NDLI: Discriminant Analysis of Sunflower Seeds for Fatty Acid Composition Using NIR Spectroscopy

Content Provider	Springer Nature Link
Author	Grunvald, Anna Karolina Carvalho, Claudio Guilherme Portela Leite, Rodrigo Santos Mandari, José Marcos Gontijo Gonçalves, Juliana Leite Bastos Andrade, Carlos Alberto Scapim, Carlos Alberto
Copyright Year	2012
Abstract	Near-infrared reflectance (NIR) spectroscopy data from sunflower seeds of genotypes differing in oleic and linoleic fatty acid contents were evaluated by discriminant analysis. A single husked seed was used for spectral analysis of each genotype. We applied two clustering strategies to discriminate the genotypes. First, we fit three calibration curves for high oleic × low oleic, high oleic × mid-oleic and mid-oleic × low oleic genotype-derived fatty acids. Next, we fit just one curve to all these three groups. All these curves were established using principal component analysis. The clustering precision was determined by d, the Mahalanobis distance between the genotype and the closest group, and D, the distance up to the next group. The spectral range used for calibration was 1,651–1,952 nm. The genotypes were well classified when d was close to one and the ratio D/d was close to or higher than two. The discriminant analysis allowed the classification of the high oleic and mid-oleic genotypes even though they had similar signals in gas chromatography (GC). Although both clustering strategies were similar, the first one allowed a better discrimination between the mid-oleic and low oleic genotypes.
Starting Page	995
Ending Page	1001
Page Count	7
File Format	PDF
ISSN	0003021X
Journal	Journal of the American Oil Chemists' Society
Volume Number	89
Issue Number	6
e-ISSN	15589331
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-01-18
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Oleic acid Linoleic acid Helianthus annuus Oil quality Food Science Biomaterials Agriculture Biotechnology Industrial Chemistry/Chemical Engineering
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Chemical Engineering

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