scholarly journals Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

2010 ◽  
Vol 15 (4) ◽  
pp. 047002 ◽  
Author(s):  
Janaína Duarte ◽  
Marcos T. T. Pacheco ◽  
Antonio Balbin Villaverde ◽  
Rosangela Z. Machado ◽  
Renato A. Za^ngaro ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Quantitative Analysis ◽  
Toxoplasma Gondii ◽  
Least Squares ◽  
Partial Least Squares ◽  
Multivariate Statistics ◽  
Near Infrared ◽  
Domestic Cats

Near-infrared Raman spectroscopy to detect anti- Toxoplasma gondii antibodies in blood sera of domestic cats

2001 ◽  
Author(s):  
Janaina Duarte ◽  
Marcos T. T. Pacheco ◽  
Landulfo Silveira, Jr. ◽  
Rosangela Z. Machado ◽  
Rodrigo A. L. Martins ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Toxoplasma Gondii ◽  
Near Infrared ◽  
Domestic Cats

N-way partial least squares combined with new self-construction strategy—A promising approach of using near infrared spectral data for quantitative determination of multiple compounds

2019 ◽  
Vol 28 (2) ◽  
pp. 113-121
Author(s):  
Xiang-Zhi Zhang ◽  
Ai-Jun Ma ◽  
Na Feng ◽  
Bao Qiong Li
Keyword(s):  
Quantitative Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Least Squares Method ◽  
Three Dimensional ◽  
Near Infrared Spectra ◽  
Infrared Spectral ◽  
Construction Strategy ◽  
Partial Least Squares Method

Because of the complexity of near infrared spectral data, effective strategies are necessary proposed for accurate quantitative analysis purpose. This work explores a new self-construction strategy for the arrangement of conventional near infrared two-dimensional spectra into new self-constructed three-dimensional spectra, and investigate the feasibility of N-way partial least squares combined with the new self-constructed three-dimensional near infrared spectra for obtaining accurate quantitative determination results. A proof-of-concept model system, the quantitative analysis of four components (moisture, oil, protein, and starch) in corn samples, was applied to evaluate the performance of the proposed strategy. The ability of the newly proposed approach to predict the target compounds was checked with test samples. The established models have good predictive power for the target compounds with acceptable values of Rp (range from 0.82 to 0.997) and RMSEP (range from 0.03 to 0.47). Compared with partial least squares method on pretreated near infrared spectra and N-way partial least squares method on the basis of near infrared self-constructed three-dimensional spectra, the proposed method is competitive.

Sign in / Sign up

Export Citation Format

Share Document