Application of near-infrared spectroscopy for the fast detection and sorting of wood–plastic composites and waste wood treated with wood preservatives

2015 ◽  
Vol 50 (2) ◽  
pp. 313-331 ◽  
Author(s):  
Dirk Mauruschat ◽  
Burkhard Plinke ◽  
Jochen Aderhold ◽  
Jan Gunschera ◽  
Peter Meinlschmidt ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Wood Preservatives ◽  
Waste Wood ◽  
Wood Plastic Composites ◽  
Fast Detection ◽  
Plastic Composites

Use of near-infrared spectroscopy for prediction of biomass and polypropylene in wood plastic composites

2016 ◽  
Vol 50 (4) ◽  
pp. 705-714 ◽  
Author(s):  
Gaiyun Li ◽  
Wanli Lao ◽  
Xianwu Zou ◽  
Yanming Han ◽  
Dongbin Fan
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Wood Plastic Composites ◽  
Plastic Composites

Detection of Inorganic Wood Preservatives on Timber by near Infrared Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A171-A173 ◽  
Author(s):  
Roger Feldhoff ◽  
Thomas Huth-Fehre ◽  
Karl Cammann
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Treated Wood ◽  
Untreated Wood ◽  
Wood Preservative ◽  
Wood Preservatives ◽  
Copper Salts ◽  
Absorption Bands ◽  
Waste Wood

The recycling of waste wood causes great problems due to the variety of toxic wood preservatives, varnishes and paints used. The fast and reliable distinction and sorting of treated and untreated wood on demolition sites could open new ways of wood recycling, e. g. for the production of chip boards. For this purpose, prepared wood samples treated with inorganic wood preservatives (arsenic, boron, copper salts) were investigated by near infrared-spectroscopy. In most cases, treated wood samples could be distinguished from untreated ones. Furthermore the type of wood preservative could be identified. The observed spectral features are electronic absorption bands and changes in the OH–band due to interaction with salt molecules.

Fast Non-Destructive Detection of Wool Content in Blended Fabrics Based on Near-Infrared Spectroscopy Technology

2015 ◽  
Vol 671 ◽  
pp. 356-362 ◽  
Author(s):  
Zhi Feng Chen ◽  
Yuan Quan Hong ◽  
Chang Jiang Wan ◽  
Lian Ying Zhao
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Detection Method ◽  
Quantitative Model ◽  
National Standard ◽  
Fast Detection ◽  
Significant Difference ◽  
Validation Set ◽  
Non Destructive

A fast non-destructive method of detection of wool content in blended fabrics was studied based on Near Infrared spectroscopy technology in order to avoid the time-consuming, tedious work and the destruction of samples in the traditional inspection. 621 wool/nylon, wool/polyester and wool/nylon/polyester blended fabrics were taken as research objects. To get the wool content, we established the wool near-infrared quantitative model by partial least squares (PLS) method after analyzing the color and composition of the samples. For verifying the validity and practicability of the model, 100 samples were chosen as an independent validation set. The variance analysis shows that there is no significant difference between Near Infrared fast detection method and national standard method (GB/T2910-2009),which indicates that this method is expected to be a means of fast non-destructive detection and will have extensive application future in the field of wool content detection.

Use of near infrared spectroscopy coupled with chemometrics for fast detection of irradiated dry fermented sausages

Food Control ◽  
2020 ◽  
Vol 110 ◽  
pp. 107009 ◽  
Author(s):  
Maria Olga Varrà ◽  
Luca Fasolato ◽  
Lorenzo Serva ◽  
Sergio Ghidini ◽  
Enrico Novelli ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Fast Detection ◽  
Fermented Sausages ◽  
Dry Fermented Sausages

scholarly journals Fast detection of cocoa shell in cocoa powders by near infrared spectroscopy and multivariate analysis

Food Control ◽  
2019 ◽  
Vol 99 ◽  
pp. 68-72 ◽  
Author(s):  
Maribel Alexandra Quelal-Vásconez ◽  
María Jesús Lerma-García ◽  
Édgar Pérez-Esteve ◽  
Alberto Arnau-Bonachera ◽  
José Manuel Barat ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Fast Detection ◽  
Cocoa Shell

Applied Study of Pattern Recognition and Near Infrared Spectroscopy

2012 ◽  
Vol 239-240 ◽  
pp. 223-228
Author(s):  
Jing Yin
Keyword(s):  
Pattern Recognition ◽  
Infrared Spectroscopy ◽  
Olive Oil ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Support Vector ◽  
Fast Detection ◽  
Applied Study ◽  
Detection Technology ◽  
The Status

According to the status of lacking fast detection technology to adulteration olive oil, the paper presented a new method based on near infrared spectroscopy technology and pattern recognition. 10 samples of pure olive oil were collected. 2 kinds of adulteration samples were respectively made up with soybean oil and rapeseed oil. The Identification models were build respectively by support vector machines and hierarchial clustering. The result showed that the model’s performance built by SVM was better than the model by hierarchial clustering. The recognition ratio and prediction ratio of SVM were 100%.The experiments shown that the fast detection technology based on NIR and pattern recognition had better feasibility and practicability in identifying adulteration olive oil.

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