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.

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.

Sorghum [Sorghum bicolor (L.) Moench], a staple food crop in Mali, has low yields for several reasons including that many farmers do not have the financial resources to purchase state‐of‐the‐art genetics and fertilizers and information is not available on how to optimize yields for heirloom variety. To improve their economic and environmental sustainability, Mali farmers need to understand how to invest their limited resources. In many situations this involves the use of open‐pollinated varieties that have a range of tillering capabilities. This study determined the best population density and nitrogen (N) fertilization combinations for eight locally available sorghum varieties. The research was conducted in 2018 and 2019 and the experimental design was split‐split‐plot randomized block, the treatments were two plant densities (26,600 and 53,300 plants ha^–1), three N levels (0 kg ha^–1, 89 kg ha^–1, and 178 kg ha^–1), and eight varieties that had a range of tillering characteristics. Each treatment was replicated three times and six of the varieties were open pollinated. Results showed that each variety had a different yield response to plant density and N rate. For example, the tall guinea (hybrids FADDA and PABLO) and the short durra‐caudatum A12‐79 cultivar produced higher yields when planted at 53,300 plants ha^–1 and fertilized with 178 kg N ha^–1 N2D2 treatment. For the short guinea‐caudatum improved varieties C2_007‐03 and C2_075‐15 and caudatum GRINKAN and SOUMBA varieties the optimum seeding rate was 53,300 plants ha^–1 that were fertilized with 89 kg N ha^–1 (N1D2). For the tall local guinea TIEBILE variety the highest yields were observed when it was seeded at a rate of 26,600 plants ha^–1 and fertilized with 89 kg N ha^–1. Grain yield increase was associated with yield components and growth traits for eight varieties studied. Panicle numbers per square meter and chlorophyll index were associated with grain yield in guinea hybrid. Grain number per panicle and 1,000 grain weight were involved in increasing grain yield in caudatum varieties. Nitrogen rate and planting density combination in terms of grain yield varied with different sorghum [Sorghum bicolor (L.) Moench] varieties studied. Knowledge of optimum combinations will help producers decide which option to promote to booster sorghum production in Mali.

Sahelian Africa must meet the challenge of providing enough food to meet its growing population. Therefore, novel breeding and intensive production methods are needed to mitigate this challenge. The objective of this study was to calibrate and validate sorghum varieties leaf area index (LAI) values estimated from Unmanned Aerial Vehicle (UAV) at different growing seasons in Senegal and Mali. To achieve this objective, four experiments were conducted with 14 sorghum (sorghum bicolor) varieties between 2017 and 2019. At the study sites, LAI was measured and crop reflectance was measured with a multispectral camera mounted on a UAV. The study showed that normalized difference vegetation index (NDVI) and simple ratio (SR) were highly correlated to the area index. The results of validation model revealed a better prediction of measured LAI from NDVI (R² = 0.92) and SR (R² = 0.89) vegetation indices in 2019 dry season in Senegal. In addition, the LAI predictions for Mali from NDVI (p < 0.01) and SR (p < 0.01) were highly correlated. Findings showed that vegetation indices can be used to estimate LAI in Mali and Sahel.

While the green revolution adapted a handful of crops to homogenous and high-input industrialized agriculture, much of the global population still relies on local food production from low-input smallholder farms that grow highly variable crop cultivars. The high diversity of the grain and bioenergy crop sorghum, and many other crops that were not homogenized during the green revolution, not only provides the raw materials for breeders to make substantial gains in cultivar improvement, but also constrains breeding efforts due to highly specialized locally adapted plant phenotypes. Here, we construct a 33-member pangenome and identify trait-associated variants in 1,988 cultivars and landraces. We then apply these resources to explore the complex interplay between historical contingency, ongoing adaptation, and the potential for future gains through climate-aware genome-enabled breeding. Specifically, our analyses conclusively demonstrate that multiple nested, deeply diverged, and previously uncharacterized structural variants in the domestication gene SHATTERING1 distinguish the previously established multicentric origin of sorghum. We then apply landscape genomics tests to reveal how gene flow, adaptation, and secondary contact created the complex genetic mosaic in current global breeding networks. Further analysis of climate-gene associations highlights candidate loci underlying adaptation, including the biosynthetic gene cluster for the cyanogenic glucoside dhurrin. Combined, the pangenome-informed variants developed here will enable both trait discovery and subsequent marker assays to accelerate breeding and provide a framework for similar applications in other diverse and non-model crops.

Sorghum is a major cereal crop that plays an important role in food security for millions of people in arid and semi‐arid regions, but its production is threatened by drought. Therefore, understanding the genetic basis of transpiration rate during the early development stage is a key step towards improving sorghum production. The objectives were to study the physiological mechanisms for water‐saving in sorghum under non–limiting water conditions and to map QTL related to leaf transpiration along with root and plant morphology traits. We phenotyped 177 recombinant inbred lines derived from a cross between CSM63E and 93B1057 in plastic pots, under semi‐controlled conditions using a randomised complete block design (RCBD) with four replications. Results showed a wide range of phenotypic variation in the RIL population. The broad‐sense heritability ranged from 0.46 for leaf dry weight to 0.76 for plant height. We also reported a positive correlation between root (root dry weight, root volume, total number of nodal roots, root length and root area) and leaf (green leaf number, leaf dry weight and leaf area) traits. The transpiration rate traits were negatively associated with root and leaf traits, while there was a positive correlation with plant height. This study allowed the mapping of 23 QTLs on Chromosomes 1, 2, 3, 4, 6, 8 and 9, including seven QTLs for transpiration rate traits, five QTLs for root traits and seven QTLs for leaf and plant height traits. Additional studies can be conducted in drought conditions to identify more QTL associated with traits in sorghum.