Phenotypic classification of sugarcane from near infrared spectra obtained directly from stalk using ordered predictors selection and partial least squares-discriminant analysis | Zendy

Luíz Alexandre Peternelli | Zendy; Márcio Henrique Pereira Barbosa | Zendy; Jussara V. Roque | Zendy; Reinaldo F. Teófilo | Zendy

Open Access

Phenotypic classification of sugarcane from near infrared spectra obtained directly from stalk using ordered predictors selection and partial least squares-discriminant analysis

Author(s) -

Luíz Alexandre Peternelli,

Márcio Henrique Pereira Barbosa,

Jussara V. Roque,

Reinaldo F. Teófilo

Publication year - 2019

Publication title -

im publications open llp ebooks

Language(s) - English

Resource type - Book series

DOI - 10.1255/nir2017.157

Subject(s) - partial least squares regression , linear discriminant analysis , selection (genetic algorithm) , pattern recognition (psychology) , statistics , mathematics , stalk , feature selection , biology , artificial intelligence , computer science , horticulture

Author Summary: A new method was developed for the early selection of sugarcane genotypes using near infrared spectroscopy combined with partial least squares discriminant analysis (PLS-DA) and a variable selection method named ordered predictors selection (OPS). The use of the OPS method improved the predictive capacity of PLS-DA models to classify the sugarcane samples correctly according to fiber content (FC) and pol percent (PP).

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