Mineral Composition of Lippia alba (Mill.) N.E. Brown Leaves

Neste trabalho descreve-se a composição mineral das folhas de Lippia alba (Mill.) que são utilizadas na preparação de chá utilizado na medicina popular. Assim, as folhas da espécie foram coletadas em cidades brasileiras e as amostras foram digeridas usando ácido nítrico e peróxido de hidrogênio em placa aquecedora e, em seguida, foram analisadas empregando espectrometria de emissão óptica com plasma acoplado indutivamente (ICP OES). Para avaliação da exatidão foi utilizado o material de referência certificado, folhas de maçã NIST SRM 1515. Os resultados demonstraram que cálcio, magnésio e fósforo têm conteúdo médio de 1.950, 2.856 e 2.335 mg 100 g-1 e variações de concentrações de 767-3.887, 314-8.591 e 247-9.214 mg 100 g-1, respectivamente. Os micro-elementos, bário, zinco, cobre, ferro, manganês e níquel têm conteúdos médios de 2,16; 2,95; 0,94; 11,2; 4,25 e 0,09 mg 100 g-1, para variações de concentrações de 0,66-7,1; 1,35-6,3; 0,33-1,7; 0,98-34; 0.82-7,4 e 0,03-0,15 mg 100 g-1, respectivamente. Os dados foram também avaliados usando análise de componentes principais (PCA).


Introduction
The use of native plants as herbal medicine is a tradition in Brazilian culture.The use of plants began long ago, probably originating with indigenous tribes and slaves.The latter group likely adapted their native recipes to incorporate local plants and procedures.Many of these plants are still used as leaf infusions and in other medicinal preparations.][3][4][5][6] Lippia alba (Mill.)N.E.Brown, popularly known as "erva-cidreira", is an aromatic shrub that belongs to the Verbenaceae family.The genus Lippia encompasses about 200 species that grow in the wild in Central and South America, and in Africa.L. alba possesses sedative properties; it has also been used as an infusion, such as tea in Brazilian folk medicine, against intestinal and gastric illnesses. 7Interestingly, the composition of L. alba essential oils showed variations related to the part of the plant employed in the distillation, the plant's state of development and its geographic location, the characteristics of the soil, the climate, and other local conditions. 8From these reports, at least four L. alba chemotypes have been identified in terms of the main monoterpene constituents in the essential oils; each of these chemotypes has a distinct odor. 8,9One of the chemotypes is characterized by a high content of 1,8-cineole, limonene, and carvone; the second has a limonene, carvone, and myrcene signature; the third is represented mainly by geranial and neral, and the fourth is rich in linalool. 8,9Although an extensive body of work dealing with essential oils of L. alba exists, there have been no studies examining the relative presence of metals in the different chemotypes of this species so far.
.In a recent paper, 20 sixteen trace metallic analytes (Ba, Ca, Ce, Co, Cr, Cu, Fe, K, La, Mg, Mn, Na, Ni, P, Sr and Zn) in acid digests of herbal teas were determined.The data were subjected to chemometric evaluation in an attempt to classify the herbal tea samples.The plants were classified into five groups by principal component analysis (PCA).
Principal component analysis is a well-known, unsupervised, exploratory technique used for visualizing information in large data sets.PCA can be used to simplify data by reducing the number of variables into a smaller number of orthogonal variables (principal components, PCs).The PCs are linear combinations of the original variables and maximize the variability contained within them, thereby displaying most of the original variability in a smaller number of dimensions.Each variable has a loading on each PC.The loading reflects both how much the variable contributed to that PC and how well that PC takes into account the variation of that variable over the data points.Thus, the graphical presentation of the pair-wise components (score plots) allows the natural grouping of the samples to be observed, indicating the similarity among the samples and allowing different groups of samples to be identified.The loadings can be used to understand how much each variable contributes to the meaningful variation in the data and to interpret variable relationships.
In this paper, the leaf mineral content (Ba, Zn, Cu, Fe, Mn, Ni, Ca, Mg and P) of 28 L. alba specimens were evaluated; of these 27 samples were collected in the Bahia State (Brazil) and one was from the city of Rio de Janeiro.The data were subjected to principal component analysis to verify eventual similarities among the samples as well as to determine correlations between the elements and outliers detection.

Instrumentation
An inductively coupled plasma optical emission spectrometer with an axially viewed configuration (ICP OES, VISTA PRO, Varian, Mulgrave, Australia) was used for the content determination of Ba, Zn, Cu, Fe, Mn, Ni, Ca, Mg and P. The ICP OES system was equipped with a solid-state CCD that allows simultaneous measurements from 167 to 785 nm.The instrumental parameters used were as follows: RF generator, 40 MHz; applied power, 1300 W; plasma gas flow-rate, 15.0 L min -1 ; auxiliary gas flow-rate, 1.5 L min -1 ; nebulizer gas flow-rate, 0.7 L min -1 , and sample uptake rate, 0.8 mL min -1 .The sample introduction system employed was a concentric nebulizer and a cyclonic spray chamber.The analysis was carried out at the following wavelengths (nm): Ca II (317.933),Fe II (259.939),Mg II (285.213),P I (214.914),Cu I (324.754),Ba II (455.397),Mn II (257.610),Ni II (221.645) and Zn II (213.857),where "I" represents an atomic line and "II" an ionic line.In most cases, the wavelengths of the analytical lines were selected considering the most prominent line; secondary lines were used as an alternative to prevent possible interferences.All analyses were performed in triplicate and were checked by standard additions.Vol.21, No. 10, 2010

Reagents and reference solutions
All reagents were of analytical grade unless otherwise stated.Ultrapure water was obtained from an EASYpure RF (Barnstedt, Dubuque, IA, USA).Nitric acid and hydrogen peroxide were of Suprapur quality (Merck, Darmstadt, Germany).Laboratory glassware was kept overnight in a 10% v/v nitric acid solution.The glassware was rinsed with deionized water and dried in a dust free environment before use.Commercially available metal standard solutions (1,000 ± 0.002 mg L -1 ) (Titrisol, Merck) were prepared for the standard working range.Analytical curves were obtained for concentrations from 6.0 to 100.0 mg L -1 for Ca, Mg and P and from 0.05 to 10.0 mg L -1 for Ba, Zn, Cu, Fe, Mn and Ni.

Sample collection and storage
During the period of August 2004 to September 2005, 27 leaf samples were collected in 12 different cities in the Bahia State and one sample in the city of Rio de Janeiro, in Brazil.The respective cities were Amélia Rodrigues (AMR), Camaçari (CAM), Cruz das Almas (CZA), Euclides da Cunha (EUC), Feira de Santana (FSA), Jequié (JEQ), Lauro de Freitas (LAF), Ribeira do Pombal (RIP), Salvador (SSA), Simões Filho (SIF), Tucano (TUC), Vera Cruz (VEC) and Rio de Janeiro (RIO).The individual samples of 100 g each were kept in separate polyethylene bags and stored in a refrigerator at 6 °C for less than one day. 23Afterwards, the non-edible parts were removed, and the leaf samples were washed first with deionized water and then with 3% v/v Extran solution.The samples were dried in an air flow oven at 40 °C for 24 h, later homogenized in a blender and stored in polyethylene bags.

Humidity determination
The humidity of each sample was determined by mass loss after drying in an air flow oven at 40 ºC for 20 h, as recommended by the Association of Official Analytical Chemists. 24mple digestion About 0.5 g of leaf sample was accurately weighed into glass vessels, and 10.0 mL of concentrated nitric acid were added.The hot plate temperature was adjusted to 125 °C, the sample was digested for 30 min, and 3.0 mL of 30% m/m hydrogen peroxide were added.Heating was maintained to allow evaporation and yielded a final volume of ca. 5 mL.Later, the digested material was quantitatively transferred to a 50 mL volumetric flask and diluted with deionized water.

Validation of analytical method
The limit of detection (LOD) and limit of quantification (LOQ) for each element evaluated were determined based on the IUPAC recommendation, where LOD = (3s)/S, LOQ = (10s)/S, where s is the relative standard deviation of the measurements of a blank solution and S represents the slope of the analytical curve used for quantification.The results are presented in Table 1.
The accuracy of the method used for determination of the elements was confirmed by the analysis of a certified reference material produced by the National Institute of Standard and Technology (Gaithersburg, MD, USA), namely NIST apple leaves STM 1515.This material was submitted to the same procedure employed for the leaves samples.The results obtained are in agreement with the certified values (Table 1).

Results and Discussion
The percentage humidity for all 28 samples varied from 64.50 to 86.80%, averaging 76.81%.These results also demonstrated that the mineral content of the L. alba depends fundamentally of the humidity of the leaf analyzed.
The contents of Ba, Zn, Cu, Fe, Mn, Ni, Ca, Mg and P in the 28 leaf samples were determined (Supplementary Information).Calcium, Mg and P were present at the highest concentrations; their average content was 1,950, 2,856 and 2,335 mg 100 g -1 , respectively, while the concentration ranges were 767-3,887, 314-8,591 and 247-9,214 mg 100 g -1 , respectively.The micro-elements Ba, Zn, Cu, Fe, Mn and Ni had an average content of 2.16, 2.95, 0.94, 11.2, 4.25 and 0.09 mg 100 g -1 , respectively, and concentration ranges of 0.66-7.1,1.35-6.3,0.33-1.7,0.98-34, 0.82-7.4and 0.03-0.15mg 100 g -1 , respectively.These results match previous reports in the literature for metal content determination in tea leaves, 22,25 demonstrating that L. alba leaves can be a source of Ca, Mg and P in the human diet.
Data were evaluated using principal component analysis (PCA).A data matrix was constructed using the determined elements as columns and the leaf samples as rows.Principal component analysis was performed on auto-scaled data due to the different orders of magnitude of the concentration of the elements.
The results of the PCA revealed that the first three principal components explained only 63.35% of total variance.Figure 1 shows the loadings of the first two principal components.PC1 represents 29.36% of the variability of the data, and is mainly associated with Fe and Ba concentrations.These two elements are positively correlated and account for the major variability presented in data set.The score plot of the first two components is shown in Figure 2. Samples with high scores on PC1 (TUC1, TUC2, TUC3, TUC 4, RIO, SSA2, CZA, and RIP, all circled in Figure 2) have high concentrations of Fe and Ba (as can also be seen in Table S1).These samples are from a region where the industrial extraction of iron ore and barite occur.
The second principal component (PC2, describing 18.56% of the total variance) is primarily associated with variations in P, Mg, Zn and Ca contents.All these variables present negative loadings in PC2.Thus, samples with negative scores have higher than average values for these elements.The score plot (Figure 2) does not show well-defined clusters.
Finally, the third principal component (PC3) explains only 15.43% of the total variance and is associated with Cu (positive value) and Mn (negative value).From the scores plot (not shown) there are no evident clusters or outliers.

Conclusions
This paper is the first to report the evaluation of the mineral composition of Lippia alba leaves.The samples analyzed indicate that L. alba contains Ca, Mg and P as macroelements as well as Ba, Zn, Cu, Fe, Mn and Ni as microelements.
The exploratory analysis using principal component was applied to verify eventual similarities among the samples and correlations between elements and the outliers  detection.PCA helped to identify that the concentrations of the elements Ba and Fe are responsible for the major variability in the data set.Samples which presented high concentrations of these elements are from a region where the industrial extraction of iron ore and barite occur.The PCA results also provided no evidence of well defined clusters or outliers in this data set.

Figure 1 .
Figure 1.PCA results for the mineral content of Lippia alba leaves.The loading plot is shown.PC1 and PC2 explain 29.36% and 18.56% of the total variance, respectively.

Figure 2 .
Figure 2. PCA results for the mineral content of Lippia alba leaves.The score plot is shown; objects are labeled according to the site of sample collection.