**2.1 Material and methods**

404 Macro to Nano Spectroscopy

Fig. 3. Two-dimensional model derived from PCA of 700 quantitative variables of 10

Entre Rios; SF, Santa Fe populations. Numbers indicate when there is more than one

confers the antioxidant activity (Harborne & Williams, 1992; Rice-Evans et al., 1995).

Currently, the morphoanatomical studies of these species in sect. Caulopterae only provide incomplete information which makes it difficult to differentiate each one properly in the non-flowering condition when the size of capitulum of each one varies (Giuliano, 2000; Müller, 2006). This fact has lead to the misuse of the same common name for botanically diverse species, which surely have different chemical compositions and therefore different pharmacological properties (Abdel-Malek et al., 1996; Desmarchelier et al*.*, 1997; De Oliveira

population of the same species.

*Baccharis* populations. Ba, *B. articulata*; Bt, *B. trimera*. BA, Buenos Aires; COR, Corrientes; ER,

authors have contributed to the infrageneric classification of *Baccharis* in general and regional floras (Ariza Espinar, 1973; Baker, 1882-1884; Barroso, 1976; Cuatrecasas, 1967; De Candolle, 1836; Giuliano, 2001; Heering, 1904; Lessing, 1831; Weddell, 1855-1856) and it was De Candolle (1836) who was the first to subdivide the genus in eight sections, mainly based on leaf morphology. More recently, Giuliano (2001) grouped 96 Argentine *Baccharis* species into 15 sections, among which the sect. Caulopterae DC. is characterized by the presence of species with alate stems. Two of nine Argentine species from this sect., i.e., *Baccharis articulata* (Lam.) Pers. and *Baccharis crispa* Spreng. are included in the National Argentine Pharmacopeia Ed. VI (1978), and a third one, *Baccharis trimera* (Less.) DC. in the Brazilian Pharmacopeia Ed. IV (2002) with the common name of "Carquejas". The nine species of this sect. are traditionally used in infusions or decoctions, as hepatic, colagogue, diuretic, ulcer healing and external antiseptics. They are also used in herbal remedies and phytotherapy and in the preparation of spirits and soft drinks (Correa, 1985; Gupta, 1995; Hieronymus, 1882; Martínez Crovetto, 1981; Sorarú & Bandoni, 1978; Toursarkissian, 1980). Beneficial effects of these species can be attributed in part to their high content of flavonoids. The chemistry of the flavonoids is predictive of their free radical scavenging activity, which Fifty three samples of nine *Baccharis* species were collected from wild materials in different locations in Argentina. All samples were botanically identified by our group and voucher specimens were deposited at the herbarium of the National University of Rosario, Argentina (Table 1).

The aerial parts of the dried plants (5 g) were macerated (24 h, 3x) with absolute ethyl alcohol. The ethanolic extract was filtered and concentrated in a rotary evaporator at a temperature lower than 100 ºC. Thirty mg of dry extract were mix in 3 ml dichloromethane (DCM) and left for 1 h and then filtered with common filter paper. A dilution of 50 µl of this solution in 950 µl of methanol was prepared and filtered twice with a 0.45 µm Millipore filter (Lonni et al*.*, 2003, 2005).

Spectrophotometric analyses were carried out using a Biochrom Model Libra S12 UV/Visible Spectrophotometer, equipped with tungsten halogen and deuterium arc light sources with a single solid state silicon photodiode detector, and operating software.

TLC analyses were carried out using silica gel 60 F254, Merck; mobile phase, DCM: Hexane:

MeOH (4:2:1). Chromatograms were evaluated under UV light at 254 and 365 nm to detect the presence of flavonoids. TLC was additionally sprayed with a diphenylborinic acid ethanolamine/polyethylene glycol reagent. Apigenin, chlorogenic acid, genkwanin, luteolin, quercetin and rutin were used as markers (purchased from Extrasynthèse, France).

HPLC analyses were carried out using a Spectra Physics Model SP8800 ternary pump chromatograph with Spectra 100 UV/Visible detector, having as chromatographic conditions, methanol eluent, 1 ml min-1 flow, Luna C18 phenomenex (250 x 4.6 mm, 5 µm particle size). The injection volume was 100 µl and elution was monitored al 254 nm. Apigenin, genkwanin and luteolin were used as markers (purchased from Extrasynthèse, France).

TLC and HPLC analysis were applied in order to complement the studies carried out by PCA of the spectrophotometric data and to find potential markers of the species that could not be characterized by the previous method.

Quality Control of Herbal Medicines with Spectrophotometry and Chemometric Techniques

al., 1998).

**2.2 Results and discussion** 

SF, Santa Fe; SL, San Luis.

**2.2.1 Spectrophotometric analysis** 

*phyteumoides* from *B. trimera* and *B. triangularis* samples.

– Application to *Baccharis* L. Species Belonging to Sect – Caulopterae DC. (Asteraceae) 407

Before PCA the data were pre-processed with normalization to unit area technique (Beebe et

Seven hundred absorbance values were utilised as quantitative variables for population analysis. Samples were collected in different provinces and seasons, mainly taking into account the quantitative variability of secondary metabolites during the year (Table 1). The principal component analysis showed that the first nine components explain almost 98.81% of the total variability. The second (PC2) and the third (PC3) principal components gathered relevant information for classifying species. Figure 4, shows a two dimension plot of PC2 vs. PC3 using all the variables. Samples could be classified in five large groups containing the species *B. crispa*, *B. microcephala*, *B. phyteumoides*, *B. triangularis* and *B. trimera*. PC2 clearly separates *B. microcephala* and *B. trimera* populations from *B. crispa* and *B. phyteumoides* populations. Moreover, samples corresponding to *B. triangularis* species were separated from those belonging to *B. microcephala*, *B. trimera*, *B. crispa* and *B. phyteumoides* populations by PC2. While PC3 separates *B. microcephala* samples from the rest of the species, it also separates *B. crispa* samples from *B. phyteumoides*, *B. trimera* and *B. triangularis* and between samples of the two latter species. However, PC3 did not completely distinguish *B.* 

Fig. 4. Two dimensional model of PC2 *vs.* PC3 (15.63 and 7.80 %, respectively) derived from PCA of 700 quantitative variables of 53 *Baccharis* populations. Ba, *B. articulata*; Bc, *B. crispa*; Bg, *B. gaudichaudiana*; Bm, *B. microcephala*; Bp, *B. penningtonii*; Bphy, *B. phyteumoides*; Bs, *B. sagittalis*; Btr, *B. triangularis*; Bt, *B. trimera*; BA, Buenos Aires; CHU, Chubut; CO, Córdoba; COR, Corrientes; ER, Entre Ríos; FO, Formosa; LP, La Pampa; MI, Misiones; RN, Río Negro;


Table 1. Collection data of analysed samples of *Baccharis* species. The abbreviation mean: species: Ba, *B. articulata*; Bc, *B. crispa*; Bg, *B. gaudichaudiana*; Bm, *B. microcephala*; Bp, *B. penningtonii*; Bphy, *B. phyteumoides*; Bs, *B. sagittalis*; Btr, *B. triangularis*; Bt, *B. trimera*; provinces: BA, Buenos Aires; CHU, Chubut; CO, Córdoba; COR, Corrientes; ER, Entre Ríos; FO, Formosa; LP, La Pampa; MI, Misiones; RN, Río Negro; SF, Santa Fe; SL, San Luis. Numbers indicate when there is more than one population of the same species. **a** Material extracted from Herbarium; b Names of collectors, numbers not provided by the Herbarium.
