Phytochemical Analysis

Cover image for Vol. 24 Issue 3

May/June 2013

Volume 24, Issue 3

Pages 193–287

  1. Research Articles

    1. Top of page
    2. Research Articles
    1. Development, Optimisation and Validation of a Stability-Indicating HPLC Method of Achyrobichalcone Quantification using Experimental Designs (pages 193–200)

      Juliana P. Carini, Samuel Kaiser, George G. Ortega and Valquiria L. Bassani

      Version of Record online: 15 SEP 2012 | DOI: 10.1002/pca.2399

      Achyrobichalcone, a new biflavonoid found in Achyrocline satureioides, was recently isolated. To assess its quality, we develop, optimise and validate a stability-indicating HPLC method. The optimisation was performed by Box-Behnken design and robustness by Plackett-Burman design. Factors as column temperature, flow rate and acetonitrile content were significant for resolution between achyrobichalcone and impurities peaks and retention factor. The analyte was unstable only in alkaline media. The new method affords to evaluate the quality and stability of achyrobichalcone obtained by isolation.

    2. Dehydropyrrolizidine Alkaloids in Two Cryptantha Species: Including Two New Open Chain Diesters One of Which is Amphoteric (pages 201–212)

      Steven M. Colegate, Dale R. Gardner, T. Zane Davis, Joseph M. Betz and Kip E. Panter

      Version of Record online: 15 OCT 2012 | DOI: 10.1002/pca.2400

      Prompted by a livestock poisoning outbreak near Kingman, Arizona, analysis of Cryptantha inequata and C. utahensis revealed dehydropyrrolizidine alkaloids at approximately 0.05 % and 0.09% w/w respectively. Cryptantha inequata produced mainly echimidine, acetylechimidine and echiuplatine; dehydropyrrolizidine alkaloids previously associated with Echium plantagineum. Echiuplatine was elucidated as an amphoteric, open chain diester with angelic acid and 3-hydroxy-3-methylglutaric acid. Along with lycopsamine, intermedine and dihydroxyechiumine, C. utahensis produced cryptanthine, an open chain diester with angelic acid and 2,3-dihydroxy-2-methylbutanoic acid. All pyrrolizidine alkaloids detected were present in the plants mainly as their N-oxides. The dehydropyrrolizidine alkaloids detected are expected to be toxic but the low levels in the plants potentially mitigate the risk. The identification of the amphoteric echiuplatine provides a cautionary note with respect to the analysis of total dehydropyrrolizidine alkaloid content.

    3. HPLC–ESI–QTOF–MS as a Powerful Analytical Tool for Characterising Phenolic Compounds in Olive-leaf Extracts (pages 213–223)

      Rosa Quirantes-Piné, Jesús Lozano-Sánchez, Miguel Herrero, Elena Ibáñez, Antonio Segura-Carretero and Alberto Fernández-Gutiérrez

      Version of Record online: 15 SEP 2012 | DOI: 10.1002/pca.2401

      HPLC–ESI–QTOF was used to characterise the phenolic compounds from two olive-leaf extracts obtained by pressurised liquid extraction using water and ethanol as extracting solvents. The information provided by QTOF mass spectrometer enabled the in-depth characterisation of both olive-leaf extracts, allowing the tentative identification of 31 different phenolic compounds in these extracts, including secoiridoids, simple phenols, flavonoids, cinnamic-acid derivatives and benzoic acids. Lucidumoside C was also identified for the first time in olive leaves.

    4. Improvements in the Separation Capabilities of Sequential Injection Chromatography: Determination of Intracellular Dissolved Free Amino Acid Profiles in Three Taxonomic Groups of Microalgae (pages 224–229)

      Marilda Rigobello-Masini and Jorge C. Masini

      Version of Record online: 11 OCT 2012 | DOI: 10.1002/pca.2402

      Amino Acids were determined by reversed phase sequential injection chromatography using fluorimetric detection of their indole derivatives, exploring an instrument configuration capable to handle pressures of up to 1000 psi. Separation was achieved by stepwise elution with six mobile phases with concentrations of methanol increasing from 8 to 65 % (v/v) in 10 mM phosphate buffer (pH 7.2). The proposed method found different profiles of dissolved free amino acids among three species of algae, suggesting its adequacy for metabolic studies.

    5. Design of Experiment Approach for the Process Optimisation of Microwave Assisted Extraction of Lupeol from Ficus racemosa Leaves Using Response Surface Methodology (pages 230–247)

      Anup Kumar Das, Vivekananda Mandal and Subhash C. Mandal

      Version of Record online: 15 OCT 2012 | DOI: 10.1002/pca.2403

      • A microwave assisted extraction (MAE) of lupeol for industrial scale-up using response surface methodology (RSM) is proposed.
      • Data from single factor analysis of a Plackett–Burman design were fitted to a Box–Behnken design (BBD) to build response surfaces.
      • The BBD used a regression equation to predict optimal MAE conditions with optimum yield.
      • Validation of the MAE process showed that the regression model fitted well with the experimental data, as evident from only a slight deviation (%RSD = 0.69) between predicted and experimental yield.
    6. HPLC Determination of the Major Active Flavonoids and GC–MS Analysis of Volatile Components of Dysphania graveolens (Amaranthaceae) (pages 248–254)

      Harry Álvarez-Ospina, Isabel Rivero Cruz, Georgina Duarte, Robert Bye and Rachel Mata

      Version of Record online: 5 OCT 2012 | DOI: 10.1002/pca.2405

      Dysphania graveolens is used in Mexican traditional medicine against gastrointestinal ailments. Previous investigations revealed that its flavonoids are important active principles; however, there is not a reliable and accurate analytical method for determining these compounds in the crude drug or preparations of the plant. Therefore, a suitable validated HPLC method for quantifying the major active flavonoids was developed. According to GC–MS analysis of the volatile compounds extracted by HS–SPME and by hydrodistillation, the most relevant volatile components in the species were monoterpenoids.

    7. Production of Polyclonal Antibody Against Madecassoside and Development of Immunoassay Methods for Analysis of Triterpene Glycosides in Centella asiatica (pages 256–262)

      Patcharin Tassanawat, Waraporn Putalun, Gorawit Yusakul, Boonchoo Sritularak, Thaweesak Juengwatanatrakul and Hiroyuki Tanaka

      Version of Record online: 19 OCT 2012 | DOI: 10.1002/pca.2406

      ELISA and Eastern blotting methods for analysis of triterpene glycosides in Centella asiatica were developed using polyclonal antibody against madecassoside.

    8. UPLC–Q-TOF–HDMS Analysis of Constituents in the Root of Two Kinds of Aconitum Using a Metabolomics Approach (pages 263–276)

      Hui Sun, Mo Wang, Aihua Zhang, Bei Ni, Hui Dong and Xijun Wang

      Version of Record online: 6 DEC 2012 | DOI: 10.1002/pca.2407

      Metabolomics based UPLC-Q-TOF-HDMS coupled with pattern recognition analyses was effective for analysis of constituents in the root of two kinds of Aconitume species. Twenty-two metabolites between the mother root of Aconitum carmichaelii Debx and lateral root of Aconitum carmichaelii Debx, 13 metabolites between the Aconitum carmichaelii Debx and root of Aconitum kusnezoffii Reichb have been identified.

    9. Metabolome Classification of Brassica napus L. Organs via UPLC–QTOF–PDA–MS and Their Anti-oxidant Potential (pages 277–287)

      Mohamed A. Farag, Mohamed G. Sharaf Eldin, Hanaa Kassem and Mohamed Abou el Fetouh

      Version of Record online: 11 OCT 2012 | DOI: 10.1002/pca.2408

      In this study a comparison has been made between the metabolite composition of Brassica. napus L. organs including roots, stems, leaves, inflorescence and seeds. UPLC-qTOF-MS was utilized in order to localize metabolites belonging to various chemical classes (i.e. oxygenated fatty acids, flavonols, phenolic acids and sinapoyl choline derivatives). The vast majority of identified metabolites were flavonol glycosides that accumulated in most plant parts. Principal component analysis (PCA) and partial least squares-discriminant analysis (OPLS-DA) of biochemical profile were used for organs classification.

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