Discrimination of Maize Seeds by Near Infrared Ray Hyperspectral Imaging with Local Learning

2015 ◽  
Vol 52 (4) ◽  
pp. 041102
Author(s):  
唐金亚 Tang Jinya ◽  
黄敏 Huang Min ◽  
朱启兵 Zhu Qibing
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Local Learning ◽  
Maize Seeds ◽  
Near Infrared Ray

scholarly journals Application of near-infrared hyperspectral imaging to identify a variety of silage maize seeds and common maize seeds

RSC Advances ◽  
2020 ◽  
Vol 10 (20) ◽  
pp. 11707-11715 ◽  
Author(s):  
Xiulin Bai ◽  
Chu Zhang ◽  
Qinlin Xiao ◽  
Yong He ◽  
Yidan Bao
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Silage Maize ◽  
Maize Seeds

NIR-HSI and chemometrics were used to identify different varieties of common and silage maize seeds.

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.

Application of long-wave near infrared hyperspectral imaging for determination of moisture content of single maize seed

2021 ◽  
Vol 254 ◽  
pp. 119666
Author(s):  
Zheli Wang ◽  
Shuxiang Fan ◽  
Jingzhu Wu ◽  
Chi Zhang ◽  
Fengying Xu ◽  
...  
Keyword(s):  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Maize Seed ◽  
Long Wave

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

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

Near-infrared-ray computed tomography with an 808 nm laser beam and high spatial resolutions

2021 ◽  
Vol 92 (1) ◽  
pp. 013702
Author(s):  
Eiichi Sato ◽  
Yasuyuki Oda ◽  
Sohei Yoshida ◽  
Kunihiro Yoshioka ◽  
Hodaka Moriyama ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Laser Beam ◽  
Near Infrared ◽  
Near Infrared Ray

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

Visible and near-infrared hyperspectral imaging techniques allow the reliable quantification of prognostic markers in lymphomas: A pilot study using the Ki67 proliferation index as an example

2020 ◽  
Vol 91 ◽  
pp. 55-64
Author(s):  
Ella Willenbacher ◽  
Andrea Brunner ◽  
Wolfgang Willenbacher ◽  
Bettina Zelger ◽  
Dominik Wolf ◽  
...  
Keyword(s):  
Pilot Study ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Prognostic Markers ◽  
Imaging Techniques ◽  
Proliferation Index ◽  
Reliable Quantification

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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