scholarly journals Anatomical Properties and Near Infrared Spectra Characteristics of Four Shorea Species from Indonesia

2020 ◽  
Vol 27 (3) ◽  
pp. 247
Author(s):  
Danang Sudarwoko Adi ◽  
Sung-Wook Hwang ◽  
Dwi Ajias Pramasari ◽  
Yusup Amin ◽  
Hairi Cipta ◽  
...  

This study investigated the anatomical properties and absorbance characteristics of NIR spectra of four Shorea species from Indonesia. Macroscopic section revealed that Balau has similarity with Heavy Red Meranti, whereas White Meranti was almost identical with Light Red Meranti. All of the woods have diffuse porous and axial resin canals in tangential lines at the microscopic level. Original NIR spectra of Shorea species showed different absorbance characteristic. Wood density was assumed to be one of the factors that affected to the absorbances. Principal component analysis (PCA) of second derivative NIR spectra at the wavenumber 8,000-4,000 cm-1 (full) and 6,200-5,600 cm-1 (specific) showed different orientation among the Principal Component (PC) number. PC1, which contained highest spectral variation, had two closed clusters (1) Balau and Heavy Red Meranti and (2) White and Light Red Meranti at full spectral range. In contrast, the results at specific range were (1) Balau and White Meranti and (2) Heavy and Light Red Meranti. Hierarchical clustering dendrogram using PCA data from two spectral regions resulted in two types of clustering, the 8,000-4,000 cm-1 was somehow related to ‘density’, while the 6,200-5,600 cm-1 was grouped in ‘color’ information from visual inspection.  From both spectral regions, k-nearest neighbour (k-NN) classification models revealed 100% accuracy in identification four Shorea species using NIR spectra.

NIR news ◽  
2019 ◽  
Vol 30 (3) ◽  
pp. 6-8
Author(s):  
Mirosław Antoni Czarnecki ◽  
Michał Kwaśniewicz

This work shows the effect of the chain length on near-infrared spectra of 1-alcohols and is based on a recent paper by Kwaśniewicz and Czarnecki ( Appl Spectrosc 2018, 72: 288). Near-infrared spectra of 1-alcohols from methanol to 1-decanol in the pure liquid phase were recorded from 5200 to 9000 cm−1. The similarities and differences between the spectra were analyzed by the classical and chemometric methods (principal component analysis). The obtained results reveal that the near-infrared spectra of methanol, ethanol, and 1-propanol are appreciably different from the spectra of higher 1-alcohols. As shown, the degree of self-association of 1-alcohols decreases with the increase in the chain length.


2018 ◽  
Vol 72 (8) ◽  
pp. 1199-1204 ◽  
Author(s):  
Xiaoli Luan ◽  
Minjun Jin ◽  
Fei Liu

The fault detection problem of the oil desalting process is investigated in this paper. Different from the traditional fault detection approaches based on measurable process variables, near-infrared (NIR) spectroscopy is applied to acquire the process fault information from the molecular vibrational signal. With the molecular spectra data, principal component analysis was explored to calculate the Hotelling T2 and squared prediction error, which act as fault indicators. Compared with the traditional fault detection approach based on measurable process variables, NIR spectra-based fault detection illustrates more sensitivity to early failure because of the fact that the changes in the molecular level can be identified earlier than the physical appearances on the process. The application results show that the detection time of the proposed method is earlier than the traditional method by about 200 min.


2013 ◽  
Vol 827 ◽  
pp. 209-212
Author(s):  
Xiao Li Yang ◽  
Fan Wang ◽  
Wen Chao Wang ◽  
Yun Xiu Chen ◽  
Ji Shu Chen

We studied moisture determination in bituminous coal and lignitic coal samples using near-infrared (NIR) spectra. This research was developed by applying partial least squares regression (PLS) and discrete wavelet transform (DWT). Firstly, the NIR spectra were pre-processed by DWT for fitting and compression. Then, the compressed data were used to build regression model with PLS for moisture determination in coal samples. Compression performance at different resolution scales was investigated. Using the compressed data, PLS can obtain more accurate result than using raw spectra. The number of principal component in PLS model was investigated too. The results show DWT-PLS can obtain satisfactory determination performance for moisture analysis in bituminous coal and lignitic coal.


2003 ◽  
Vol 11 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Laila Stordrange ◽  
Olav M. Kvalheim ◽  
Per A. Hassel ◽  
Dick Malthe-Sørenssen ◽  
Fred Olav Libnau

Partial least squares (PLS) is a powerful tool for multivariate linear regression. But what if the data show a non-linear structure? Near infrared spectra from a pharmaceutical process were used as a case study. An ANOVA test revealed that the data are well described by a 2nd order polynomial. This work investigates the application of regression techniques that account for slightly non-linear data. The regression techniques investigated are: linearising data by applying transformations, local PLS, i.e. splitting of data, and quadratic PLS. These models were compared with ordinary PLS and principal component regression (PCR). The predictive ability of the models was tested on an independent data set acquired a year later. Using the knowledge of non-linear pattern and important spectral regions, simpler models with better predictive ability can be obtained.


2014 ◽  
Vol 926-930 ◽  
pp. 961-964
Author(s):  
Jiao Jiao Yin

Because the reflectivity of astaxanthin vary in different bands (mainly 400nm-600nm), so we use the visible-near infrared spectra technique to irradiate the salmon. Because in daily life, people grade the salmon flesh with a color card. In this paper, we first use principal component analysis to reduce the dimensionality of the spectral data of salmon, then use linear discriminant analysis method, least squares support vector machine classification method to distinguish the flesh quality. The correct classification rates are 60%and73.3%. The results show that we can use visible – near infrared spectra to distinguish the quality of the salmon which doesn’t be dissected.


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