Studies to Measure Cotton Fibre Length, Strength, Micronaire and Colour by vis/NIR Reflectance Spectroscopy. Part II: Principal Components Regression

Author:

Montalvo Joseph G.1,Buco Steven E.2,Ramey Harmon H.3

Affiliation:

1. Southern Regional Research Center, Agricultural Research Service, US Department of Agriculture, New Orleans, LA 70179, USA

2. Statistical Resources, Inc., 7332 Highland Road, Baton Rouge, LA 70808, USA

3. Fiber Technology Branch, Agricultural Marketing Service, US Department of Agriculture, Memphis, TN 38122, USA

Abstract

In Part I of this series, both cotton fibre property and reflectance spectra data on 185 US cottons including four Pimas were analysed by descriptive statistics. In this paper, principal components regression (PCR) models for measuring six properties from the cotton's vis/NIR reflectance spectra are critically examined. These properties are upper-half mean length (UHM), uniformity index (UI), bundle strength (STR), micronaire (MIC) and colour (Rd and +b). The spectra were recorded with a scanning spectrophotometer in the wavelength range from 400 to 2498 nm. A variety of spectral processing options, some of which give improved PCR analysis results, were applied prior to the regressions and allowed for testing of over 100 PCR models. All PCR model results are based on the PRESS statistic by one-out-rotation, a fast approximation of the PRESS statistic (to reduce computer time) or on cluster analysis using separate calibration and validation data sets. The standard error of prediction (SEP) of all the properties except UHM compared well to the reference method precision. The precision of the UHM measure by reflectance spectroscopy was strongly influenced by the sample repack error. The SEP of UHM, UI and STR was improved by excluding the Pimas from the data set.

Publisher

SAGE Publications

Subject

Spectroscopy

Reference12 articles.

1. Studies to Measure Cotton Fibre Length, Strength, Micronaire and Colour by Vis/NIR Reflectance Spectroscopy. Part I: Descriptive Statistics of Fibre Properties and Reflectance Spectra

2. Martens H. and Næs T., in Near-Infrared Technology in the Agricultural and Food Industries, Ed by Williams P. and Norris K. American Assoc. of Cereal Chemists, St. Paul, Minnesota, pp. 57 (1987).

3. Partial least-squares regression: a tutorial

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