A Blueprint for Building Resilience and Food Security in <scp>MENA</scp> and <scp>SSA</scp> Drylands: Diversifying Agriculture With Neglected and Underutilized Species
Bibliographic record
Abstract
ABSTRACT Drylands, encompassing 41% of global land and supporting over 2 billion people, face significant challenges, including water scarcity, extreme temperatures, and soil degradation. Dryland spans vast areas of Middle East and North Africa (MENA) and Sub‐Sahara Africa (SSA) regions and poses a threat to food security and resilience. This study examines the potential of neglected and underutilized species (NUS) to improve dryland food and nutrition security, focusing on their agronomic performance, water productivity, economic viability, and nutritional benefits. Using long‐term data from FAOSTAT, USDA Food Data Central, and peer‐reviewed literature, we analyzed trends in the cultivation, yield, and nutritional contributions of 26 NUS across 22 countries in the MENA region comparing them with major staples—rice, wheat, and maize. Between 1961 and 2022, NUS crop areas in MENA fluctuated, decreasing by 7.0% since 2018 to 21.17 Mha. Despite this, NUS demonstrated superior water productivity—up to 30% higher than major cereals. For instance, sorghum and cowpea achieved 2.5 kg/m 3 compared to maize (0.83 kg/m 3 ) and wheat (0.91 kg/m 3 ) and exhibited strong heat tolerance, withstanding temperatures of up to 42°C and 38°C, respectively. Despite a negative trade balance, NUS significantly contributed to dietary calories, surpassing wheat. A field experiment in Merchouch, Morocco, confirmed that NUS offered a higher economic value per unit than wheat, and outperformed conventional crops across key indicators. Integrating NUS into dryland farming systems can enhance food security, sustainability, and resilience to climate change. Advancing NUS requires breeding programs, tailored good agricultural practices, value addition and market linkage, supportive policies, and farmer education. Collaborative efforts among international organizations, governments, and civil society are crucial to mainstreaming NUS in agrifood systems and contributing to the diversity, sustainability, and resilience of dryland farming systems in MENA and SSA regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".