Application of Extended Multiplicative Signal Correction to Short-Wavelength near Infrared Spectra of Moisture in Marzipan

Panero, Pedro dos Santos; Panero, Francisco dos Santos; Panero, João dos Santos; Silva, Henrique Eduardo Bezerra da

doi:10.4236/jdaip.2013.13005

Cited by 12 publications

(8 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The multiplicative scatter correction (MSC) (Martens, Jensen, & Geladi, 1983) is one of the most commonly applied corrections because of its ability to estimate and remove both additive and multiplicative effects. The multiplicative scatter correction is achieved by regressing a measured spectrum against a reference spectrum, commonly the average of all samples (Martens & Naes, 1989; Santos Panero, Santos Panero, Santos Panero, & Bezerra da Silva, 2013). Other common scatter correction methods include extended multiplicative scatter correction (EMSC) (Martens & Stark, 1991), detrending, and standard normal variate (SNV) correction (Barnes, Dhanoa, & Lister, 1989).…”

Section: Approaches To Hyperspectral Analysismentioning

confidence: 99%

Approaches, applications, and future directions for hyperspectral vegetation studies: An emphasis on yield‐limiting factors in wheat

Bruning

Berger

Lewis

et al. 2020

The Plant Phenome Journal

View full text Add to dashboard Cite

Hyperspectral instruments acquire spectral information in many narrow, contiguous bands throughout the visible, near-infrared and shortwave regions of the electromagnetic spectrum. Hyperspectral techniques are becoming very powerful tools for characterizing plants and nondestructively quantifying their chemical and physical properties because of their ability to provide layered trait information within the same spectral region. However, to effectively make use of hyperspectral sensing, an understanding of the theory behind these techniques, the power, and the limitations of the resulting data is required. This article presents an overview of hyperspectral sensing in regard to principles, instrumentation, processing methods, and current applications, specifically focusing on the quantification of yield-limiting factors in wheat (Triticum aestivum L.). The spectral properties of plants across the electromagnetic spectrum are first described to achieve a better understanding of plant-light interactions. Basic information about different imaging approaches is provided as are the necessary considerations for the analysis of hyperspectral data. Some of the major technical challenges associated with hyperspectral imaging as well as future directions are discussed. Finally, as an example crop, the use of hyperspectral techniques for quantifying yield-limiting factors in wheat is presented.

show abstract

Section: Approaches To Hyperspectral Analysismentioning

confidence: 99%

Approaches, applications, and future directions for hyperspectral vegetation studies: An emphasis on yield‐limiting factors in wheat

Bruning

Berger

Lewis

et al. 2020

The Plant Phenome Journal

View full text Add to dashboard Cite

show abstract

“…EMSC is a model-based pre-processing algorithm, capable to correct physical and chemical features in IR reflectance. It provides baseline correction and normalization as well as separation and quantification of chemical and physical variations in the vibrational spectra, making the subsequent calibration models simpler and statistically more robust (Panero et al 2013). Although it loses some information, it estimates mathematical parameters instead, which can be used to study the different effects separately (Afseth and Kohler 2012).…”

Section: Ftir Analysismentioning

confidence: 99%

FTIR analysis of chemical changes in wood induced by steaming and longitudinal compression

et al. 2020

View full text Add to dashboard Cite

Pleating is an optimal way to increase bendability of wood used in diverse industrial applications. It results in the excessive buckling of cell walls and modifications of constitutive polymers. However, thoughtful understanding of the physical–chemical mechanisms of that modification process is very limited. The main purpose of the present study was to identify changes in functional groups of wood polymers induced by longitudinal compression. Four types of wood samples prepared from beech and sessile oak (untreated, steamed, longitudinally compressed and fixated for 1 min as well as longitudinally compressed and fixated for 18 h) were assessed by infrared spectroscopy. The spectra interpretation revealed that changes can be observed in hydroxyl as well as in carbon–oxygen single and carbon-hydrogen functional groups of polysaccharides and lignin. Beech wood seems to be more susceptible to investigated modification processes as compared to oak. Detailed interpretation of infrared spectra allows identification of changes in the hygroscopicity of wood as well as alterations in the linkage between structural elements in the polymer matrix of wood induced by the applied treatments. Graphic Abstract

show abstract

“…The advantages were as follows: In the wavelet domain, DWT transformed discrete signals into approximate wavelet coefficients and detailed wavelet coefficients more quickly and conveniently. The data collected by the spectrometer are distributed in the range of 600–2400 nm in the form of discrete data points, which is the commonality of mainstream spectrometers [ 39 , 40 , 41 ]. Therefore, the discrete wavelet transformation is a good prospect in the field of NIR analysis, especially in the aspects of noise reduction and spectral data compression.…”

Section: Discussionmentioning

confidence: 99%

Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds

Jiang

Cao

et al. 2020

Sensors

View full text Add to dashboard Cite

Lipid content is an important indicator of the edible and breeding value of Pinus koraiensis seeds. Difference in origin will affect the lipid content of the inner kernel, and neither can be judged by appearance or morphology. Traditional chemical methods are small-scale, time-consuming, labor-intensive, costly, and laboratory-dependent. In this study, near-infrared (NIR) spectroscopy combined with chemometrics was used to identify the origin and lipid content of P. koraiensis seeds. Principal component analysis (PCA), wavelet transformation (WT), Monte Carlo (MC), and uninformative variable elimination (UVE) methods were used to process spectral data and the prediction models were established with partial least-squares (PLS). Models were evaluated by R2 for calibration and prediction sets, root mean standard error of cross-validation (RMSECV), and root mean square error of prediction (RMSEP). Two dimensions of input data produced a faster and more accurate PLS model. The accuracy of the calibration and prediction sets was 98.75% and 97.50%, respectively. When the Donoho Thresholding wavelet filter ‘bior4.4’ was selected, the WT–MC–UVE–PLS regression model had the best predictions. The R2 for the calibration and prediction sets was 0.9485 and 0.9369, and the RMSECV and RMSEP were 0.0098 and 0.0390, respectively. NIR technology combined with chemometric algorithms can be used to characterize P. koraiensis seeds.

show abstract

Application of Extended Multiplicative Signal Correction to Short-Wavelength near Infrared Spectra of Moisture in Marzipan

Cited by 12 publications

References 17 publications

Approaches, applications, and future directions for hyperspectral vegetation studies: An emphasis on yield‐limiting factors in wheat

Approaches, applications, and future directions for hyperspectral vegetation studies: An emphasis on yield‐limiting factors in wheat

FTIR analysis of chemical changes in wood induced by steaming and longitudinal compression

Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds

Contact Info

Product

Resources

About