MWPLS Method Applied to the Waveband Selection of NIR Spectroscopy Analysis for Brix Degree of Sugarcane Clarified Juice

2011 ◽  
Author(s):  
Pan Tao ◽  
Shan Yu ◽  
Wu Zhentao ◽  
Chen Zenghai ◽  
Li Pengzhao
Keyword(s):  
Nir Spectroscopy ◽  
Spectroscopy Analysis ◽  
Selection Of ◽  
Brix Degree

Waveband Selection for NIR Spectroscopy Analysis of Wastewater COD

2011 ◽  
Vol 480-481 ◽  
pp. 393-396 ◽  
Author(s):  
Tao Pan ◽  
Wei Wei Chen ◽  
Zeng Hai Chen ◽  
Jun Xie
Keyword(s):  
Model Prediction ◽  
Near Infrared ◽  
Oxygen Demand ◽  
Nir Spectroscopy ◽  
Model Complexity ◽  
Moving Window ◽  
Optimal Model ◽  
Spectroscopy Analysis ◽  
Selection For ◽  
Selection Of

Waveband selection of near-infrared (NIR) spectroscopy analysis of wastewater chemical oxygen demand (COD) by moving window partial least squares (MWPLS) method with changeable size, the optimization of PLS factor was combined with MWPLS method. According to the prediction effect, the optimal model was selected, and the corresponding waveband, number of adopted wavelengths, PLS factor, RMSEP, RP were 820-850nm, 16, 13, 25.5 mg/L, and 0.968 respectively, which was obviously superior to the optimal PLS model on the whole spectral collecting region. The result shows that the MWPLS method can improve the model prediction effect, reduce model complexity, and provide valuable reference for designing special NIR spectrometer.

Prediction of Stilbene Content from Heartwood Increment Cores of Scots Pine Using near Infrared Spectroscopy Methodology

2016 ◽  
Vol 24 (6) ◽  
pp. 517-528 ◽  
Author(s):  
Susanna Pulkka ◽  
Vincent Segura ◽  
Anni Harju ◽  
Tarja Tapanila ◽  
Johanna Tanner ◽  
...  
Keyword(s):  
Scots Pine ◽  
High Throughput ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tree Breeding ◽  
Decay Resistance ◽  
Increment Core ◽  
Automatic Selection ◽  
Non Destructive ◽  
Selection Of

High-throughput and non-destructive methods for quantifying the content of the stilbene compounds of Scots pine ( Pinus sylvestris L.) heartwood are needed in the breeding for decay resistance of heartwood timber. In this study, near infrared (NIR) spectroscopy calibrations were developed for a large collection of solid heartwood increment core samples in order to predict the amount of the stilbene pinosylvin (PS), its monomethyl ether (PSM) and their sum (STB). The resulting models presented quite accurate predictions in an independent validation set with R2V values ranging between 0.79 and 0.91. The accuracy of the models strongly depended on the chemical being calibrated, with the lowest accuracy for PS, intermediate accuracy for PSM and highest accuracy for STB. The effect of collecting one, two or more (up to five) spectra per sample on the calibration models was studied and it was found that averaging multiple spectra yielded better accuracy as it may account for the heterogeneity of wood along the increment core within and between rings. Several statistical pretreatments of the spectra were tested and an automatic selection of wavenumbers prior to calibration. Without the automatic selection of wavenumbers, a first derivative of normalised spectra yielded the best accuracies, whereas after the automatic selection of wavenumbers, no particular statistical pretreatment appeared to yield better results than any other. Finally, the automatic selection of wavenumbers slightly improved the accuracy of the models for all traits. These results demonstrate the potential of NIR spectroscopy as a high-throughput and non-destructive phenotyping technique in tree breeding for the improvement of decay resistance in heartwood timber.

Generalized two-dimensional correlation NIR spectroscopy analysis of the structures on n-propanol and n-butanol

2019 ◽  
Vol 1181 ◽  
pp. 436-443 ◽  
Author(s):  
Hao Liu ◽  
Weiming Zhou ◽  
Dong Ying ◽  
Bingren Xiang ◽  
Pinggan Li
Keyword(s):  
Nir Spectroscopy ◽  
Two Dimensional ◽  
Spectroscopy Analysis

Effects of measurement technique and sample preparation on NIR spectroscopy analysis of livestock slurry and digestates

2015 ◽  
Vol 134 ◽  
pp. 42-54 ◽  
Author(s):  
A. Finzi ◽  
R. Oberti ◽  
A.S. Negri ◽  
F. Perazzolo ◽  
G. Cocolo ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Measurement Technique ◽  
Nir Spectroscopy ◽  
Spectroscopy Analysis

Model Optimization for near-Infrared Spectroscopy Analysis of Chemical Oxygen Demand of Wastewater

2012 ◽  
Vol 500 ◽  
pp. 832-837 ◽  
Author(s):  
Tao Pan ◽  
Wei Wei Chen ◽  
Wen Jie Huang ◽  
Rui Tuo Qu
Keyword(s):  
Chemical Oxygen Demand ◽  
Near Infrared ◽  
Oxygen Demand ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Simultaneous Optimization ◽  
Model Optimization ◽  
Spectroscopy Analysis ◽  
Smoothing Parameters

A directly rapid quantitative analysis method for chemical oxygen demand (COD) of wastewater samples was established by near-infrared (NIR) spectroscopy and partial least square (PLS) method. The optimization of Savitzky-Golay (SG) smoothing modes combined with PLS factor was applied to optimize the model of NIR spectroscopy analysis here. The waveband used for modeling was the combination of 400-1878 nm and 2088-2338 nm. The optimal smoothing parameters were the 5th derivative smoothing, 5th degree polynomial, 17 smoothing points, the optimal PLS factor, root mean squared error of predication (RMSEP) and correlation coefficient of predication (RP) were 7, 33.2 (mg/L) and 0.929 respectively, which was obviously superior to the direct PLS model without SG smoothing and ones based on the whole spectral collecting region 400-2500 nm. This demonstrated that NIR spectroscopy can be applied to the rapid determination of COD of wastewater, large-scale simultaneous optimization selection of SG smoothing parameters and PLS factor can be effectively applied to the model optimization of NIR analysis.

scholarly journals The Combined Optimization of Savitzky-Golay Smoothing and Multiplicative Scatter Correction for FT-NIR PLS Models

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Huazhou Chen ◽  
Qiqing Song ◽  
Guoqiang Tang ◽  
Quanxi Feng ◽  
Liang Lin
Keyword(s):  
Latent Variables ◽  
Near Infrared ◽  
Scatter Correction ◽  
Nir Spectroscopy ◽  
Spectroscopy Analysis ◽  
Multiplicative Scatter Correction ◽  
Pls Modeling ◽  
Smoothing Parameters ◽  
Better Than

The combined optimization of Savitzky-Golay (SG) smoothing and multiplicative scatter correction (MSC) were discussed based on the partial least squares (PLS) models in Fourier transform near-infrared (FT-NIR) spectroscopy analysis. A total of 5 cases of separately (or combined) using SG smoothing and MSC were designed and compared for optimization. For every case, the SG smoothing parameters were optimized with the number of PLS latent variables (F), with an expanded number of smoothing points. Taking the FT-NIR analysis of soil organic matter (SOM) as an example, the joint optimization of SG smoothing and MSC was achieved based on PLS modeling. The results showed that the optimal pretreatment was successively using SG smoothing and MSC, in which the SG smoothing parameters were 4th degree of polynomial, 2nd-order derivative, and 67 smoothing points, the best corresponding F, RMSEP, and RP were 7, 0.3982 (%), and 0.8862, respectively. This result was far better than those without any pretreatment. The combined optimization of SG smoothing and MSC could obviously improve the modeling result for NIR analysis of SOM. In addition, a new method for the classification of calibration and prediction was proposed by normalization principle. The optimizations were done on this basis of this classification.

An efficient method to reduce grain angle influence on NIR spectra for predicting extractives content from heartwood stem cores of T. sinensis

2019 ◽  
Author(s):  
Yanjie Li ◽  
Xin Dong ◽  
Yang Sun ◽  
Jun Liu ◽  
Jingmin Jiang
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Solid Wood ◽  
Normal Variation ◽  
Grain Angle ◽  
Multivariate Correlation ◽  
Standard Normal ◽  
Predict Model ◽  
Non Destructive ◽  
Selection Of

Abstract BackgroundA fast and reliable non-destructive method for qualifying the content of extracts content (EC) in heartwood of T. sinensis cores is needed in the breeding program for studying the genetically infect on EC. However, the affecting of grain angle on near infrared (NIR) spectra prediction model for EC is unclear. In this study, NIR spectra were collected both from cross section and radial section of wood core samples in order to predict the EC in heartwood.ResultsThe effect of grain angle on calibration EC model was studied. Several different spectra pre-processing methods were tested for calibration. It was found that standard normal variation (SNV) followed by 1st derivative yield the best calibration for EC. Grain angle has a significant influence on the predict model for EC when use the whole NIR spectra. However, after using the significant multivariate correlation (sMC) selection of the prior of wavenumbers for EC, the influence of grain angle have been significantly reduced. ConclusionsIt was suggested that NIR spectroscopy could be a promising methods to predict EC in solid wood without the infection of grain angle.

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