Department of Agronomy, Universidade Federal de Viçosa, Viçosa, MG, Brazil.
Department of Chemistry, Universidade Federal de Viçosa, Viçosa, MG, Brazil.
Phytochemistry. 2022 Jul;199:113175. doi: 10.1016/j.phytochem.2022.113175. Epub 2022 Apr 7.
Identifying compounds present in the sugarcane epicuticular wax and using these compounds to classify the genotypes susceptible and resistant to the initial attack of sugarcane borer (Diatraea saccharalis) was the aim of this study. A greenhouse experiment was performed in a factorial scheme with and without borer infestation using genotypes previously characterized as resistant or susceptible in field-based experiments. Sugarcane whorls of six-month-old plants were collected before (BI) and after (AI) 72 h of sugarcane borer infestation. The sugarcane epicuticular wax was extracted in both times, i.e., BI and AI and its chemical composition was assessed by gas chromatography coupled to mass spectrometry (GC-MS). Twenty-five compounds were identified for both BI and AI. Classification models were built using partial least squares for discriminant analysis (PLS-DA) and linear discriminant analysis (LDA). Variable selection methods were used to improve the classification models. Ordered predictors selection for discriminant analysis (OPSDA) selected compounds that correctly classified all the test samples before borer infestation (Error = 0.000), and exhibited the most suitable classification parameters for the test set after borer infestation (Error = 0.111). The C30 pentacyclic triterpene friedelin and a high alcohol/aldehyde ratio were associated with the classification of resistant genotypes. Our findings have applicability in developing a screening methodology for breeding programs interested in identifying genotypes resistant to the initial feeding of sugarcane borer.
本研究旨在鉴定甘蔗表皮蜡中存在的化合物,并利用这些化合物对易感染和抗甘蔗螟(Diatraea saccharalis)初始攻击的基因型进行分类。采用有和无螟虫侵染的温室因子设计方案,对先前在田间实验中被鉴定为抗性或敏感性的基因型进行了实验。在甘蔗螟虫侵染前(BI)和侵染后 72 小时(AI)收集 6 个月大的植株的甘蔗轮,提取甘蔗表皮蜡,并通过气相色谱-质谱联用(GC-MS)评估其化学成分。BI 和 AI 均鉴定出 25 种化合物。采用偏最小二乘判别分析(PLS-DA)和线性判别分析(LDA)构建分类模型。使用有序预测器选择判别分析(OPSDA)对变量进行选择,该方法可正确分类所有未受螟虫侵染的测试样本(错误=0.000),并在受螟虫侵染后对测试集表现出最适合的分类参数(错误=0.111)。C30 五环三萜化合物friedelin 和高醇/醛比与抗性基因型的分类有关。本研究结果可应用于开发一种筛选方法,用于有兴趣鉴定抗甘蔗螟初始取食的基因型的育种计划。