Template-Oriented Genetic Algorithm Feature Selection of Analyte Wavelets in the Raman Spectrum of a Complex Mixture

Tavassoli, Najmeh; Chen, Z.; Bain, Alison; Melo, Larisse Rayanne Miranda de; Chen, D.; Grant, Edward R.

doi:10.1021/ac502203d

Cited by 13 publications

(8 citation statements)

References 50 publications

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“…Here we elect to apply a genetic algorithm (GA) in concert with conventional PLS regression to quantitatively search for the xylan and mannan related signal features. 46 For this purpose, we implement Riccardo’s PLS-GA toolbox in Matlab. 47,48 We seek, in particular, to gain insight from the emphasis of this algorithm on the autocorrelation between the adjacent frequencies, which establishes the most correlated spectral regions, as opposed to dispersed variables.…”

Section: Resultsmentioning

confidence: 99%

Multivariate Analysis of Hemicelluloses in Bleached Kraft Pulp Using Infrared Spectroscopy

Chen

Jang

et al. 2016

Appl Spectrosc

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The hemicellulose composition of a pulp significantly affects its chemical and physical properties and thus represents an important process control variable. However, complicated steps of sample preparation make standard methods for the carbohydrate analysis of pulp samples, such as high performance liquid chromatography (HPLC), expensive and time-consuming. In contrast, pulp analysis by attenuated total internal reflection Fourier transform infrared spectroscopy (ATR FT-IR) requires little sample preparation. Here we show that ATR FT-IR with discrete wavelet transform (DWT) and standard normal variate (SNV) spectral preprocessing offers a convenient means for the qualitative and quantitative analysis of hemicelluloses in bleached kraft pulp and alkaline treated kraft pulp. The pulp samples investigated include bleached softwood kraft pulps, bleached hardwood kraft pulps, and their mixtures, as obtained from Canadian industry mills or blended in a lab, and bleached kraft pulp samples treated with 0-6% NaOH solutions. In the principal component analysis (PCA) of these spectra, we find the potential both to differentiate all pulps on the basis of hemicellulose compositions and to distinguish bleached hardwood pulps by species. Partial least squares (PLS) multivariate analysis gives a 0.442 wt% root mean square errors of prediction (RMSEP) for the prediction of xylan content and 0.233 wt% RMSEP for the prediction of mannan content. These data all support the idea that ATR FT-IR has a great potential to rapidly and accurately predict the content of xylan and mannan for bleached kraft pulps (softwood, hardwood, and their mixtures) in industry. However, the prediction of xylan and mannan concentrations presented a difficulty for pulp samples with modified cellulose crystalline structure.

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Section: Resultsmentioning

confidence: 99%

Multivariate Analysis of Hemicelluloses in Bleached Kraft Pulp Using Infrared Spectroscopy

Chen

Jang

et al. 2016

Appl Spectrosc

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“…In recent years, emerging Raman spectroscopy and spectral imaging technologies such as THz imaging have attracted considerable attention in the noninvasive evaluation of sugars in foods (Qin and others ; Tavassoli and others ). Raman spectroscopy is more sensitive to the symmetrical vibrations of the covalent bonds and presents distinct and visible peaks representing the various C‐O, C‐C, and OCH‐bonds in glucose, fructose, and sucrose, the position or shape of which in the Raman profiles are closely related to the contents of the compounds.…”

Section: Emerging Detection Techniques For Sugarsmentioning

confidence: 99%

“…Raman spectroscopy is more sensitive to the symmetrical vibrations of the covalent bonds and presents distinct and visible peaks representing the various C‐O, C‐C, and OCH‐bonds in glucose, fructose, and sucrose, the position or shape of which in the Raman profiles are closely related to the contents of the compounds. Tavassoli and others () identified glucose in a solution of sugar mixtures based on Raman spectroscopy combined with the genetic algorithm, and improved the model accuracy. Since the major peaks in fruits are mainly related to pigments, which produce undesirable background fluorescence, noble metal nanoparticle surface‐enhanced Raman spectroscopy is promising to enhance the weak peaks related to carbohydrates and sense the subtle changes occurring in fruits (Gopal and others ).…”

Section: Emerging Detection Techniques For Sugarsmentioning

confidence: 99%

“…In particular, Magwaza and others () showed the possibility of partial least squares regression (PLSR) models based on NIR spectra (350 to 1000 nm) for predicting fructose, glucose, and sucrose contents in 150 intact mandarin fruits at harvest. However, as a NIR spectrum has a strong response to water, and presents overlapping between peaks of water and sugars, Raman spectroscopy is a good alternative to NIR due to its low response to water (Tavassoli and others ). Moreover, since fruit quality attributes are highly variable and not homogeneous in spatial distributions, with the ability at displaying spatial variation, hyperspectral imaging (HSI) and terahertz (THz) imaging have emerged as possible tools for the evaluation of sugar content in fruits.…”

Section: Introductionmentioning

confidence: 99%

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Recent Developments in Methods and Techniques for Rapid Monitoring of Sugar Metabolism in Fruits

Sun

et al. 2016

Comp Rev Food Sci Food Safe

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The major sugars in fruits, including glucose, fructose, and sucrose, play a critical role in fruit quality control and maturity evaluation. Many novel methods and techniques such as enzymatic and nonenzymatic biosensors, nuclear magnetic resonance, and near-infrared spectroscopy have been developed to provide the rapid estimation of sugar inversion under different storage conditions. This review provides a description of recent advancements in these technologies for the determination of sugar contents in fruits. The prospects of emerging spectroscopic technologies such as Raman spectroscopy, hyperspectral imaging, and terahertz imaging, for assessing sugars in intact fruits are discussed. The challenges for further developments of these methods and technologies to meet the increasing demand for rapid and on-line quality control are also presented.

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“…As spectral data are of high dimensionality and contain useless information, many feature extraction methods as non-negative matrix factorization [22] and principal component analysis (PCA) [23,24] are applied to extract the main information and eliminate irrelevant information. In addition, many preprocessing methods as Savitzky−Golay derivation [25,26], wavelet transform [27] and polynomial fitting [28] are commonly used to eliminate background noise and baseline drift. This study aimed to explore the feasibility of applying SERS and chemometric methods to analyze pirimiphos-methyl in wheat using a portable Raman spectrometer.…”

Section: Introductionmentioning

confidence: 99%

Detection of Pirimiphos-Methyl in Wheat Using Surface-Enhanced Raman Spectroscopy and Chemometric Methods

Weng

Dong

et al. 2019

Molecules

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Pesticide residue detection is a hot issue in the quality and safety of agricultural grains. A novel method for accurate detection of pirimiphos-methyl residues in wheat was developed using surface-enhanced Raman spectroscopy (SERS) and chemometric methods. A simple pretreatment method was conducted to extract pirimiphos-methyl residue from wheat samples, and highly effective gold nanorods were prepared for SERS measurement. Raman peaks assignment was calculated using density functional theory. The Raman signal of pirimiphos-methyl can be detected when the concentrations of residue in wheat extraction solution and contaminated wheat is as low as 0.2 mg/L and 0.25 mg/L, respectively. Quantification of pirimiphos-methyl was performed by applying regression models developed by partial least squares regression, support vector machine regression and random forest with principal component analysis using different preprocessed methods. As for the contaminated wheat samples, the relative deviation between gas chromatography-mass spectrometry value and predicted value is in the range of 0.10%–6.63%, and predicted recovery is 94.12%–106.63%, ranging from 23.93 mg/L to 0.25 mg/L. Results demonstrated that the proposed SERS method is an effective and efficient analytical tool for detecting pirimiphos-methyl in wheat with high accuracy and excellent sensitivity.

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Template-Oriented Genetic Algorithm Feature Selection of Analyte Wavelets in the Raman Spectrum of a Complex Mixture

Cited by 13 publications

References 50 publications

Multivariate Analysis of Hemicelluloses in Bleached Kraft Pulp Using Infrared Spectroscopy

Multivariate Analysis of Hemicelluloses in Bleached Kraft Pulp Using Infrared Spectroscopy

Recent Developments in Methods and Techniques for Rapid Monitoring of Sugar Metabolism in Fruits

Detection of Pirimiphos-Methyl in Wheat Using Surface-Enhanced Raman Spectroscopy and Chemometric Methods

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