Comparative Evaluation of Bioactive Compounds and Functional Activities in Thai Honeys from Different Floral Origins

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Antioxidant activities were evaluated using FRAP, DPPH, and AEAC assays, while total phenolic content (TPC) and total flavonoid content (TFC) were determined. Quantitative analysis of phenolic and flavonoid compounds, antimicrobial activity (MIC), and basic physicochemical parameters were conducted. Multivariate analyses (PCA and Pearson correlation) were applied to link the biochemical composition of honeys with biological activities. Manuka and premium longan honeys exhibited the highest phenolic and flavonoid levels and strong antioxidant capacities. Major compounds-gallic acid, caffeic acid, quercetin, and catechin-showed significant correlations with TPC, TFC, and both antioxidant and antimicrobial effects. PCA grouped Manuka and premium longan honeys in a high-bioactivity cluster, closely associated with antioxidant variables and low MIC values, particularly against Staphylococcus aureus (7.5% w/v). Lychee honey showed high flavonoid content but limited antimicrobial activity, while coffee and conventional longan honeys displayed moderate activities. In contrast, Siam weed honey exhibited the lowest bioactive levels, consistent with its weak antioxidant and antimicrobial properties. Multivariate analyses confirmed that phenolics and flavonoids are the main drivers of honey bioactivities. These findings highlight premium longan honey as a promising valuable bioresource for functional food and cosmeceutical development, supporting its potential to enhance local economic value. Thai honey phenolic compounds flavonoids antioxidant activity antimicrobial activity bioactive compounds Figures Figure 1 Figure 2 1. Introduction The market for health foods and natural cosmetics has seen accelerated growth, particularly in honey-based products and skincare, which have gained popularity through the concepts of clean beauty and sustainability. A recent report projected that the global honey market will expand from USD 9.01 billion in 2022 to USD 13.57 billion by 2030, with a compound annual growth rate of approximately 5.3% [ 1 ]. Key driving factors include enhanced health awareness, consumer demand for safe and natural products, and the trend toward reduced use of synthetic chemicals [ 2 ]. These trends support the development of functional products with distinctive properties such as antioxidant, anti-inflammatory, and skin health-promoting, underscoring the need to investigate the potential of honey as a raw material that can address both efficacy and sustainability demands. Honey is a natural product with a complex composition that includes sugars, enzymes, and organic acids. It also contains bioactive compounds such as polyphenols and flavonoids, which play critical roles as antioxidants, antimicrobials, and anti-inflammatory agents [ 3 ]. These attributes have established honey as a promising raw material for the development of functional foods and natural cosmetics. The phenolic and flavonoid compounds are the main active constituents contributing to both antioxidant and antimicrobial activities in honey [ 4 ]. Antioxidant mechanisms involve electron or hydrogen atom donation, which inhibits oxidation reactions. In addition, these compounds can chelate transition metal ions such as Fe²⁺ and Cu²⁺ that catalyze Fenton reactions [ 5 ]. This process reduces lipid peroxidation and slows cellular deterioration [ 3 ]. These bioactivities arise from the synergistic effects among phenolics, flavonoids, and other phytochemicals [ 6 ]. In addition, physicochemical factors such as low pH, high sugar concentration, and low water activity contribute to inhibiting microbial growth and maintaining the stability of bioactive properties [ 6 , 7 ]. Antimicrobial mechanisms by honey involve both peroxide-based and non-peroxide-based effects. The peroxide-based mechanism involves the generation of hydrogen peroxide (H₂O₂) by the enzyme glucose oxidase, which can damage cell walls and inhibit microbial enzymes [ 7 ]. However, this mechanism is heat-sensitive, meaning that raw honey, which does not undergo heat treatment, generally has higher potential than its processed counterpart [ 8 ]. Manuka honey demonstrates strong activity through a non-peroxide-based mechanism, with methylglyoxal (MGO) as the key compound. MGO disrupts bacterial cell wall structures and interferes with cellular metabolism, even in the absence of H₂O₂.This mechanism enables effective inhibition of both pathogenic and multidrug-resistant bacteria [ 6 , 7 , 9 ]. Additionally, the combination of low pH and high sugar concentration enhances osmotic pressure, reinforcing the antimicrobial properties of honey [ 10 ]. Beyond general mechanisms, honey contains phenolic and flavonoid compounds that significantly contribute to antioxidant and antimicrobial properties. Phenolic acids can disrupt membrane integrity and denature proteins [ 11 ]. On the other hand, flavonoids inhibit quorum sensing and enzymes involved in cell wall biosynthesis, thereby reducing biofilm formation and microbial growth [ 4 ]. Therefore, analysis of specific compounds and their relationship with biological activities is essential to understanding honey’s bioactive potential [ 12 , 13 ]. Although Thailand is a major honey producer in Asia, there is still a lack of studies linking phenolic and flavonoid composition to biological activities. Most research has evaluated only total phenolic content (TPC), total flavonoid content (TFC), and overall antioxidant capacity [ 5 ], without focusing on quantitative profiling or systematic comparison with Manuka honey. No previous study has systematically compared Thai honeys using an integrated evaluation of phenolic–flavonoid composition, antioxidant capacity, antimicrobial activity, and multivariate analysis. This study aims to evaluate the biological potential of Thai honeys from different floral origins in comparison with Manuka honey. Antioxidant activity (FRAP, DPPH, AEAC), bioactive compound contents (TPC, TFC), quantitative analysis of phenolic and flavonoid compounds, and antimicrobial activity were assessed. Furthermore, relationships between composition and bioactivity were analyzed using Pearson correlation and PCA. This study provides a systematic perspective emphasizing the potential of Thai honeys, particularly premium longan honey, as a premium raw material for the development of functional foods and natural cosmetics. 2. Materials and Methods 2.1 Honey Samples Six types of honey were used in this study: longan honey, premium longan honey (raw), Siam weed honey, lychee honey, coffee honey, and Manuka honey. All Thai honeys were obtained from an authenticated local apiary in Chiang Mai, Thailand, where floral origin was identified based on the predominant flowering source and producer certification. Manuka honey was sourced from a certified New Zealand producer. All samples were stored at 4°C in airtight containers until analysis. 2.2 Determination of Antioxidant Activities and Bioactive Compound Contents 2.2.1 Ferric Reducing Antioxidant Power (FRAP) Assay The ferric reducing antioxidant power (FRAP) was determined according to [ 14 ] with minor modifications. FRAP reagent was freshly prepared by mixing 300 mM acetate buffer (pH 3.6), 10 mM TPTZ in 40 mM HCl, and 20 mM FeCl₃·6H₂O (10:1:1, v/v/v). For the assay, 0.2 mL of honey solution (50% w/v in distilled water) was mixed with 1.5 mL of FRAP reagent and incubated at 37°C for 4 min. The absorbance was measured at 593 nm using a UV–Vis spectrophotometer (M509T, Spectronic Camspec Ltd., UK). Calibration was performed using FeSO₄·7H₂O standard solution (300–2,000 µg/mL). The results were expressed as µmol Fe²⁺ equivalents per 100 g honey. Each determination was carried out in triplicate. 2.2.2 DPPH Radical Scavenging Activity and Ascorbic Acid Equivalent Antioxidant Capacity (AEAC) The antioxidant activity was measured using the DPPH assay according to [ 15 ] with slight modifications. For the assay, 0.75 mL of honey solution (30% w/v in distilled water) was mixed with 1.5 mL of 0.1 mM DPPH solution in methanol and incubated in the dark at room temperature for 15 min. The absorbance was measured at 517 nm using a UV–Vis spectrophotometer. Calibration was performed with butylated hydroxytoluene (BHT, 3–50 µg/mL) for DPPH and L-ascorbic acid (3–50 µg/mL) for AEAC. The results were expressed as mg BHT equivalents and mg AAE per 100 g honey. Measurements were conducted in triplicate for all samples. 2.2.3 Total Phenolic Content (TPC) Total phenolic content was determined using the Folin–Ciocalteu method described by [ 16 ] with slight modifications. For each assay, 1 mL of honey solution (10% w/v in distilled water) was mixed with 2.5 mL of 0.2 N Folin–Ciocalteu reagent, left for 5 min, and then 2 mL of 7.5% Na₂CO₃ was added. The mixture was incubated in the dark at room temperature for 2 h. The absorbance was measured at 760 nm using a UV–Vis spectrophotometer. Calibration was performed with gallic acid (10–100 µg/mL). Results were expressed as mg gallic acid equivalents (GAE) per 100 g honey, and all measurements were carried out in triplicate. 2.2.4 Total Flavonoid Content (TFC) Total flavonoid content was determined using the aluminum chloride colorimetric method described by [ 15 ] with slight modifications. For the assay, 1 mL of honey solution (50% w/v in distilled water) was mixed with 5 mL of 2% AlCl₃ solution in methanol and incubated at room temperature in the dark for 10 min. The absorbance was then measured at 415 nm using a UV–Vis spectrophotometer. Calibration was performed with catechin (5–40 µg/mL). Results were expressed as mg catechin equivalents (CE) per 100 g honey, and all measurements were carried out in triplicate. 2.3 Quantitative Analysis of Phenolic and Flavonoid Compounds The quantitative determination of phenolic and flavonoid compounds in honey samples was performed using High-Performance Liquid Chromatography (HPLC) (Shimadzu LC-20A Series, Kyoto, Japan), equipped with a diode array detector set at 280 nm, modified from [ 17 ]. Separation was carried out on an Ultra Aqueous C18 column (250 × 4.6 mm, 5 µm; RESTEK, Bellefonte, PA, USA). The mobile phase consisted of solvent A (formic acid: distilled water, 5:95, v/v) and solvent B (acetonitrile: formic acid: distilled water, 85:5:10, v/v/v). The gradient elution program was as follows: 0–4 min, 80% A; 4–8 min, linear gradient to 25% A; 8–10 min, held at 25% A; 10–17 min, returned to 80% A; and 17–20 min, re-equilibrated at 80% A. The flow rate was maintained at 1.0 mL/min, and the injection volume was 10 µL. Chromatograms were monitored at 280 nm, and quantification was achieved by external calibration using authentic standards. Phenolic acid standards included gallic acid, caffeic acid, p-coumaric acid, o-coumaric acid, and rosmarinic acid, while flavonoid standards included catechin, quercetin, epigallocatechin gallate, epicatechin, and naringin. Calibration curves were constructed within the range of 25–50 µg/mL. All analyses were conducted in triplicate, and results were expressed as mg per 100 g of honey. 2.4 Antimicrobial Activity (MIC Assay) The antimicrobial activity of honey samples was determined using by the broth microdilution method following [ 18 ] and [ 19 ]. Five skin-associated bacteria were tested: Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853), Kocuria rhizophila (ATCC 9341), and Bacillus subtilis (ATCC 6633). Honey samples were dissolved in sterile distilled water and two-fold serially diluted in Mueller–Hinton broth in 96-well plates to final concentrations of 0.06–30% (w/v). Bacterial suspensions were adjusted to 5 × 10⁵ CFU/mL and added to each well, followed by incubation at 37°C for 18 h. The minimum inhibitory concentration (MIC) was defined as the lowest concentration of honey that showed no visible bacterial growth compared with the control. All assays were conducted in triplicate. 2.5 Physicochemical Properties and Sugar Compositions Physicochemical analyses of honey samples were performed according to [ 20 ]. Total soluble solids (°Brix) were measured using a digital hand refractometer (ATAGO, Japan). Moisture content was determined by oven-drying at 105°C for 2 h, cooling in a desiccator for 30–45 min, and reweighing to constant weight. pH was measured using a calibrated pH meter (Mettler Toledo, Switzerland). All measurements were conducted in triplicate. The sugar composition of honey samples was analyzed using high-performance liquid chromatography (HPLC) (Shimadzu LC-20A Series, Kyoto, Japan) according to the modified method of [ 21 ]. Five grams of the honey sample were diluted with 10 mL of distilled water, thoroughly mixed, and left overnight. The injection volume was 20 µL. Separation was performed on a Zorbax NH₂ column (250 × 4.6 mm, 5 µm; Agilent Technologies, USA) at 40°C with acetonitrile:water (85:15, v/v) as the mobile phase at a flow rate of 1.0 mL/min. Detection was performed using a refractive index detector (RID), and quantification of glucose, fructose, and sucrose was achieved using external calibration with authentic standards. Results were expressed as g/100 g honey, and each sample was analyzed in triplicate. 2.6 Statistical Analysis All statistical analyses were performed using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). One-way analysis of variance (ANOVA) was conducted, and significant differences among means were identified using the Least Significant Difference (LSD) test at p < 0.05. Pearson correlation analysis was applied to assess relationships among measured parameters. Principal Component Analysis (PCA) was conducted to visualize multivariate relationships and clustering patterns of honey samples. The results are presented as the mean ± standard deviation (SD) of triplicate determinations. 3. Results and Discussion 3.1 Antioxidant Activities and Bioactive Compound Contents Six types of honey-longan, premium longan (raw honey), Siam weed, lychee, coffee, and Manuka-were analyzed for antioxidant activity using the ferric reducing antioxidant power (FRAP), DPPH radical scavenging activity, and ascorbic acid equivalent antioxidant capacity (AEAC) assays. Bioactive compound contents, including total phenolic content (TPC) and total flavonoid content (TFC), were also determined (Table 1 ). Table 1 Antioxidant activities and bioactive compound contents of Thai honeys from different floral sources. Honey sample FRAP value (µmol Fe 2+ /100 g) DPPH scavenging activity (mg BHT eq./100 g) AEAC (mg AAE/100 g) Total Phenolic Content (mg GAE/100 g) Total Flavonoid Content (mg CE/100 g) Longan 538.73 ± 2.15 e 17.39 ± 1.11 c 12.59 ± 0.74 c 53.58 ± 2.89 c 43.39 ± 0.49 b Premium longan (raw honey) 849.28 ± 0.65 b 27.06 ± 0.12 b 20.54 ± 0.10 b 65.23 ± 2.08 b 58.89 ± 1.05 a Siam weed 224.58 ± 0.49 f 9.46 ± 0.45 d 6.07 ± 0.66 d 32.36 ± 2.78 d 29.60 ± 1.27 c Lychee 575.90 ± 1.52 d 16.61 ± 0.96 c 11.94 ± 1.20 c 53.85 ± 2.36 c 57.81 ± 0.40 b Coffee 662.23 ± 0.42 c 18.16 ± 0.75 c 13.22 ± 1.09 c 50.73 ± 1.69 c 57.12 ± 0.43 b Manuka 991.97 ± 1.57 a 30.72 ± 1.52 a 23.56 ± 0.89 a 68.02 ± 2.77 a 61.23 ± 1.37 a Values are presented as mean ± standard deviation (SD, n = 3). Different superscript letters within the same column indicate significant differences (p < 0.05). Manuka honey indicated the highest values across all parameters, including FRAP, DPPH, AEAC, TPC, and TFC, with statistically significant differences (p < 0.05). These findings are consistent with [ 22 ], who reported that Manuka honey contains polyphenols such as p-hydroxybenzoic acid and chlorogenic acid, contributing to its strong antioxidant properties. Premium longan honey (raw honey) ranked second, showing significantly higher values across all parameters than conventional longan honey. The absence of heat treatment during production helps preserve thermolabile compounds such as polyphenols, flavonoids, glucose oxidase, vitamin C, and organic acids [ 8 , 23 ]. Conventional longan honey is typically harvested early (around 7 days), leading to high moisture content and the need for heat treatment (50–65°C) to reduce water content before packaging. By contrast, raw honey is harvested after a longer maturation period (18–21 days), allowing natural moisture reduction to occur gradually without heating. As a result, premium longan honey demonstrates bioactivities comparable to those of Manuka. Among processed honeys, coffee honey displayed the strongest potential, characterized by high TFC and higher FRAP and AEAC values than longan, lychee, and Siam weed honeys. This result corresponds with the presence of caffeic acid and chlorogenic acid identified in quantitative profiling [ 5 , 24 ]. Longan and lychee honeys exhibited similar antioxidant activities with comparable TPC levels. However, lychee honey had slightly higher TFC, which may reflect structural differences in its predominant flavonoids. Siam weed honey exhibited the lowest antioxidant capacity across all parameters, consistent with its minimal phenolic and flavonoid contents, suggesting that floral origin may limit the diversity of bioactive constituents. Based on antioxidant capacity, the honeys could be categorized into three groups: high potential (Manuka and premium longan), moderate potential (coffee, lychee, and conventional longan), and low potential (Siam weed). These results highlight the influence of floral origin and processing conditions on honey bioactivities. In particular, variations in polyphenol and flavonoid concentrations are directly associated with antioxidant and antimicrobial properties. The antioxidant activity of honey is directly correlated with its phenolic and flavonoid composition, as these compounds function as electron or hydrogen atom donors to inhibit oxidative reactions [ 24 ]. Gallic acid, caffeic acid, quercetin, and catechin, in particular, have been reported to play important roles in antioxidant, anti-inflammatory, and antimicrobial activities [ 3 , 13 ]. The high antioxidant capacity of Manuka and premium longan honeys reflects their abundant polyphenolic content, with premium longan additionally benefiting from the preservation of thermosensitive compounds due to the absence of heat treatment [ 8 ]. Pearson’s correlation matrix (Fig. 2 ) further demonstrated strong positive correlations between TPC and TFC with FRAP, DPPH, and AEAC, with TPC showing r > 0.90 with all parameters. These findings align with [ 5 ], who suggested that TPC and TFC can serve as reliable indicators of honey’s antioxidant activity. Other supportive constituents, such as vitamins and enzymes (e.g., glucose oxidase), may act synergistically [ 25 ], contributing to complex bioactivities that cannot be explained by individual compounds alone. The results confirm that Thai premium longan honey (raw honey) exhibits antioxidant potential comparable to that of Manuka. TPC and TFC may therefore serve as reliable indicators of honey’s bioactive quality, highlighting its potential as a high-value raw material. Collectively, these findings suggest that premium longan honey could serve as a valuable alternative to Manuka in functional food and cosmetic applications. 3.2 Quantitative Analysis of Phenolic and Flavonoid Compounds Tables 2 and 3 present the quantitative analysis of phenolic and flavonoid compounds in six types of honey. Five major phenolic acids were identified: gallic acid, caffeic acid, p-coumaric acid, o-coumaric acid, and rosmarinic acid, with significant variations among honey types (p < 0.05) (Table 2 ). Manuka and premium longan honeys (raw honey) exhibited the highest total phenolic content, dominated by gallic acid and caffeic acid. Coffee and conventional longan honeys showed moderate total phenolic levels, though they were still relatively rich in gallic acid and caffeic acid. Lychee honey contained higher levels of caffeic acid and rosmarinic acid compared to other types, whereas p-coumaric acid was detected among all the selected honeys at comparable levels. In contrast, o-coumaric acid and rosmarinic acid were only detected in certain samples. Siam weed honey contained the lowest phenolic levels, consistent with its weak antioxidant potential, emphasizing the role of gallic acid and caffeic acid in honey bioactivity. Table 2 Phenolic compound composition of Thai honeys from different floral sources. Honey Sample Phenolic compound composition (mg/100 g) Gallic acid Caffeic acid p-coumeric acid o-coumeric acid Rosmarinic acid Sum of phenolic compounds Longan 1.70 ± 0.08 b 0.22 ± 0.03 b 0.16 ± 0.02 a 0.09 ± 0.09 b 0.04 ± 0.01 b 2.22 Premium longan (raw honey) 1.80 ± 0.04 ab 0.21 ± 0.02 b 0.17 ± 0.01 a 0.11 ± 0.01 a 0.05 ± 0.04 b 2.32 Siam weed 0.75 ± 0.01 c 0.18 ± 0.01 c 0.12 ± 0.03 b 0.09 ± 0.04 b nd 1.14 Lychee 1.69 ± 0.01 b 0.24 ± 0.02 b 0.17 ± 0.05 a nd 0.08 ± 0.04 a 2.17 Coffee 1.77 ± 0.02 b 0.23 ± 0.01 b 0.15 ± 0.05 a nd 0.05 ± 0.01 b 2.20 Manuka 1.98 ± 0.09 a 0.27 ± 0.01 a 0.17 ± 0.01 a 0.09 ± 0.06 b nd 2.60 Values are presented as mean ± standard deviation (SD, n = 3). Different superscript letters within the same column indicate significant differences (p < 0.05). “nd” indicates not detected. Table 3 Flavonoid compound composition of Thai honeys from different floral sources. Honey Sample Flavonoid compound composition (mg/100 g) Catechin Quercetin Epigallocatechin gallate Epicatechin Naringin Sum of flavonoid compounds Longan 3.59 ± 0.08 d 0.19 ± 0.0 a 0.38 ± 0.01 a 0.07 ± 0.01 b 0.10 ± 0.0 c 4.33 Premium longan (raw honey) 6.31 ± 0.03 b 0.18 ± 0.0 ab 0.37 ± 0.00 b 0.06 ± 0.01 b 0.13 ± 0.02 bc 7.05 Siam weed 0.93 ± 0.01 e 0.11 ± 0.0 b 0.39 ± 0.01 b 0.09 ± 0.01 b 0.12 ± 0.01 bc 1.64 Lychee 3.11 ± 0.05 de 0.19 ± 0.0 ab 0.24 ± 0.00 c 0.40 ± 0.0 a 0.46 ± 0.0 a 4.39 Coffee 4.15 ± 0.04 c 0.18 ± 0.0 ab 0.39 ± 0.01 b nd 0.09 ± 0.00 c 4.86 Manuka 7.81 ± 0.0 a 0.21 ± 0.0 a 0.44 ± 0.01 b 0.09 ± 0.0 b 0.16 ± 0.0 b 8.72 Values are presented as mean ± standard deviation (SD, n = 3). Different superscript letters within the same column indicate significant differences (p < 0.05). “nd” indicates not detected. For flavonoids, five compounds were detected: catechin, quercetin, epigallocatechin gallate, epicatechin, and naringin, showing significant differences in type and concentration among samples (p < 0.05) (Table 3 ). Manuka and premium longan honeys exhibited the highest total flavonoid levels, with catechin as the dominant constituent. Coffee and lychee honeys showed moderate levels, with lychee honey being particularly rich in epicatechin and naringin, which may contribute to its distinct antioxidant activity. Catechin was especially abundant in Manuka and premium longan honeys, consistent with their strong antioxidant capacities. In contrast, Siam weed honey exhibited the lowest diversity and concentration of flavonoids. Quercetin and epigallocatechin gallate were present at comparable levels in several honeys, except for Siam weed honey, which contained the lowest quercetin levels, and coffee honey, which lacked epicatechin. Overall, the floral origin and production process influenced flavonoid composition and bioactivity of honey. Honeys rich in catechin, epicatechin, and quercetin generally exhibited stronger biological activities. Quantitative profiling revealed that honeys from six floral origins varied in phenolic and flavonoid composition. Gallic acid was the predominant constituent in many samples, particularly premium longan (raw honey) and Manuka, and plays a critical role in antioxidant activity [ 3 ]. Caffeic acid and p-coumaric acid, detected at moderate levels, also exhibit antioxidant and anti-inflammatory properties and are associated with higher TPC values [ 4 , 12 ]. The main mechanism of these phenolic acids is attributed to their multiple hydroxyl groups, which readily donate electrons to neutralize free radicals, thereby stabilizing reactive species and preventing oxidative chain reactions [ 3 ]. Among flavonoids, catechin and quercetin were strongly correlated with high TFC and were abundant in Manuka, premium longan, and lychee honeys. Both compounds are well-known for their antioxidant, anti-inflammatory, and immunomodulatory properties [ 5 , 26 ]. Quercetin provides photoprotective benefits against UV radiation and promotes collagen synthesis [ 24 ]. Epicatechin and naringin, abundant in lychee and coffee honeys, have been reported to support skin elasticity and reduce cellular inflammation [ 22 ]. Comparison among honey types indicated that Manuka and premium longan honeys (raw honey) contained the most diverse and concentrated bioactive compounds, particularly gallic acid, caffeic acid, quercetin, and catechin. These findings align with their high TPC, TFC, FRAP, DPPH, AEAC, and antimicrobial (MIC) activities, reflecting the direct contribution of phenolic and flavonoid constituents to [ 11 ]. Coffee honey exhibited high TFC with abundant caffeic acid and catechin, supporting its moderate antioxidant and antimicrobial properties. Lychee honey was notable for its high TFC due to quercetin and naringin, despite moderate TPC. Conventional longan honey shared a similar composition with raw honey but exhibited lower bioactivity, likely due to processing factors such as heating and shorter harvest duration [ 8 ]. Siam weed honey consistently showed the lowest bioactivities, consistent with its low levels of gallic acid and catechin. Certain phenolic and flavonoid compounds were also implicated in honey’s antimicrobial activities, particularly gallic acid and catechin, which were abundant in Manuka and premium longan honeys (raw honey). These compounds significantly inhibited Staphylococcus aureus , a skin-associated pathogen [ 6 ]. This observation is consistent with reports that catechin and chlorogenic acid inhibit the growth of Staphylococcus aureus and Cutibacterium acnes by disrupting cell wall structures and inhibiting specific enzymes [ 27 ]. Catechin, for instance, acts by binding to the cell membrane and reducing cytoplasmic membrane potential [ 4 ]. Furthermore, the pro-oxidant action of gallic acid can induce oxidative damage in bacterial cells [ 6 ]. In contrast, coffee, lychee, and Siam weed honeys, while containing some bioactive compounds, exhibited insufficient diversity and concentration to exert strong antimicrobial effects [ 28 ]. 3.3 Antimicrobial Activity This study evaluated the antimicrobial activity of six floral honeys against five skin-associated bacteria: Staphylococcus aureus , a major pathogen in acne vulgaris and skin infections such as folliculitis and abscesses [ 29 ]; Pseudomonas aeruginosa , commonly isolated from infected, burn, and chronic wounds, which forms biofilms and secretes tissue-damaging toxins [ 30 ]; Escherichia coli , which may contaminate open wounds and trigger inflammation in chronic ulcers [ 31 ]; Kocuria rhizophila , a commensal skin bacterium that contributes to microbiome balance [ 32 ]; and Bacillus subtilis , known to suppress pathogens and promote skin immunity [ 33 ]. These microorganisms are key targets in skin-care applications aiming to reduce inflammation, control infection, and support microbial homeostasis. As shown in Table 4 , premium longan honey (raw honey) exhibited the lowest MIC values, inhibiting S. aureus at 7.5% (w/v) and suppressing both Gram-positive bacteria ( S. aureus, K. rhizophila, B. subtilis ) and Gram-negative bacteria ( P. aeruginosa, E. coli ) at concentrations ≤ 15.0% (w/v). Manuka honey displayed comparable efficacy against Gram-positive bacteria but was less effective against Gram-negative strains, requiring concentrations up to 30.0% (w/v) for inhibition. Conventional longan honey showed MIC values of 15.0% (w/v) against most bacteria, increasing to 30.0% (w/v) for P. aeruginosa . Although less potent than raw honey, its activity remained within the effective antimicrobial range and was comparable to Manuka honey, particularly against Gram-positive bacteria. In contrast, coffee, lychee, and Siam weed honeys consistently exhibited the weakest antimicrobial potential, with MIC values of 30.0% (w/v) across all tested bacteria, indicating significantly lower efficacy compared with high-bioactivity honeys. Table 4 Minimum inhibitory concentration (MIC) of Thai honeys from different floral sources against skin-associated bacteria (% w/v). Honey Sample Staphylococcus aureus (gram+) Pseudomonas aeruginosa (gram-) Kocuria rhizophila (gram+) Escherichia coli (gram-) Bacillus subtilis (gram+) Longan 15 ± 0.00 b 30 ± 0.00 a 15 ± 0.00 b 15 ± 0.00 b 15 ± 0.00 b Premium longan (raw honey) 7.5 ± 0.00 c 15 ± 0.00 b 15 ± 0.00 b 15 ± 0.00 b 15 ± 0.00 b Siam weed 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a Lychee 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a Coffee 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a 30 ± 0.00 a Manuka 7.5 ± 0.00 c 30 ± 0.00 a 15 ± 0.00 b 30 ± 0.00 a 15 ± 0.00 b Values are presented as mean ± standard deviation (SD, n = 3). Different superscript letters within the same column indicate significant differences (p < 0.05). MIC (minimum inhibitory concentration) represents the lowest concentration of honey that inhibited visible microbial growth, expressed as % (w/v). Gram-positive bacteria generally responded more sensitively to honey, particularly to high-bioactivity types such as premium longan (raw honey) and Manuka, which inhibited growth at ≤ 15% (w/v). Gram-negative bacteria were more resistant, requiring higher concentrations for inhibition. Phenolic and flavonoid profiling supported these findings, as honeys rich in gallic acid, caffeic acid, and catechin (e.g., premium longan raw honey and Manuka) exhibited stronger antimicrobial activities [ 3 , 6 ]. These compounds disrupt microbial membranes and inhibit specific enzymes [ 4 ]. Commensal bacteria such as K. rhizophila and B. subtilis were also sensitive to high-bioactivity honeys, similar to pathogens, suggesting potential applications for targeted modulation of the skin microbiome [ 32 , 33 ]. The antimicrobial mechanisms of honey are multifactorial and broadly categorized as peroxide-based and non-peroxide-based. The peroxide-based effect involves hydrogen peroxide (H₂O₂) generated by glucose oxidase secreted by bees during honey production, although this enzyme is heat- and light-sensitive [ 7 ]. Consequently, raw honeys that bypass heating retain stronger antimicrobial activity than processed honeys [ 8 ]. By contrast, Manuka honey is distinguished by non-peroxide-based mechanisms, relying on specific compounds such as methylglyoxal (MGO), defensin-1, phenolic acids, and flavonoids, which effectively inhibit both pathogenic and drug-resistant bacteria even in the absence of H₂O₂ [ 6 , 10 ]. In addition to chemical mechanisms, honey exerts physical effects through its high sugar concentration (> 80%), creating osmotic pressure that dehydrates microbial cells; its acidic pH (3.2–4.5); and low water activity (0.56–0.62), which together create unfavorable conditions for bacterial growth [ 34 ]. Honeys with higher levels of gallic acid, catechin, and caffeic acid also showed synergistic effects, disrupting cell walls and inducing oxidative stress [ 35 ]. Although premium longan and conventional longan honeys shared similar MIC values against certain Gram-positive strains, particularly S. aureus , K. rhizophila , and B. subtilis , raw honey exhibited superior bioactivity overall. This reflects its higher antioxidant levels and enriched bioactive compounds, which were preserved by extended in-hive maturation and the absence of heat treatment [ 8 , 23 ]. Premium longan honey (raw honey) demonstrated antimicrobial activity comparable to Manuka honey, supported by low MIC values and high bioactive compound content, particularly polyphenols involved in antimicrobial mechanisms. These findings support the potential of Thai raw honey as a reliable local alternative for developing skincare products targeting antimicrobial and anti-inflammatory functions. 3.4 Physicochemical and Sugar Compositions The analysis of basic physicochemical properties of the six honeys (Table 5 ) revealed significant differences (p 80°Brix), whereas Siam weed honey had the lowest (~ 76°Brix). Glucose content ranged from 32 to 38 g/100 g, while fructose ranged from 29 to 31 g/100 g across all honeys, with Manuka showing the highest values, followed by longan and premium longan honeys. Coffee honey showed intermediate levels. No sucrose or maltose was detected in any of the samples, confirming purity and proper maturation. The fructose-to-glucose (F/G) ratio exceeded 1.0 in all honeys, indicating slower crystallization and a prolonged liquid state, which is advantageous for both product quality and marketability. Table 5 Basic chemical composition of Thai ho neys from different floral sources. Honey Sample Total Soluble Solids (°Brix) Glucose (g/100 g) Fructose (g/100 g) pH Moisture (% wet basis) Longan 79.57 ± 0.12 b 35.57 ± 0.02 b 29.81 ± 0.06 b 3.49 ± 0.05 b 20.90 ± 0.04 ns Premium longan (raw honey) 79.53 ± 0.34 b 35.75 ± 0.22 b 29.35 ± 0.49 b 3.43 ± 0.01 b 19.95 ± 0.14 ns Siam weed 76.30 ± 0.16 b 32.48 ± 0.06 d 29.01 ± 0.19 b 3.75 ± 0.01 a 20.66 ± 0.86 ns Lychee 79.67 ± 0.12 b 34.20 ± 0.52 c 29.35 ± 0.17 b 3.40 ± 0.05 b 20.95 ± 0.59 ns Coffee 80.70 ± 0.16 a 34.62 ± 0.28 bc 30.35 ± 0.08 a 3.82 ± 0.01 a 20.89 ± 0.42 ns Manuka 81.23 ± 0.12 a 38.11 ± 0.11 a 31.07 ± 0.05 a 3.36 ± 0.02 c 20.50 ± 0.41 ns Values are presented as mean ± standard deviation (SD, n = 3). Different superscript letters within the same column indicate significant differences (p 0.05). The pH values varied significantly among samples (p < 0.05). Manuka honey was the most acidic (pH 3.36 ± 0.02), followed by premium longan and lychee honeys, whereas coffee and Siam weed honeys exhibited slightly higher pH values (around 3.75 ± 0.01), indicating less acidity but still within the normal acidic range of natural honeys (pH 3.4–4.0). Moisture content across all samples remained within the accepted standard (< 21%) and showed no significant differences. Fundamental parameters such as TSS, glucose and fructose contents, pH, and moisture serve as indicators of honey quality and stability [ 36 ]. Manuka and coffee honeys showed higher TSS and sugar contents than other samples, consistent with their characteristic sweetness and quality [ 37 ]. Honeys with lower pH, such as Manuka and premium longan, exhibited stronger acidity-a critical factor for microbial inhibition and product stability [ 38 ]. Moisture contents in all samples were within standard limits, ensuring stability and reducing fermentation risk [ 38 ]. The absence of sucrose and maltose confirmed honey purity and appropriate harvesting practices [ 39 ]. Furthermore, an F/G ratio greater than 1 is advantageous for maintaining liquid form over time [ 36 ]. The differences observed between premium longan (raw honey) and conventional longan honeys reflect the influence of processing: raw honey that bypasses heat treatment better preserves quality [ 8 ]. 3.5 Multivariate Analysis: PCA Interpretation of Bioactive and Antimicrobial Profiles of Honeys Principal component analysis (PCA) was applied to describe the relationships among quantitative phenolic and flavonoid compounds, total phenolic content (TPC), total flavonoid content (TFC), antioxidant activities (FRAP, DPPH, AEAC), and antimicrobial activity (MIC) in honeys derived from different floral sources. The PCA (Fig. 1 ) revealed that PC1 (Dim1) and PC2 (Dim2) together explained 75.1% of the total variance (52.4% and 22.7%, respectively), sufficient to distinguish the biochemical differences among honeys from various floral origins. PC1 showed strong positive correlations with TPC, TFC, antioxidant activities (FRAP, DPPH, AEAC), and major phenolic/flavonoid compounds, including gallic acid, catechin, and quercetin. PC2, on the other hand, was associated with antimicrobial activity (MIC) against skin-related bacteria, including Staphylococcus aureus , Pseudomonas aeruginosa , Kocuria rhizophila , Escherichia coli , and Bacillus subtilis . The PCA biplot (Fig. 1 ) grouped honeys according to their bioactivities into three major clusters. The high-potential cluster (Cluster 1) included Manuka and premium longan (raw honey), with high antioxidant and bioactive variables such as catechin, AEAC, DPPH, FRAP, and TPC. These two honeys exhibited the highest phenolic and flavonoid contents, as well as pronounced antioxidant and antimicrobial properties, particularly the lowest MIC against S. aureus (7.5% w/v). The moderate-potential cluster (Cluster 2) consisted of lychee, coffee, and conventional longan honeys. Lychee honey, positioned in the lower region of the plot, contained naringin, epicatechin, and rosmarinic acid. Despite its high TFC, it exhibited limited antimicrobial activity. Coffee honey, located in the upper left quadrant, was associated with caffeic acid and demonstrated moderate antioxidant activity together with selective antimicrobial effects. Conventional longan honey was positioned with epigallocatechin gallate and o-coumaric acid, showing moderate bioactivity but significantly lower than premium longan honey. Finally, the low-potential cluster (Cluster 3) comprised Siam weed honey, which was distinctly separated from all major bioactive variables, reflecting its lowest bioactivities among the tested honeys. Comparisons between premium and conventional longan honeys emphasized that, despite sharing the same floral origin, raw honey preserved higher levels of bioactive compounds and functional activities owing to extended in-hive maturation and absence of heat treatment. The loading plot indicated that gallic acid, catechin, quercetin, and caffeic acid were the most influential contributors to honey classification, showing strong associations with TPC, TFC, and antioxidant indices (FRAP, DPPH, AEAC). In contrast, MIC values were negatively correlated with gallic acid and catechin, indicating that higher concentrations of these compounds corresponded to stronger antimicrobial activities (lower MIC). These results point out the critical function of specific phenolic and flavonoid compounds in driving the functional bioactivities of honey. 3.6 Pearson Correlation Matrix Analysis: Correlation Between Bioactive Compounds and Biological Activities The Pearson correlation matrix (Fig. 2 ) confirmed and complemented the PCA findings by illustrating the relationships between phenolic/flavonoid compounds and the biological activities of honey. Several significant positive and negative correlations were observed. Gallic acid exhibited a strong positive correlation with FRAP ( r = 0.90, p < 0.01) and total phenolic content (TPC), highlighting its role as a major antioxidant compound. This observation aligns with the results reported by [ 3 ]. Catechin exhibited a strong correlation with total flavonoid content (TFC) (r ≈ 0.80), reflecting its contribution as a potent antioxidant flavanol, particularly abundant in Manuka and coffee honeys [ 5 ]. Quercetin was also highly correlated with both TFC (r = 0.85) and AEAC (r = 0.76), confirming its significance as a flavonol with antioxidant capacity [ 5 ]. TPC displayed a moderate negative correlation with the MIC against Staphylococcus aureus (r = − 0.664), reinforcing its potential antimicrobial activity. This finding aligns with [ 13 ]. By contrast, basic physicochemical parameters such as pH, moisture, glucose, and fructose showed no clear correlations with the biological activities examined. Taken together, the Pearson correlation matrix and PCA highlighted the pivotal roles of phenolic and flavonoid compounds as primary drivers of antioxidant and antimicrobial activities. These compounds may serve as biomarker candidates for identifying honey varieties with superior bioactive potential, facilitating their application in functional food and cosmeceutical development. Among the honeys tested, Manuka and premium longan (raw honey) displayed distinctive bioactive profiles, positioning them as high-potential candidates for product innovation. Notably, premium longan honey, as a Thai local product, should be further promoted for commercial utilization to enhance community-level economic value. 4. Conclusion This study compared six Thai honeys against Manuka, the premium honey. Manuka and premium longan (raw) honeys showed the highest potential and were enriched with phenolic and flavonoid compounds such as gallic acid, caffeic acid, quercetin, and catechin. These compounds were strongly associated with antioxidant and antimicrobial properties. Premium longan honey outperformed conventional longan. Its natural in-hive maturation, without heat treatment, preserved thermosensitive compounds and maintained bioactivities comparable to Manuka. Lychee honey contained high flavonoids but showed limited antimicrobial effects, while coffee and conventional longan honeys displayed moderate activities. In contrast, Siam weed honey consistently exhibited the lowest bioactive contents and functional properties. Multivariate analyses confirmed the functional clustering of honeys and identified key compounds driving bioactivity. Collectively, the findings highlight premium longan honey as a high-value local alternative to Manuka for functional food and cosmeceutical development. Future work should validate these findings in vivo and advance prototype products to fully exploit their bioactive potential. Declarations Ethical approval was not required for this study because it involved only honey samples and in-vitro antioxidant and antimicrobial assays. No experiments involving human participants, personal data, or live vertebrate animals were conducted. Therefore, informed consent to participate was not applicable. Acknowledgement This research project was financially supported by the Thailand Science Research and Innovation (TSRI), Fundamental Fund, through Rajamangala University of Technology Lanna. Author contributions WS was solely responsible for the study conception and design, sample preparation, experimental work, data acquisition, data analysis, interpretation of results, and manuscript writing. WS approved the final version of the manuscript. Funding This research project was financially supported by the Thailand Science Research and Innovation (TSRI), Fundamental Fund, through Rajamangala University of Technology Lanna (Grant number: FF2568P0031). Consent to publish Not applicable.This study did not involve human participants, personal data, or any identifiable information; therefore, consent for publication was not required. Competing interests The authors declare no competing interests. Clinical trial registration: Not applicable References Grand View Research. 2023. 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1","display":"","copyAsset":false,"role":"figure","size":52728,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) biplot illustrating the distribution of honey samples from different floral sources. Symbols represent individual honey types, while vectors represent bioactive compounds and functional variables, including antioxidant activities (FRAP, DPPH, AEAC), total phenolic content (TPC), total flavonoid content (TFC), representative phenolic acids (e.g., gallic, caffeic, p-coumaric, o-coumaric, rosmarinic acids), flavonoids (e.g., catechin, quercetin, epigallocatechin gallate, epicatechin, and naringin), and minimum inhibitory concentration (MIC) values against five skin-associated bacterial strains (\u003cem\u003eStaphylococcus aureus, Pseudomonas aeruginosa, Kocuria rhizophila, Escherichia coli,\u003c/em\u003e and \u003cem\u003eBacillus subtilis\u003c/em\u003e). MIC variables were positioned opposite to antioxidant and phenolic vectors, reflecting their negative correlations.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8166840/v1/177eac8cdf8d7bf622c77258.png"},{"id":98619472,"identity":"20554e9f-a01f-4dec-9435-ae457acc849e","added_by":"auto","created_at":"2025-12-19 15:48:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":333154,"visible":true,"origin":"","legend":"\u003cp\u003ePearson’s correlation matrix heatmap showing the relationships among antioxidant activities (FRAP, DPPH, AEAC), total phenolic content (TPC), total flavonoid content (TFC), quantified phenolic acids (e.g., gallic, caffeic, and p-coumaric acids), quantified flavonoids (e.g., catechin, quercetin, and epigallocatechin gallate), and MIC values against five skin-associated bacterial strains (\u003cem\u003eStaphylococcus aureus, Pseudomonas aeruginosa, Kocuria rhizophila, Escherichia coli,\u003c/em\u003e and \u003cem\u003eBacillus subtilis\u003c/em\u003e). Positive correlations are indicated in red, while negative correlations are indicated in blue. The heatmap highlights the mechanistic linkage between phenolic/flavonoid composition, antioxidant capacity, and antibacterial efficacy of the tested honeys.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8166840/v1/4a4c11bc5a15d8a15335860c.png"},{"id":98775322,"identity":"a9b9662b-b57c-4a84-9c6a-cd71382328df","added_by":"auto","created_at":"2025-12-22 12:19:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1714587,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8166840/v1/bd948ed5-4a6c-4576-af50-255e129d7d07.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Evaluation of Bioactive Compounds and Functional Activities in Thai Honeys from Different Floral Origins","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe market for health foods and natural cosmetics has seen accelerated growth, particularly in honey-based products and skincare, which have gained popularity through the concepts of clean beauty and sustainability. A recent report projected that the global honey market will expand from USD 9.01\u0026nbsp;billion in 2022 to USD 13.57\u0026nbsp;billion by 2030, with a compound annual growth rate of approximately 5.3% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Key driving factors include enhanced health awareness, consumer demand for safe and natural products, and the trend toward reduced use of synthetic chemicals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These trends support the development of functional products with distinctive properties such as antioxidant, anti-inflammatory, and skin health-promoting, underscoring the need to investigate the potential of honey as a raw material that can address both efficacy and sustainability demands.\u003c/p\u003e \u003cp\u003eHoney is a natural product with a complex composition that includes sugars, enzymes, and organic acids. It also contains bioactive compounds such as polyphenols and flavonoids, which play critical roles as antioxidants, antimicrobials, and anti-inflammatory agents [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These attributes have established honey as a promising raw material for the development of functional foods and natural cosmetics.\u003c/p\u003e \u003cp\u003eThe phenolic and flavonoid compounds are the main active constituents contributing to both antioxidant and antimicrobial activities in honey [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Antioxidant mechanisms involve electron or hydrogen atom donation, which inhibits oxidation reactions. In addition, these compounds can chelate transition metal ions such as Fe\u0026sup2;⁺ and Cu\u0026sup2;⁺ that catalyze Fenton reactions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This process reduces lipid peroxidation and slows cellular deterioration [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese bioactivities arise from the synergistic effects among phenolics, flavonoids, and other phytochemicals [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, physicochemical factors such as low pH, high sugar concentration, and low water activity contribute to inhibiting microbial growth and maintaining the stability of bioactive properties [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAntimicrobial mechanisms by honey involve both peroxide-based and non-peroxide-based effects. The peroxide-based mechanism involves the generation of hydrogen peroxide (H₂O₂) by the enzyme glucose oxidase, which can damage cell walls and inhibit microbial enzymes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, this mechanism is heat-sensitive, meaning that raw honey, which does not undergo heat treatment, generally has higher potential than its processed counterpart [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eManuka honey demonstrates strong activity through a non-peroxide-based mechanism, with methylglyoxal (MGO) as the key compound. MGO disrupts bacterial cell wall structures and interferes with cellular metabolism, even in the absence of H₂O₂.This mechanism enables effective inhibition of both pathogenic and multidrug-resistant bacteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, the combination of low pH and high sugar concentration enhances osmotic pressure, reinforcing the antimicrobial properties of honey [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond general mechanisms, honey contains phenolic and flavonoid compounds that significantly contribute to antioxidant and antimicrobial properties. Phenolic acids can disrupt membrane integrity and denature proteins [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. On the other hand, flavonoids inhibit quorum sensing and enzymes involved in cell wall biosynthesis, thereby reducing biofilm formation and microbial growth [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, analysis of specific compounds and their relationship with biological activities is essential to understanding honey\u0026rsquo;s bioactive potential [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough Thailand is a major honey producer in Asia, there is still a lack of studies linking phenolic and flavonoid composition to biological activities. Most research has evaluated only total phenolic content (TPC), total flavonoid content (TFC), and overall antioxidant capacity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], without focusing on quantitative profiling or systematic comparison with Manuka honey. No previous study has systematically compared Thai honeys using an integrated evaluation of phenolic\u0026ndash;flavonoid composition, antioxidant capacity, antimicrobial activity, and multivariate analysis.\u003c/p\u003e \u003cp\u003eThis study aims to evaluate the biological potential of Thai honeys from different floral origins in comparison with Manuka honey. Antioxidant activity (FRAP, DPPH, AEAC), bioactive compound contents (TPC, TFC), quantitative analysis of phenolic and flavonoid compounds, and antimicrobial activity were assessed. Furthermore, relationships between composition and bioactivity were analyzed using Pearson correlation and PCA. This study provides a systematic perspective emphasizing the potential of Thai honeys, particularly premium longan honey, as a premium raw material for the development of functional foods and natural cosmetics.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Honey Samples\u003c/h2\u003e \u003cp\u003eSix types of honey were used in this study: longan honey, premium longan honey (raw), Siam weed honey, lychee honey, coffee honey, and Manuka honey. All Thai honeys were obtained from an authenticated local apiary in Chiang Mai, Thailand, where floral origin was identified based on the predominant flowering source and producer certification. Manuka honey was sourced from a certified New Zealand producer. All samples were stored at 4\u0026deg;C in airtight containers until analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Determination of Antioxidant Activities and Bioactive Compound Contents\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Ferric Reducing Antioxidant Power (FRAP) Assay\u003c/h2\u003e \u003cp\u003eThe ferric reducing antioxidant power (FRAP) was determined according to [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] with minor modifications. FRAP reagent was freshly prepared by mixing 300 mM acetate buffer (pH 3.6), 10 mM TPTZ in 40 mM HCl, and 20 mM FeCl₃\u0026middot;6H₂O (10:1:1, v/v/v). For the assay, 0.2 mL of honey solution (50% w/v in distilled water) was mixed with 1.5 mL of FRAP reagent and incubated at 37\u0026deg;C for 4 min. The absorbance was measured at 593 nm using a UV\u0026ndash;Vis spectrophotometer (M509T, Spectronic Camspec Ltd., UK). Calibration was performed using FeSO₄\u0026middot;7H₂O standard solution (300\u0026ndash;2,000 \u0026micro;g/mL). The results were expressed as \u0026micro;mol Fe\u0026sup2;⁺ equivalents per 100 g honey. Each determination was carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003e2.2.2 DPPH Radical Scavenging Activity and Ascorbic Acid Equivalent Antioxidant Capacity (AEAC)\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe antioxidant activity was measured using the DPPH assay according to [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] with slight modifications. For the assay, 0.75 mL of honey solution (30% w/v in distilled water) was mixed with 1.5 mL of 0.1 mM DPPH solution in methanol and incubated in the dark at room temperature for 15 min. The absorbance was measured at 517 nm using a UV\u0026ndash;Vis spectrophotometer. Calibration was performed with butylated hydroxytoluene (BHT, 3\u0026ndash;50 \u0026micro;g/mL) for DPPH and L-ascorbic acid (3\u0026ndash;50 \u0026micro;g/mL) for AEAC. The results were expressed as mg BHT equivalents and mg AAE per 100 g honey. Measurements were conducted in triplicate for all samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Total Phenolic Content (TPC)\u003c/h2\u003e \u003cp\u003eTotal phenolic content was determined using the Folin\u0026ndash;Ciocalteu method described by [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] with slight modifications. For each assay, 1 mL of honey solution (10% w/v in distilled water) was mixed with 2.5 mL of 0.2 N Folin\u0026ndash;Ciocalteu reagent, left for 5 min, and then 2 mL of 7.5% Na₂CO₃ was added. The mixture was incubated in the dark at room temperature for 2 h. The absorbance was measured at 760 nm using a UV\u0026ndash;Vis spectrophotometer. Calibration was performed with gallic acid (10\u0026ndash;100 \u0026micro;g/mL). Results were expressed as mg gallic acid equivalents (GAE) per 100 g honey, and all measurements were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Total Flavonoid Content (TFC)\u003c/h2\u003e \u003cp\u003eTotal flavonoid content was determined using the aluminum chloride colorimetric method described by [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] with slight modifications. For the assay, 1 mL of honey solution (50% w/v in distilled water) was mixed with 5 mL of 2% AlCl₃ solution in methanol and incubated at room temperature in the dark for 10 min. The absorbance was then measured at 415 nm using a UV\u0026ndash;Vis spectrophotometer. Calibration was performed with catechin (5\u0026ndash;40 \u0026micro;g/mL). Results were expressed as mg catechin equivalents (CE) per 100 g honey, and all measurements were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Quantitative Analysis of Phenolic and Flavonoid Compounds\u003c/h2\u003e \u003cp\u003eThe quantitative determination of phenolic and flavonoid compounds in honey samples was performed using High-Performance Liquid Chromatography (HPLC) (Shimadzu LC-20A Series, Kyoto, Japan), equipped with a diode array detector set at 280 nm, modified from [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Separation was carried out on an Ultra Aqueous C18 column (250 \u0026times; 4.6 mm, 5 \u0026micro;m; RESTEK, Bellefonte, PA, USA). The mobile phase consisted of solvent A (formic acid: distilled water, 5:95, v/v) and solvent B (acetonitrile: formic acid: distilled water, 85:5:10, v/v/v). The gradient elution program was as follows: 0\u0026ndash;4 min, 80% A; 4\u0026ndash;8 min, linear gradient to 25% A; 8\u0026ndash;10 min, held at 25% A; 10\u0026ndash;17 min, returned to 80% A; and 17\u0026ndash;20 min, re-equilibrated at 80% A. The flow rate was maintained at 1.0 mL/min, and the injection volume was 10 \u0026micro;L.\u003c/p\u003e \u003cp\u003eChromatograms were monitored at 280 nm, and quantification was achieved by external calibration using authentic standards. Phenolic acid standards included gallic acid, caffeic acid, p-coumaric acid, o-coumaric acid, and rosmarinic acid, while flavonoid standards included catechin, quercetin, epigallocatechin gallate, epicatechin, and naringin. Calibration curves were constructed within the range of 25\u0026ndash;50 \u0026micro;g/mL. All analyses were conducted in triplicate, and results were expressed as mg per 100 g of honey.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Antimicrobial Activity (MIC Assay)\u003c/h2\u003e \u003cp\u003eThe antimicrobial activity of honey samples was determined using by the broth microdilution method following [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Five skin-associated bacteria were tested: \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (ATCC 25923), \u003cem\u003eEscherichia coli\u003c/em\u003e (ATCC 25922), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (ATCC 27853), \u003cem\u003eKocuria rhizophila\u003c/em\u003e (ATCC 9341), and \u003cem\u003eBacillus subtilis\u003c/em\u003e (ATCC 6633). Honey samples were dissolved in sterile distilled water and two-fold serially diluted in Mueller\u0026ndash;Hinton broth in 96-well plates to final concentrations of 0.06\u0026ndash;30% (w/v). Bacterial suspensions were adjusted to 5 \u0026times; 10⁵ CFU/mL and added to each well, followed by incubation at 37\u0026deg;C for 18 h. The minimum inhibitory concentration (MIC) was defined as the lowest concentration of honey that showed no visible bacterial growth compared with the control. All assays were conducted in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Physicochemical Properties and Sugar Compositions\u003c/h2\u003e \u003cp\u003ePhysicochemical analyses of honey samples were performed according to [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Total soluble solids (\u0026deg;Brix) were measured using a digital hand refractometer (ATAGO, Japan). Moisture content was determined by oven-drying at 105\u0026deg;C for 2 h, cooling in a desiccator for 30\u0026ndash;45 min, and reweighing to constant weight. pH was measured using a calibrated pH meter (Mettler Toledo, Switzerland). All measurements were conducted in triplicate.\u003c/p\u003e \u003cp\u003eThe sugar composition of honey samples was analyzed using high-performance liquid chromatography (HPLC) (Shimadzu LC-20A Series, Kyoto, Japan) according to the modified method of [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Five grams of the honey sample were diluted with 10 mL of distilled water, thoroughly mixed, and left overnight. The injection volume was 20 \u0026micro;L. Separation was performed on a Zorbax NH₂ column (250 \u0026times; 4.6 mm, 5 \u0026micro;m; Agilent Technologies, USA) at 40\u0026deg;C with acetonitrile:water (85:15, v/v) as the mobile phase at a flow rate of 1.0 mL/min. Detection was performed using a refractive index detector (RID), and quantification of glucose, fructose, and sucrose was achieved using external calibration with authentic standards. Results were expressed as g/100 g honey, and each sample was analyzed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). One-way analysis of variance (ANOVA) was conducted, and significant differences among means were identified using the Least Significant Difference (LSD) test at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Pearson correlation analysis was applied to assess relationships among measured parameters. Principal Component Analysis (PCA) was conducted to visualize multivariate relationships and clustering patterns of honey samples. The results are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) of triplicate determinations.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Antioxidant Activities and Bioactive Compound Contents\u003c/h2\u003e \u003cp\u003eSix types of honey-longan, premium longan (raw honey), Siam weed, lychee, coffee, and Manuka-were analyzed for antioxidant activity using the ferric reducing antioxidant power (FRAP), DPPH radical scavenging activity, and ascorbic acid equivalent antioxidant capacity (AEAC) assays. Bioactive compound contents, including total phenolic content (TPC) and total flavonoid content (TFC), were also determined (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntioxidant activities and bioactive compound contents of Thai honeys from different floral sources.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoney sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFRAP value\u003c/p\u003e \u003cp\u003e(\u0026micro;mol Fe\u003csup\u003e2+\u003c/sup\u003e/100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDPPH scavenging activity\u003c/p\u003e \u003cp\u003e(mg BHT eq./100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAEAC\u003c/p\u003e \u003cp\u003e(mg AAE/100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal Phenolic Content\u003c/p\u003e \u003cp\u003e(mg GAE/100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal Flavonoid Content\u003c/p\u003e \u003cp\u003e(mg CE/100 g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e538.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremium longan (raw honey)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e849.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.23\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiam weed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLychee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e575.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManuka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e991.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD, n\u0026thinsp;=\u0026thinsp;3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDifferent superscript letters within the same column indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eManuka honey indicated the highest values across all parameters, including FRAP, DPPH, AEAC, TPC, and TFC, with statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings are consistent with [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], who reported that Manuka honey contains polyphenols such as p-hydroxybenzoic acid and chlorogenic acid, contributing to its strong antioxidant properties.\u003c/p\u003e \u003cp\u003ePremium longan honey (raw honey) ranked second, showing significantly higher values across all parameters than conventional longan honey. The absence of heat treatment during production helps preserve thermolabile compounds such as polyphenols, flavonoids, glucose oxidase, vitamin C, and organic acids [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Conventional longan honey is typically harvested early (around 7 days), leading to high moisture content and the need for heat treatment (50\u0026ndash;65\u0026deg;C) to reduce water content before packaging. By contrast, raw honey is harvested after a longer maturation period (18\u0026ndash;21 days), allowing natural moisture reduction to occur gradually without heating. As a result, premium longan honey demonstrates bioactivities comparable to those of Manuka.\u003c/p\u003e \u003cp\u003eAmong processed honeys, coffee honey displayed the strongest potential, characterized by high TFC and higher FRAP and AEAC values than longan, lychee, and Siam weed honeys. This result corresponds with the presence of caffeic acid and chlorogenic acid identified in quantitative profiling [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Longan and lychee honeys exhibited similar antioxidant activities with comparable TPC levels. However, lychee honey had slightly higher TFC, which may reflect structural differences in its predominant flavonoids. Siam weed honey exhibited the lowest antioxidant capacity across all parameters, consistent with its minimal phenolic and flavonoid contents, suggesting that floral origin may limit the diversity of bioactive constituents.\u003c/p\u003e \u003cp\u003eBased on antioxidant capacity, the honeys could be categorized into three groups: high potential (Manuka and premium longan), moderate potential (coffee, lychee, and conventional longan), and low potential (Siam weed). These results highlight the influence of floral origin and processing conditions on honey bioactivities. In particular, variations in polyphenol and flavonoid concentrations are directly associated with antioxidant and antimicrobial properties.\u003c/p\u003e \u003cp\u003eThe antioxidant activity of honey is directly correlated with its phenolic and flavonoid composition, as these compounds function as electron or hydrogen atom donors to inhibit oxidative reactions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Gallic acid, caffeic acid, quercetin, and catechin, in particular, have been reported to play important roles in antioxidant, anti-inflammatory, and antimicrobial activities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The high antioxidant capacity of Manuka and premium longan honeys reflects their abundant polyphenolic content, with premium longan additionally benefiting from the preservation of thermosensitive compounds due to the absence of heat treatment [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePearson\u0026rsquo;s correlation matrix (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e) further demonstrated strong positive correlations between TPC and TFC with FRAP, DPPH, and AEAC, with TPC showing r\u0026thinsp;\u0026gt;\u0026thinsp;0.90 with all parameters. These findings align with [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], who suggested that TPC and TFC can serve as reliable indicators of honey\u0026rsquo;s antioxidant activity. Other supportive constituents, such as vitamins and enzymes (e.g., glucose oxidase), may act synergistically [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], contributing to complex bioactivities that cannot be explained by individual compounds alone.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results confirm that Thai premium longan honey (raw honey) exhibits antioxidant potential comparable to that of Manuka. TPC and TFC may therefore serve as reliable indicators of honey\u0026rsquo;s bioactive quality, highlighting its potential as a high-value raw material. Collectively, these findings suggest that premium longan honey could serve as a valuable alternative to Manuka in functional food and cosmetic applications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Quantitative Analysis of Phenolic and Flavonoid Compounds\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e present the quantitative analysis of phenolic and flavonoid compounds in six types of honey. Five major phenolic acids were identified: gallic acid, caffeic acid, p-coumaric acid, o-coumaric acid, and rosmarinic acid, with significant variations among honey types (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Manuka and premium longan honeys (raw honey) exhibited the highest total phenolic content, dominated by gallic acid and caffeic acid. Coffee and conventional longan honeys showed moderate total phenolic levels, though they were still relatively rich in gallic acid and caffeic acid. Lychee honey contained higher levels of caffeic acid and rosmarinic acid compared to other types, whereas p-coumaric acid was detected among all the selected honeys at comparable levels. In contrast, o-coumaric acid and rosmarinic acid were only detected in certain samples. Siam weed honey contained the lowest phenolic levels, consistent with its weak antioxidant potential, emphasizing the role of gallic acid and caffeic acid in honey bioactivity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhenolic compound composition of Thai honeys from different floral sources.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHoney Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003ePhenolic compound composition (mg/100 g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGallic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaffeic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-coumeric acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eo-coumeric acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRosmarinic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSum of phenolic compounds\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremium longan (raw honey)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiam weed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLychee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManuka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD, n\u0026thinsp;=\u0026thinsp;3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eDifferent superscript letters within the same column indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u0026ldquo;nd\u0026rdquo; indicates not detected.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFlavonoid compound composition of Thai honeys from different floral sources.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHoney Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eFlavonoid compound composition (mg/100 g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatechin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEpigallocatechin gallate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEpicatechin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNaringin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSum of flavonoid compounds\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremium longan (raw honey)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiam weed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLychee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManuka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD, n\u0026thinsp;=\u0026thinsp;3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eDifferent superscript letters within the same column indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u0026ldquo;nd\u0026rdquo; indicates not detected.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor flavonoids, five compounds were detected: catechin, quercetin, epigallocatechin gallate, epicatechin, and naringin, showing significant differences in type and concentration among samples (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Manuka and premium longan honeys exhibited the highest total flavonoid levels, with catechin as the dominant constituent. Coffee and lychee honeys showed moderate levels, with lychee honey being particularly rich in epicatechin and naringin, which may contribute to its distinct antioxidant activity. Catechin was especially abundant in Manuka and premium longan honeys, consistent with their strong antioxidant capacities. In contrast, Siam weed honey exhibited the lowest diversity and concentration of flavonoids. Quercetin and epigallocatechin gallate were present at comparable levels in several honeys, except for Siam weed honey, which contained the lowest quercetin levels, and coffee honey, which lacked epicatechin.\u003c/p\u003e \u003cp\u003eOverall, the floral origin and production process influenced flavonoid composition and bioactivity of honey. Honeys rich in catechin, epicatechin, and quercetin generally exhibited stronger biological activities.\u003c/p\u003e \u003cp\u003eQuantitative profiling revealed that honeys from six floral origins varied in phenolic and flavonoid composition. Gallic acid was the predominant constituent in many samples, particularly premium longan (raw honey) and Manuka, and plays a critical role in antioxidant activity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Caffeic acid and p-coumaric acid, detected at moderate levels, also exhibit antioxidant and anti-inflammatory properties and are associated with higher TPC values [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The main mechanism of these phenolic acids is attributed to their multiple hydroxyl groups, which readily donate electrons to neutralize free radicals, thereby stabilizing reactive species and preventing oxidative chain reactions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong flavonoids, catechin and quercetin were strongly correlated with high TFC and were abundant in Manuka, premium longan, and lychee honeys. Both compounds are well-known for their antioxidant, anti-inflammatory, and immunomodulatory properties [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Quercetin provides photoprotective benefits against UV radiation and promotes collagen synthesis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Epicatechin and naringin, abundant in lychee and coffee honeys, have been reported to support skin elasticity and reduce cellular inflammation [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComparison among honey types indicated that Manuka and premium longan honeys (raw honey) contained the most diverse and concentrated bioactive compounds, particularly gallic acid, caffeic acid, quercetin, and catechin. These findings align with their high TPC, TFC, FRAP, DPPH, AEAC, and antimicrobial (MIC) activities, reflecting the direct contribution of phenolic and flavonoid constituents to [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Coffee honey exhibited high TFC with abundant caffeic acid and catechin, supporting its moderate antioxidant and antimicrobial properties. Lychee honey was notable for its high TFC due to quercetin and naringin, despite moderate TPC. Conventional longan honey shared a similar composition with raw honey but exhibited lower bioactivity, likely due to processing factors such as heating and shorter harvest duration [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Siam weed honey consistently showed the lowest bioactivities, consistent with its low levels of gallic acid and catechin.\u003c/p\u003e \u003cp\u003eCertain phenolic and flavonoid compounds were also implicated in honey\u0026rsquo;s antimicrobial activities, particularly gallic acid and catechin, which were abundant in Manuka and premium longan honeys (raw honey). These compounds significantly inhibited \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, a skin-associated pathogen [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This observation is consistent with reports that catechin and chlorogenic acid inhibit the growth of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and \u003cem\u003eCutibacterium acnes\u003c/em\u003e by disrupting cell wall structures and inhibiting specific enzymes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Catechin, for instance, acts by binding to the cell membrane and reducing cytoplasmic membrane potential [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, the pro-oxidant action of gallic acid can induce oxidative damage in bacterial cells [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In contrast, coffee, lychee, and Siam weed honeys, while containing some bioactive compounds, exhibited insufficient diversity and concentration to exert strong antimicrobial effects [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Antimicrobial Activity\u003c/h2\u003e \u003cp\u003eThis study evaluated the antimicrobial activity of six floral honeys against five skin-associated bacteria: \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, a major pathogen in acne vulgaris and skin infections such as folliculitis and abscesses [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, commonly isolated from infected, burn, and chronic wounds, which forms biofilms and secretes tissue-damaging toxins [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]; \u003cem\u003eEscherichia coli\u003c/em\u003e, which may contaminate open wounds and trigger inflammation in chronic ulcers [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]; \u003cem\u003eKocuria rhizophila\u003c/em\u003e, a commensal skin bacterium that contributes to microbiome balance [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]; and \u003cem\u003eBacillus subtilis\u003c/em\u003e, known to suppress pathogens and promote skin immunity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These microorganisms are key targets in skin-care applications aiming to reduce inflammation, control infection, and support microbial homeostasis.\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, premium longan honey (raw honey) exhibited the lowest MIC values, inhibiting \u003cem\u003eS. aureus\u003c/em\u003e at 7.5% (w/v) and suppressing both Gram-positive bacteria (\u003cem\u003eS. aureus, K. rhizophila, B. subtilis\u003c/em\u003e) and Gram-negative bacteria (\u003cem\u003eP. aeruginosa, E. coli\u003c/em\u003e) at concentrations\u0026thinsp;\u0026le;\u0026thinsp;15.0% (w/v). Manuka honey displayed comparable efficacy against Gram-positive bacteria but was less effective against Gram-negative strains, requiring concentrations up to 30.0% (w/v) for inhibition. Conventional longan honey showed MIC values of 15.0% (w/v) against most bacteria, increasing to 30.0% (w/v) for \u003cem\u003eP. aeruginosa\u003c/em\u003e. Although less potent than raw honey, its activity remained within the effective antimicrobial range and was comparable to Manuka honey, particularly against Gram-positive bacteria. In contrast, coffee, lychee, and Siam weed honeys consistently exhibited the weakest antimicrobial potential, with MIC values of 30.0% (w/v) across all tested bacteria, indicating significantly lower efficacy compared with high-bioactivity honeys.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMinimum inhibitory concentration (MIC) of Thai honeys from different floral sources against skin-associated bacteria (% w/v).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoney Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus aureus (gram+)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(gram-)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eKocuria rhizophila\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(gram+)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(gram-)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eBacillus subtilis\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(gram+)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremium longan (raw honey)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiam weed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLychee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManuka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD, n\u0026thinsp;=\u0026thinsp;3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDifferent superscript letters within the same column indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMIC (minimum inhibitory concentration) represents the lowest concentration of honey that inhibited visible microbial growth, expressed as % (w/v).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGram-positive bacteria generally responded more sensitively to honey, particularly to high-bioactivity types such as premium longan (raw honey) and Manuka, which inhibited growth at \u0026le;\u0026thinsp;15% (w/v). Gram-negative bacteria were more resistant, requiring higher concentrations for inhibition. Phenolic and flavonoid profiling supported these findings, as honeys rich in gallic acid, caffeic acid, and catechin (e.g., premium longan raw honey and Manuka) exhibited stronger antimicrobial activities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These compounds disrupt microbial membranes and inhibit specific enzymes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Commensal bacteria such as \u003cem\u003eK. rhizophila\u003c/em\u003e and \u003cem\u003eB. subtilis\u003c/em\u003e were also sensitive to high-bioactivity honeys, similar to pathogens, suggesting potential applications for targeted modulation of the skin microbiome [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe antimicrobial mechanisms of honey are multifactorial and broadly categorized as peroxide-based and non-peroxide-based. The peroxide-based effect involves hydrogen peroxide (H₂O₂) generated by glucose oxidase secreted by bees during honey production, although this enzyme is heat- and light-sensitive [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Consequently, raw honeys that bypass heating retain stronger antimicrobial activity than processed honeys [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. By contrast, Manuka honey is distinguished by non-peroxide-based mechanisms, relying on specific compounds such as methylglyoxal (MGO), defensin-1, phenolic acids, and flavonoids, which effectively inhibit both pathogenic and drug-resistant bacteria even in the absence of H₂O₂ [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to chemical mechanisms, honey exerts physical effects through its high sugar concentration (\u0026gt;\u0026thinsp;80%), creating osmotic pressure that dehydrates microbial cells; its acidic pH (3.2\u0026ndash;4.5); and low water activity (0.56\u0026ndash;0.62), which together create unfavorable conditions for bacterial growth [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Honeys with higher levels of gallic acid, catechin, and caffeic acid also showed synergistic effects, disrupting cell walls and inducing oxidative stress [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough premium longan and conventional longan honeys shared similar MIC values against certain Gram-positive strains, particularly \u003cem\u003eS. aureus\u003c/em\u003e, \u003cem\u003eK. rhizophila\u003c/em\u003e, and \u003cem\u003eB. subtilis\u003c/em\u003e, raw honey exhibited superior bioactivity overall. This reflects its higher antioxidant levels and enriched bioactive compounds, which were preserved by extended in-hive maturation and the absence of heat treatment [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePremium longan honey (raw honey) demonstrated antimicrobial activity comparable to Manuka honey, supported by low MIC values and high bioactive compound content, particularly polyphenols involved in antimicrobial mechanisms. These findings support the potential of Thai raw honey as a reliable local alternative for developing skincare products targeting antimicrobial and anti-inflammatory functions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Physicochemical and Sugar Compositions\u003c/h2\u003e \u003cp\u003eThe analysis of basic physicochemical properties of the six honeys (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) revealed significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in their physicochemical composition. Manuka and coffee honeys exhibited the highest total soluble solids (TSS\u0026thinsp;\u0026gt;\u0026thinsp;80\u0026deg;Brix), whereas Siam weed honey had the lowest (~\u0026thinsp;76\u0026deg;Brix). Glucose content ranged from 32 to 38 g/100 g, while fructose ranged from 29 to 31 g/100 g across all honeys, with Manuka showing the highest values, followed by longan and premium longan honeys. Coffee honey showed intermediate levels. No sucrose or maltose was detected in any of the samples, confirming purity and proper maturation. The fructose-to-glucose (F/G) ratio exceeded 1.0 in all honeys, indicating slower crystallization and a prolonged liquid state, which is advantageous for both product quality and marketability.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic chemical composition of Thai ho neys from different floral sources.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoney Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Soluble Solids\u003c/p\u003e \u003cp\u003e(\u0026deg;Brix)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e(g/100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFructose\u003c/p\u003e \u003cp\u003e(g/100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMoisture\u003c/p\u003e \u003cp\u003e(% wet basis)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremium longan (raw honey)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiam weed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLychee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManuka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD, n\u0026thinsp;=\u0026thinsp;3).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDifferent superscript letters within the same column indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u0026ldquo;ns\u0026rdquo; indicates not significantly different (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe pH values varied significantly among samples (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Manuka honey was the most acidic (pH 3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02), followed by premium longan and lychee honeys, whereas coffee and Siam weed honeys exhibited slightly higher pH values (around 3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01), indicating less acidity but still within the normal acidic range of natural honeys (pH 3.4\u0026ndash;4.0). Moisture content across all samples remained within the accepted standard (\u0026lt;\u0026thinsp;21%) and showed no significant differences.\u003c/p\u003e \u003cp\u003eFundamental parameters such as TSS, glucose and fructose contents, pH, and moisture serve as indicators of honey quality and stability [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Manuka and coffee honeys showed higher TSS and sugar contents than other samples, consistent with their characteristic sweetness and quality [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Honeys with lower pH, such as Manuka and premium longan, exhibited stronger acidity-a critical factor for microbial inhibition and product stability [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Moisture contents in all samples were within standard limits, ensuring stability and reducing fermentation risk [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe absence of sucrose and maltose confirmed honey purity and appropriate harvesting practices [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Furthermore, an F/G ratio greater than 1 is advantageous for maintaining liquid form over time [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The differences observed between premium longan (raw honey) and conventional longan honeys reflect the influence of processing: raw honey that bypasses heat treatment better preserves quality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Multivariate Analysis: PCA Interpretation of Bioactive and Antimicrobial Profiles of Honeys\u003c/h2\u003e \u003cp\u003ePrincipal component analysis (PCA) was applied to describe the relationships among quantitative phenolic and flavonoid compounds, total phenolic content (TPC), total flavonoid content (TFC), antioxidant activities (FRAP, DPPH, AEAC), and antimicrobial activity (MIC) in honeys derived from different floral sources.\u003c/p\u003e \u003cp\u003eThe PCA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed that PC1 (Dim1) and PC2 (Dim2) together explained 75.1% of the total variance (52.4% and 22.7%, respectively), sufficient to distinguish the biochemical differences among honeys from various floral origins. PC1 showed strong positive correlations with TPC, TFC, antioxidant activities (FRAP, DPPH, AEAC), and major phenolic/flavonoid compounds, including gallic acid, catechin, and quercetin. PC2, on the other hand, was associated with antimicrobial activity (MIC) against skin-related bacteria, including \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eKocuria rhizophila\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003eBacillus subtilis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe PCA biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) grouped honeys according to their bioactivities into three major clusters. The high-potential cluster (Cluster 1) included Manuka and premium longan (raw honey), with high antioxidant and bioactive variables such as catechin, AEAC, DPPH, FRAP, and TPC. These two honeys exhibited the highest phenolic and flavonoid contents, as well as pronounced antioxidant and antimicrobial properties, particularly the lowest MIC against \u003cem\u003eS. aureus\u003c/em\u003e (7.5% w/v). The moderate-potential cluster (Cluster 2) consisted of lychee, coffee, and conventional longan honeys.\u003c/p\u003e \u003cp\u003eLychee honey, positioned in the lower region of the plot, contained naringin, epicatechin, and rosmarinic acid. Despite its high TFC, it exhibited limited antimicrobial activity. Coffee honey, located in the upper left quadrant, was associated with caffeic acid and demonstrated moderate antioxidant activity together with selective antimicrobial effects.\u003c/p\u003e \u003cp\u003eConventional longan honey was positioned with epigallocatechin gallate and o-coumaric acid, showing moderate bioactivity but significantly lower than premium longan honey. Finally, the low-potential cluster (Cluster 3) comprised Siam weed honey, which was distinctly separated from all major bioactive variables, reflecting its lowest bioactivities among the tested honeys. Comparisons between premium and conventional longan honeys emphasized that, despite sharing the same floral origin, raw honey preserved higher levels of bioactive compounds and functional activities owing to extended in-hive maturation and absence of heat treatment.\u003c/p\u003e \u003cp\u003eThe loading plot indicated that gallic acid, catechin, quercetin, and caffeic acid were the most influential contributors to honey classification, showing strong associations with TPC, TFC, and antioxidant indices (FRAP, DPPH, AEAC). In contrast, MIC values were negatively correlated with gallic acid and catechin, indicating that higher concentrations of these compounds corresponded to stronger antimicrobial activities (lower MIC). These results point out the critical function of specific phenolic and flavonoid compounds in driving the functional bioactivities of honey.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Pearson Correlation Matrix Analysis: Correlation Between Bioactive Compounds and Biological Activities\u003c/h2\u003e \u003cp\u003eThe Pearson correlation matrix (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e) confirmed and complemented the PCA findings by illustrating the relationships between phenolic/flavonoid compounds and the biological activities of honey. Several significant positive and negative correlations were observed.\u003c/p\u003e \u003cp\u003eGallic acid exhibited a strong positive correlation with FRAP ( r\u0026thinsp;=\u0026thinsp;0.90, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and total phenolic content (TPC), highlighting its role as a major antioxidant compound. This observation aligns with the results reported by [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Catechin exhibited a strong correlation with total flavonoid content (TFC) (r\u0026thinsp;\u0026asymp;\u0026thinsp;0.80), reflecting its contribution as a potent antioxidant flavanol, particularly abundant in Manuka and coffee honeys [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Quercetin was also highly correlated with both TFC (r\u0026thinsp;=\u0026thinsp;0.85) and AEAC (r\u0026thinsp;=\u0026thinsp;0.76), confirming its significance as a flavonol with antioxidant capacity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTPC displayed a moderate negative correlation with the MIC against \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (r = \u0026minus;\u0026thinsp;0.664), reinforcing its potential antimicrobial activity. This finding aligns with [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. By contrast, basic physicochemical parameters such as pH, moisture, glucose, and fructose showed no clear correlations with the biological activities examined.\u003c/p\u003e \u003cp\u003eTaken together, the Pearson correlation matrix and PCA highlighted the pivotal roles of phenolic and flavonoid compounds as primary drivers of antioxidant and antimicrobial activities. These compounds may serve as biomarker candidates for identifying honey varieties with superior bioactive potential, facilitating their application in functional food and cosmeceutical development.\u003c/p\u003e \u003cp\u003eAmong the honeys tested, Manuka and premium longan (raw honey) displayed distinctive bioactive profiles, positioning them as high-potential candidates for product innovation. Notably, premium longan honey, as a Thai local product, should be further promoted for commercial utilization to enhance community-level economic value.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study compared six Thai honeys against Manuka, the premium honey. Manuka and premium longan (raw) honeys showed the highest potential and were enriched with phenolic and flavonoid compounds such as gallic acid, caffeic acid, quercetin, and catechin. These compounds were strongly associated with antioxidant and antimicrobial properties. Premium longan honey outperformed conventional longan. Its natural in-hive maturation, without heat treatment, preserved thermosensitive compounds and maintained bioactivities comparable to Manuka. Lychee honey contained high flavonoids but showed limited antimicrobial effects, while coffee and conventional longan honeys displayed moderate activities. In contrast, Siam weed honey consistently exhibited the lowest bioactive contents and functional properties. Multivariate analyses confirmed the functional clustering of honeys and identified key compounds driving bioactivity. Collectively, the findings highlight premium longan honey as a high-value local alternative to Manuka for functional food and cosmeceutical development. Future work should validate these findings in vivo and advance prototype products to fully exploit their bioactive potential.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical approval was not required for this study because it involved only honey samples and in-vitro antioxidant and antimicrobial assays. No experiments involving human participants, personal data, or live vertebrate animals were conducted. Therefore, informed consent to participate was not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research project was financially supported by the Thailand Science Research and Innovation (TSRI), Fundamental Fund, through Rajamangala University of Technology Lanna.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWS was solely responsible for the study conception and design, sample preparation, experimental work, data acquisition, data analysis, interpretation of results, and manuscript writing. WS approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research project was financially supported by the Thailand Science Research and Innovation (TSRI), Fundamental Fund, through Rajamangala University of Technology Lanna (Grant number: FF2568P0031).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.This study did not involve human participants, personal data, or any identifiable information; therefore, consent for publication was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGrand View Research. 2023. 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J Entomol Zool Stud. 2024;12(2B):9308. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.22271/j.ento.2024.v12.i2b.9308\u003c/span\u003e\u003cspan address=\"10.22271/j.ento.2024.v12.i2b.9308\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discoverfood","sideBox":"Learn more about [Discover Food](https://www.springer.com/44187)","snPcode":"","submissionUrl":"","title":"Discover Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Thai honey, phenolic compounds, flavonoids, antioxidant activity, antimicrobial activity, bioactive compounds","lastPublishedDoi":"10.21203/rs.3.rs-8166840/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8166840/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study compares the biological potential of six varieties of honey from different floral origins in Thailand, including longan, premium longan (raw honey), Siam weed, lychee, coffee, and Manuka. Antioxidant activities were evaluated using FRAP, DPPH, and AEAC assays, while total phenolic content (TPC) and total flavonoid content (TFC) were determined. Quantitative analysis of phenolic and flavonoid compounds, antimicrobial activity (MIC), and basic physicochemical parameters were conducted. Multivariate analyses (PCA and Pearson correlation) were applied to link the biochemical composition of honeys with biological activities. Manuka and premium longan honeys exhibited the highest phenolic and flavonoid levels and strong antioxidant capacities. Major compounds-gallic acid, caffeic acid, quercetin, and catechin-showed significant correlations with TPC, TFC, and both antioxidant and antimicrobial effects. PCA grouped Manuka and premium longan honeys in a high-bioactivity cluster, closely associated with antioxidant variables and low MIC values, particularly against \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (7.5% w/v). Lychee honey showed high flavonoid content but limited antimicrobial activity, while coffee and conventional longan honeys displayed moderate activities. In contrast, Siam weed honey exhibited the lowest bioactive levels, consistent with its weak antioxidant and antimicrobial properties. Multivariate analyses confirmed that phenolics and flavonoids are the main drivers of honey bioactivities. These findings highlight premium longan honey as a promising valuable bioresource for functional food and cosmeceutical development, supporting its potential to enhance local economic value.\u003c/p\u003e","manuscriptTitle":"Comparative Evaluation of Bioactive Compounds and Functional Activities in Thai Honeys from Different Floral Origins","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-19 15:48:34","doi":"10.21203/rs.3.rs-8166840/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-05T06:58:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-05T06:54:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-29T15:20:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T20:17:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139401726090371566115488195404746859490","date":"2026-01-26T13:27:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T09:55:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278436377253359018697298448134688847284","date":"2026-01-21T13:14:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169783479708488806993064075944252995797","date":"2026-01-20T16:38:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256543194695170659067506926950137768951","date":"2026-01-20T08:13:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28619827300104568467788894817890344431","date":"2026-01-20T02:47:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T16:35:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294626014594814055509445653907238044759","date":"2026-01-19T13:42:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-20T13:15:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T08:41:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52200213630618493132361853208324335417","date":"2025-12-17T11:46:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60947205858079673565403958173518671593","date":"2025-12-17T08:58:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-17T07:55:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-16T05:51:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T09:53:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-06T16:02:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Food","date":"2025-12-02T10:14:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discoverfood","sideBox":"Learn more about [Discover Food](https://www.springer.com/44187)","snPcode":"","submissionUrl":"","title":"Discover Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"acd0bb64-deaa-44ac-a513-98ec48d438ae","owner":[],"postedDate":"December 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T11:40:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-19 15:48:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8166840","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8166840","identity":"rs-8166840","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}