July
2001
Volume
78
Number
4
Pages
391
—
394
Authors
Chanintorn
Sitakalin
,
1
and
Jean-Francois C.
Meullenet
1
,
2
Affiliations
Department of Food Science, University of Arkansas, 2650N. Young Avenue, Fayetteville 72704;
Corresponding author. Phone: 501-575 6822. Fax: 501-575 6936. E-mail: jfmeull@comp.uark.edu
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RelatedArticle
Accepted March 6, 2001.
Abstract
ABSTRACT
Spectral stress strain analysis was used in combination with partial least squares (PLS) regression and artificial neural networks (ANN) to predict nine sensory texture attributes of cooked rice. The models calculated with ANN were significantly more accurate in predicting most of the sensory texture characteristics evaluated than the PLS models. Furthermore, ANN models were more robust and discriminative than PLS models.
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ArticleCopyright
© 2001 American Association of Cereal Chemists, Inc.