Principal Discriminant Variate (PDV) Method for Classification of Multicollinear Data: Application to Diagnosis of Mastitic Cows Using near Infrared Spectra of Blood Samples

NIR news ◽  
2002 ◽  
Vol 13 (6) ◽  
pp. 5-8 ◽  
Author(s):  
Jian-Hui Jiang ◽  
Roumiana Tsenkova ◽  
Yukihiro Ozaki
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Blood Samples ◽  
Data Application ◽  
Near Infrared Spectra

scholarly journals Discrimination of mineral waters using near infrared spectroscopy and aquaphotomics

2014 ◽  
Vol 68 (2) ◽  
pp. 257-264 ◽  
Author(s):  
Jelena Muncan ◽  
Lidija Matija ◽  
Jovana Simic-Krstic ◽  
Srecko Nijemcevic ◽  
Djuro Koruga
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Dynamic Properties ◽  
Mineral Waters ◽  
Molecular Organization ◽  
Human Organism ◽  
Water Molecules ◽  
Near Infrared Spectra ◽  
Healthy Functioning

Despite that water is one of the most studied materials today its dynamic properties are still not well understood. Water state in human organism is of high importance for normal healthy functioning of human body. Different kinds of water are usually classified according to its present solutes, and concentrations of these solutes, but though it is known that water molecules can form clusters around present solutes, classification of waters based on types of water molecular organization and present clusters is not present in current literature. In this study we used multivariate analysis for classification of commercial mineral waters based on their near infrared spectra (NIR). Further, we applied Aquaphotomics, a new approach for interpretation of near infrared spectra of water, which gives insight into organization of water molecules in each of these waters.

Reagentless Near-Infrared Determination of Glucose in Whole Blood Using Multivariate Calibration

1992 ◽  
Vol 46 (10) ◽  
pp. 1575-1578 ◽  
Author(s):  
David M. Haaland ◽  
M. Ries Robinson ◽  
Gary W. Koepp ◽  
Edward V. Thomas ◽  
R. Philip Eaton
Keyword(s):  
Infrared Spectra ◽  
Glucose Concentration ◽  
Whole Blood ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Blood Chemistry ◽  
Standard Errors ◽  
Diabetic Patients ◽  
Blood Samples ◽  
Near Infrared Spectra

Noninvasive monitoring of glucose in diabetic patients is feasible with the use of near-infrared spectroscopic measurements. As a step toward the final goal of the development of a noninvasive monitor, the near-infrared spectra (4250 to 6600 cm−1) of glucose-doped whole blood samples were obtained along with reference glucose values. Glucose concentrations and spectra of blood samples obtained from four subjects were subjected to multivariate calibration with the use of partial least-squares (PLS) methods. The cross-validated PLS standard errors of prediction for glucose concentration based on data obtained from each individual subject's blood samples averaged 33 mg/dL over the range from 3 to 743 mg/dL. Cross-validated standard errors for glucose concentration from PLS calibrations based on data from all four subjects were 39 mg/dL. However, when PLS models based upon three subjects' data were used for prediction on the fourth, glucose prediction abilities were poor. It is suggested that blood chemistry differences were sufficiently different for the four subjects to require that a larger number of subjects be included in the calibration for adequate prediction abilities to be obtained from near-infrared spectra of blood from subjects not included in the calibration.

scholarly journals Comprehensive chemometric classification of snack products based on their near infrared spectra

LWT ◽  
2020 ◽  
Vol 133 ◽  
pp. 110130
Author(s):  
Eszter Benes ◽  
Dávid Bajusz ◽  
Attila Gere ◽  
Marietta Fodor ◽  
Anita Rácz
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Near Infrared Spectra ◽  
Snack Products
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