A study on the use of near-infrared spectroscopy for the rapid quantification of major compounds in Tanreqing injection

2013 ◽  
Vol 101 ◽  
pp. 1-7 ◽  
Author(s):  
Wenlong Li ◽  
Zhiwei Cheng ◽  
Yuefei Wang ◽  
Haibin Qu
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Rapid Quantification

Rapid Quantification of Kinematical Viscosity in Aviation Kerosene by Near-Infrared Spectroscopy

2006 ◽  
Vol 20 (6) ◽  
pp. 2486-2488 ◽  
Author(s):  
Zhi-na Xing ◽  
Ju-xiang Wang ◽  
Yong Ye ◽  
Gang Shen
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Aviation Kerosene ◽  
Rapid Quantification

scholarly journals Rapid quantification of rice (Oryza sativa) qualities based on adaptive near infrared spectroscopy

2021 ◽  
Vol 922 (1) ◽  
pp. 012020
Author(s):  
R Hayati ◽  
A A Munawar ◽  
A Marliah
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Principal Component ◽  
Component Analysis ◽  
Partial Least Square ◽  
Rice Samples ◽  
Rapid Quantification

Abstract Determination of rice quality parameters is the key factor affecting sustainable agriculture practices. The main purpose of this present study is to develop prediction models based on adaptive near infrared spectroscopy (NIRS) for rapid quantification of rice qualities in form of protein content. Rice samples were obtained from several paddy field in Aceh province with different cultivars. Near infrared spectral data of rice samples were acquired and in wavelength range from 1000 to 2500 nm and recorded as diffuse reflectance spectrum. Prediction models were established using principal component analysis (PCA), principal component analysis (PCR) and partial least square regression (PLSR). The results showed that NIRS combined with PCA can classify rice samples based on their cultivars. Moreover, this approach with PCR and PLSR can also predicted and determined protein contents with satisfactory performance achieving maximum correlation coefficient (r) of 0.81 and ratio prediction to deviation (RPD) index of 2.84 for PCR and r of 0.90 and RPD of 3.19 for PLSR respectively. Based on achieved results, it may conclude that adaptive NIRS approach can be used to quantify rice qualities rapidly and non-destructively.

scholarly journals Potential of Visible and Near Infrared Spectroscopy and Pattern Recognition for Rapid Quantification of Notoginseng Powder with Adulterants

Sensors ◽  
2013 ◽  
Vol 13 (10) ◽  
pp. 13820-13834 ◽  
Author(s):  
Pengcheng Nie ◽  
Di Wu ◽  
Da-Wen Sun ◽  
Fang Cao ◽  
Yidan Bao ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Rapid Quantification
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