The effect of elevated temperatures on trichomes, essential oil composition and yield of Lippia javanica : A chemometric approach

variety of natural phytochemicals to enhance their defence and survival mechanisms against harsh environmental conditions, and when these mechanisms fail, plants consequently die. We investigated the impact of high temperatures coupled with the specific duration of exposure on the yield and composition of essential oils and trichomes in leaves of Lippia javanica . Plants were exposed to increasing temperatures (25 °C to 47 °C) for different durations (48 h to 144 h). Response surface methodology was applied to assess the interaction between temperature and length of exposure on the essential oil yield, trichome length, and trichome diameter. Essential oils were recovered from the control and treated leaf samples using hydrodistillation and volatile compounds were identified through gas chromatography–mass spectrometry (GC-MS). Multivariate analysis modelling allowed different clustering patterns to be detected. That is, increasing temperatures raised the oil yield, trichome length, and diameter from 1.007 mg/100 g to 3.58 mg/100 g, 50 µm to 160 µm, and 25 µm to 60 µm, respectively. Significant chemical differences between the essential oils were confirmed by the principal component and orthogonal projections to latent structures, which identified separate clusters for the control and treated samples. The current findings indicate that L. javanica has coping mechanisms against high temperatures.


Introduction
The fundamental cause of climate change has been identified as the worldwide rise of greenhouse gases. 1,2 The increase in greenhouse gases results in increased temperatures which significantly impact the secretion of secondary metabolites in medicinal plants. 3 Hence, plants exposed to abiotic stresses show crucial variations in their secondary metabolites. 4 Moreover, plant responses to high temperatures are complex, and include deleterious effects and adaptive traits. 5 The most basic morphological traits and biological processes key to plant growth are sensitive to temperature. 3,4 As temperatures increase, the net photosynthetic rate is negatively affected, which leads to a decline in plant performance. 4 Phenology is also driven by temperature 6,7 ; thus, any moderate increase in temperature leads to the escalation in developmental processes resulting in the early blooming of plants 8 .
South Africa is one of the countries in the world that has experienced a drastic increase in temperatures over the last 40 years. 9 This means that medicinal plants are now exposed to higher temperatures than previously. Lippia javanica (Burm. F.) Spreng, commonly known as the fever tree, is a southern African indigenous medicinal plant in the Verbenaceae family and is widely distributed in the warmer eastern and northern provinces of South Africa. The shrub is used by indigenous people and herbal/traditional healers as an inexpensive, safer, and more desirable alternative for treating numerous ailments. [10][11][12] The shrub is used to treat chronic respiratory diseases 11,13,14 , skin disorders 12,15,16 , and a wide range of immune-suppressant ailments such as malaria and HIV/Aids 13,14,17 . The commonly used parts of the shrub are the leaves and stems, but sometimes roots may also be utilised. 18 Leaves and stems of L. javanica are together used as inhalants, teas, food additives or leafy vegetables, and for topical formulations 12,19 , whereas roots are used as an antidote against eye infections and food poisoning 12 . These different plant parts are commonly used because they contain high concentrations of secondary metabolites or phytochemicals, which are secreted in response to physiological and ecological pressures such as pathogens, insects, temperature extremes, and UV radiation. [20][21][22] Plant leaves have been identified as the most flexible and adaptive part of a plant in response to changing environmental conditions 23 ; thus the histology of the leaf reveals more dynamics than that of the root and stem 24,25 . Leaves of L. javanica contain trichomes which are specialised hairs on the adaxial and abaxial leaf surfaces. [25][26][27] Glandular trichomes are an essential organ in the Verbenaceae family. 26 These trichomes secrete and store phytochemicals that contain medicinal properties. [25][26][27] The density of trichomes on leaves is dependent on the environmental conditions to which the plant is exposed. 25 The harsher the environmental conditions, the greater the density of trichomes, because trichomes increase the production of essential oils, flavonoids and phenolics which increase the plasticity of the plant.
Research studies have reported that leaves of L. javanica are an excellent source of essential oils. [11][12][13][14] Chagonda and Chalchat 11 found that L. javanica has antiviral, antioxidant, antidiarrhoeal, antitrypanosomal, anti-inflammatory, antibacterial and anticonvulsant essential oil properties. The shrub has aromatic ingredients that have a range of commercially valuable properties. 12 For example, L. javanica's essential oils incorporated in candle wax provide mosquito repellent properties (repelling no less than 95% of mosquitoes) better than most available commercial products (which repel only 42% of mosquitoes). 12 This suggests that L. javanica is used as a source of revenue in both the formal and informal sectors.
Numerous studies have been conducted on the wide range of chemical extracts used in traditional healing. 21,28 Most studies have focused exclusively on the phytochemistry and trichome density of L. javanica. 19,25,26 However, no studies investigated the impact of high temperatures on the essential oil yield and related histological changes in L. javanica. Therefore, in the present study, we used a chemometric approach to evaluate the effects of temperature variation and time as abiotic agents impacting the production of essential oils in the leaves of L. javanica.

Plant material and chemicals
Samples of L. javanica (grown for ~2 years) were obtained from Mountain Herb Estate in Hartbeespoort (25.7236° S, 27.9653° E) and maintained in the greenhouse at the University of the Witwatersrand (26.1929° S, 28.0305° E), South Africa. Before moving samples into the climate test incubator (Conviron -CMP6010, Canada), they were watered twice a day for a month and were kept in the greenhouse at 25 °C/20 °C (day and night simulation). All the chemicals used in this investigation were of analytical grade. Hexane and anhydrous sodium sulfate were purchased from Merck (Johannesburg, South Africa).  (Table 1).

Extraction of essential oils
Essential oils were extracted from the air-dried harvested leaves of the control and treated samples using a Clevenger-type apparatus for the hydrodistillation process. 27 A volume of 1 L of water was added to 300 g of leaf samples for 4 h. The recovered essential oil was then isolated and dried with anhydrous sodium sulfate, filtered through a small cottonwool plug, and shifted to a pre-weighed amber vial. 27 The total yield was calculated using the formula below:

Essential oil analysis (GC-MS/FID)
Before injection into the chromatogram, 15% (v/v) of essential oil samples in hexane were prepared before the analysis. They were scrutinised using a Hewlett-Packard G1800A GCD system gas chromatograph (GC) combined with flame-ionisation detection (FID) and a mass spectrometry (MS) detector. An Innowax FSC column (60 m × 0.25 mm diameter) was utilised, and helium was the carrier gas, with a 0.8 mL/min flow rate. 27 The GC-MS was maintained at an oven temperature of 60 °C for the first 10 min, and then the temperature was programmed to rise to 220 °C at a rate of 10 °C/min, and it was kept constant at 220 °C for 10 min. Then again, temperature was programmed to rise to 240 °C at a rate of 10 °C/min. Split flow was adjusted to 50 mL/min, whereas the injector and detector temperatures were adjusted to 250 °C. The mass spectra/ionisation was taken at 70 eV, and the mass range was from 35 m/z to 425 m/z. Qualitative characterisation of L. javanica essential oil samples was performed using a GC-MS.
The US National Institute of Standards and Technology (NIST) Mass Spectral Library was used to characterise the shrub's essential oil compounds. Using literature and databases, essential oil components were tentatively identified by comparing the retention indices, molecular weight, and mass fragmentation patterns. All matches reported in our study had match quality >90% with respect to the experimental spectrum. The first step was a spectrum comparison in all the matches, which offers a range of potential matches. The second step was a postsearch filter which rejected retention indices inconsistent with indices of unknown components. Using these calculated retention indices and interactive search filters built into the library decreases the chances of incorrect identifications.

Unsupervised and supervised machine learning exploratory approach
The complex total ion chromatogram data set (Supplementary figure 2) obtained from the essential oil GC-MS analysis was processed using commercial Leco Chroma TOF software. Total ion chromatogram data were aligned, and the baseline was corrected and smoothed. A MS Excel spreadsheet including all the main ion fragments for each peak was made and used for further assessment through SIMCA-17 (Umetrics AB, Malmo, Sweden). Various scaling approaches were applied before creating the unsupervised principal component (PCA) model. The PCA model was then used to investigate the relationship between variables and correlation for each variable to the principal components. The score plot was employed to identify similarity between individual clusters. The graphical output of this clustering tool shows the group-inclusive associations between classes and the value of the clustering criterion related to each treatment of the plant. 29 The essential oils variability obtained through the clusters on the PCA scores plot was further assessed by the supervised orthogonal projections to latent structures discriminant analysis (OPLS-DA) model.
The samples were assigned classes based on the treatment of the plants.
OPLS-DA loadings plots identified chemical markers driving the observed variability within the control and treated samples. The data set was randomly subdivided into the testing set (30%) and training set (70%). The OPLS-DA model was developed using the training data set, whereas the testing data set was used for cross-validation, validation, and prediction ability of the model. 30 The variability of the essential oil compounds within the control and treated groups were identified using OPLS-DA scores and S-plots.
A multiple linear regression was applied to calculate the fitting model and response surface. The R 2 and Q 2 values indicate the adequacy of the models (where R 2 shows the model fit and Q 2 shows an estimate of the future prediction precision), predicted vs. observed plot, and coefficient plots. A partial least squares regression was employed to assess the response surface and fitting model response surface. The adequacy of the models was evaluated using Q 2 (an estimate of the future prediction precision) and R 2 (the model fit values).

Response surface methodology optimisation
The response surface methodology was used to assess the impact of temperature and time on the yield of essential oils and related histological modification of L. javanica. The model was achieved based on the experimental design defined by the central composite design. These experiments were carried out at all possible level combinations of temperature and time, and the response was given as the essential oil yield, trichome diameter, and trichome height (Table 1) The coefficients plot ( Figure 2) revealed that high temperatures significantly affect the yield of essential oils, trichome height, and trichome diameter (p=0.002); in contrast, time does not significantly influence plant stress. The increase in temperature from 25 °C to 47 °C increased essential oil yield, trichome length, and trichome diameter from 1.007 mg/100 g to 3.58 mg/100 g, 50 µm to 160 µm, and 25 µm to 60 µm, respectively. This finding suggests that an increase in essential oil secretion, trichome height and diameter is a defence mechanism for plants exposed to environmental stress. Our data show that time did not affect plant stress; nonetheless, it is well recognised that the longer a plant is exposed to environmental stress, the more harmful the conditions are to the plant. Several studies have shown that the increase in glandular trichome length and diameter are directly correlated to the yield of essential oils produced by the plant (Supplementary figure 1). 31,32 Moreover, other studies have reported that both essential oil yield and the quality of aromatic compounds are primarily affected by environmental factors such as altitude, light intensity, and seasonality. 11,28,33 Our findings are consistent with these studies because exposing L. javanica to high temperatures increased the length and diameter of trichomes, which was associated with the increase in essential oil yield (2.67% more than the control at 47 °C/144 h).
Our results clearly show that the production of essential oils in L. javanica is temperature sensitive (Supplementary figure 1) and that the increase in the secretion of essential oils is an indicator of environmental stress. However, it is unclear how these environmental factors affect the quality of essential oils. Al-Gabbiesh et al. 34 stated that plants exposed to environmental stresses reveal a higher concentration and yield of essential oils than those cultivated under ambient conditions. In this context, however, exposure to environmental stresses significantly reduces plant growth because carbon meant to be allocated to growth is redirected to the production of secondary metabolites for plant survival. 4,34 Therefore, environmental stress could increase the toxicity of volatile compounds, which may be harmful to humans. The toxicity level may also depend on the duration of exposure to environmental stress.

Characterisation and identification of essential oils by GC-MS
The GC-MS analysis yielded 50 essential oil components (Supplementary  table 1). The essential oils extracted from the control and treated samples displayed differences in their chemical composition. The primary essential oils found in the control samples were linalool, carvone, piperitenone and tagetenone, while the treated samples were contained eucalyptol, camphor, fenchone eucalyptol, p-cymene, caryophyllene and terpinen-4-ol. The largest relative peak area of the major compounds revealed significant chemical variations within the control and treated samples (Supplementary figure 3).
All samples fell within the Hotelling's T 2 ellipse on the scores plot (Figure 3), suggesting the nonexistence of strong outliers, and therefore all data were included. The total variation across the data was 99.7% (R 2 X cum = 0.997), whereas Q 2 cum was 0.987, indicating a good model. The scores scatter plot of PC1 against PC2 (Figure 4) shows four clusters corresponding to the control and treatments. About 56.8% and 31.1% of the sample variability were explained by PC1 and PC2, respectively ( Table 2). An OPLS-DA model was created from the data for the control and treated samples. Centre-scaled models generated the best statistics for the selected data set compared to other scaling approaches ( Table 2).    (Figure 4), confirming the chemical variation of essential oils found in L. javanica at elevated temperatures. Major essential oil constituents (linalool, -(-) carvone, tagetenone and piperitenone) in the control disappeared in the high temperature treatments ( Figure 5). However, eucalyptol, camphor, and p-cymene were major essential oils not previously present in the control and were produced when plants were exposed to high temperatures.
Several essential oil constituents are not produced at certain temperature ranges; thus, temperature alterations significantly impact the essential oil composition of plants. A study by Lee and Ding 35 found that the specific ratio of essential oil constituents determines the therapeutic and wellness-enhancing properties of the oil. However, a study by Nakatsu et al. 36 suggested that, although there are differences in the composition of essential oils of various plants, there is considerable overlap in their overall properties. For example, Tetradenia riparia and Virola surinamensis have different essential oil profiles, but they are both reported to treat malaria symptoms. 34 Therefore, the changes observed in the oil constituents of L. javanica after exposure to high temperatures may not suggest changes in the biological activity of the shrub. More research, however, is required to ascertain any changes in the biological activity of L. javanica and the implications of the additional compounds secreted in response to high temperatures.

Conclusion
Temperature was the most critical factor influencing the production of essential oils, trichome length and trichome diameter in L. javanica. A significant degree of chemical variation was evident between the control and treated samples. Four essential oil compounds successfully identified within the control were not present in the treated samples and three compounds detected in the treated samples were absent in the control. This variation suggests resistance against high temperatures and January/February 2023 other physiological and ecological pressures. The increase in defence essential oil compounds could also indicate an increase in the medicinal properties of the shrub in treating various ailments. More studies should be conducted to investigate the pharmacological activities and toxicity levels of L. javanica exposed to high temperatures in order to elucidate any changes in the medicinal properties of the shrub.