Botanical gardens play an increasingly important role in supporting the Sustainable Development Goals by linking plant diversity with broader themes of sustainability across terrestrial ecosystems (Smith et al., 2018). Orman Botanical Garden, established in 1875, is among the most prominent and historically significant botanical gardens in Egypt, covering an area of approximately 11.76 hectares (Diwan et al., 2004). Due to its ecological characteristics and social functions, it is also considered an urban forest. Urban forests, as noted by Nowak and Dwyer (Nowak and Dwyer, 2007), contribute to biodiversity conservation, provide recreational and social spaces, improve air quality, and enhance the visual appeal of urban settings. Among the six botanical gardens assessed in Egypt, Orman Garden demonstrated the highest levels of species richness and diversity (Hamdy et al., 2007). Detailed knowledge of the composition and structural characteristics of tree species in such gardens provides essential insights for biodiversity conservation. Understanding these ecological aspects is crucial for evaluating the long-term sustainability of conservation efforts and informing the management of urban forest ecosystems (Kacholi, 2014).

Secondary metabolites are a diverse group of bioactive organic compounds produced by plants that are not directly involved in primary metabolic processes such as growth and reproduction. Instead, they play crucial ecological and physiological roles, including defense against herbivores and pathogens, attraction of pollinators, and adaptation to abiotic stresses (Yang et al., 2018; Isah, 2019). These metabolites include alkaloids, flavonoids, terpenoids, phenolics, tannins, and glycosides, many of which are well-documented for their pharmacological relevance. Several of these compounds exhibit strong antioxidant, antimicrobial, anti-inflammatory, anticancer, and hepatoprotective activities, making them of significant interest in pharmaceutical and nutraceutical research (Akula and Ravishankar, 2011; Isah, 2019). Understanding the diversity and physiological basis of these compounds is therefore essential for identifying and prioritizing medicinally important plants, especially when applying non-destructive techniques such as hyperspectral remote sensing to screen for bioactive potential.

About 800 species of woody plants, including trees, shrubs, and vines, that are members of the Moraceae family, are found in the genus Ficus. About 100 of these species are native to Africa and the adjacent islands, and they are spread throughout different tropical ecosystems (Aweke, 1979). Multipurpose plants like ficus are commonly employed in rural development (Mohamed et al., 2018; Sandhu et al., 2023). They can provide food, fuel, timber, medication, and raw materials for some chemical companies. Additionally, they are visually pleasing enough to be employed as ornamental plants, with each species designated for its appropriate role in the landscape, such as screen, structure, group, specimen, avenue, shelter, shade, and hedge (Brickell, 2019). There are about 800 species of woody plants in the genus Ficus, including trees, shrubs, and vines, pertaining to the family Moraceae. About 100 species are native to Africa and neighboring islands, and the rest are spread throughout other tropical ecosystems. During the reign of Mohamed Ali Pasha, numerous Ficus spp. were introduced to Egyptian territory (Hamdy et al., 2007). They were positioned next to palaces, water canals, and the Nile River. They are extensively used for adornment in gardens, roadways, and indoor spaces for some species that have adapted well to Egyptian conditions.

Ficus spp., including F. religiosa, F. racemosa, and F. benghalensis, are essential in a lot of traditional and Ayurvedic medicine formulas. These species are recognized for their carminative, astringent, anti-inflammatory, antioxidant, and anticancer properties. Their bark, leaves, fruits, and latex are also thought to be very effective in treating a variety of organic molecules produced via metabolic pathways. These organic molecules are classified into primary metabolites (Joseph and Raj, 2010; Rasool et al., 2023).

The family Moringaceae comprises fast-growing, drought-tolerant flowering plants that have been highly valued since ancient times by civilizations such as the Egyptians, Greeks, and Romans for their nutritional and medicinal benefits. Within this family, Moringa stands as the sole genus, encompassing approximately 33 species, with four species widely recognized: M. oleifera, M. ovalifolia, M. peregrina, and M. stenopetala (Mabberley, 1987). These species predominantly thrive in semi-arid, tropical, and subtropical regions, including the Horn of Africa, Madagascar, southwestern parts of Africa, tropical Asia, and extending westward into Egypt. They are found across nearly all phytogeographical zones, as reported by National Research Council et al. (1996) and Mridha (2015).

Moringa spp. play a significant medico-socioeconomic role, functioning as natural bioreactors that generate a variety of organic molecules through metabolic pathways. These metabolites are classified into primary metabolites—such as proteins, carbohydrates, and lipids—and secondary metabolites, including alkaloids, carotenoids, moringine, moringinine, phytoestrogens, caffeoylquinic acids, tannins, phytosterols, terpenoids, glycosides, flavonoids, and phenolic compounds (Anwar et al., 2007).

Hyperspectral remote sensing technology is an essential instrument that allows the collection of detailed data over a wide range of electromagnetic frequencies. The goal of the work under evaluation is to uncover small differences between Ficus species based on their spectral characteristics by utilizing hyperspectral remote sensing. Simultaneously, this study examines these species’ morphological characteristics, which are crucial elements that impact their methods of adaptation and interactions with their environments (Wang et al., 2023).

Plant species’ physiology, morphology, and anatomical structure are among the elements that influence their spectral properties (Kycko et al., 2014; Jarocińska et al., 2016). The visible-infrared (VNIR) and shortwave infrared (SWIR) spectral profiles of leaves show differences that are linked to pigments such as carotenoids and chlorophyll as well as water content and dry matter content (Feret et al., 2008). Even closely related species differ in the reflectance characteristics of their vegetation due to differences in pigment and water content, as well as structural changes in their canopies and leaves. Accordingly, species identification is made easier by the uniqueness of these spectral characteristics (Thenkabail et al., 2000). Monitoring changes in ecosystems depends heavily on how plants interact with the electromagnetic spectrum through absorption, transmission, and reflection.

The spectral reflectance of plant tissues is largely governed by biochemical and structural components, particularly pigments such as chlorophylls, carotenoids, and anthocyanins. These pigments are often involved in the biosynthesis of secondary metabolites, which play a central role in plant defence, stress response, and pharmacological potential (Gitelson et al., 2001; Isah, 2019). Reflectance in specific spectral regions—especially the visible, red-edge, and NIR—can therefore serve as an indirect indicator of the physiological state and biochemical richness of plants, making hyperspectral indices a useful tool in medicinal plant screening (Sims and Gamon, 2002; Colovic et al., 2022).

The similarity in reflectance patterns in the visible region among species likely reflects shared chlorophyll absorption at approximately 650 nm (red) and in the blue range. In contrast, variation in NIR and SWIR may reflect differences in leaf structure, water content, or physiological status. The distinctive spectral behavior of species such as F. microcarpa and F. benghalensis demonstrates the strength of hyperspectral indices in species-level discrimination.

Remote sensing, particularly hyperspectral sensing, captures the reflectance of electromagnetic radiation from plant surfaces, which is strongly influenced by morphological and physiological characteristics of vegetation. Leaf pigments such as chlorophylls and carotenoids absorb light in the blue and red regions, while cellular structure and internal water content affect reflectance in the near-infrared (NIR) and shortwave infrared (SWIR) regions (Ustin et al., 2004; Clevers et al., 2011). Variations in leaf thickness, surface texture, and internal mesophyll structure produce distinct spectral signatures that can be used to assess plant health, species identity, and biochemical composition (Asner and Martin, 2008; Homolová et al., 2013). Thus, remote sensing provides a non-destructive, rapid method to evaluate vegetation traits related to both structure and function.

In order to evaluate vegetation health, classify land cover, examine phenology, identify changes in climate and land use, and track drought conditions, vegetation indices were developed (Padilla et al., 2011). In remote sensing, different vegetation indices have been developed. The Normalized Difference Vegetation Index (NDVI) is a prominent and widely used index in international environmental and climatic change research (Bhandari et al., 2012). The ratio difference between the recorded vegetation reflectance values in the red and near-infrared bands is what gives rise to the NDVI.

Given the medicinal importance of Ficus spp. and Moringa spp. and the potential of hyperspectral techniques in plant characterization, this study aims to explore how spectral indices can support species discrimination and health assessment. Additionally, the study aims to enhance taxonomic understanding of selected Ficus spp. and Moringa spp. by combining detailed morphological observations with hyperspectral reflectance measurements. It explores the extent to which spectral profiles correspond with observable physical traits across the studied taxa and assesses their relevance to species differentiation. The analysis focuses on identifying distinct spectral signatures and informative wavelength regions that contribute to species discrimination. Moreover, by linking spectral indices to physiological parameters, the study examines the potential of hyperspectral data as a proxy for evaluating plant health and inferring medicinal relevance. This integrated approach supports the non-destructive classification and prioritization of medicinally important plant species.

To achieve the outlined objectives, a multi-step methodology was adopted combining field-based morphological measurements with hyperspectral reflectance analysis.

The following section presents the variation in spectral indices and morphological features across the examined taxa, highlighting statistically significant patterns related to their physiological and medicinal characteristics.

While the previous section detailed the quantitative spectral differences among taxa, this section interprets those patterns in the context of plant structure and known medicinal attributes. Morphological characteristics, particularly leaf shape, margin, and apex, demonstrated marked differences among the species, supporting their taxonomic distinctiveness and aiding in spectral discrimination. For example, F. auriculata exhibited large, round-ovate leaves with a high single leaf area (460.5 cm²), contrasting sharply with the smaller, ovate leaves of F. microcarpa (35 cm²). These physical differences, alongside variations in bark color and growth form (tree vs. shrub), are important taxonomic tools.

Spectral reflectance of plant leaves is the absorption occurring at 650 nm in the visible red range. This absorption is mostly caused by chlorophyll pigments found in the green-leaf chloroplasts, which are found in the Palisade leaf’s outer layers. Furthermore, these spectra differ from white ones by having a similar degree of absorption in the blue band. As such, the majority of visible wavelength reflectance is found in the green area of the spectrum. According to Gamal et al. (2020), Khdery et al. (2021), Khdery et al. (2023), and Yones et al. (2024), given that all the samples are vegetative samples, the spectral reflectance pattern of the taxa under investigation, as depicted in Figure 2, revealed the same trend in spectrum reflectance.

The results show that every single plant species is highly compatible with the overall spectral signature, especially in different spectral regions like the visible and infrared light. Interestingly, it was found that, in comparison to the SWIR1 region, the SWIR II region had less reflectance (Aboelghar and Khdery, 2017).

The findings suggest that SWIR II wavelengths are particularly effective in discriminating among Ficus species, aligning with previous studies (Aboelghar et al., 2017). The visible region, especially the blue band, offered limited discriminatory power. Notably, species such as F. hispida and F. benjamina demonstrated characteristic high reflectance in the NIR region, which may reflect structural or biochemical traits.

Both Moringa spp. exhibited typical spectral behavior associated with healthy green vegetation, including low reflectance in the visible region (400–700 nm), a pronounced red edge near 700 nm, and strong reflectance in the NIR range.

Notably, distinct water absorption features were observed around 1,450 nm, 1,950 nm, and 2,500 nm, consistent with known water-related absorption bands. These differences between M. oleifera and M. peregrina in the NIR and SWIR regions may reflect variations in internal leaf structure, water content, or pigment concentration.

The spectral characteristics of plant species are influenced by their physiological, morphological, and anatomical traits (Gitelson et al., 2024). Species with large, thick, and dark leaves, such as F. benghalensis, exhibited higher NDVI and chlorophyll content, consistent with strong vegetative health and photosynthetic capacity. These findings align with previous work by Apan et al. (2003) and Uto and Kosugi (2012), who demonstrated the significant role of structural and pigment properties in shaping vegetation spectra.

The moderate NDVI and SR values recorded for F. asperrima may reflect average chlorophyll content and light absorption efficiency at the leaf level, suggesting moderate physiological performance relative to other Ficus species examined. Low PRI and MCARI, may indicate limited photosynthetic performance and average vegetation density. The negative ARI2 value suggests minimal anthocyanin presence, which could correlate with its relatively lower traditional medicinal use, such as in wound healing.

In contrast, F. racemosa displayed high MCARI and ARI2 values, indicating strong pigment concentration and photosynthetic activity. The moderate PRI and NDRE values suggest a balanced nitrogen status and moderate physiological stress. These spectral traits are in line with its well-documented anti-inflammatory and astringent properties in ethno medicine (Bhivasane et al., 2024). These spectral features are consistent with the species’ known pharmacological relevance; however, no direct link between these indices and specific medicinal functions is implied (Patel et al., 2023).

Our findings revealed significant correlations between spectral indices such as NDVI, MCARI, and ARI2 and the estimated medicinal score. These indices are known to reflect chlorophyll content, anthocyanin levels, and overall metabolic activity, which are closely tied to the presence of bioactive secondary metabolites (Gamon et al., 1992; Delegido et al., 2013). This supports previous studies suggesting that hyperspectral features can be used as non-destructive proxies for estimating the pharmacological relevance of plant species.

Notably, F. benghalensis demonstrated exceptional NDVI (0.945) and SR (39.3), along with high ARI2 (0.30), MCARI (0.51), and NDRE (0.61), indicative of robust pigment accumulation—including anthocyanins, chlorophyll, and nitrogen-associated pigments—suggesting strong physiological performance (Mascarini et al., 2006). These reflect its medicinal value in wound healing, antimicrobial, and antidiabetic applications.

F. benjamina exhibited high SR (25.47), CRI (24.91), and NDRE (0.55), indicating elevated structural and pigment-related reflectance features. Conversely, F. religiosa presented lower NDVI (0.104) and PRI (0.058), possibly suggesting environmental stress or reduced chlorophyll content. This trend was mirrored in its spectral indices, including weaker PSRI and CRI, making it less potent from a spectral and medicinal perspective (Khdery, 2020; Khdery et al., 2021; Khdery et al., 2023; Yones et al., 2019). The low NDVI and RENDVI values observed in F. religiosa may reflect poor chlorophyll content and possible physiological stress. Despite this, the species continues to be valued in herbal medicine, potentially due to the presence of non-photosynthetic phytochemicals (Dmitriev et al., 2023).

In F. auriculata, elevated CRI and PSRI values suggest strong carotenoid activity and potential onset of senescence. Moderate ARI2 and NDRE levels may indicate some antioxidant potential and nitrogen assimilation.

The low MCARI and negative ARI2 in F. hispida point to limited chlorophyll and anthocyanin content, possibly reflecting lower metabolic or photosynthetic activity in this species.

The red-edge indices (RENDVI and Clred-edge) further supported this differentiation, with healthier species showing higher values. This is in line with the red-edge’s established sensitivity to chlorophyll concentration and stress levels (Maxwell and Johnson, 2000; Zarco-Tejada et al., 2003).

Linear Discriminant Analysis (LDA) identified unique wavelength ranges specific to several Ficus species—especially F. hispida, F. racemosa, and F. religiosa—reinforcing the potential for hyperspectral separation of species with both taxonomic and pharmacological importance. These findings confirm that hyperspectral indices, when integrated with morphological features, provide a powerful tool for assessing medicinal plant potential among Ficus species (Khdery et al., 2021; Khdery et al., 2023). The differences observed in the reflectance spectra between M. peregrina and M. oleifera can be attributed to variations in leaf structure, water content, and pigment concentration. The higher reflectance values of M. oleifera in the NIR region suggest a denser or more scattering internal leaf structure compared to M. peregrina. This is consistent with the known characteristics of M. oleifera, which generally has thicker leaves and a higher water retention capacity.

Distinct absorption features around 1,450 nm, 1,950 nm, and 2,500 nm correspond to water absorption bands, and the depth of these features suggests slightly lower water content in M. peregrina. In the visible region, both species show low reflectance due to chlorophyll absorption, but M. oleifera reflects slightly more in the green (~550 nm), indicating higher chlorophyll content, consistent with its antioxidant and anti-inflammatory properties (AbdAlla et al., 2023; Tshabalala et al., 2021; Rébufa et al., 2017).

The spectral profile of M. oleifera, characterized by high NDVI, SR, reflects strong vegetative vigor and carotenoid presence. Moderate MCARI and high NDRE/RENDVI values may indicate robust chlorophyll expression and nitrogen content, supporting the species’ efficiency in photosynthesis and metabolism. These traits are consistent with its documented pharmacological applications in antioxidant defence and metabolic regulation.

In contrast, M. peregrina exhibited lower spectral index values across most parameters. Despite this, the negative PSRI and modest NDWI suggest healthy and hydrated foliage. Although the overall spectral intensity is lower than that of M. oleifera, M. peregrina still retains significance in specific traditional uses such as dermatological and anti-inflammatory treatments.

Morphologically, M. oleifera has darker, tripinnate leaves and a broader vegetation, contributing to stronger NIR reflectance, while M. peregrina has smaller, bipinnate, waxy leaves that may reduce internal scattering. This structure aligns with its adaptation to arid environments, as supported by the shallower water absorption features and higher NDWI (Taha, 2016).

Vegetation indices further confirm these differences: M. oleifera shows high NDVI, and NDRE values, consistent with superior pigment content and photosynthetic capacity, aligning with its broad therapeutic uses including hepatoprotection and metabolic regulation. M. peregrina, though lower in most indices, shows decent water retention and pigment signals, which support its application in dermatological and traditional remedies (Cheng et al., 2020). Spectral analysis of M. oleifera and M. peregrina indicated marked physiological divergence. M. oleifera exhibited high NDVI (0.487), SR (7.36) and NDRE (0.498), which are known to correlate with increased chlorophyll, carotenoid, and nitrogen content, respectively (Peñuelas et al., 1993; Gitelson et al., 2003; Zarco-Tejada et al., 2003; Peñuelas et al., 1995), as also outlined in Table 4. These parameters are consistent with its well-documented roles in antioxidant, hepatoprotective, and antidiabetic therapies (Dung et al., 2023).

These findings demonstrate that hyperspectral indices effectively distinguish Moringa spp. based on their physiological and structural features. While spectral traits showed potential associations with literature-based medicinal relevance, further targeted biochemical analyses are needed to establish direct pharmacological links. Overall, the vegetation indices corroborate the spectral reflectance results, highlighting that M. oleifera exhibits superior photosynthetic activity, pigment content, and structural health compared to Moringa peregrina, while M. peregrina may possess slight advantages in water retention under dry conditions.

The observed correlations between spectral indices and medicinal scores suggest preliminary associations between physiological activity and traditional medicinal relevance. While the correlation coefficients were moderate, they indicate that certain hyperspectral traits may reflect underlying biochemical or pharmacological properties, supporting their utility in exploratory screening applications. NDVI, which reflects chlorophyll density and biomass, showed a clear positive correlation with medicinal potential, supporting findings by Kizilgeci et al. (2021) that associate high NDVI with metabolic activity and secondary metabolite synthesis. MCARI, which emphasizes chlorophyll absorption in the red region, also correlated well with medicinal score, reinforcing its usefulness for detecting physiologically active plants (Gitelson et al., 2003). The strong association of RENDVI, which is sensitive to vegetation structure and red-edge changes, further validates its application in identifying medicinally significant species (Delegido et al., 2013; Colovic et al., 2022).

On the other hand, ARI2 and NDRE did not correlate strongly with medicinal value. These indices, although effective in assessing stress-related pigments and nitrogen status, may not reflect the specific biochemical profiles responsible for pharmacological effects. Similarly, PSRI’s negative correlation may be due to its association with senescence, which often reduces the biosynthesis of active compounds. These findings highlight the importance of selecting spectral indices aligned with physiological markers of medicinal relevance. NDVI, MCARI, and RENDVI emerge as priority tools for remote sensing-based medicinal plant screening.

It is worth noting that the current sampling strategy prioritized interspecific variation under controlled conditions. Future work with broader replication per species will allow intra-species variability assessments.

Also, to further enhance the interpretation of spectral–medicinal relationships, future work is encouraged to include direct phytochemical quantification and bioactivity assays. These analyses would complement the current literature-based scoring framework and provide stronger empirical validation for the use of hyperspectral indices in assessing medicinal potential.

Findings are reinforced by recent studies demonstrating the utility of hyperspectral remote sensing as a proxy for detecting plant biochemical traits relevant to medicinal potential. Boonrat et al. (2025) applied hyperspectral imaging combined with machine learning to dynamically map total phenolic and flavonoid contents in sunflower microgreens, achieving R² values up to 0.97 for flavonoids—highlighting strong spectral correlations with secondary metabolite levels. Song and Wang (2022) developed a hyperspectral index that effectively tracks seasonal changes in the chlorophyll-to-carotenoid ratio in deciduous forests, showing strong relationships with field-measured pigment ratios. This study contributes to the growing body of literature advocating for non-destructive, spectral-based approaches to screen and prioritize medicinal plants for conservation and pharmacological research.

Spectral variation among species may reflect ecological adaptations, such as differences in leaf structure, water use, or stress tolerance. High NIR and red-edge reflectance often indicate traits linked to resilience and productivity. Such traits can guide conservation priorities, especially for species adapted to harsh or shifting environments (Corbin et al., 2025).

Also, Spectral variation among the studied species revealed insights into their ecological adaptations. For example, differences in NDWI and PRI values suggest varying water use strategies and photoprotective mechanisms, respectively. Such traits are particularly relevant in arid and semi-arid regions where physiological resilience is key to survival. These variations can serve as functional indicators for prioritizing species in conservation planning or selecting candidates for climate-resilient agriculture. Recent research confirms that hyperspectral data can effectively capture such traits and predict species responses to environmental stressors, thereby supporting their use in ecological monitoring and conservation strategies (Asner et al., 2015; Schneider et al., 2017).

This study demonstrates the utility of hyperspectral indices for taxonomic discrimination of plant species. While spectral traits were analyzed in relation to literature-derived medicinal relevance scores, further pharmacological and biochemical assays are required to substantiate any medicinal claims. This study demonstrated the effectiveness of integrating hyperspectral remote sensing with morphological analysis as a non-invasive approach for identifying medicinally relevant Ficus spp. and Moringa spp. based on their physiological Vigor and phytochemical potential. The reflectance spectra across the 350–2,500 nm range revealed species-specific spectral patterns, with the Near-Infrared (NIR) and Short-Wave Infrared (SWIR) regions being the most informative for spectral discrimination.

Among the Ficus spp., F. benghalensis and F. racemosa exhibited high NDVI, SR, and ARI2 values, indicating strong photosynthetic activity and accumulation of key pigments such as chlorophylls, carotenoids, and anthocyanins. These pigment profiles are consistent with physiological vigor and may be indirectly associated with the species’ reported medicinal properties, such as antimicrobial, wound healing, and anti-diabetic applications. F. benjamina also showed high reflectance in chlorophyll-and nitrogen-sensitive indices, supporting its documented antioxidant and anti-inflammatory roles. In contrast, F. religiosa displayed the lowest NDVI and NIR reflectance, suggesting reduced physiological vitality and possible environmental stress, consistent with its relatively limited pigment-based medicinal value. For the Moringa spp., M. oleifera consistently demonstrated higher NIR reflectance, NDVI, SR, and NDRE values compared to M. peregrina, reflecting greater leaf density, chlorophyll and carotenoid content, and nitrogen assimilation. These spectral traits are related strongly with its well-established pharmacological functions including antioxidant, hepatoprotective, and metabolic regulation. Conversely, M. peregrina, although spectrally less vigorous, showed spectral signals consistent with its drought tolerance and niche medicinal uses in dermatological and anti-inflammatory treatments. Morphologically, species with broader, darker leaves—such as F. benghalensis and M. oleifera—exhibited stronger spectral signatures, while species with narrower or waxy leaves—such as F. microcarpa and M. peregrina—reflected weaker signals. Absorption features near 1,450 nm, 1,950 nm, and 2,500 nm further revealed interspecific differences in leaf water content, particularly between the Moringa spp.

Vegetation indices such as NDVI, PSRI, MCARI, and RE-NDVI were significantly correlated with morphological traits like leaf area, apex shape, and pigmentation across all species. These findings reinforce the utility of hyperspectral imaging, combined with morphological observation, as a non-destructive and precise approach for identifying medicinally relevant plant species and prioritizing them for further pharmacological investigation.