15 through a series of enzymatic steps. Isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP) serve as five-carbon precursors for isoprenoid synthesis (Chaves et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). These condense to form geranylgeranyl diphosphate (GGDP) via geranylgeranyl diphosphate synthase (GGPPS) (Haney et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), which is subsequently converted to copalyl diphosphate (CDP) by ent-copalyl diphosphate synthase (CPS) (Sun et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). CDP then undergoes multiple transformations such cyclization, oxidation, and rearrangement which mediated by cytochrome P450 monooxygenases (CYPs) and other enzymes, ultimately yielding gibberellin A15. In conclusion, the detailed characterization of SCG metabolites via advanced analytical techniques such as LC-MS provides critical insights into their chemical complexity and application potential. By employing sustainable extraction methods and elucidating biosynthetic pathways, this study advances the valorisation of SCGs in alignment with circular economy principles and environmental sustainability goals within the coffee industry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioactive secondary metabolite and the properties\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe profiling of metabolites from SCGs has been extensively studied, revealing the presence of secondary metabolites with substantial potential as value-added products in pharmaceutical and cosmetic applications. Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e categorizes the primary secondary metabolites identified through LC-MS analysis, illustrating their diverse functionalities, including antioxidant properties, UV radiation protection, antibacterial effects, anti-inflammatory activity, and anti-cellulite benefits. These compounds have been extensively documented, demonstrating their efficacy across various applications.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUse of main secondary metabolites in SCGs for different purposes.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePotential\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSecondary metabolite\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAntioxidant properties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaffeic acid (Purushothaman et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eCGAs (Liang and Kitts, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wang et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProtection against UV radiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaffeine (Conney et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003ePhenolic compound including flavonoids, Quinic acids, ferulic acid) (Ghazi, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eCGAs (Bhattacharyya et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Xue et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnti-bacterial properties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaffeine (Almeida et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Woziwodzka et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnti-inflammatory properties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaffeine (Castaldo et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Eichwald et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eCGAs (Huang et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eCaffeic acid (Zielińska et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnti-cellulite properties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaffeine (Herman and Herman, \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Vogel et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eA review by Esp\u0026iacute;ndola et al. emphasized the significance of caffeic acid in hepatocarcinoma, a form of liver cancer. Research suggests that caffeic acid exerts potent anticancer effects by modulating key signalling pathways involved in cell growth, proliferation, and apoptosis. Its chemical structure facilitates interactions with specific molecular targets within hepatocarcinoma cells, influencing cancer-related cellular mechanisms (Sun et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Liang et al. further classified CGAs into subcategories such as CQAs, p-CoQAs and FQAs (Liang and Kitts, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eEpidemiological studies indicate a correlation between coffee consumption and a reduced risk of chronic diseases, suggesting that CGAs mitigate oxidative stress by regulating intracellular redox balance. Additionally, these compounds exhibit anti-inflammatory effects through modulation of metabolic pathways (Liang and Kitts, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Conney et al. demonstrated caffeine\u0026rsquo;s protective role against UVB-induced skin cancer, proposing mechanisms that include its function as a natural sunscreen and its ability to induce apoptosis in precancerous and cancerous lesions via p53-dependent and independent pathways (Conney et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Similarly, Ghazi et al. reported that polyphenolic compounds, particularly flavonoids derived from plant and algal extracts which provide photoprotection against ultraviolet radiation. These compounds serve as effective UV filters due to their antioxidant and anti-inflammatory properties, offering a promising natural alternative to synthetic UV blockers in skincare formulations (Ghazi, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn line with these findings, Xue et al. investigated CGAs\u0026rsquo; protective role against UVA-induced skin photoaging, revealing their regulation of collagen metabolism and apoptosis in human dermal fibroblasts. These properties suggest their potential for integration into photoprotective and anti-aging cosmetic formulations (Xue et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, Bhattacharyya et al. demonstrated that CGA-phospholipid complexes provided enhanced protection against UVA-induced oxidative stress compared to conventional formulations. Notably, the protective effects were most pronounced when UVA irradiation occurred four hours post-application, indicating sustained photoprotection (Bhattacharyya et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eBeyond photoprotection, caffeine has been shown to enhance the antibacterial efficacy of widely used antibiotics. Woziwodzka et al. investigated caffeine\u0026rsquo;s effect on 30 antibiotics against Staphylococcus aureus, finding that it potentiated the antibacterial activity of specific antibiotics, particularly ciprofloxacin and tetracycline, against Gram-negative pathogens (Woziwodzka et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, Almeida et al. examined the antimicrobial effects of coffee extracts and their chemical constituents against nine enterobacteria strains. Their results indicated that caffeine, CGAs, and protocatechuic acid exhibited potent antimicrobial effects, with caffeine and protocatechuic acid demonstrating significant activity against Salmonella enterica. Importantly, the caffeine concentration in coffee extracts was sufficient to exert meaningful antimicrobial effects, reinforcing its relevance in food safety applications (Almeida et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSecondary metabolites in SCGs also exhibit anti-inflammatory and anti-cellulite properties. Eichwald et al. explored caffeine\u0026rsquo;s influence on gene expression related to inflammation, adenosine receptors, epigenetics, and oxidative metabolism in mouse vastus lateralis muscle subjected to lipopolysaccharide (LPS)-induced inflammation. The findings suggest that caffeine pre-treatment reduced pro-inflammatory biomarker expression, fostering an anti-inflammatory environment. Additionally, the modulation of adenosine receptors and epigenetic mechanisms implies that caffeine\u0026rsquo;s anti-inflammatory effects may be mediated through epigenetic alterations (Eichwald et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Castaldo et al. investigated the antioxidant and anti-inflammatory properties of coffee compounds, demonstrating that digestion may enhance their bioactivity. These findings contribute to understanding coffee\u0026rsquo;s health benefits, particularly regarding its potential post-simulated gastrointestinal digestion (Castaldo et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe dermatological applications of caffeine have been validated through scientific studies, particularly in cellulite treatment. Vogel et al. assessed the quality of caffeine-containing cosmetic formulations for cellulite reduction (Vogel et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Their study examined microbiological safety, pH stability, colour retention, caffeine concentration, and viscosity. While caffeine content and viscosity remained stable, microbiological analysis revealed that mold and yeast concentrations exceeded permissible thresholds set by the Brazilian pharmacopoeia, and pH levels declined over time, increasing acidity. Despite these challenges, the study affirmed caffeine\u0026rsquo;s viability as an active ingredient in anti-cellulite treatments, reinforcing its relevance in cosmetic dermatology.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study underscores the potential of SCGs as a valuable derivative of industrial crops, contributing to the sustainable extraction of bioactive compounds. The application of UAE combined with a glycerol/methanol co-solvent system demonstrated enhanced efficiency in recovering phenolic-rich metabolites, with optimized yields of TPC and TFC. Comparative evaluation of seven solvents highlights the critical role of solvent polarity in influencing extraction outcomes, with glycerol/methanol providing superior performance. Comprehensive LC-MS profiling identified a wide spectrum of bioactive, including caffeine, CGAs, and phenolic compounds, renowned for their multifunctional applications. This systematic metabolite mapping reinforces the role of SCGs in waste valorization and supports their integration into circular bioeconomy models. Furthermore, the adoption of UAE with eco-friendly co-solvents offers a green and scalable extraction platform, reducing dependency on conventional, solvent-intensive methods. These findings position SCGs as a renewable, high-value resource, promoting the development of optimized extraction strategies and broadening their utility across pharmaceutical, cosmetic, and nutraceutical industries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbubakar IR, Maniruzzaman KM, Dano UL, AlShihri FS, AlShammari MS, Ahmed SMS, Al-Gehlani WAG, Alrawaf TI (2022) Environmental Sustainability Impacts of Solid Waste Management Practices in the Global South. 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Nutrients 13:554. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/nu13020554\u003c/span\u003e\u003cspan address=\"10.3390/nu13020554\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 2 and 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Spent coffee grounds, bioactive compounds, extraction, solvent, industrial crop","lastPublishedDoi":"10.21203/rs.3.rs-7024028/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7024028/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSpent coffee grounds (SCGs), an abundant byproduct of Coffea arabica L., hold significant potential as a renewable resource for bioactive compounds. This study explores ultrasound-assisted extraction (UAE) as a sustainable approach to enhance the recovery of phenolic-rich metabolites using seven solvents with varying polarity. The optimized glycerol/methanol co-solvent system achieved the highest extraction efficiency, with a total phenolic content (TPC) of 6.059\u0026thinsp;\u0026plusmn;\u0026thinsp;0.089 mg GAE/g and a total flavonoid content (TFC) of 8.549\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 mg QE/g. Comprehensive liquid chromatography\u0026thinsp;\u0026minus;\u0026thinsp;mass spectrometry (LC-MS) analysis identified key secondary metabolites, including caffeine, chlorogenic acids (CGAs), and phenolic compounds which contribute to diverse functional properties such as antioxidant, antimicrobial, UV-protective, anti-inflammatory, and anti-cellulite activities. These bioactive components have substantial applications in industrial crop-based pharmaceuticals, cosmetics, and bio-based materials. By integrating UAE with environmentally friendly co-solvents, this study presents a scalable and sustainable extraction strategy, reducing reliance on conventional solvents while maximizing yield and purity. Additionally, the findings support waste valorization and circular economy principles, positioning SCGs as a viable industrial crop resource with significant implications for biorefinery processes, bio-based product development, and sustainable cropping systems. This research provides a systematic framework for solvent selection in metabolite extraction, reinforcing its relevance to industrial crop management and sustainable bioactive compound production. The demonstrated efficacy of UAE establishes SCGs as an untapped industrial crop derivative, contributing to the advancement of green extraction technologies and industrial applications.\u003c/p\u003e","manuscriptTitle":"Extraction and characterization of bioactive compounds from coffee by-products: physicochemical and LC-MS analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-11 19:12:55","doi":"10.21203/rs.3.rs-7024028/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6bdb95ed-73bd-4183-afc4-9e2103f6c135","owner":[],"postedDate":"July 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-26T17:44:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-11 19:12:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7024028","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7024028","identity":"rs-7024028","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}