利用有序预测因子选择和偏最小二乘判别分析从甘蔗茎秆直接获得的近红外光谱进行表型分类

L. Peternelli, M. H. Barbosa, J. Roque, R. Teófilo
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引用次数: 0

摘要

作者摘要:建立了一种利用近红外光谱结合偏最小二乘判别分析(PLS-DA)和有序预测因子选择(OPS)进行甘蔗基因型早期选择的新方法。OPS方法的使用提高了PLS-DA模型根据纤维含量(FC)和pol百分比(PP)对甘蔗样品进行正确分类的预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Phenotypic classification of sugarcane from near infrared spectra obtained directly from stalk using ordered predictors selection and partial least squares-discriminant analysis
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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