Conventional field phenotyping for drought tolerance, the most important factor limiting yield at a global scale, is labor-intensive and time-consuming. Automated greenhouse platforms can increase the precision and throughput of plant phenotyping and contribute to a faster release of drought tolerant varieties. The aim of this work was to establish a framework of analysis to identify early traits which could be efficiently measured in a greenhouse automated phenotyping platform, for predicting the drought tolerance of field grown soybean genotypes. A group of genotypes was evaluated, which showed variation in their drought susceptibility index (DSI) for final biomass and leaf area. A large number of traits were measured before and after the onset of a water deficit treatment, which were analyzed under several criteria: the significance of the regression with the DSI, phenotyping cost, earliness, and repeatability. The most efficient trait was found to be transpiration efficiency measured at 13 days after emergence. This trait was further tested in a second experiment with different water deficit intensities, and validated using a different set of genotypes against field data from a trial network in a third experiment. The framework applied in this work for assessing traits under different criteria could be helpful for selecting those most efficient for automated phenotyping.

No abstract

No abstract

No abstract

The objective of this work was to find practical procedures to overcome methodological drawbacks encountered during studies on sunflower downy mildew. Techniques for recovering living isolates of Plasmopara halstedii from the field and for the preservation of infected leaf samples for further molecular analysis were developed. A Polymerase Chain Reaction (PCR)-based test for the detection of P. halstedii in sunflower leaves and a method to remove azoxystrobin from fungicide-treated seeds are proposed. In situ-inoculations of pre-germinated seeds allowed the recovery of living isolates from the field. Three sample-preservation methods were evaluated (silica, heating and lyophilization) resulting in high yield and quality of the DNA extract. It was detected the presence of the pathogen in symptomless leaves through PCR using molecular markers based on expressed sequence tags. A treatment using sodium hypochlorite is recommended for the removal of azoxystrobin from fungicide treated seeds.