Discriminating Important Agronomic and Industrial Parameters of White Oat Cultivars Treated with Fungicide Based on SIMCA Algorithm

• 作者: Cileide Maria Medeiros Coelho Clovis Arruda Souza Julhana Cristina Sponchiado Virgilio Gavicho Uarrota
• 来源期刊: 农业科学与技术：B
• 学科: 农学
• 关键词: OAT cultivars SIMCA modeling non-supervised techniques FUNGICIDE application growth yield principal componentanalysis hierarchical cluster analysis model classification.
• 年，卷（期）: nykxjs-b,（2）
• 页码范围: 86-99
• 页数: 14页
• 分类号: S

摘要

Selection of effective agronomic and industrial parameters of oat cultivars is a decisive step in oat breeding programs fordevelopment of new oat and elite cultivars. In this study, a new approach was utilized to distinguish the most informative agronomicand industrial parameters that are most affected with fungicide application in oat cultivars. Four subsequent field experiments from2007 to 2010 were conducted in completely randomized block design （CRBD） with split plots. Total nine oat cultivars with orwithout fungicide application were evaluated for plant height, sieve yield, grain yield, lodging index, weight of hectoliter andde-hulling index. Soft independent modeling of class analogy （SIMCA） was conducted as one-class and multi-classes models toidentify important variables that can be used to discriminate samples. Results showed that SIMCA was effective, and lodging index,de-hulling index, sieve yield, plant height and grain yield were most affected oat parameters. Therefore, SIMCA algorithm can beused to easily discriminate some agronomic and quality parameters of oats.