Near-Infrared Hyperspectral Imaging Rapidly Detects the Decay of Postharvest Strawberry Based on Water-Soluble Sugar Analysis

2019 ◽  
Vol 12 (4) ◽  
pp. 936-946 ◽  
Author(s):  
Qiang Liu ◽  
Kangli Wei ◽  
Hui Xiao ◽  
Sicong Tu ◽  
Ke Sun ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Soluble Sugar ◽  
Water Soluble ◽  
Sugar Analysis

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

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

scholarly journals Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS)

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Jie Kuai ◽  
Shengyong Xu ◽  
Cheng Guo ◽  
Kun Lu ◽  
Yaoze Feng ◽  
...  
Keyword(s):  
Prediction Model ◽  
Spectral Data ◽  
Near Infrared ◽  
Soluble Sugar ◽  
Computing Time ◽  
Colorimetric Method ◽  
Mature Stage ◽  
Near Infrared Reflectance ◽  
Lodging Resistance ◽  
Physiological Basis

The chemical composition of rape stalk is the physiological basis for its lodging resistance. By taking the advantage of NIRS, we developed a rapid method to determine the content of six key composition without crushing the stalk. Rapeseed stalks in the mature stage of growth were collected from three cultivation modes over the course of 2 years. First, we used the near-infrared spectroscope to scan seven positions on the stalk samples and took their average to form the spectral data. The stalks were then crushed and sieved; then the ratio of carbon and nitrogen, ratio of acid-insoluble lignin and lignin, and the content of soluble sugar and cellulose were determined using the combustion method, weighing method, and colorimetric method, respectively. The partial least squares regression (PLSR) method was used to establish a prediction model between the spectral data and the chemical measurements, and all models were evaluated by an internal interaction verification and an external independent test set sample. To improve the accuracy of the model and reduce the computing time, some optimization methods have been applied. Some outliers were removed, and then the data were preprocessed to determine the best spectral information band and the optimal principal component number. The results showed that elimination of outliers effectively improved the precision of the prediction model and that no spectral pretreatment method exhibited the highest prediction accuracy. In summary, the NIRS-based prediction model could facilitate the rapid nondestructive detection in the key components of rapeseed stalk.

scholarly journals Retraction: Water-soluble multidentate polymers compactly coating Ag2S quantum dots with minimized hydrodynamic size and bright emission tunable from red to second near-infrared region

Nanoscale ◽  
2020 ◽  
Vol 12 (41) ◽  
pp. 21459-21459
Author(s):  
Charlotte Marshall
Keyword(s):  
Quantum Dots ◽  
Near Infrared ◽  
Infrared Region ◽  
Water Soluble ◽  
Hydrodynamic Size ◽  
Near Infrared Region ◽  
Ag2s Quantum Dots ◽  
Bright Emission

Retraction of ‘Water-soluble multidentate polymers compactly coating Ag2S quantum dots with minimized hydrodynamic size and bright emission tunable from red to second near-infrared region’ by Rijun Gui et al., Nanoscale, 2014, 6, 5467–5473, DOI: 10.1039/C4NR00282B.

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