Sorghum is the fifth most important cereal crop world-wide and feeds millions of people in the Sahel. However, it often faces early-stage water deficit due to false onsets of rainy seasons resulting in production decrease. Therefore, developing early drought tolerant material becomes a necessity but requires a good knowledge of adaptation mechanisms, which remains to be elucidated. The present study aimed at assessing the effects of early drought stress on ten elite sorghum varieties tested over two years (2018–2019) at the National Agronomic Research Centre (CNRA) of Bambey (Senegal, West Africa). Two different water regimes (well-watered and drought stress) were applied during the dry season. Water stress was applied by withholding irrigation 25 days after sowing for one month, followed by optimal irrigation until maturity. Soil moisture measurements were performed and allowed to follow the level of stress (down to a fraction of transpirable soil water (FTSW) of 0.30 at the end of stress). An agro-physio-morphological monitoring was carried out during the experiment. Results showed highly significant effects of early drought stress in sorghum plants growth by decreasing leaf appearance, biomass, height but also yield set up. The combined analysis of variance revealed highly significant differences (p ≤ 0.01) between varieties in the different environments for most characters. Under water deficit, the variability was less strong on leaf appearance and plant height at the end of stress. The adaptation responses were related to the capacity of varieties to grow up fast and complete their cycle rather, increase the dead leaves weight, reduce photosynthesis rate, stomatal conductance, leaf transpiration and increase the roots length density. However, varieties V1, V2, V8 and V9 showed promising behavior under stress and could be suitable for further application in West Africa for sorghum breeding and farming.

Meeting food demand for the growing population will require an increase to crop production despite climate changes and, more particularly, severe drought episodes. Sorghum is one of the cereals most adapted to drought that feed millions of people around the world. Valorizing its genetic diversity for crop improvement can benefit from extensive phenotyping. The current methods to evaluate plant biomass, leaves area and plants height involve destructive sampling and are not practical in breeding. Phenotyping relying on drone based imagery is a powerful approach in this context. The objective of this study was to develop and validate a high throughput field phenotyping method of sorghum growth traits under contrasted water conditions relying on drone based imagery. Experiments were conducted in Bambey (Senegal) in 2018 and 2019, to test the ability of multi-spectral sensing technologies on-board a UAV platform to calculate various vegetation indices to estimate plants characteristics. In total, ten (10) contrasted varieties of West African sorghum collection were selected and arranged in a randomized complete block design with three (3) replicates and two (2) water treatments (well-watered and drought stress). This study focused on plant biomass, leaf area index (LAI) and the plant height that were measured weekly from emergence to maturity. Drone flights were performed just before each destructive sampling and images were taken by multi-spectral and visible cameras. UAV-derived vegetation indices exhibited their capacity of estimating LAI and biomass in the 2018 calibration data set, in particular: normalized difference vegetative index (NDVI), corrected transformed vegetation index (CTVI), seconded modified soil-adjusted vegetation index (MSAVI2), green normalize difference vegetation index (GNDVI), and simple ratio (SR) (r2 of 0.8 and 0.6 for LAI and biomass, respectively). Developed models were validated with 2019 data, showing a good performance (r2 of 0.92 and 0.91 for LAI and biomass accordingly). Results were also promising regarding plant height estimation (RMSE = 9.88 cm). Regression plots between the image-based estimation and the measured plant height showed a r2 of 0.83. The validation results were similar between water treatments. This study is the first successful application of drone based imagery for phenotyping sorghum growth and development in a West African context characterized by severe drought occurrence. The developed approach could be used as a decision support tool for breeding programs and as a tool to increase the throughput of sorghum genetic diversity characterization for adaptive traits.