Resistance mechanism of sugarcane genotypes to the sugarcane borer - Wartha, Cleiton Antônio (2018)
The sugarcane borer Diatraea saccharalis Fabr. (Lepidoptera: Crambidae) is the main insect pest affecting sugarcane fields in Brazil. Damage caused by borer herbivory occurs through the opening of galleries, breaking of stalks, lateral sprouts and reduction of agricultural yield. The development of borer resistant cultivars is a strategy for integrated pest management, reduction of production costs and long-lasting cultivars. Anatomical, biochemical and morphological traits are involved in resistance. However, there is a shortage of studies seeking for resistance sources at the initial feeding of the pest in younger leaves. In this sense, the objective of this study was to identify the constitutive or induced chemical components of sugarcane epicuticular wax that can be associated with resistance before infestation (BI) and after infestation (AI) with sugarcane borer. A greenhouse experiment was performed in a factorial scheme in a completely randomized design with four replicates, with and without borer infestation using 11 clones previously characterized as resistant or susceptible in field-based experiments. Sugarcane whorl of six-month-old plants were collected before and after 72 hours of sugarcane borer infestation. The chemical composition of the epicuticular wax was assessed by gas chromatography associated with mass spectrometry (GC-MS). The relative importance of each compound was analyzed by means of logistic regression, using the integrated area data of the 17 main peaks identified. Before infestation, the most important compounds in the classification of resistant and susceptible genotypes were octacosanal, triacontane, lanosterol and tetratriacontane. After the borer infestation, the compounds selected by the adjusted model were hexacosanol, octacosanol and dotriacontanol and in the combined analysis (BI and AI) were hexacosanol, hexacosanal, octacosane, lanosterol, triacontanol and dotriacontanol. The apparent error rate of the adjusted logistic models for BI, AI and combined analysis was respectively of 13.6%, 11.4% and 6.8%. Our findings have applicability in the development of a screening methodology to identify potential genotypes for resistance to sugarcane borer in early stages of sugarcane breeding programs.