Soybean (Glycine max (L.) Merr.) may contribute to the agro-ecological transition of cropping systems in Europe, but its productivity is severely affected by summer drought. New drought-avoidance cropping strategies, such as early sowing, require cultivars with high early plant growth under suboptimal conditions. This study aims at phenotyping early-stage root and shoot traits of 10 cultivars commonly grown in Europe. Cultivars were grown in minirhizotrons under two soil moisture status in controlled conditions. Root and shoot traits were evaluated at 10 days after sowing. Field early growth of two cultivars was also analyzed under early and conventional sowing dates. A significant intraspecific variability (p < 0.05) was found for most investigated shoot and root morpho-physiological traits regardless of the soil moisture status under controlled conditions. However, no significant difference among cultivars (p > 0.05) was found in terms of root architectural traits that were mainly affected by water stress. Total root length was positively correlated with shoot length and shoot dry matter (p < 0.05). Under field conditions, the differences between cultivars were expressed by the canopy cover at emergence, which determines the subsequent canopy cover dynamics. The significant early growth difference among cultivars was not related to the maturity group. Cultivars characterized by high root depth and length, high root density and narrow root angle could be considered as good candidates to cope with water stress via better soil exploration. New agronomic strategies mobilizing the diversity of cultivars could thus be tested to improve soybean water use efficiency in response to climate change.

Introduction Plant and crop metabolomic analyses may be used to study metabolism across genetic and environmental diversity. Complementary analytical strategies are useful for investigating metabolic changes and searching for biomarkers of response or performance. Methods and objectives The experimental material consisted in eight sunflower lines with two line status, four restorers (R, used as males) and four maintainers (B, corresponding to females) routinely used for sunflower hybrid varietal production, respectively to complement or maintain the cytoplasmic male sterility PET1. These lines were either irrigated at full soil capacity (WW) or submitted to drought stress (DS). Our aim was to combine targeted and non-targeted metabolomics to characterize sunflower leaf composition in order to investigate the effect of line status genotypes and environmental conditions and to find the best and smallest set of biomarkers for line status and stress response using a custom-made process of variables selection. Results Five hundred and eighty-eight metabolic variables were measured by using complementary analytical methods such as ¹H-NMR, MS-based profiles and targeted analyses of major metabolites. Based on statistical analyses, a limited number of markers were able to separate WW and DS samples in a more discriminant manner than previously published physiological data. Another metabolic marker set was able to discriminate line status. Conclusion This study underlines the potential of metabolic markers for discriminating genotype groups and environmental conditions. Their potential use for prediction is discussed.

Soybean (Glycine max (L.) Merr.) may contribute to the agro-ecological transition of cropping systems in Europe, but its productivity is severely affected by summer drought. The crop is mainly grown in southern and continental parts of Europe, whereby increasing drought and heat waves are expected in the near future. Agronomic strategies, such as early sowing, require cultivars with enhanced early plant growth traits under suboptimal conditions. Moreover, efficient water uptake by root delays dehydration and promotes drought avoidance. In general, changes in root morphology and root architecture are important pathways for plant adaptation to water stress conditions. This paper reviews the cultivar differences in soybean for root morphological and architectural traits especially during early growth stage. Previous works reported cultivar differences for root traits in soybean but they did not deal with cultivars commonly grown in Europe on which little information is available to date. Genotypic differences in available early-stage root traits can be used as a framework to design soybean ideotypes less vulnerable to drought. To this aim, high-throughput phenotyping supported by digital methods and crop modelling offer new avenues for the exploration of target root traits involved in drought avoidance.

The responses of eco‐physiological processes such as leaf expansion, plant transpiration and senescence to soil water deficit have been reported to be genotype‐dependent in different crops. To study such responses in soybean (Glycine max. (L.) Merr.), a 2‐year (2017 and 2021) outdoor pot experiment was carried out on the Heliaphen automated phenotyping platform at INRAE in Toulouse (France). Six soybean cultivars (Sultana‐MG 000, ES Pallador‐MG I, Isidor‐MG I, Santana‐MG I/II, Blancas‐MG II and Ecudor‐MG II) belonging to four maturity groups (MG) commonly grown in Europe were subjected to progressive soil water deficit from the reproductive stage R1 for 17 and 23 days in 2017 and 2021, respectively. The fraction of transpirable soil water (FTSW) was used as an indicator of soil water deficit. Non‐linear regression was used to calculate FTSWt, that is, the FTSW threshold for which the rate of the eco‐physiological process in stressed plants starts to diverge from a reference value. According to FTSWt, the three eco‐physiological processes showed significant differences in sensitivity to water deficit: leaf expansion exhibits the highest sensitivity and the widest range (FTSWt: 0.44–0.93), followed by plant transpiration (FTSWt: 0.17–0.56), with leaf senescence showing the narrowest range (FTSWt: 0.05–0.16). Among six cultivars, regarding leaf expansion, Cvs Santana (FTSWt = 0.48 in 2017; FTSWt = 0.44 in 2021), Blancas (FTSWt = 0.51 in 2017; FTSWt = 0.48 in 2021) and Ecudor (FTSWt = 0.46 in 2017; FTSWt = 0.52 in 2021) in late MGs (I/II to II) exhibited higher tolerance to soil drying. Conversely, the cv. Sultana in the earliest MG (000) showed the highest sensitivity (FTSWt = 0.91 in 2017; FTSWt = 0.93 in 2021) to water deficit. However, concerning the FTSWt values for plant transpiration (0.17–0.56 in 2017; 0.19–0.31 in 2021) and senescence (0.05–0.16 in 2017; 0.06–0.16 in 2021), their range did not demonstrate a correlated trend with the MG. In addition, a negative linear correlation was observed between values of FTSWt of normalised leaf expansion at the whole‐plant level (NLE) and specific leaf area (SLA) measured on irrigated plants for both years. This suggests that genotypes with high values of SLA could be associated with higher tolerance of leaf expansion to soil water deficit. Such a non‐destructive phenotyping method under outdoor conditions could bring new information to variety testing process and provide paths for integrating genotypic variability into crop growth models used for simulating soybean eco‐physiological responses to water deficit across the plant, field and even regional scales.

The purpose of this study was to identify genomic regions controlling seed protein content, kernel and hull weights, and seed density in water-stress conditions in sunflower ( Helianthus annuus L.). The experiments consisted of a split-plot design (water treatment and recombinant inbred lines) with three blocks in two environments (greenhouse and field). High significant variation was observed between genotypes for all traits as well as for water treatment × genotype interaction. Several specific and nonspecific QTLs were detected for all traits under well-watered and water-stress conditions. Two SSR markers, ORS671_2 and HA2714, linked to protein content were identified that have no interaction with water treatments in greenhouse conditions. We also detected the E35M60_4 marker associated with kernel weight that had no interaction with water treatments. A specific QTL for protein content was detected with important phenotypic variance (17%) under water-stress conditions. Overlapping QTLs for protein content and seed density were identified in linkage group 15. This region probably has a peliotropic effect on protein content and seed density. QTLs for protein content colocated with grain weight traits were also identified.