scholarly journals Localisation and characterisation of incipient brown-rot decay within spruce wood cell walls using FT-IR imaging microscopy

2010 ◽  
Vol 47 (6) ◽  
pp. 257-267 ◽  
Author(s):  
Karin Fackler ◽  
Jasna S. Stevanic ◽  
Thomas Ters ◽  
Barbara Hinterstoisser ◽  
Manfred Schwanninger ◽  
...  
Holzforschung ◽  
2011 ◽  
Vol 65 (3) ◽  
Author(s):  
Karin Fackler ◽  
Jasna S. Stevanic ◽  
Thomas Ters ◽  
Barbara Hinterstoisser ◽  
Manfred Schwanninger ◽  
...  

AbstractSpruce wood that had been degraded by white-rot fungi (Trametes versicolororCeriporiopsis subvermispora)and suffered mass losses up to 17% was investigated by transmission Fourier transform infrared (FT-IR) imaging microscopy. A significant marker during incipient simultaneous white-rot (T. versicolor) was the cleavage of glycosidic bonds of polysaccharides that preceded their metabolisation. Simultaneous white-rot processes were also characterised by a relative decrease of the overall lignin content and a relative accumulation of wood polysaccharides. No early marker was found for selective white-rot (C. subvermispora) that removes mainly lignin by an oxidative process. This feature was detected only in wood samples exhibiting mass losses higher than 12%. Furthermore, it was shown, that simultaneous and selective white-rot processes were unevenly distributed within the wood samples but quite evenly distributed within single tracheids.


2016 ◽  
Vol 85 ◽  
pp. 202-207 ◽  
Author(s):  
Sefa Durmaz ◽  
Özlem Özgenç ◽  
İsmail H. Boyacı ◽  
Ümit C. Yıldız ◽  
Emir Erişir

2012 ◽  
Vol 62 ◽  
pp. 279-285 ◽  
Author(s):  
Elisabetta Giorgini ◽  
Giorgia Gioacchini ◽  
Carla Conti ◽  
Paolo Ferraris ◽  
Simona Sabbatini ◽  
...  

The Analyst ◽  
2013 ◽  
Vol 138 (21) ◽  
pp. 6645 ◽  
Author(s):  
Tomasz P. Wrobel ◽  
Lukasz Mateuszuk ◽  
Renata B. Kostogrys ◽  
Stefan Chlopicki ◽  
Malgorzata Baranska

2021 ◽  
pp. 000370282110509
Author(s):  
Laurin Lux ◽  
Yamuna Dilip Phal ◽  
Pei-Hsuan Hsieh ◽  
Rohit Bhargava

Infrared (IR) spectroscopic imaging instruments’ performance can be characterized and optimized by an analysis of their limit of detection (LoD). Here we report a systematic analysis of the LoD for Fourier transform IR (FT-IR) and discrete frequency IR (DFIR) imaging spectrometers. In addition to traditional measurements of sample and blank data, we propose a decision theory perspective to pose the determination of LoD as a binary classification problem under different assumptions of noise uniformity and correlation. We also examine three spectral analysis approaches, namely absorbance at a single frequency, sum of absorbance over selected frequencies and total spectral distance – to suit instruments that acquire discrete or contiguous spectral bandwidths. The analysis is validated by refining the fabrication of a bovine serum albumin protein microarray to provide eight uniform spots from 2.8 nL of solution for each concentration over a wide range (0.05 -10 mg/mL). Using scanning parameters that are typical for each instrument, we estimate a LoD of 0.16 mg/mL and 0.12 mg/mL for widefield and line scanning FT-IR imaging systems, respectively, usingthespectraldistanceapproach,and0.22mg/mLand0.15mg/mL using an optimal set of discrete frequencies. As expected, averaging and the use of post-processing techniques such as minimum noise fraction (MNF) transformation results in LoDs as low as 0.075 mg/mL that correspond to a spotted protein mass of 112 fg/pixel. We emphasize that these measurements were conducted at typical imaging parameters for each instrument and can be improved using the usual trading rules of IR spectroscopy. This systematic analysis and methodology for determining the LoD can allow for quantitative measures of confidence in imaging an analyte’s concentration and a basis for further improving IR imaging technology.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Paulina Koziol ◽  
Magda K. Raczkowska ◽  
Justyna Skibinska ◽  
Sławka Urbaniak-Wasik ◽  
Czesława Paluszkiewicz ◽  
...  

The Analyst ◽  
2021 ◽  
Author(s):  
Danuta Liberda ◽  
Paulina Koziol ◽  
Magda K. Raczkowska ◽  
Wojciech M. Kwiatek ◽  
Tomasz P. Wrobel

Infrared (IR) imaging can be used for fast, accurate and non-destructive pathology recognition of biopsies when supported by machine learning algorithms regardless of the presence of interference effects obscuring the spectra.


Trees ◽  
2004 ◽  
Vol 18 (1) ◽  
pp. 102-108 ◽  
Author(s):  
Notburga Gierlinger ◽  
Dominique Jacques ◽  
Michael Grabner ◽  
Rupert Wimmer ◽  
Manfred Schwanninger ◽  
...  

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