Showing results (11-20 of 37) with videos related to

Sort By:
Pageof 4
Analytical Sciences : the International Journal of the Japan Society for Analytical Chemistry|March 29, 2022
Application of near-infrared spectroscopy to agriculture and forestrySatoru Tsuchikawa, Te Ma, Tetsuya Inagaki
Plos One|May 5, 2017
The effect of path length, light intensity and co-added time on the detection limit associated with NIR spectroscopy of potassium hydrogen phthalate in aqueous solutionTetsuya Inagaki, Tomoko Watanabe, Satoru Tsuchikawa
Applied Spectroscopy|August 16, 2008
Near-infrared spectroscopic monitoring of the water adsorption/desorption process in modern and archaeological woodTetsuya Inagaki, Hitoshi Yonenobu, Satoru Tsuchikawa
Applied Spectroscopy|November 15, 2008
Near-infrared spectroscopic investigation of the hydrothermal degradation mechanism of wood as an analogue of archaeological objects. Part I: softwoodTetsuya Inagaki, Katsuya Mitsui, Satoru Tsuchikawa
Biomacromolecules|December 11, 2007
Monitoring of hydroxyl groups in wood during heat treatment using NIR spectroscopyKatsuya Mitsui, Tetsuya Inagaki, Satoru Tsuchikawa
The Analyst|February 23, 2005
Near-infrared spectroscopic observation of the ageing process in archaeological wood using a deuterium exchange methodSatoru Tsuchikawa, Hitoshi Yonenobu, H W Siesler
Applied Spectroscopy|August 16, 2008
Discriminant analyzing system for wood wastes using a visible-near-infrared chemometric imaging techniqueHikaru Kobori, Hitoshi Yonenobu, Junichi Noma, et al.
Optics Express|May 4, 2016
Optical properties of drying wood studied by time-resolved near-infrared spectroscopyKeiji Konagaya, Tetsuya Inagaki, Ryunosuke Kitamura, et al.
Foods (Basel, Switzerland)|January 25, 2025
The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging TechnologyHidemasa Taketoshi, Tetsuya Inagaki, Satoru Tsuchikawa, et al.
The Analyst|October 8, 2019
Cognitive spectroscopy for wood species identification: near infrared hyperspectral imaging combined with convolutional neural networksHideaki Kanayama, Te Ma, Satoru Tsuchikawa, et al.
Pageof 4