Toward a UV–visible–near-infrared hyperspectral imaging platform for fast multiplex reflection spectroscopy

2010 ◽  
Vol 35 (20) ◽  
pp. 3330 ◽  
Author(s):  
Jianping Li ◽  
Robert K. Y. Chan
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Reflection Spectroscopy ◽  
Uv Visible

Pork Tissue Recognition Using Visible and Near Infrared Hyperspectral Imaging

2020 ◽  
Author(s):  
Chih-Cheng Pai ◽  
Yang-Chu Chen ◽  
Keng-Hao Liu ◽  
Yuan-Hsun Tsai ◽  
Po-Chi Hu ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared

scholarly journals Identification of peat type and humification by laboratory VNIR/SWIR hyperspectral imaging of peat profiles with focus on fen-bog transition in aapa mires

2020 ◽  
Author(s):  
L. Granlund ◽  
M. Keinänen ◽  
T. Tahvanainen
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Support Vector ◽  
High Resolution Imaging ◽  
Factors Affecting ◽  
Vector Machines ◽  
Resolution Imaging ◽  
Shortwave Infrared ◽  
Type Classification ◽  
Wide Potential

Abstract Aims Hyperspectral imaging (HSI) has high potential for analysing peat cores, but methodologies are deficient. We aimed for robust peat type classification and humification estimation. We also explored other factors affecting peat spectral properties. Methods We used two laboratory setups: VNIR (visible to near-infrared) and SWIR (shortwave infrared) for high resolution imaging of intact peat profiles with fen-bog transitions. Peat types were classified with support vector machines, indices were developed for von Post estimation, and K-means clustering was used to analyse stratigraphic patterns in peat quality. With separate experiments, we studied spectral effects of drying and oxidation. Results Despite major effects, oxidation and water content did not impede robust HSI classification. The accuracy between Carex peat and Sphagnum peat in validation was 80% with VNIR and 81% with SWIR data. The spectral humification indices had accuracies of 82% with VNIR and 56%. Stratigraphic HSI patterns revealed that 36% of peat layer shifts were inclined by over 20 degrees. Spectral indices were used to extrapolate visualisations of element concentrations. Conclusions HSI provided reliable information of basic peat quality and was useful in visual mapping, that can guide sampling for other analyses. HSI can manage large amounts of samples to widen the scope of detailed analysis beyond single profiles and it has wide potential in peat research beyond the exploratory scope of this paper. We were able to confirm the capacity of HSI to reveal shifts of peat quality, connected to ecosystem-scale change.

Spatial distribution of total polyphenols in multi-type of tea using near-infrared hyperspectral imaging

LWT ◽  
2021 ◽  
pp. 111737
Author(s):  
Yujie Wang ◽  
Ying Liu ◽  
Yuyu Chen ◽  
Qingqing Cui ◽  
Luqing Li ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Total Polyphenols

scholarly journals Dermacozine N, the First Natural Linear Pentacyclic Oxazinophenazine with UV–Vis Absorption Maxima in the Near Infrared Region, Along with Dermacozines O and P Isolated from the Mariana Trench Sediment Strain Dermacoccus abyssi MT 1.1T

Marine Drugs ◽  
2021 ◽  
Vol 19 (6) ◽  
pp. 325
Author(s):  
Bertalan Juhasz ◽  
Dawrin Pech-Puch ◽  
Jioji N. Tabudravu ◽  
Bastien Cautain ◽  
Fernando Reyes ◽  
...  
Keyword(s):  
Linear Regression ◽  
Density Functional ◽  
Near Infrared ◽  
Linear Regression Analysis ◽  
2D Nmr ◽  
Multiple Linear Regression Analysis ◽  
Infrared Region ◽  
Cellular Level ◽  
Mariana Trench ◽  
Uv Visible

Three dermacozines, dermacozines N–P (1–3), were isolated from the piezotolerant Actinomycete strain Dermacoccus abyssi MT 1.1T, which was isolated from a Mariana Trench sediment in 2006. Herein, we report the elucidation of their structures using a combination of 1D/2D NMR, LC-HRESI-MSn, UV–Visible, and IR spectroscopy. Further confirmation of the structures was achieved through the analysis of data from density functional theory (DFT)–UV–Visible spectral calculations and statistical analysis such as two tailed t-test, linear regression-, and multiple linear regression analysis applied to either solely experimental or to experimental and calculated 13C-NMR chemical shift data. Dermacozine N (1) bears a novel linear pentacyclic phenoxazine framework that has never been reported as a natural product. Dermacozine O (2) is a constitutional isomer of the known dermacozine F while dermacozine P (3) is 8-benzoyl-6-carbamoylphenazine-1-carboxylic acid. Dermacozine N (1) is unique among phenoxazines due to its near infrared (NIR) absorption maxima, which would make this compound an excellent candidate for research in biosensing chemistry, photodynamic therapy (PDT), opto-electronic applications, and metabolic mapping at the cellular level. Furthermore, dermacozine N (1) possesses weak cytotoxic activity against melanoma (A2058) and hepatocellular carcinoma cells (HepG2) with IC50 values of 51 and 38 μM, respectively.

A method using near infrared hyperspectral imaging to highlight the internal quality of apple fruit slices

2021 ◽  
Vol 175 ◽  
pp. 111497
Author(s):  
Weijie Lan ◽  
Benoit Jaillais ◽  
Catherine M.G.C. Renard ◽  
Alexandre Leca ◽  
Songchao Chen ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Apple Fruit ◽  
Internal Quality

Evaluation of melon drying using hyperspectral imaging technique in the near infrared region

LWT ◽  
2021 ◽  
Vol 143 ◽  
pp. 111092
Author(s):  
Jose Marcelino S. Netto ◽  
Fernanda A. Honorato ◽  
Patrícia M. Azoubel ◽  
Louise E. Kurozawa ◽  
Douglas F. Barbin
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging Technique ◽  
Infrared Region ◽  
Near Infrared Region

Bison muscle discrimination and color stability prediction using near-infrared hyperspectral imaging

2021 ◽  
Vol 209 ◽  
pp. 1-13
Author(s):  
Muhammad Mudassir Arif Chaudhry ◽  
Md Mahmudul Hasan ◽  
Chyngyz Erkinbaev ◽  
Jitendra Paliwal ◽  
Surendranath Suman ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Color Stability ◽  
Stability Prediction
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