Attendees also had the opportunity to familiarize themselves with the Phenobuggy — a tractor-mounted, GPS-assisted multi-sensor head. Discussions ensued regarding the crop traits measurable through these devices and their pivotal role in breeding schemes. Notably, the Phenobuggy enables rapid and precise measurement of phenotypic traits such as green fraction, senescence, vegetation indices, leaf area index, biomass, spike number, and plant height. Conversations underscored the importance of developing proxy approaches that connect above-ground measurements with root traits.
Subsequent sessions delved into soil coring, root seminal angle measurement using the clear pot method, and shovelomics sampling, along with data collection employing WinRhizo. WinRhizo, an image analysis system tailored for root measurement, encompasses morphology, topology, architecture, and color analyses. The significance of standardizing root system characteristics for image analysis was discussed, alongside recognition of error dependency on the response variable of interest, potentially influencing effect size and error probability. Method validation for each analyzed dataset was deemed essential. Furthermore, insights were shared on how root system morphology influences crop adaptation to diverse soil types, drawing upon the experiences of ICARDA and INRA across different experimental stations in Morocco.
The concluding segment of the workshop focused on data analysis, machine learning, and phenomic selection. Breeders emphasized the need for approaches facilitating precise evaluation of genetic variability in quantitative traits, given their pivotal role in breeding endeavors. This necessitates the deployment of accurate, rapid, and cost-effective evaluation tools. For intricate traits such as yield, genomic selection emerged as a viable option, leveraging genome-wide marker data to estimate breeding values. Alternatively, phenomic prediction, facilitated by multimodal machine learning models, seeks to predict the performance of untested individuals through the amalgamation of genomic, phenomic, and environmental data. Consensus among participants affirmed the compatibility of this predictive approach in augmenting genetic gains in plant breeding.
By fostering collaboration and sharing best practices in root system analysis and phenotyping, the workshop emerged as a pivotal forum for the exchange of pertinent information pertaining to the agropedoclimatic conditions and specificities of the Mediterranean experimental site chosen by Root2Res, or Agroclimatic Zone 3 (ACZ3). Local demonstrators can be found in this website’s homepage.
