Aegilops tauschii is the diploid progenitor of the D subgenome of hexaploid wheat (Triticum aestivum L.) and is an important source of genetic variation for wheat breeding. As a consequence of a strong domestication bottleneck, it is known that T. aestivum is strongly depleted in polymorphisms particularly in the DD genome. Crop wild relatives offer a wide range of interesting and underutilized alleles due to the broad genetic variability still present in nature. Our objective was to assess the phenotypic diversity for root and plant morpho-physiological traits in the 242 accessions of the OWWC (Open Wild Wheat Consortium, http://www.openwildwheat.org/), all provided with whole-genome resequencing and suitable to highly precise GWAS, aiming at identifying novel QTLs governing all examined traits. The collection includes Turkey-to-Afghanistan-Central Asian lines (L1 lineage) and southwestern coastal Caspian Sea (L2), with the latter being involved in wheat domestication. Agronomic data were gathered from two field exeriments (2 m long single row plots and two reps) conducted in Cadriano, Italy, in 2019/2020 and 2020/2021. Traits of agronomic interest included phenology, growth habit, tillering, spike traits, anthocyanin accumulation, shoot and root biomass and were scored either by visual evaluation / counting or by scanning of plant sample followed by image digital analysis (in ImageJ). Roots system architecture traits were analyzed from plants grown in growth chamber, using eight randomized blocks per two replicates, with each block including 4 Aegilops tauschii, durum and bread wheat cultivars as repeated checks. Pre-germinated seedlings were grown on filter paper sheets placed on black polycarbonate screening plates soaked in a modified Hoagland nutrient solution. After ten days, images of seminal roots were collected for measuring the following traits: root growth angle, root length, root diameter, root network area, lateral root density and length. All phenotipic data were analyzed with a mixed model statistical analysis, correcting data for position in the field, GxE interaction for multi-years trials and for Blocks in root experiment. A k-mer based GWAS was performed in collaboration with John Innes Center (Norwich, UK) using the same pipeline published in Gaurav et al., Nat Biotechnol 40, 422–431 (2022). Interesting QTL peaks were detected for different traits: senescence (chr3 and chr7), heading date (chr7 and chr2), Flag leaf length (chr4 and chr7), elevation angle (chr5, chr4 and chr2), peduncle length (chr2 and chr7), Root length (chr2, chr3 and chr7), lateral root density score (chr6, chr7 and chr2), lateral root length score (chr2, chr6 and chr7) and RGA (chr3). The most interesting peaks (Bonferroni’s adjusted P-values supported by multiple k-mer analysis) for different traits will be evaluated for content in candidate genes, comparing orthologues and level of expression in Triticum aestivum cv. Chinese Spring expression browsers.