WAVELENGTH SELECTION FOR PREDICTING PHYSICOCHEMICAL PROPERTIES OF APPLE FRUIT BASED ON NEAR-INFRARED SPECTROSCOPY

Near Infrared ◽

Apple Fruit ◽

Wavelength Selection ◽

Potential effectiveness of visible and near infrared spectroscopy coupled with wavelength selection for real time grapevine leaf water status measurement

Journal of the Science of Food and Agriculture ◽

10.1002/jsfa.8676 ◽

2017 ◽

Vol 98 (5) ◽

pp. 1935-1943 ◽

Cited By ~ 8

Author(s):

Valentina Giovenzana ◽

Roberto Beghi ◽

Simone Parisi ◽

Lucio Brancadoro ◽

Riccardo Guidetti

Keyword(s):

Infrared Spectroscopy ◽

Real Time ◽

Near Infrared ◽

Water Status ◽

Leaf Water ◽

Wavelength Selection ◽

Leaf Water Status ◽

Potential Effectiveness ◽

Optical wavelength selection for portable hemoglobin determination by near-infrared spectroscopy method

Infrared Physics & Technology ◽

10.1016/j.infrared.2017.09.004 ◽

2017 ◽

Vol 86 ◽

pp. 98-102 ◽

Cited By ~ 7

Author(s):

Han Tian ◽

Ming Li ◽

Yue Wang ◽

Dinggao Sheng ◽

Jun Liu ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared ◽

Spectroscopy Method ◽

Wavelength Selection ◽

Optical Wavelength ◽

Wavelength Selection for Classifying Paddy Rice by Near-Infrared Spectroscopy

Cereal Chemistry ◽

10.1094/cc-83-0335 ◽

2006 ◽

Vol 83 (4) ◽

pp. 335-339 ◽

Cited By ~ 2

Author(s):

Chang-Chun Liu ◽

Jai-Tsung Shaw ◽

Keen-Yik Poong ◽

Mei-Chu Hong ◽

Ming-Lai Shen

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared ◽

Paddy Rice ◽

Wavelength Selection ◽

Wavelength selection for the determination of glucose in human serum by near-infrared spectroscopy

10.1063/1.55777 ◽

1998 ◽

Cited By ~ 1

Author(s):

Qing Ding ◽

Gary W. Small

Keyword(s):

Infrared Spectroscopy ◽

Human Serum ◽

Near Infrared ◽

Wavelength Selection ◽

Near-infrared spectroscopy and wavelength selection for estimating basic density in Mimosa tenuiflora [Willd.] Poiret wood

Wood Science and Technology ◽

10.1007/s00226-014-0652-1 ◽

2014 ◽

Vol 48 (5) ◽

pp. 949-959 ◽

Cited By ~ 3

Author(s):

Katarine M. F. Diesel ◽

Fernanda S. L. da Costa ◽

Alexandre S. Pimenta ◽

Kássio M. G. de Lima

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared ◽

Basic Density ◽

Wavelength Selection ◽

Selection For ◽

Mimosa Tenuiflora

Wavelength selection method for near-infrared spectroscopy based on standard-sample calibration transfer of mango and apple

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2021.106448 ◽

2021 ◽

Vol 190 ◽

pp. 106448

Author(s):

Lisha Li ◽

Xiaogang Jang ◽

Bin Li ◽

Yande Liu

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared ◽

Standard Sample ◽

Selection Method ◽

Wavelength Selection ◽

Calibration Transfer

2019 First International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) ◽

Features and Window Size Selection for Quadcopter Control Using Functional Near-Infrared Spectroscopy

10.1109/ica-symp.2019.8646261 ◽

2019 ◽

Author(s):

Amad Zafar ◽

Usman Ghafoor ◽

M. Atif Yaqub ◽

Keum-Shik Hong

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared ◽

Window Size ◽

Functional Near Infrared Spectroscopy ◽

Size Selection ◽

Subject-Specific feature selection for near infrared spectroscopy based brain-computer interfaces

Computer Methods and Programs in Biomedicine ◽

10.1016/j.cmpb.2020.105535 ◽

2020 ◽

Vol 195 ◽

pp. 105535

Author(s):

Eda Akman Aydin

Keyword(s):

Feature Selection ◽

Infrared Spectroscopy ◽

Near Infrared ◽

Brain Computer Interfaces ◽

Computer Interfaces ◽

Subject Specific ◽

Recognition of osmotolerant yeast spoilage in kiwi juices by near-infrared spectroscopy coupled with chemometrics and wavelength selection

RSC Advances ◽

10.1039/c7ra12266g ◽

2018 ◽

Vol 8 (1) ◽

pp. 222-229 ◽

Cited By ~ 4

Author(s):

Chen Niu ◽

Yahong Yuan ◽

Hong Guo ◽

Xin Wang ◽

Xuan Wang ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared ◽

Wavelength Selection ◽

Svm Model ◽

First Time ◽

Osmotolerant Yeast

The study developed a NIR-SVM model for accurate recognition of osmotolerant yeasts in kiwi juice for the first time.

Molecular spectroscopic wavelength selection using combined interval partial least squares and correlation coefficient optimization

Analytical Methods ◽

10.1039/c9ay00898e ◽

2019 ◽

Vol 11 (24) ◽

pp. 3108-3116 ◽

Cited By ~ 1

Author(s):

Weiwei Jiang ◽

Changhua Lu ◽

Yujun Zhang ◽

Wei Ju ◽

Jizhou Wang ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Least Squares ◽

Partial Least Squares ◽

Correlation Coefficient ◽

Near Infrared ◽

Vital Role ◽

Wavelength Selection ◽

Coefficient Optimization

Wavelength selection plays a vital role in employing near-infrared spectroscopy for analyzing samples.