Journal Published Online: 01 January 2001
Volume 29, Issue 1

Overcoming Multicollinearity in Near Infrared Analysis for Lycopene Content Estimation in Tomatoes by Using Ridge Regression

CODEN: JTEVAB

Abstract

High intercorrelation between absorbance at different wavelengths is common in near infrared analysis and was observed in an experiment to determine lycopene in tomatoes. Simulation analysis and experiments were conducted to estimate the effects of this problem on the estimators and on the predictive ability of linear regression and ridge regression. Applying linear regression to the experimental data resulted in very large parameter values, implying poor predictive ability. When linear regression gives very large parameter values, the estimated parameters are practically random numbers and are not correlated to the true ones. Ridge regression yielded estimators with normal values, but which are still poorly correlated with the true parameters. However, the predictive ability of the derived equation is good and may be used in practice to determine lycopene content in tomatoes since it is relatively easy to update.

Author Information

Pasternak, H
Institute of Agricultural Engineering, Volcani Center, A. R. O., Israel
Schmilovitch, Z
Institute of Agricultural Engineering, Volcani Center, A. R. O., Israel
Fallik, E
Institute of Postharvest Technology, Volcani Center, A. R. O., Israel
Edan, Y
Institute of Agricultural Engineering, Volcani Center, A. R. O., Israel Ben-Gurion University of the Negev, Beer Sheva, Israel
Pages: 7
Price: $25.00
Related
Reprints and Permissions
Reprints and copyright permissions can be requested through the
Copyright Clearance Center
Details
Stock #: JTE12392J
ISSN: 0090-3973
DOI: 10.1520/JTE12392J