scholarly journals Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits

Data in Brief ◽  
2019 ◽  
Vol 27 ◽  
pp. 104789 ◽  
Author(s):  
Agus Arip Munawar ◽  
Kusumiyati ◽  
Devi Wahyuni
Keyword(s):  
Spectroscopic Data ◽  
Near Infrared ◽  
Quality Attributes ◽  
Infrared Spectroscopic ◽  
Simultaneous Prediction

Characterization of fast pyrolysis bio-oil properties by near-infrared spectroscopic data

2018 ◽  
Vol 133 ◽  
pp. 9-15 ◽  
Author(s):  
Torbjörn A. Lestander ◽  
Linda Sandström ◽  
Henrik Wiinikka ◽  
Olov G.W. Öhrman ◽  
Mikael Thyrel
Keyword(s):  
Spectroscopic Data ◽  
Near Infrared ◽  
Fast Pyrolysis ◽  
Bio Oil ◽  
Infrared Spectroscopic

Open-source python module for automated preprocessing of near infrared spectroscopic data

2020 ◽  
Vol 1108 ◽  
pp. 1-9 ◽  
Author(s):  
Jari Torniainen ◽  
Isaac O. Afara ◽  
Mithilesh Prakash ◽  
Jaakko K. Sarin ◽  
Lauri Stenroth ◽  
...  
Keyword(s):  
Open Source ◽  
Spectroscopic Data ◽  
Near Infrared ◽  
Infrared Spectroscopic

scholarly journals Near infrared spectroscopic assessment of developing engineered tissues: correlations with compositional and mechanical properties

The Analyst ◽  
2017 ◽  
Vol 142 (8) ◽  
pp. 1320-1332 ◽  
Author(s):  
Arash Hanifi ◽  
Uday Palukuru ◽  
Cushla McGoverin ◽  
Michael Shockley ◽  
Eliot Frank ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Spectroscopic Data ◽  
Near Infrared ◽  
Engineered Tissues ◽  
Infrared Spectroscopic ◽  
Engineered Cartilage ◽  
Non Destructive

Non-destructive near infrared spectroscopic data can be utilized for assessment of compositional and mechanical properties of engineered cartilage.

Regression models based on new local strategies for near infrared spectroscopic data

2016 ◽  
Vol 933 ◽  
pp. 50-58 ◽  
Author(s):  
F. Allegrini ◽  
J.A. Fernández Pierna ◽  
W.D. Fragoso ◽  
A.C. Olivieri ◽  
V. Baeten ◽  
...  
Keyword(s):  
Spectroscopic Data ◽  
Regression Models ◽  
Near Infrared ◽  
Infrared Spectroscopic

A Comparison of Fourier and Wavelet Transforms in the Processing of near Infrared Spectroscopic Data: Part 1. Data Compression

2003 ◽  
Vol 11 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Tom Fearn ◽  
Anthony M.C. Davies
Keyword(s):  
Data Compression ◽  
Infrared Spectra ◽  
Wavelet Transforms ◽  
Spectroscopic Data ◽  
Near Infrared ◽  
Spectral Imaging ◽  
Good Choice ◽  
Near Infrared Spectra ◽  
Infrared Spectroscopic ◽  
Recent Trends

The advent of spectral imaging and recent trends towards the compilation of large spectral databases have caused renewed interest in the compression of near infrared spectra for purposes of storage. A comparison of approaches using Fourier and wavelet transforms shows that wavelets are generally, though not always, more efficient than Fourier at compressing near infrared spectra. The Daubechies extremal phase wavelet of order 4 is a good choice for this purpose.

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