Introduction

Persea americana (avocado) is globally valued for its nutritional and therapeutic properties and is known by various names across cultures, such as, Mparachichi (Swahili), Ovakedo (Uganda), Maluma (South Africa), Paya (Twi), Pia (Yoruba), Avocatier or Zaboka (French), and Pagua (Spanish)1. While the fruit is widely consumed for its rich content of healthy fats, vitamins, and antioxidants2,3, increasing scientific attention is now turning to the pharmacological potential of its non-edible parts, particularly the leaves. In traditional medicine systems across Africa and Latin America, avocado leaves have long been used to manage ailments such as diabetes, hypertension, and inflammatory disorders4,5,6. Despite their ethnomedicinal relevance and environmental abundance, the leaves are often discarded as agricultural waste and remain underutilized in scientific research relative to the fruit.

Avocado leaves are widely available, non-commercialized, and typically discarded, making them a sustainable and low-cost resource for therapeutic exploration, particularly in low-resource settings. They are known to contain a diverse spectrum of phytochemicals, including flavonoids, polyphenols, terpenoids, and fatty acid derivatives, which have been linked to antioxidant, anti-inflammatory, and metabolic effects1. Understanding their composition through phytochemical profiling is therefore crucial for both validating traditional claims and identifying potential drug leads.

Gas Chromatography-Mass Spectrometry (GC-MS) and Fourier Transform Infrared (FT-IR) spectroscopy are established tools in natural product chemistry. GC-MS provides detailed resolution of volatile and semi-volatile compounds7,8, while FT-IR enables rapid identification of functional groups characteristic of bioactive phytochemical classes such as phenolics, alkaloids, and glycosides9,10. Used in combination, these techniques offer a comprehensive approach to plant compound characterization.

Although previous studies have used GC-MS to investigate P. americana leaf extracts11,12,13,14, few have examined the comparative influence of solvent polarity on extractable constituents. Moreover, no published work has systematically compared ethanolic and ethyl acetate extracts of P. americana leaves using an integrated GC-MS and FT-IR approach. These two solvents differ markedly in polarity, which directly impacts the type and quantity of phytochemicals recovered. Furthermore, the phytochemical profile of P. americana leaves grown in Uganda, a country with diverse agroecological zones, remains underexplored and may yield distinct chemotypic signatures.

The aim of this study is to characterize and compare the phytochemical content of ethanolic and ethyl acetate extracts of avocado (P. americana) leaves collected from Uganda using both FT-IR and GC-MS. By linking functional groups and compound identities to known pharmacological effects, this work seeks to assess how solvent polarity influences phytochemical extraction, identify compounds of potential therapeutic relevance, and provide foundational data to guide future bioactivity studies, including antidiabetic and anti-inflammatory screening.

This research addresses a current gap in phytochemical profiling literature and emphasizes the value of underutilized plant parts as a sustainable resource for natural product drug discovery.

Materials and methodology

Collection, identification, and preparation of plant specimens

Fresh leaves of Persea americana (avocado) were collected from the botanical premises of Kampala International University (KIU), Ishaka, Uganda. The plant was taxonomically identified and authenticated by Dr. Eunice of the Biology Department, Mbarara University of Science and Technology, and a voucher specimen (ID: AOM-2024-001) was deposited for reference.

The leaves were rinsed with distilled water to remove surface dust and contaminants, and then shade-dried in a well-ventilated space at ambient temperature for 14 days to preserve heat-sensitive phytochemicals and minimize microbial contamination. The dried material was pulverized using a high-speed electric blender and sieved to a fine powder for uniform extraction efficiency.

Extraction methods (cold maceration)

Two solvents of varying polarity, ethanol (polar) and ethyl acetate (semi-polar), were used to extract phytoconstituents to evaluate solvent-specific extraction efficiency.

Sample preparation

The finely blended powdered avocado leaves were weighed using an analytical balance, and the reading was recorded at equilibrium.

Exactly 600 g of powdered avocado leaves was separately soaked in 3000 mL of ethanol or ethyl acetate (1:5 w/v) in sterile glass containers. The mixtures were kept at room temperature (25 ± 2 °C) for 72 h with occasional shaking/stirring every 6–12 h to facilitate solute diffusion.

Filtration and concentration

After maceration (72 h), the extracts were filtered through double-layered muslin cloth followed by Whatman No. 1 filter paper to remove residual plant debris.

The combined filtrates (ethanol and ethyl acetate) were concentrated at lower pressure using a rotary evaporator at temperatures below the solvent boiling points (ethanol: 40 °C; ethyl acetate: 35 °C) to prevent thermal degradation. Final drying was performed using a vacuum oven at 40 °C. Extract yields were calculated as; 49.72 g (8.29% yield) for Ethanolic extract and 32.38 g (5.40% yield) for Ethyl acetate extract.

The concentrated crude extracts were stored in sealed amber bottles at 4 °C for further analysis.

Gas chromatography-mass spectrometry (GC-MS) analysis

GC-MS principle

The model of the instrument used for the analysis is Agilent technologies 7890 GC system and the model of the detector is Agilent technologies 5975 MSD (Mass Spect. Detector). The principle behind the GC analysis is separation techniques. In separation techniques, there are two phases-the mobile and the stationary phase. The mobile phase is the carrier gas (Helium, 99.99% purity), while the stationary phase is the column. The model of the column is HP5 MS with length 30 m, internal diameter 0.320 mm, while the thickness is 0.25 µm. The oven temperature program is initial temperature of 80 °C to hold for 1 min. It increases by 10° per minute to the final temperature of 240 °C to hold for 6 min. The injection volume is 1 µl and the heater or detector temperature is 250 °C.

Operation: The sample extracted was put in a vial bottle and the vial bottle was placed in auto injector sample compartment. The automatic injector injects the sample into the liner. The mobile phase pushes the sample from the liner into the column where separation takes place into different components at different retention time. The MS interpret the spectrum MZ (mass to charge ratio) with molar mass and structures.

Compound identification

The extract’s bioactive compounds were identified by analyzing their retention times on an HP-5MS column using gas chromatography (GC) and by comparing their mass spectra with the NIST 14 library installed in the MassHunter software (Agilent Technologies), with a match threshold of ≥  80%.

FTIR spectroscopy procedure

Fourier-transform infrared (FT-IR) analysis was performed using a Buck Scientific M530 spectrophotometer (USA) equipped with a deuterated triglycine sulfate (DTGS) detector and a potassium bromide (KBr) beam splitter, as described by Dike et al.15. A 1.0 g portion of the extract was homogenized with 0.5 mL of Nujol and mounted onto a salt pellet for transmission analysis using the KBr pellet method. Spectra were recorded in the range of 4000 to 600 cm⁻1 with a resolution of 4 cm⁻1 and 32 co-added scans. Spectral data were processed using the Gramme A1 software and interpreted in transmittance mode15,16.

The analysis focused primarily on the functional group region (4000–1000 cm⁻1), which includes distinct absorption bands characteristic of major phytochemical groups such as flavonoids, polyphenols, glycosides, and terpenoids. Although peaks below 1000 cm⁻1 (fingerprint region) were not emphasized due to spectral complexity and overlap, future comparative studies incorporating spectral libraries may improve compound specificity in this region.

Results

Extract yield

Table 1 illustrates the percentage yield, calculated using the formula; Yield (%) = (Mass of Extract Obtained/Mass of Plant Material Used) × 100, based on an initial plant material weight of 600 g. Under the same extraction conditions, the ethanolic extract yielded 8.29%, while the ethyl acetate extract yielded 5.40%.

$${\text{Yield}}\left( \% \right)\;{\text{for}}\;{\text{Ethanol}}\;{\text{Extract}} = \frac{{{\text{Mass}}\;{\text{of}}\;{\text{Extract}}\;{\text{Obtained}}}}{{{\text{Mass}}\;{\text{of}}\;{\text{Plant}}\;{\text{Material}}\;{\text{Used}}}} \times 100$$
Table 1 Percentage yield of ethanolic and ethyl acetate extracts of Persea americana leaves.
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Given: Mass of extract obtained = 49.72 g, Mass of plant material used = 600 g

$$\begin{aligned} {\text{Yield}}\left( \% \right) = & \frac{49.72}{{600}} \times 100 \\ = & 0.0829 \times 100 \\ = & 8.29\% \\ \end{aligned}$$
$${\text{Yield}}\left( \% \right)\;{\text{for}}\;{\text{Ethyl}}\;{\text{Acetate}}\;{\text{Extract}} = \frac{{{\text{Mass}}\;{\text{of}}\;{\text{Extract}}\;{\text{Obtained}}}}{{{\text{Mass}}\;{\text{of}}\;{\text{Plant}}\;{\text{Material}}\;{\text{Used}}}} \times 100$$

Given: Mass of extract obtained = 32.38 g.

Mass of plant material used = 600 g

$$\begin{aligned} {\text{Yield}} \left( \% \right) \, = & \frac{32.38}{{600}} \times 100 \\ = & 0.05397 \times 100 \\ = & 5.40\% \\ \end{aligned}$$

Tables 2 and 3 below presents the list of phytochemical constituents identified in the extracts of ethanol and ethyl acetate of avocado leaves through Gas Chromatography-Mass Spectrometry, with each compound’s molecular formula, molecular weight, and retention time (RT) given.

Table 2 GC-MS analysis of the phytocompounds found in Persea americana leaf extract in ethanol.
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Table 3 GC-MS analysis of phytocompounds in ethylacetate leaf extract of Persea americana.
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A comparative analysis of the major phytochemicals in the ethanolic and ethyl acetate extracts is provided in Table 4, with the presence or absence of key compounds noted, offering insights into the solvent-dependent extraction of bioactive metabolites.

Table 4 Comparative analysis of ethanolic and ethyl acetate extracts: key phytochemical differences.
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Table 5 summarizes the functional groups detected in the ethanolic and ethyl acetate extracts of avocado leaves using FT-IR spectroscopy. The distinctive absorption peaks and their corresponding functional groups are listed, indicating the presence of various bioactive compounds.

Table 5 Fourier-transform infrared (FTIR) spectral data of ethanolic and ethyl acetate extracts of Persea americana leaves.
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Table 6 summarizes the comparative interpretation of FT-IR spectral bands in ethanolic and ethyl acetate extracts of Persea americana leaves. The wavenumbers, assigned functional groups, and inferred phytochemical classes indicate the presence of diverse bioactive constituents including flavonoids, terpenoids, fatty acids, esters, and polyphenols in both extracts, with certain spectral differences attributed to solvent polarity.

Table 6 Comparative FT-IR spectral interpretation of ethanolic and ethyl acetate extracts of Persea americana leaves.
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Figure 1 (Related Figs. 2, 3, 4, 5, 6 and 7 and Supplementary Figures S1–S6) and Fig. 8 (Related Figs. 9, 10, 11, 12, 13, and 14 and Supplementary Figures S7–S31) show the GC-MS chromatogram and identified bioactive compounds in the ethanolic and ethyl acetate extracts of avocado (Persea americana) leaves. The x-axis displays the retention time (RT) in minutes, while the y-axis represents the relative abundance of the detected compounds. Each peak corresponds to a distinct phytochemical compound, with variations in peak height reflecting the relative concentration of each component. The chromatographic profile illustrates the diversity of bioactive compounds present in the extract, which were subsequently identified based on their retention times using an HP-5MS capillary column and matched against the NIST 14 spectral library in MassHunter software (Agilent Technologies) with a match threshold of ≥ 80%. “Expanded visual data and experimental outputs not included in the main text are available in Supplementary Figs. S1–S31.

Fig. 1
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(Related Figs. 2, 3, 4, 5, 6 and 7 and Supplementary Figures S1–S6): GC-MS Chromatogram and Identified Bioactive Compounds in the Ethanolic Extract of Persea americana Leaves.

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Fig. 2
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Representative mass spectrum and library identification for Peak 1 in the ethanol extract of Persea americana leaves. Corresponding compound identities are presented in Table 2.

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Fig. 3
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Representative mass spectrum and library identification for Peak 2 in the ethanol extract of Persea americana leaves. Corresponding compound identities are presented in Table 2.

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Fig. 4
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Representative mass spectrum and library identification for Peak 3 in the ethanol extract of Persea americana leaves. Corresponding compound identities are presented in Table 2.

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Fig. 5
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Representative mass spectrum and library identification for Peak 4 in the ethanol extract of Persea americana leaves. Corresponding compound identities are presented in Table 2.

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Fig. 6
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Representative mass spectrum and library identification for Peak 5 in the ethanol extract of Persea americana leaves. Corresponding compound identities are presented in Table 2.

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Fig. 7
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Representative mass spectrum and library identification for Peak 6 in the ethanol extract of Persea americana leaves. Corresponding compound identities are presented in Table 2. Additional data supporting peaks 7–12 in the ethanolic extract of Persea americana leaves are provided in Supplementary Figs. S1–S6. The corresponding compound identities are presented in Table 2.

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Fig. 8
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(Related Figs. 9, 10, 11, 12, 13, and 14 and Supplementary Figures S7–S31): GC-MS Chromatogram and Identified Bioactive Compounds in the Ethyl Acetate Extract of Persea americana Leaves.

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Fig. 9
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Representative mass spectrum and library identification for Peak 1 in the ethyl acetate extract of Persea americana leaves. Corresponding compound identities are presented in Table 3.

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Fig. 10
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Representative mass spectrum and library identification for Peak 2 in the ethyl acetate extract of Persea americana leaves. Corresponding compound identities are presented in Table 3.

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Fig. 11
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Representative mass spectrum and library identification for Peak 3 in the ethyl acetate extract of Persea americana leaves. Corresponding compound identities are presented in Table 3.

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Fig. 12
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Representative mass spectrum and library identification for Peak 4 in the ethyl acetate extract of Persea americana leaves. Corresponding compound identities are presented in Table 3.

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Fig. 13
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Representative mass spectrum and library identification for Peak 5 in the ethyl acetate extract of Persea americana leaves. Corresponding compound identities are presented in Table 3.

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Fig. 14
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Representative mass spectrum and library identification for Peak 6 in the ethyl acetate extract of Persea americana leaves. Corresponding compound identities are presented in Table 3. Additional data supporting peaks 7–31 in the ethyl acetate extract of Persea americana leaves are provided in Supplementary Fig. S7–S31. The corresponding compound identities are presented in Table 3.

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The FT-IR spectrum of the extracts of ethanol and ethyl acetate Persea americana (avocado) leaves is shown in Figs. 15 and 16. It displays characteristic absorption peaks corresponding to various functional groups present in the extract. The x-axis represents the wavenumber (cm⁻1), while the y-axis indicates transmittance (%). Prominent peaks observed in the spectrum suggest the presence of functional groups such as hydroxyl (−OH), carbonyl (C=O), alkene (C=C), and aromatic compounds, which are indicative of phytochemical constituents including flavonoids, alkaloids, tannins, and phenolic compounds.

Fig. 15
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FTIR Spectrum of the Ethanol Extract of Persea americana Leaves.

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Fig. 16
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FTIR Spectrum of Ethyl Acetate Extract of Persea americana Leave.

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Discussion

This study investigated the phytochemical composition of Persea americana (avocado) leaves using FT-IR and GC-MS, focusing on the influence of two solvents, ethanol and ethyl acetate, on extractable bioactive compounds. While the ethanolic extract had a higher extraction yield (8.29%) than the ethyl acetate extract (5.40%), GC-MS analysis revealed a greater number and diversity of compounds in the ethyl acetate extract (31 peaks) compared to (12 peaks) in the ethanolic extract. This underscores that extraction yield alone does not directly equate to phytochemical richness and highlights the importance of solvent polarity and analytical sensitivity in natural product research.

GC-MS is well-recognized for its sensitivity and precision in profiling volatile and semi-volatile phytochemicals, offering reliable compound identification through spectral matching and retention data7,8. In this study, the ethanolic and ethyl acetate extracts shared several major functional groups, such as hydroxyl (−OH), carbonyl (C=O), and aromatic (C=C), alkenes (C=C), methylene (C–H₂), methyl (C–H₃), and esters (C–O) as revealed by FT-IR spectroscopy, a distinct absence of C–H stretching vibrations in the ethanolic extract indicated a lower abundance of aliphatic hydrocarbon chains. This suggests a subtle variation in lipophilic content between the two extracts. In contrast, GC-MS analysis showed more pronounced qualitative differences in compound profiles; although a few compounds, such as caryophyllene and 13-Octadecenal, were present in both extracts, the majority of identified constituents were unique to each solvent. This divergence highlights the differential solubility of volatile and semi-volatile phytochemicals depending on solvent polarity, even when the overall functional group landscape appears similar1,53,54.

GC-MS profiling of ethanolic extract of Persea americana leaves (PA-ETH) identified key constituents such as 13-Octadecenal (Z) (35.9%), which has reported antimicrobial, antibacterial, and antioxidant activity.55,56,57, and Phytol (2.32%), a diterpene alcohol known for its anticancer, anti-inflammatory, antioxidant, and antimicrobial effects29,30,31. Additional compounds, linoleic acid ethyl ester, hexadecanoic acid methyl ester, and 5, 8-Octadecadienoic acid, methyl ester, are known for lipid-lowering, anti-inflammatory, antioxidant and antibacterial effects25,26,27,28,58,59,60,61,62. Notably, 13-Oxabicyclo [10.1.0] tridecane (10.69%) was present in substantial quantity but lacks reported pharmacological activity, suggesting its novelty or underexploration in phytomedicine.

In contrast, the ethyl acetate extract of Persea americana leaves (PA-ETHYL) showed a broader spectrum of bioactive compounds. These included 2,6,10-Dodecatrien-1-ol, 3,7,11-trimethyl-, (Z,E) (12.31%), Hexadecane (1.14%), 13-Tetradece-11-yn-1-ol (3.23%), and Z,Z-5,16-Octadecadien-1-ol acetate (3.59%), which have reported antimicrobial, antifungal, Hypolipidemic, anti-inflammatory, and sedative activities21,34,38,41,46,52. Eicosane (0.96%), also found in this extract, has demonstrated anticancer and analgesic properties as reported by Tiloke et al. and Okechukwu63,64. Additionally, several compounds detected in the ethyl acetate extract, such as Succinic acid, tridec-2-yn-1-yl ester (1.43%), 3-Eicosyne (1.54%), 1,8,11-Heptadecatriene, (Z,Z) (1.12%), 2-Nonadecanone, O-methyloxime (15.76%), 2-Tridecanone, O-methyloxime (2.95%), 1,5-Heptadiene, 2,6-dimethyl- (1.06%), Cyclopentane, 1-isobutylidene-3-methyl- (4.50%), 1,4-Hexadiene, 3,3,5-trimethyl- (4.54%), 7-Tetradecyne (1.12%), and E-2-Methyl-3-tetradecen-1-ol acetate (1.49%), currently lack documented pharmacological functions. These findings highlight a pool of underexplored constituents with potential therapeutic value that warrant further investigation.

Notably, caryophyllene was detected in both extracts, whereas its oxidized derivative, caryophyllene oxide, was exclusive to the ethyl acetate extract. Both compounds are well documented for their potent anti-inflammatory effects, primarily mediated via CB₂ receptor activation, as reported by Bagher et al. and Klauke et al.65,66. In addition, they exhibit anticancer and neuroprotective activities, supported by findings from Dougnon (2021) and Alghareeb et al.67,68. Similarly, 9, 12-octadecadienoic acid (Z,Z) (3.66%), identified in the ethyl acetate extract, has been associated with anti-inflammatory and cardioprotective62,69,70.

When compared with previous phytochemical studies on P. americana leaves from various geographical regions, such as Brazil (Lima et al.)11, Turkey (Uysal et al.)12, Egypt (Abd Elkader et al., Mahmoud et al.)13,53, Cameroon (Njateng et al.)14, and Nigeria (Oboh et al.)71, our findings reveal notable consistencies and distinctions. Several compounds detected in our study including, linoleic acid derivatives, and phytol, have also been reported in these studies, suggesting a shared core phytochemical profile across regions. Furthermore, FT-IR analysis confirmed overlapping functional groups such as hydroxyl (−OH), carbonyl (C=O), and aromatic (C=C), which are commonly associated with phenolics, flavonoids, and terpenoids as documented in earlier works.

However, variations in compound abundance and chemical diversity suggest that Uganda’s unique agroecological conditions may influence plant metabolite profiles. This regional variation highlights the importance of localized phytochemical profiling in validating ethnopharmacological uses and informing plant-based drug discovery.

These findings also reinforce that solvent polarity plays a critical role in shaping the phytochemical landscape of P. americana leaf extracts, with ethanol favoring antioxidant-rich compounds, and ethyl acetate yielding greater chemical diversity with broader bioactive potential.

FT-IR and GC-MS integration

FT-IR spectra supported the presence of phenolic and flavonoid-like compounds through bands corresponding to hydroxyl (−OH), carbonyl (C=O), alkene (C=C), and ester (C–O) functional groups. However, many flavonoids and phenolic acids are non-volatile and thermolabile, making them poorly detectable via GC-MS. This explains why such classes, though indicated by FT-IR, were underrepresented in the GC-MS profile. This also illustrates the strength of a dual-platform approach: FT-IR offers class-level functional group identification, while GC-MS confirms molecular identities of thermally stable components.

Implications and future directions

While GC-MS offers a robust semi-quantitative overview of extractable volatile compounds, its limitations must be acknowledged. The detected peak areas do not reflect absolute concentrations, and many non-volatile bioactives, particularly flavonoids and glycosides, remain undetected without prior derivatization. Thus, for a complete phytochemical fingerprint, future studies should incorporate high-resolution techniques such as UPLC-MS/MS or HPLC for flavonoid and polyphenol quantification.

Furthermore, bioassay-guided fractionation, in vitro/in vivo validation, and toxicological studies are needed to establish safety, dose–response, and therapeutic mechanisms. These steps will help link compound profiles to real-world bioactivity, including antidiabetic, anti-inflammatory, and antioxidant potential.

Conclusion

This study provides the first combined FT-IR and GC-MS phytochemical profiling of Persea americana leaves from Uganda, revealing a rich diversity of bioactive constituents influenced by solvent polarity. Both ethanolic and ethyl acetate extracts contained overlapping functional groups, including phenolics, flavonoids, and esters, with subtle differences in lipophilic content. While ethanol yielded a higher extract weight, ethyl acetate revealed greater chemical diversity by GC-MS, particularly in compounds associated with antioxidant, anti-inflammatory, and antimicrobial activity. These solvent-dependent variations underscore the importance of extraction strategy in natural product research.

These findings highlight the therapeutic promise of avocado leaves, an underutilized and accessible plant material with potential applications in managing oxidative stress, inflammation, and metabolic disorders. This work lays a foundation for future studies involving UPLC-MS/MS profiling, bioassay-guided isolation, and pharmacological validation, and supports the development of avocado leaf-based nutraceuticals in sustainable drug discovery.