Classification of Amazonian rosewood essential oil by Raman spectroscopy and PLS-DA with reliability estimation

Almeida, Mariana Ramos; Fidelis, Carlos H.V.; Barata, Lauro Euclides Soares; Poppi, Ronei J.

doi:10.1016/j.talanta.2013.09.025

Cited by 89 publications

(47 citation statements)

References 23 publications

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“…Linalool, a monoterpene alcohol, is the most abundant component of C. camphora leaf extracts tested by GC-MS in this study and the major constituents of Aniba rosaeodora , Arisaema franchetianum , Arisaema lobatum , Croton cajucara and Ocimum forskolei essential oils [38–41]. Linalool-rich extracts from various plants present properties against bacteria [42], viruses [43], insects [44] and parasites (protozoa and helminths) [45–47, 40] and the results presented in this work further support the molluscicidal and anti-parasite activity of linalool-rich exacts from plants.…”

Section: Discussionmentioning

confidence: 99%

Linalool, derived from Cinnamomum camphora (L.) Presl leaf extracts, possesses molluscicidal activity against Oncomelania hupensis and inhibits infection of Schistosoma japonicum

et al. 2014

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BackgroundSchistosomiasis japonicum remains a considerable economic and public health concern in China, the Philippines and Indonesia. Currently available measures to control the unique intermediate host Oncomelania hupensis are frequently associated with severe side effects. Previous studies have demonstrated that linalool-rich extracts from various plants exhibited promising biological activities including cytotoxic, anti-microbial and anti-parasitic properties.MethodsWe identified the components of leaf extracts from Cinnamomum camphora by gas chromatography coupled to mass spectrometry (GC-MS) and investigated molluscicidal and larvicidal effects of linalool against O. hupensis and Schistosoma japonicium. The ultrastructural alterations in gills, salivary gland, stomach and hepatopancreas of snails were observed under the light microscope and transmission electron microscope, and lesions to tegument of cercaria were examined under a light microscope and fluorescence microscope. We then evaluated the effects of linalool on skin penetration and migration of schistosomula and adult survival by measurement of worm burden and egg counts in Balb/C mice infected with linalool-treated cercariae.ResultsIn the present work, 44 components were identified from the leaf extracts of C. camphora, of which linalool was the most abundant constituent. Linalool exhibited the striking molluscicidal and larvicidal effects with LC50 = 0.25 mg/L for O. hupensis and LC50 = 0.07 mg/L for cercaria of S. japonicium. After exposure to linalool, damage to the gills and hepatopancreas of the snails, and to the tegument and body-tail joint of cercariae was apparent. In addition, linalool markedly reduced the recovered schistosomulum from mouse skin after challenge infection, and therefore decreased the worm burden in infected animals, but not fecundity of female adults of the parasite.ConclusionsOur findings indicated that linalool might be a novel chemotherapeutic agent against S. japonicium and the snail intermediate host.

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Section: Discussionmentioning

confidence: 99%

Linalool, derived from Cinnamomum camphora (L.) Presl leaf extracts, possesses molluscicidal activity against Oncomelania hupensis and inhibits infection of Schistosoma japonicum

et al. 2014

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“…Many classification schemes have been successfully applied to Raman spectra, some of which include constrained regression [6], [7], partial least squares [8], nonnegative matrix factorization [9], correlation methods [10], [11], vector similarity methods [12], principal and independent component analysis (PCA/ICA) [13]- [16], support vector machines (SVM), [17], [18] and artificial neural networks (ANNs) [19]. Of particular interest to us are the subset of these mineral classification schemes, which are intended for, or are capable of, the identification of Raman spectra mixtures using a preexisting library such as the commonly used RRUFF database.…”

Section: Previous Workmentioning

confidence: 99%

A Fast Classification Scheme in Raman Spectroscopy for the Identification of Mineral Mixtures Using a Large Database With Correlated Predictors

Cochrane

Blacksberg

2015

IEEE Trans. Geosci. Remote Sensing

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Robust classification methods are vital to the successful implementation of many material characterization techniques, particularly where large databases exist. In this paper, we demonstrate an extremely fast classification method for the identification of mineral mixtures in Raman spectroscopy using the large RRUFF database. However, this method is equally applicable to other techniques meeting the large database criteria, these including laser-induced breakdown, X-ray diffraction, and mass spectroscopy methods. Classification of these multivariate datasets can be challenging due in part to the various obscuring features inherently present within the underlying dataset and in part to the volume and variety of information known a priori. Some of the more specific challenges include the observation of mixtures with overlapping spectral features, the use of large databases (i.e., the number of predictors far outweighs the number of observations), the use of databases that contain groups of correlated spectra, and the ever present, clouding contaminants of noise, undesired background, and spectrometer artifacts. Although many existing classification algorithms attempt to address these problems individually, not many address them as a whole. Here, we apply a multistage approach, which leverages well-established constrained regression techniques, to overcome these challenges. Our modifications to conventional algorithm implementations are shown to increase speed and performance of the classification process. Unlike many other techniques, our method is able to rapidly classify mixtures while simultaneously preserving sparsity. It is easily implemented, has very few tuning parameters, does not require extensive parameter training, and does not require data dimensionality reduction prior to classification.Index Terms-Classification, elastic net (EN), planetary mineralogy, Raman spectroscopy, regression.

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“…The authors concluded that it was possible to perform quality control of essential oils even if the differentiation of varieties was not investigated . A dispersive Raman analysis showed a characterization of rosewood oil extracted from several parts of the Amazon tree Aniba rosaeodora , wood and leaf/branch oils were differentiated by PLS‐DA regression . In this paper, the authors have shown examples of applications using Raman and IR vibrational spectroscopies for the evaluation of eucalyptus essential oil .…”

Section: Introductionmentioning

confidence: 99%

Raman spectroscopy for identification and quantification analysis of essential oil varieties: a multivariate approach applied to lavender and lavandin essential oils

Lafhal

Vanloot

Bombarda

et al. 2015

J. Raman Spectrosc.

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International audienceLavender (Lavandula angustifolia) is used for cosmetics, perfumes and medicine (antimicrobial activity and relaxant properties) while lavandin (sterile hybrid of L. angustifolia P. Mill.xLavandula latifolia (L.f.) Medikus) is used for air fresheners, deodorants and soaps. These plants are widely cultivated for essential oil production. In this study, 104 samples were analyzed including 62 lavandin and 42 lavender oil samples from several varieties. The Raman spectra are similar but can be differentiated by chemometrics treatment. Data structure may be studied by PCA. A PLS regression model was used for quantitative analysis of the main compounds such as linalyl acetate, linalool and eucalyptol. The reference data were obtained by gas chromatography. The performance of the method was also tested to discriminate between the two species and the seven varieties (Abrial, Fine, Grosso, Maillette, Matherone, Sumian and Super) by PLS-DA regression. The examination of PLS and PLS-DA regression coefficients allowed for the identification of species and of the varieties' metabolomic markers

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Classification of Amazonian rosewood essential oil by Raman spectroscopy and PLS-DA with reliability estimation

Cited by 89 publications

References 23 publications

Linalool, derived from Cinnamomum camphora (L.) Presl leaf extracts, possesses molluscicidal activity against Oncomelania hupensis and inhibits infection of Schistosoma japonicum

Linalool, derived from Cinnamomum camphora (L.) Presl leaf extracts, possesses molluscicidal activity against Oncomelania hupensis and inhibits infection of Schistosoma japonicum

A Fast Classification Scheme in Raman Spectroscopy for the Identification of Mineral Mixtures Using a Large Database With Correlated Predictors

Raman spectroscopy for identification and quantification analysis of essential oil varieties: a multivariate approach applied to lavender and lavandin essential oils

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