The total phenolic content of extracts in decreasing order is ethanol extract (CDA Et) > acetone extract (CDA ACE) > phenolic extract (CDA MW) > n-hexane extract (CDA nHX)> chloroform extract (CDA CHL) > dichloromethane extract (CDA DCM). The ordering of extracts in terms of antioxidant activity from highest to lowest is CDA Et > CDA MW > CDA DCM > CDA CHL > CDA ACE > CDA nHX in DPPH, ABTS and FRAP assays. A significant relationship is found between antioxidant potential and total phenolic content, suggesting that phenolic compounds are the major contributors to the antioxidant activity of C. didymus.

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A new glycoside of flavonol (1) and a new glycoside of a cycloartane-type triterpene (2) were isolated from the leaves and the roots of Astragalus caprinus, respectively. Their structures were elucidated in turn by spectroscopic data interpretation as 3-O-[[beta-D-xylopyranosyl(1-->3)-alpha-L-rhamnopyranosyl(1-->6)][beta-D-apiofuranosyl(1-->2)]]-beta-D-galactopyranosyl kaempferol (1) and 3-O-(beta-D-xylopyranosyl)-24-O-(beta-D-glucopyranosyl)-20,25-epoxycycloartane-3beta,6alpha,16beta,24alpha-tetrol (2).

Astragalus caprinus MAIRE (Fabaceae) is an endemic of North Africa, the leaves of which are used as an antihaemorrhoidal in Tunisian folk medicine. Our previous paper describing the structure of a new 3-O-tetraglycoside of kaempferol from this plant was the first phytochemical report on this species.1) Here we report the isolation and structural elucidation of five new flavonol glycosides. Results and DiscussionThe methanolic extract of dried leaves from A. caprinus, once prepurified, was fractionated by repeated column and preparative thin-layer chromatography to give 1-5.Analysis of the 1 H-and 13 C-NMR spectra of compound 1 (Table 1; all assignments based on heteronuclear single quantum coherence-total correlation spectroscopy (HSQC-TOCSY) and heteronuclear multiple bond correlation (HMBC) experiments) showed the presence of one aromatic system and four sugar moieties. The 1 H-NMR resonances of two metacoupled doublets at d 6.19 and 6.38 ppm (1H, Jϭ1.9 Hz), correlated with the carbons at 99.8 and 94.7 ppm, respectively, in the HSQC spectrum, characterized the 6-and 8-protons of a flavonoid 5,7 dihydroxy A-ring.2) Ring B was assigned as a 1,4-substituted benzene ring (d H 8.07, d, 2H, Jϭ8.8 Hz; 6.89, d, 2H, Jϭ8.8 Hz) from a HMBC experiment. Thus, the aglycone of 1 was identified as 3,5,7,4Ј-tetrahydroxyflavone (kaempferol), as suggested by its UV spectral properties. A HSQC-TOCSY experiment was performed to identify the spin systems of sugar units, starting from anomeric protons at d 5.57 (d, Jϭ7.8 Hz), 5.22 (s), 4.52 (s) and 4.32 (d, Jϭ7.4 Hz); on the basis of the chemical shifts, multiplicity of the signals and values of the coupling constants, the sugars were identified as b-galactopyranosyl (Gal), a-rhamnopyranosyls (Rha a and Rha b) and b-xylopyranosyl (Xyl).3) The common D-configuration for Gal and Xyl, and the L-configuration for Rha were assumed according to those most often encountered among the plant glycosides. HMBC experiments showed long-range correlations between ϩ at m/z 873 and fragment ion peaks corresponding to successive losses of four sugar moities, namely a rhamnosyl, a pentosyl, a rhamnosyl and an hexosyl, respectively; the high resolution (HR)-FAB-MS was in agreement with the corresponding formula C 38 H 48 O 23 . Acid hydrolysis of 1 yielded kaempferol and sugars, which were identified as galactose, rhamnose and xylose by co-TLC with authentic samples. 4)The 1 H-and 13 C-NMR spectra of compound 2 (Table 1) showed the same signals as those observed for 1, but with significant downfield shifts of H-3 (d 5.06 ) and C-3 (d 77.7 ) of the galactose, as well as concomitant upfield shifts of the adjacent carbons C-2 and C-4.3) One additional 1,4-substituted benzene ring (d H 6.82, d, 2H, Jϭ8.8 Hz; 7.79 , d, 2H, Jϭ8.8 Hz), together with two olefinic protons doublets (Jϭ 15.8 Hz) at d 6.45 and 7.73, as well as one ester carbonyl carbon at d 168.4, indicated the presence of a trans-pcoumaroyl moiety. Its linkage to Gal C-3 was corroborated by the long range coupling of the ester carbonyl carbon...

Four new flavonol 3-O-glycosides were isolated from the leaves of Astragalus caprinus. Their structures were elucidated by spectroscopic methods as rhamnocitrin-3-O-[3-hydroxy-3-methylglutaroyl(1-->6)][beta-D-apiofuranosyl(1-->2)]-beta-D-galactopyranoside (1), rhamnetin-3-O-[3-hydroxy-3-methylglutaroyl(1-->6)][beta-D-apiofuranosyl(1-->2)]-beta-D-galactopyranoside (2), kaempferol-3-O-[beta-D-xylopyranosyl(1-->3)-alpha-L-rhamnopyranosyl(1-->6)]-beta-D-galactopyranoside (3), and quercetin-3-O-[beta-D-xylopyranosyl(1-->3)-alpha-L-rhamnopyranosyl(1-->6)][beta-D-apiofuranosyl(1-->2)]-beta-D-galactopyranoside (4).

Background. Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends’ preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.

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