scholarly journals The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process

2014 ◽  
Vol 07 (06) ◽  
pp. 1450022 ◽  
Author(s):  
Lian Li ◽  
Baoyang Ding ◽  
Qi Yang ◽  
Shang Chen ◽  
Huaying Ren ◽  
...  

Near infrared spectroscopy (NIRS) is based on molecular overtone and combination vibrations. It is difficult to assign specific features under complicated system. So it is necessary to find the relevance between NIRS and target compound. For this purpose, the chondroitin sulfate (CS) ethanol precipitation process was selected as the research model, and 90 samples of 5 different batches were collected and the content of CS was determined by modified carbazole method. The relevance between NIRS and CS was studied throughout optical pathlength, pretreatment methods and variables selection methods. In conclusion, the first derivative with Savitzky–Golay (SG) smoothing was selected as the best pretreatment, and the best spectral region was selected using interval partial least squares (iPLS) method under 1 mm optical cell. A multivariate calibration model was established using PLS algorithm for determining the content of CS, and the root mean square error of prediction (RMSEP) is 3.934 g⋅L-1. This method will have great potential in process analytical technology in the future.

2018 ◽  
Author(s):  
WC Aw ◽  
JWO Ballard

AbstractThe aim of the study was to investigate the accuracy of near-infrared spectroscopy (NIRS) in determining triglyceride level and species of wild caught Drosophila. NIRS is a remote sensing method that uses the near-infrared region of the electromagnetic spectrum. It detects the absorption of light by molecular bonds and can be used with live insects. We employ the chemometric approach to combine spectra and reference data from a known sample to produce a multivariate calibration model. Once the calibration model was developed, we used an independent set to validate the accuracy of the calibration model. The optimized calibration model for triglyceride quantification yielded an accuracy of 73%. Simultaneously, we used NIRS to discriminate two species of Drosophila. Flies from independent sets were correctly classified into D. melanogaster and D. simulans with accuracy higher than 80%. Finally, we show that the biological interpretations derived from reference data and the NIRS predictions do not differ. These results suggest that NIRS has the potential to be used as a high throughput screening method to assess a live individual insect’s triglyceride level and taxonomic status.


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