ISSN:
0886-9383
Keywords:
NIR
;
Fast Fourier transform
;
Principal component analysis
;
Discrimination
;
Baking quality
;
Wheat
;
Chemistry
;
Analytical Chemistry and Spectroscopy
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
Notes:
Digitalized continuous near infra-red reflectance (NIR) spectra are composed of a great number of data which must be reduced for microcomputer mathematical treatment. The sequence ‘fast Fourier transform preceding principal component analysis’ was tested to perform data size reduction without a large loss of information. The method was applied on a collection of wheat spectra composed of 351 data. Ten resulting data, which described 99.5% of the total variance, were kept. The relevance of the method was estimated by the ability of the resulting data (i) to regenerate the original signal, and (ii) to discriminate the baking quality of the wheat by stepwise multiple discriminant analysis. The average difference between initial and regenerated spectra was -2.4 × 10-3 log (1/R) units and the standard deviation was 1.16 × 10-3 log (1/R) units. The discrimination treatments gave 89.9% of well classified samples for the calibration test and 90.5% for the prediction test. The application of these mathematical treatments to other continuous signals is discussed.
Additional Material:
2 Ill.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1002/cem.1180010205
