Quantitative and comparative analysis of whole-plant performance for functional physiological traits phenotyping: New tools to support pre-breeding and plant stress physiology studies

A High-Throughput Gravimetric Phenotyping Platform for Real-Time Physiological Screening of Plant–Environment Dynamic Responses

“…Pre-field phenotyping assists the selection of promising candidate genotypes that have a higher probability of doing well in the field, to help make field trials more focused and cost-effective. However, pre-field phenotyping involves a number of limitations (e.g., pot effects) that can cause plants to perform differently than they would under field conditions (Sinclair et al, 2017; Gosa et al, 2019). Small pot size, water loss by evaporation and heating of the lysimeter scales are examples of factors in greenhouse experiments that may lead to pot effects (reviewed by Gosa et al, 2019).…”

A High-Throughput Physiological Functional Phenotyping System for Time- and Cost-Effective Screening of Potential Biostimulants

“…Interestingly, the sensitivity of the plants to drought in terms of the critical VWC drought point (θc), at which a further reduction in water content reduces transpiration, remained the same, possibly due to similar root sizes (Supplementary Figure 4). This is because under water-deficit conditions, when water becomes less available to the roots, plants with smaller roots will be limited more quickly (early θc) than plants with larger roots (reviewed by Gosa et al, 2018). Thus θc might be useful in predicting root phenotype.…”

“…The fact that the system can calculate the plant biomass throughout the experiment is highly beneficial as it enables a direct measurement of the whole-plant biomass gain, in real time and in a non-destructive manner. In addition, key agronomic traits (such as grain yield) are linearly correlated to water consumption (WUE, reviewed by Gosa et al, 2018). Indeed, throughout the entire experiment, water taken up by the system (representing plant agronomic WUE, slope in Figure 4C) was almost identical to the fresh-weight WUE (taken on the first few days of the experiment; Figure 4E).…”

“…Another potential bottleneck is the genotype–phenotype gap. The availability of new molecular tools has enhanced the efficiency of classical breeding and crop improvement (Spindel et al, 2015; Bhat et al, 2016; Collard and Mackill 2008; Gosa et al, 2018). To achieve meaningful results in drought tolerance, molecular approaches to crop improvement must be linked to suitable phenotyping protocols at all stages, such as the screening of germplasm collections, mutant libraries, mapping populations, transgenic lines and breeding materials, and the design of OMICs and quantitative trait locus experiments (Salekdeh et al, 2009).…”

“…Most of these facilities collect information using robotics and automated image acquisition and analysis (White et al, 2012; Kumar et al, 2015; Ghanem et al, 2015; Fischer et al, 2014; Fiorani and Schurr 2013; Gosa et al, 2018). Nevertheless, the quest for more detailed and in-depth phenotyping of the dynamic genotype◻×◻environment interactions and plant stress responses (in particular during drought) has put the capability of the existing methods into question (Ghanem et al, 2015; Li et al, 2014; Halperin et al, 2017; Rahaman et al, 2015; reviewed by Gosa et al, 2018). Herein, we demonstrate a high-throughput functional phenotyping system (HFPS) composed of gravimetric systems that enable us to compare plants’ dynamic responses to different ambient conditions in dynamic environments, due to its direct and simultaneous measurement of the yield-related physiological traits of all plants under several treatments.…”