Soil salinity is significant abiotic stress that severely limits global crop production. Chickpea (Cicer arietinum L.) is an important grain legume that plays a substantial role in nutritional food security, especially in the developing world. This study used a chickpea population collected from the International Center for Agricultural Research in the Dry Area (ICARDA) genebank using the focused identification of germplasm strategy. The germplasm included 186 genotypes with broad Asian and African origins and genotyped with 1856 DArTseq markers. We conducted phenotyping for salinity in the field (Arish, Sinai, Egypt) and greenhouse hydroponic experiments at 100 mM NaCl concentration. Based on the performance in both hydroponic and field experiments, we identified seven genotypes from Azerbaijan and Pakistan (IGs: 70782, 70430, 70764, 117703, 6057, 8447, and 70249) as potential sources for high salinity tolerance. Multi-trait genome-wide association analysis (mtGWAS) detected one locus on chromosome Ca4 at 10618070 bp associated with salinity tolerance under hydroponic and field conditions. In addition, we located another locus specific to the hydroponic system on chromosome Ca2 at 30537619 bp. Gene annotation analysis revealed the location of rs5825813 within the Embryogenesis-associated protein (EMB8-like), while the location of rs5825939 is within the Ribosomal Protein Large P0 (RPLP0). Utilizing such markers in practical breeding programs can effectively improve the adaptability of current chickpea cultivars in saline soil. Moreover, researchers can use our markers to facilitate the incorporation of new genes into commercial cultivars.

Stripe or yellow rust, caused by Puccinia striiformis Westend. f. sp. tritici is a major threat to bread wheat production worldwide. The breakdown in resistance of certain major genes and newly emerging aggressive races of stripe rusts pose serious concerns in all main wheat growing areas of the world. To identify new sources of resistance and associated QTL for effective utilization in future breeding programs an association mapping (AM) panel comprising of 600 bread wheat landraces collected from eight different countries conserved at ICARDA gene bank were evaluated for seedling and adult plant resistance against the PstS2 and Warrior races of stripe rust at the Regional Cereal Rust Research Center (RCRRC), Izmir, Turkey during 2016, 2018 and 2019. A set of 25,169 informative SNP markers covering the whole genome were used to examine the population structure, linkage disequilibrium and marker‐trait associations in the AM panel. The genome‐wide association study (GWAS) was carried out using a Mixed Linear Model (MLM). We identified 47 SNP markers across 19 chromosomes with significant SNP‐trait associations for both seedling stage and adult plant resistance. The threshold of significance for all SNP‐trait associations was determined by the false discovery rate (q) ≤ 0.05. Three genomic regions ( QYr.1D_APR, QYr.3A_seedling and QYr.7D_seedling ) identified in this study do not correspond to previously reported Yr genes or QTL, suggesting new genomic regions for stripe rust resistance.

Population growth and the impacts of climate change are placing increasing pressure on global agriculture and breeding programmes. Recent advancements in phenotyping techniques, genotyping technologies, and predictive modelling are accelerating genetic gains in breeding programmes, helping researchers and breeders develop improved crops more efficiently. However, these advancements have also led to an overwhelming torrent of fragmented data, creating significant challenges in data integration and management. To address this issue, the Breeding Application Programming Interface (BrAPI) project was established as a standardized data model for breeding data. BrAPI is an international, community-driven effort that facilitates interoperability among databases and tools, improving the sharing and interpretation of breeding-related data. This open-source standard is software-agnostic and can be used by anyone interested in breeding, phenotyping, germplasm, genotyping, and agronomy data management. This manuscript provides an overview of the BrAPI project, highlighting the significant progress made in the development of the data standard and the expansion of its community. It also presents a showcase of the wide variety of BrAPI-compatible tools that have been built to enhance breeding and research activities, demonstrating how the project is advancing agricultural innovation and data management practices.

Bread wheat (Triticum aestivum L.) is crucial for food security in North Africa, where climate change and water scarcity threaten its productivity. Optimizing agronomic practices and understanding genetic traits can enhance yield. This study evaluated 159 spring bread wheat genotypes from ICARDA under raised bed, flat, and rainfed conditions in Egypt and Morocco. Five traits, including grain yield (GY), were assessed, and a genome-wide association study (GWAS) was performed using 17,968 SNPs. A total of 181 significant marker-trait associations (MTAs) were identified, with the highest under raised beds (148), followed by rainfed (75) and flat (53) conditions. The B genome had the most associations (91). Raised bed conditions yielded an average of 8.7 t/ha, surpassing flats (7.8 t/ha) and rainfed conditions (4.0 t/ha), demonstrating a +1 t/ha advantage. The top-performing genotype, G147, achieved yields of 11.4 t/ha, 10.7 t/ha, and 4.1 t/ha under raised beds, flats, and rainfed conditions, respectively. Genotypes G91 and G87 also showed stable performance. Notably, the marker “AX-94704405” on chromosome 6B (raised beds) and “AX-109853614” on chromosome 6D (rainfed) were significantly associated with GY, making them promising for marker-assisted selection after validation. The identified high-yielding genotypes will be considered for direct release following adaptation trials and for use as parents in breeding programs to enhance wheat productivity under diverse environments.

This study assessed six tomato (Solanum lycopersicum L.) cultivars within an integrated solar-powered closed hydroponic system in Al Dhaid, UAE (25°16′11.2″ N, 55°55′52.2″ E). The system combined an insect-proof net house, closed hydroponics, root-zone cooling, ultra-low-energy drip irrigation, and a cost-effective solar-powered reverse osmosis (RO) desalination unit to address salinity constraints. The cultivars, selected for their adaptability to controlled environments in the UAE, were evaluated for yield, water-use efficiency (WUE), and fertilizer-use efficiency (FUE). Among them, Torcida recorded the highest mean yield (0.619 kg/m²/harvest), WUE (27.1 kg/m³), FUE (26.5 kg fruit/kg fertilizer), and marketable fruit ratio (66.3%), followed by Roenza, Eviva, and SV 4129 TH; Lamina was intermediate, while Saley, a bushy type, produced the lowest yield. The top cultivars achieved cumulative yields exceeding 7 kg/m²—surpassing regional open-field benchmarks (4–5 kg/m²; 3–6 kg/m³). Compared with conventional cooled hydroponic greenhouses (3.5 kg/plant; 8 kg/m³), the system demonstrated similar productivity using three times less water. The RO unit produced water at baseline 1.05 USD/m³—58–68% below regional tariffs—while minimizing reliance on grid electricity and mechanical cooling. Overall, the integrated solar-powered hydroponic–RO model proved technically reliable, resource-efficient, and economically viable, offering a scalable solution for sustainable vegetable production in hyper-arid regions.