Phylogeny of cultivated and wild wheat species using ATR–FTIR spectroscopy

Demir, Pınar; Önde, Sertaç; Severcan, Feride

doi:10.1016/j.saa.2014.07.025

Cited by 47 publications

(40 citation statements)

References 41 publications

(45 reference statements)

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“…Principal component analysis (PCA) was applied to the vibrational spectra in order to differentiate the groups. [31][32][33][34][35][47][48][49][50][51] The aim of PCA is to reduce the dimensionality of a data set consisting of a large number of interrelated variables, while keeping as much as possible the variation present in the data set. For a vibrational spectral input, this corresponds to the reduction of hundreds of absorbance values at corresponding spectral wavenumbers into a single point.…”

Section: Principal Component Analysismentioning

confidence: 99%

“…The principal components in turn describe the statistical variation in the spectra, i.e., the variability of the spectrum with respect to the mean of the spectra and thus contain the characteristics of the samples. 50,51 Each PC describes the spectral variability among samples in decreasing order. Thus, the first principal component, i.e., PC1, expresses most of the variance in the data; PC2 expresses the second largest variance in the data and so on.…”

Section: Principal Component Analysismentioning

confidence: 99%

“…An increase in the spatial separation between the two points in a scores plot corresponds to an increase in the dissimilarity between these two samples, i.e., the absorbance spectra in the case of FTIR spectra as the input. 50 The details can be found in Demir et al 50 PCA was performed on both FTIR and Raman micro spectra using the Unscrambler ® X version 10.3 (CAMO) and MATLAB (Mathworks Inc.) programs, respectively. The analyses were performed on absorbance spectra that were vector normalized, seven points smoothed with the Savitzky-Golay algorithm 52 and 2nd degree polynomial baseline corrected.…”

Section: Principal Component Analysismentioning

confidence: 99%

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Structural effects of simvastatin on rat liver tissue: Fourier transform infrared and Raman microspectroscopic studies

et al. 2016

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Simvastatin is one of the most frequently prescribed statins because of its efficacy in the treatment of hypercholesterolemia, reducing cardiovascular risk and related mortality. Determination of its side effects on different tissues is mandatory to improve safe use of this drug. In the present study, the effects of simvastatin on molecular composition and structure of healthy rat livers were investigated by Fourier transform infrared and Raman imaging. Simvastatin-treated groups received 50 mg/kg/day simvastatin for 30 days. The ratio of the area and/or intensity of the bands assigned to lipids, proteins, and nucleic acids were calculated to get information about the drug-induced changes in tissues. Loss of unsaturation, accumulation of end products of lipid peroxidation, and alterations in lipid-to-protein ratio were observed in the treated group. Protein secondary structure studies revealed significant decrease in α-helix and increase in random coil, while native β-sheet decreases and aggregated β-sheet increases in treated group implying simvastatin-induced protein denaturation. Moreover, groups were successfully discriminated using principal component analysis. Consequently, high-dose simvastatin treatment induces hepatic lipid peroxidation and changes in molecular content and protein secondary structure, implying the risk of liver disorders in drug therapy.

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Section: Principal Component Analysismentioning

confidence: 99%

Section: Principal Component Analysismentioning

confidence: 99%

Section: Principal Component Analysismentioning

confidence: 99%

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Structural effects of simvastatin on rat liver tissue: Fourier transform infrared and Raman microspectroscopic studies

et al. 2016

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“…Since all accessions were examined in the same field trials and were thus exposed to identical environment, the observed metabolomics diversity reflected specific, adaptive modifications of landrace to habitats in the place of their origin. In other studies, the biochemical traits based on non-targeted spectroscopic data have been used as markers for accession identity (Dumlupinar et al 2011;Luthria et al 2008), for investigation of the effect of environmental factors on the cereal grain quality (Andersson and Börjesdotter 2011;Shao et al 2015;Yan et al 2007), or establishing phylogenetic relationships (Demir et al 2015).…”

Section: Discussionmentioning

confidence: 99%

“…The biochemical characterization of germplasm was performed using infrared spectroscopy, a convenient approach for high-throughput analysis, which provided a metabolic fingerprint of a sample. The feasibility of this method for discriminating and taxonomic applications have been successfully proved in researches with various plant organs or parts including seeds (Demir et al 2015;Liu and Yu 2011), leaves (Kim et al 2004;Lu et al 2008), petals (Li et al 2015), roots (Naumann et al 2010), or pollens (Zimmermann and Kohler 2014).…”

Section: Introductionmentioning

confidence: 99%

Environmentally-related genotypic, phenotypic and metabolic diversity of oat (Avena sativa L.) landraces based on 67 Polish accessions

Boczkowska

Żebrowski

Nowosielski

et al. 2017

Genet Resour Crop Evol

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Here we focused on Polish oat landraces developed in the moderate temperature zone attempting to understand their genetic and phenotypic variability in context of the pressure of environmental constrains at the locations where they had evolved. Besides molecular markers and diverse phenotypic traits the Fourier transform infrared (FTIR) spectroscopy, enabling throughput metabolic fingerprinting, was used for the description of the germplasm collection. We used sophisticated multivariable analysis to integrate the data for structure analysis and to establish mutual relationships. We found that the accessions diversity across the eco-geographical variables was manifested differently depending on selected phenotypic, genetic, and metabolic criteria.Grain metabolic fingerprint derived from FTIR spectroscopy revealed the highest degree of germplasm diversity among all of the examined traits, particularly for spectral bands assigned to lipids. The landraces, which were collected in close geographical proximity, showed clear morphological and metabolic resemblances, although they represented quite different genetic backgrounds. All three levels of analysis showed the presence of selection resulting from environmental pressures and more specifically from the temperature at the landrace origin site. This research also proved that coupling of genetic polymorphism with the FTIR fingerprinting markedly extended the description of the oat landraces diversity.

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Infrared spectroscopy for ploidy estimation: An example in two species of Veronica using fresh and herbarium specimens

Buono

Albach

2023

Appl Plant Sci

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Premise: Polyploidy has become a central factor in plant evolutionary biological research in recent decades. Methods such as flow cytometry have revealed the widespread occurrence of polyploidy; however, its inference relies on expensive lab equipment and is largely restricted to fresh or recently dried material. Methods: Here, we assess the applicability of infrared spectroscopy to infer ploidy in two related species of Veronica (Plantaginaceae). Infrared spectroscopy relies on differences in the absorbance of tissues, which could be affected by primary and secondary metabolites related to polyploidy. We sampled 33 living plants from the greenhouse and 74 herbarium specimens with ploidy known through flow cytometrical measurements and analyzed the resulting spectra using discriminant analysis of principal components (DAPC) and neural network (NNET) classifiers. Results: Living material of both species combined was classified with 70% (DAPC) to 75% (NNET) accuracy, whereas herbarium material was classified with 84% (DAPC) to 85% (NNET) accuracy. Analyzing both species separately resulted in less clear results. Discussion: Infrared spectroscopy is quite reliable but is not a certain method for assessing intraspecific ploidy level differences in two species of Veronica. More accurate inferences rely on large training data sets and herbarium material. This study demonstrates an important way to expand the field of polyploid research to herbaria.K E Y W O R D S discriminant analysis of principal components (DAPC), herbaria, infrared spectroscopy, neural network, polyploidy, Veronica Appl. Plant Sci.

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Phylogeny of cultivated and wild wheat species using ATR–FTIR spectroscopy

Cited by 47 publications

References 41 publications

Structural effects of simvastatin on rat liver tissue: Fourier transform infrared and Raman microspectroscopic studies

Structural effects of simvastatin on rat liver tissue: Fourier transform infrared and Raman microspectroscopic studies

Environmentally-related genotypic, phenotypic and metabolic diversity of oat (Avena sativa L.) landraces based on 67 Polish accessions

Infrared spectroscopy for ploidy estimation: An example in two species of Veronica using fresh and herbarium specimens

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