A novel approach for development of a multivariate calibration model using a Doehlert experimental design: Application for prediction of key gasoline properties by Near-infrared Spectroscopy

2011 ◽  
Vol 107 (1) ◽  
pp. 185-193 ◽  
Author(s):  
Marcio V. Reboucas ◽  
Jamile B. Santos ◽  
Maria Fernanda Pimentel ◽  
Leonardo S.G. Teixeira
Keyword(s):  
Infrared Spectroscopy ◽  
Experimental Design ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Calibration Model ◽  
Novel Approach ◽  
Doehlert Experimental Design

scholarly journals Near-Infrared Spectroscopy for metabolite quantification and species identification

2018 ◽  
Author(s):  
WC Aw ◽  
JWO Ballard
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Triglyceride Level ◽  
High Throughput Screening ◽  
Near Infrared ◽  
Reference Data ◽  
Multivariate Calibration ◽  
Screening Method ◽  
Electromagnetic Spectrum ◽  
Calibration Model

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.

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 ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Chondroitin Sulfate ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Process Analytical Technology ◽  
Precipitation Process ◽  
Calibration Model ◽  
Optical Cell ◽  
Ethanol Precipitation

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.

Linear transformations of multivariate calibration models in near infrared spectroscopy: A comparative study

2017 ◽  
Vol 25 (4) ◽  
pp. 223-230 ◽  
Author(s):  
Joseph Dubrovkin
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Cetane Number ◽  
Total Protein Content ◽  
Prediction Errors ◽  
Calibration Data ◽  
Linear Transformations ◽  
Calibration Models

It was shown that linear transformations are suitable for use in multivariate calibration in near infrared spectroscopy as data compression tools. Partial Least Squares calibration models were built using spectral data transformed by expansion in the series of classical orthogonal polynomials, Fourier and wavelet harmonics. These models allowed effective prediction of the cetane number of diesel fuels, Brix and pol parameters of syrup in sugar production and fat and total protein content in milk. Depending on the compression ratio, prediction errors were no larger than 30% of corresponding errors obtained by the use of the non-transformed models. Although selection of the most suitable transformation depends on the calibration data and on the cross-validation method, in many cases Fourier transform gave satisfactory results.

scholarly journals Determination of glomalin in agriculture and forest soils by near-infrared spectroscopy

2017 ◽  
Vol 63 (No. 5) ◽  
pp. 226-230 ◽  
Author(s):  
Zbíral Jiří ◽  
Čižmár David ◽  
Malý Stanislav ◽  
Obdržálková Elena
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Forest Soils ◽  
Near Infrared ◽  
Arable Land ◽  
Calibration Model ◽  
Sustainable Land Management ◽  
Chemical Methods ◽  
Calibration Models

Determining and characterizing soil organic matter (SOM) cheaply and reliably can help to support decisions concerning sustainable land management and climate policy. Glomalin was recommended as one of possible indicators of SOM quality. Extracting glomalin from and determining it in soils using classical chemical methods is too complicated and therefore near-infrared spectroscopy (NIRS) was studied as a method of choice for the determination of glomalin. Representative sets of 84 different soil samples from arable land and grasslands and 75 forest soils were used to develop NIRS calibration models. The parameters of the NIRS calibration model (R = 0.90 for soils from arable land and grasslands and R = 0.94 for forest soils) proved that glomalin can be determined in air-dried soils by NIRS with adequate trueness and precision simultaneously with determination of nitrogen and oxidizable carbon.

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