Aromaticity of secondary products as the marker for sweet sorghum [Sorghum bicolor (L.) Moench] genotype and environment effects

Abstract

Although data analytics and systems modeling are increasingly being utilized to interpret genotype × environment interactions in plant breeding, chemometrics is currently underutilized. Prior reports indicated correlations between redox-active polyphenols in stem juice of sweet sorghum [ Sorghum bicolor (L.) Moench] and its resistance against sugarcane aphid [ Melanaphis sacchari (Zehntner)]. However, such correlations are often confounded by the outperforming genotype (outlier in correlations) capable of accumulating several-fold higher secondary metabolites than other cultivars examined. To investigate the underlying chemical characteristics responsible for the pest resistance, this study first employed principal component analysis (PCA) as the exploratory analysis to visualize the primary factors affecting genotype and environmental (April, May, and June planting months) dependence of juice extracted from 24 sweet sorghum cultivars. Chemical parameters arising from redox reactivity were primarily responsible for distinguishing a resistant genotype. The distance of dendrogram based on the genotype-dependent electrochemistry (cyclic voltammetry) was then used as the perturbation parameter in 2D correlation analysis to understand the controlling chemical structures; both genotype and environment were controlled by the redox reactivity and aromaticity of sweet sorghum. Aromatic structures detectable by UV/visible spectrophotometry were then used to build calibrations based on machine learning. The workflow of data analytics in this study could be applied to expedite the biomarker-driven plant breeding without repeating chemical analysis of new field samples. • Redox reactivity of sorghum juice can serve as the marker for pest resistance. • 2 D correlation analysis of cyclic voltammogram revealed genotype dependency. • Machine learning allows calibration of redox reactivity without repeated analysis.