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Wide range of genetic variation lentil diversity panel for agronomic and yield component traits in multi-location trial.in lentil diversity panel under diverse environments
No full textLentil (Lens culinaris) is a nutritionally and agronomically important legume crop, valued for its protein-rich seeds and its contribution to sustainable farming systems. To better exploit natural genetic variation, identify key agronomic and yield-related traits, accelerate genetic improvement, and address major challenges such as climate change, disease resistance, and yield stability, the development of a well-phenotyped diversity panel is essential. In this study, a total of 294 lentil accessions were evaluated at two ICARDA research stations: Terbol, Lebanon, and Marchouch, Morocco, during the 2023–24 growing season. The experiments were laid out in an alpha lattice design with two replications at each location. Several agronomic and yield component traits were recorded at both sites. Spatial row and column analysis of variance revealed highly significant differences among accessions for all measured traits in both environments (p < 0.001), indicating substantial phenotypic variability. Cluster analysis grouped the accessions into six clusters at Marchouch and four clusters at Terbol, reflecting differences in trait expression across environments. Principal component analysis (PCA) showed that the first three principal components (PC1, PC2, and PC3) explained 73.68% and 61.9% of the total variation at Marchouch and Terbol, respectively. Grain yield per plant (GYPO) and biomass per plant (BYPO) contributed the largest share of variation at both locations. At Terbol, PC1 (33.3%) was strongly associated with GYPO and BYPO, while at Marchouch, PC1 (26.48%) also showed strong associations with these traits. These results demonstrate considerable phenotypic diversity within the evaluated lentil panel and provide a valuable foundation for genome-wide association studies (GWAS) and marker-assisted selection in lentil breeding programs
National Workshop Training: Integrated Approach to Reproductive Management within Sheep and Goat Breeding Programmes
No full textTo support national efforts for rebuilding a breeding program for Tunisian sheep and goat breeds, experts in small ruminant reproduction and physiology at ICARDA and national Tunisian universities facilitated a training module on an “integrated approach to reproductive management within sheep and goat breeding programs”. The training focused on basic concepts of small ruminant reproductive management and recommended innovative practices and techniques for the implementation of a national breeding programme for sheep and goats in Tunisia
From Data to Genetic Progress: Reproductive and Productive Performance of Djallonké Goats in Mali’s CBBP Villages
No full textThis report presents the reproductive performance, as well as the growth and milk production of Djallonké goats (Chèvre Naine) in the two CBBP villages in Mali, namely Siguidolo Wéré and Noukoula. These results are based on Dtreo records collected from 2400 animals owned by 201 Malian farmers in Ségou. Current study is a first attempt to phenotypically characterize this breed
Behavioral Governance Tools for Multifunctional Forest Landscapes in Tunisia: Evidence from the Sajnen Forest
No full textThe Sajnen case study offers evidence of acceptance and intention that behavioral nudges, when carefully designed and ethically implemented, can enhance forest governance in Tunisia's multifunctional landscapes. Our research brief demonstrates that simplification and salience nudges are particularly effective, that transparency is non-negotiable for legitimacy, and that different user groups require tailored approaches. Perhaps most significantly, we found that nudge acceptance strongly predicts pro-environmental behavior intentions but that this relationship is mediated by institutional trust and constrained by structural barriers.
Looking forward, Tunisia stands at a critical juncture in forest governance. The traditional command-and-control model has shown its limitations, while the multifunctional demands on forest landscapes continue to intensify. Our findings suggest a way forward: an integrated approach that combines behavioral insights with institutional reform and structural change by integrated approach that combines behavioral insights with institutional reforms such as decentralizing decision-making to local GDAs and enhancing participatory monitoring and structural changes, including clarifying property rights and improving livelihood alternatives. These reforms are aligned with the objectives of Tunisia’s new Forest Code, which emphasizes participatory governance and sustainable landscape management. This approach recognizes that forests are not just ecological systems but social-ecological landscapes where human behavior, institutional arrangements, and biophysical processes interact continuously.
The opportunity exists for Tunisia to pioneer behaviorally informed, multifunctional forest governance in the Arab region and beyond. This requires moving beyond siloed approaches toward adaptive, participatory systems that respect local knowledge, build institutional trust, and address fundamental inequalities. It requires acknowledging that sustainable forest management is as much about governing people as it is about managing trees.
By blending insights from psychology, institutional economics, and landscape ecology, Tunisia can develop governance models that are both effective and equitable models that sustain forests while supporting the communities that depend on them. The path forward is clear: behavioral tools can help bridge the governance behavior gap, but only when implemented within transparent, participatory, and structurally sound governance frameworks. The forests of Sajnen and the communities that steward them offer both a compelling case study and a hopeful vision for what this integrated approach can achieve
From data to action: the transition path for smarter agricultural extension service in Egypt
No full textAgricultural extension systems in arid and semi-arid regions are facing increasing pressure to respond to climate variability, resource scarcity, and the growing demand for timely, site-specific advisory services. In Egypt, where agriculture plays a critical role in livelihoods and national food security, traditional extension models—largely dependent on in-person interactions—have become insufficient to address the scale, complexity, and dynamism of these challenges. Digital agricultural extension has therefore emerged as a strategic pathway to modernize advisory services, enhance their reach and effectiveness, and bridge persistent knowledge gaps between research, extension agents, and smallholder farmers.
This report documents a multi-year collaborative initiative between ICARDA, the Agricultural Research Center (ARC), and the Ministry of Agriculture and Land Reclamation (MALR), supported by CGIAR programs, to support Egypt’s transition from traditional agricultural extension toward a digitally enabled extension system. The initiative adopts a systemic perspective, recognizing that digital extension is not solely a technological intervention, but an integrated process encompassing institutional reform, digital innovation, human capacity development, and enabling policy dialogue.
Central to this collaboration is the co-design and deployment of the GeoAgro-Misr digital advisory platform, developed as a national tool to provide farmers with climate-smart, data-driven agronomic recommendations. The platform integrates remote sensing, weather forecasting, and expert knowledge to deliver location-specific guidance, while enabling two-way communication between farmers and extension experts. Rigorous validation exercises—including expert assessments, field trials, and large-scale user experience consultations—demonstrated the platform’s potential to improve water productivity, increase crop yields, and enhance farmers’ access to actionable information.
Recognizing that digital tools alone cannot deliver sustainable transformation, the initiative placed strong emphasis on institutionalization and capacity building. The establishment of the Agriculture Digital Extension Network (ADEN) provides an organizational framework to govern digital extension services, coordinate stakeholders, ensure content quality, and foster public–private partnerships. In parallel, targeted capacity-building programs were implemented to strengthen digital literacy, operational readiness, and change management skills within extension services, while engaging local farmers as digital extension ambassadors.
Complementing the technical and institutional components, the collaboration facilitated structured policy dialogue to align digital extension efforts with national strategies and inform decision-making. By linking evidence from field implementation with institutional and policy processes, the initiative contributes to a coherent transition pathway toward a resilient, scalable, and nationally owned digital extension system.
Overall, the report offers a comprehensive account of Egypt’s emerging digital extension model, highlights key lessons learned, and provides actionable insights for scaling digital advisory services within national agricultural innovation systems in Egypt and comparable contexts
Correlating the 1H NMR fingerprinting of a collection of red lentil varieties with seed colour and morphology using advanced statistical analyses
No full textThis study aimed to investigate the biochemical basis of seed morphological traits in red lentils that are important for lentil producers in relation to quality, consumers’ preferences and commercial value.
To achieve this objective, proton Nuclear Magnetic Resonance (1H NMR) spectroscopy combined with multivariate statistical analyses was employed. A collection of 64 red lentil varieties exhibiting diversity in seed colour, size, weight, and cotyledon pigmentation was analysed. Aqueous extracts of the seeds were profiled using 1H NMR, and spectra were processed into bucketed variables. Partial Least Squares Regression and Multiple Linear Regression were applied to assess relationships between spectral data and continuous morphological traits: lightness (L∗), chromatic indexes (a∗, b∗), Hundred Kernel Weight, and seed size. For categorical traits like cotyledon colour, Partial Least Squares Discriminant Analysis (PLS-DA) and binomial logistic regression were used. Variable Importance in Projection scores helped to identify key metabolite buckets significantly contributing to trait prediction. Metabolites such as leucine, fructose, and phenolic compounds were positively associated with seed size and weight, while NAD+ and short-chain fatty acids showed negative associations. Cotyledon colour classification achieved high accuracy (up to 100 %) using both PLS-DA and logistic models, with amino acids like leucine and alanine linked to yellow pigmentation and tryptophan and citrate linked to orange. Overall, the study demonstrates that 1H NMR fingerprinting, combined with rigorous statistical modelling, effectively elucidates the multivariate relationships between metabolomic profiles and key agronomic traits, providing a valuable tool for phenotypic prediction and lentil breeding
Sustainable rangeland management under climate change conditions in the MENA region: ICARDA works on NBSs at the landscape and farm levels
No full textThe presentation “Sustainable rangeland management under climate change conditions in the MENA region: ICARDA’s work on Nature-Based Solutions at landscape and farm levels,” was delivered at the IUCN World Conservation Congress, held in Abu Dhabi, UAE, from 9 to 15 October 2025, within the panel “Science in Action: Harnessing Nature-Based Solutions for Resilient Pastoral Landscapes” on 11 October 2025. This presentation highlighted ICARDA’s key achievements in developing innovative approaches and reviving and adapting traditional good practices. These efforts aim to restore and sustainably manage rangeland ecosystems while strengthening their resilience to climate change across the MENA region
Monte carlo simulation for evaluating spatial dynamics of toxic metals and potential health hazards in sebou basin surface water
No full textSurface water is vital for environmental sustainability and agricultural productivity but is highly
vulnerable to heavy metals (HMs) pollution from human activities. The focus of this research is to
provide an analysis of ecological and human exposure to HMs in the Sebou Basin, an agriculturally
significant region within Morocco’s Gharb Plain. Using a multi-index integration approach,
encompassing HM pollution indices, Human Health Risk Assessment (HHRA), Monte Carlo Simulation
(MCS), multivariate statistical analysis (MSA), and Geographic Information Systems (GIS), twenty
samples of surface water were taken and subjected to analysis. The results demonstrated notable
spatial variability, with the northwestern, southwestern, and western parts of the Sebou Basin
showing higher contamination levels. Cu exhibited the highest hazard quotient for ingestion, while
Cr exceeded the hazard index (HI) threshold in both age categories. Statistical analysis uncovered
strong associations, particularly between As and Cr, while principal component analysis (PCA) detected
two key factors explaining 74.44% of the overall variability. Pollution indices classified all samples as
highly contaminated (HPI > 30), with 65% categorized as “seriously affected” (MI > 6). The HHRA results
indicated a heightened non-carcinogenic risk for children and carcinogenic risks exceeding acceptable
thresholds (TCR > 10–4), with Ni presenting the highest risk (TCR = 2.32 × 10–3 for children). MCS results
revealed that Cu and Cr pose potential risks, with Cu exceeding the safety threshold for ingestion in
both adults and children. These results emphasize the urgent necessity for tailored strategies to reduce
contamination and foster sustainable agricultural and environmental management practices
Adjusted Crop Coefficient for Wheat Using Energy Balance Systems in North Nile Delta of Egypt
No full textAccurate crop coefficient (Kc) is essential for optimizing irrigation water use as well as enlargement water productivity in agriculture. This study aims to update the Kc values for wheat in the North Nile Delta, Egypt, using an energy balance (EB) system powered by Campbell Scientific instrumentations. Field experiments were conducted during three consecutive wheat-growing seasons of 2022/23,2023/24 and 2024/25 at Sakha Agricultural Research Station, covering an area of 4.2 hectares. Actual evapotranspiration (ETa) was measured using energy balance techniques, and Kc values were derived by comparing ETa with reference evapotranspiration (ETo) from FAO Penman Monteith approach. Results showed that FAO-56 Kc values tend to underestimate Kc during the initial (ini) and late-season (end) growth stages, while slightly overestimating mid-season Kc. The obtained Kc values for wheat were: 0.43–0.68 (Kc ini), 0.75–1.02 (Kc dev), 0.94–1.11 (Kc mid), and 0.4–0.64 (Kc end), differing from FAO-56 values. The findings suggest that local calibration of Kc is necessary for precise irrigation scheduling, enhancement water management efficiency, and consequently sustainable wheat production under water-scarce conditions
Conservation Status of Crop Wild Relatives in Lebanon’s Protected Areas: Eco-botanical Surveys for Baseline Data on Medicago
No full textLebanon, located within the Mediterranean Basin biodiversity hotspot, harbors a rich diversity of Crop Wild Relatives (CWRs), including more than 35 species of the genus Medicago (Fabaceae).
These taxa are vital genetic resources for developing climate-resilient crops and sustaining agrobiodiversity. However, their persistence is increasingly threatened by habitat degradation, overgrazing, land-use change, and climate variability. Despite Lebanon’s ecological richness and its network of protected areas, the conservation status and distribution of Medicago CWRs remain insufficiently documented.
This study, conducted in collaboration with the International Center for Agricultural Research in the Dry Areas (ICARDA), represents the second mission within a five-year monitoring program aimed at assessing Medicago CWR populations in Lebanon. Field surveys were conducted across eight protected areas using transect and quadrat sampling, combined with GIS spatial mapping and morphological characterization. A total of 232 georeferenced occurrences representing 20 taxa were recorded across 41 transects, showing clear variation in distribution patterns influenced by altitude, soil type, and disturbance gradients. Richness mapping identified the Shouf Biosphere Reserve as the main hotspot for Medicago diversity, while smaller reserves such as Mashaa Chnaniir and Bentael provided complementary habitats enhancing ecological representativeness. In addition to new field data, 14 previously unidentified accessions from earlier ICARDA missions were characterized through ex situ morphological analyses. The integration of current and previous
findings refines the understanding of Medicago distribution and ecological associations within
Lebanon’s protected areas.
The study reinforces the national baseline for Medicago CWR conservation, identifies priority taxa and sites, and supports the establishment of genetic reserves within protected areas. Ultimately, it contributes to targeted in situ and ex situ strategies that strengthen Lebanon’s agrobiodiversity conservation and align with global efforts toward sustainable biodiversity management