scholarly journals Quantification of the Geranium Essential Oil, Palmarosa Essential Oil and Phenylethyl Alcohol in Rosa damascena Essential Oil Using ATR-FTIR Spectroscopy Combined with Chemometrics

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1848
Author(s):  
Nur Cebi
Keyword(s):  
Cluster Analysis ◽  
Essential Oil ◽  
Ftir Spectroscopy ◽  
Hierarchical Cluster Analysis ◽  
Cross Validation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Rosa Damascena ◽  
Least Squares Regression ◽  
Classification Pattern

Rosa damascena essential oil is an essential oil that has the greatest industrial importance due to its unique quality properties. The study used ATR-FTIR (attenuated total reflectance-Fourier transform infrared) spectroscopy coupled with chemometrics of PLSR (partial least squares regression) and PCR (principal component regression) for quantification of probable adulterants of geranium essential oil (GEO), palmarosa essential oil (PEO) and phenyl ethyl alcohol (PEOH). Hierarchical cluster analysis was performed to observe the classification pattern of Rosa damascena essential oil, spiked samples and adulterants. Rosa damascena essential oil was spiked with each adulterant at concentrations of 0–100% (v/v). Excellent R2 (regression coefficient) values (≥0.96) were obtained in all PLSR and PCR cross-validation models. The SECV (standard error of cross-validation) values ranged between 0.43 and 4.15. The lowest SECV and bias values were observed in the PLSR and PCR models, which were built by using the raw FTIR spectra of all samples. Hierarchical cluster analysis through Ward’s algorithm and Euclidian distance had high potential to observe the classification pattern of all adulterated and authentic samples. In conclusion, the combination of ATR-FTIR spectroscopy with multivariate analysis can be used for rapid, cost-effective, easy, reliable and high-throughput detection of GEO, PEO and PEOH in Rosa damascena essential oil.

scholarly journals Rapid Screening of Mentha spicata Essential Oil and L-Menthol in Mentha piperita Essential Oil by ATR-FTIR Spectroscopy Coupled with Multivariate Analyses

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 202
Author(s):  
Osman Taylan ◽  
Nur Cebi ◽  
Osman Sagdic
Keyword(s):  
Essential Oil ◽  
Essential Oils ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Rapid Screening ◽  
Mentha Piperita ◽  
Least Squares Regression ◽  
Mentha Spicata ◽  
Quality Properties

Mentha piperita essential oil (EO) has high economic importance because of its wide usage area and health-beneficial properties. Besides health-beneficial properties, Mentha piperita EO has great importance in the flavor and food industries because of its unique sensory and quality properties. High-valued essential oils are prone to being adulterated with economic motivations. This kind of adulteration deteriorates the quality of authentic essential oil, injures the consumers, and causes negative effects on the whole supply chain from producer to the consumer. The current research used fast, economic, robust, reliable, and effective ATR-FTIR spectroscopy coupled chemometrics of hierarchical cluster analysis(HCA), principal component analysis (PCA), partial least squares regression (PLSR) and principal component regression (PCR) for monitoring of Mentha spicata EO and L-menthol adulteration in Mentha piperita EOs. Adulterant contents (Mentha spicata and L-menthol) were successfully calculated using PLSR and PCR models. Standard error of the cross-validation SECV values changed between 0.06 and 2.14. Additionally, bias and press values showed alteration between 0.06 and1.43 and 0.03 and 41.15, respectively. Authentic Mentha piperita was successfully distinguished from adulterated samples, Mentha spicata and L-menthol, by HCA and PCA analysis. The results showed that attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometrics could be effectively used for monitoring various adulterants in essential oils.

scholarly journals Chemical and Enantioselective Analysis of the Essential Oils from Different Morphological Structures of Ocotea quixos (Lam.) Kosterm

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2171
Author(s):  
Gianluca Gilardoni ◽  
Mayra Montalván ◽  
Marjorie Vélez ◽  
Omar Malagón
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Essential Oil ◽  
Essential Oils ◽  
Hierarchical Cluster Analysis ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Methyl Cinnamate ◽  
Enantiomerically Pure ◽  
Enantioselective Analysis

The traditional Ecuadorian spice Ishpingo, characterized by a strong cinnamon-like aroma, is constituted by the dry cupules of Amazonian species Ocotea quixos. Nevertheless, bark and leaves also present aromatic properties and are sometimes used as substitutes. In the present study, the essential oils, distilled from these morphological structures, are comparatively analyzed for their chemical and enantiomeric compositions. A total of 88 components were identified with 2 orthogonal GC columns, whereas 79, corresponding to more than 94%, were also quantified with at least 1 column. Major compounds were (E)-methyl cinnamate in cupules (35.9–34.2%), (E)-cinnamaldehyde in bark (44.7–47.0%), and (E)-cinnamyl acetate (46.0–50.4%) in leaves. For what concerns the enantioselective analysis, 10 chiral terpenes and terpenoids were detected, of which 6 were present as enantiomeric pairs in at least 1 essential oil, the others being enantiomerically pure. Both quantitative and enantioselective analyses were submitted to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), where their results confirmed significative difference among the three products.

scholarly journals Multivariate characteristics of selected grass varieties for seed production

2019 ◽  
Vol 55 (No. 2) ◽  
pp. 83-86
Author(s):  
Marzena Iwańska ◽  
Danuta Martyniak ◽  
Marcin Martyniak ◽  
Dariusz Gozdowski
Keyword(s):  
Principal Component Analysis ◽  
Growth Rate ◽  
Cluster Analysis ◽  
Seed Production ◽  
Plant Resistance ◽  
Hierarchical Cluster Analysis ◽  
Multivariate Analyses ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Festuca Rubra

Data were obtained in a field experiment carried out at Plant Breeding and Acclimatization Institute Radzikow (central Poland) in 2009–2011. The aim of this study was a multivariate evaluation of 13 advanced lines and cultivars of Festuca rubra, taking into account traits important in seed production. Eleven traits of the grasses and plant resistance to diseases were evaluated. On the basis of multivariate analyses, i.e. hierarchical cluster analysis and principal component analysis, groups of varieties were separated and described, relationships between the traits were evaluated as well. The traits with the biggest influence on multivariate diversity of examined varieties were correlated with the first principal component i.e. height of plants, seeds yield, growth rate of plants, leaf width and time to beginning of earing.  

scholarly journals Polymorphism analysis in some Algerian Opuntia species using morphological and phenological UPOV descriptors

2017 ◽  
Vol 95 (3) ◽  
pp. 391 ◽  
Author(s):  
Boubakr Hadjkouider ◽  
Ammar Boutekrabt ◽  
Bahia Lallouche ◽  
Salim Lamine ◽  
Néjia Zoghlami
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Phenotypic Diversity ◽  
Principal Component ◽  
Morphological Diversity ◽  
Hierarchical Cluster ◽  
Relative Magnitude ◽  
Polymorphism Analysis ◽  
Opuntia Ficus Indica ◽  
New Varieties

<p><strong>Background: </strong>In the present study, we have investigated the morphological variation in a set of five <em>Opuntia</em> species from the Algerian steppes using 49 UPOV descriptors.</p><p><strong>Questions: </strong>which of the 49 descriptors that can be used as powerful estimators of the phenotypic diversity within <em>Opuntia</em> species? How is the morphological diversity patterned in Algerian <em>Opuntia</em>?</p><p><strong>Species study/ Mathematical model: </strong><em>Opuntia ficus-indica, Opuntia amycleae, Opuntia streptacantha, Opuntia engelmannii, Opuntia robusta</em><strong>.</strong> Principal Components Analysis (PCA) and Hierarchical Cluster Analysis were used.</p><p><strong>Study site: </strong>Four counties were studied located in the Algerian steppes. The present research was carried out during 2014.</p><p><strong>Methods:</strong> 49 descriptors adopted by the International Union for the Protection of New Varieties of Plants (UPOV) were employed in the present research, where cladode, flower and fruit traits were used to determine the overall degree of polymorphism among 5 <em>Opuntia</em> species.</p><p><strong>Results:</strong> Principal Component Analysis and Hierarchical Cluster Analysis indicated a consistent differentiation between all studied species. The relative magnitude of the first two PCA eigenvectors showed that 8 descriptors out of 49 were identified as the most important descriptors for the classification of the species. The dendrogram performed on the calculated Euclidean distances between all species pairs allowed the identification of 3 groups, unlike the PCA that identified 4 groups. The species <em>Opuntia ficus-indica </em>and <em>Opuntia amycleae</em> were identified as very close morphologically.</p><p><strong>Conclusions: </strong>The present outcome represents a paramount step towards the fast selection of interesting species and for their best management and conservation.</p>

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