Ionomic and Openarray Profiling to Detect Effects of Biostimulants in Sugar Beet

Biostimulants are gaining increased attention to enhance nutrient use efficiency and tolerance to biotic and abiotic stresses in plants. However, the characterization of biostimulant effects in crops is complex and needs rigorous evaluations. In this study, we propose a method combining ionomic, molecular and morphological profiling for the accurate evaluation of the stimulating activity of two microalgae extracts, Chlorella vulgaris and Scenedesmus quadricauda, on sugar beet crop (Beta vulgaris L. subsp. vulgaris). Seedlings were grown into Hoagland’s solution under controlled condition. After 5 days of growth, 2mL/L (1 mg Corg/L) and 4 mL/L (2 mg Corg/L) of the two different microalgal extracts were added to the Hoagland’s solution. Roots were sampled 36 h after treatments. Inductively Coupled Plasma Spectrometry (ICP-OES) and nanofluidic real-time PCR (OpenArray system) were used for sample profiling. OpenArray chips were designed with TaqMan probes for 56 sugar beet genes putatively involved in sulfate starvation (Moliterni et al., in preparation). Root morphological traits were measured by means of a scanner-based image analysis system (WINRHIZO). Multivariate statistical analysis has not revealed significant changes in the ionomic profile of Hoagland’s solutions treated with the two microalgal extracts with respect to that of the untreated solution. Anyway, at the molecular level, microalgal extract supply upregulated many of the evaluated genes. Functional categorization revealed these genes to be related to various biological pathways and processes including primary and secondary metabolism and intracellular transport. Treated seedlings showed at morphological level significantly higher values for root traits related to soil exploration and nutrient uptake, such as total root length, fine roots length (diameter < 0.5 mm) and root tips number, than untreated plants. Based on our findings, the combination of ionomic, molecular and morphological profiling could become a valuable high-throughput system for the evaluation of biostimulants effects in sugar beet crop.