An Assessment of the Adaptability to Climate Change of Commercially Available Maize Varieties in Zimbabwe
Bibliographic record
Abstract
A study was undertaken to assess the adaptability to climate change of commercially available maize varieties in Zimbabwe using 2010, 2020, 2050 and 2080 climate change scenarios. The FAO’s Ecocrop Model was used to assess the suitability of early, short, medium and long season maize varieties grown under rainfed conditions in different agro-ecological regions (1 to 5) whose agricultural potential decreases progressively due to the amount of rainfall received. Regions 1 and 2 conditions are projected to decrease in size by 14%, region 3 by 26%, while regions 4 and 5 are projected to increase by 40%. The area suitable for growing early low yielding maize varieties will remain at nearly 100% in regions 1 and 2. The area suitable for growing medium maturing varieties will decline to below 20% in regions 4 and 5. Overall, only 2% of Zimbabwe s’ land area, mainly in region 1, will be suitable for growing high yielding late maturing maize varieties. The paper concludes that the currently available maize germplasm in the country is not suitable for the projected climate change conditions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".