Constraints to Vegetable Production Resulting from Pest and Diseases Induced by Climate Change and Globalization: A Review
Bibliographic record
Abstract
Vegetable production worldwide is constrained by pests and diseases which effects are exacerbated by climate change and variability. Greenhouse gas emissions are also increasing due to poor agricultural practices and other human activities. This will continue to have a negative impact on the prevalence of insect pests and diseases. This review focuses on the climatic factors that impact on insect pests and diseases of vegetable crops. High atmospheric temperatures and elevated carbon dioxide increases pest development, survival of pests and distribution of pest to new areas. The distribution of insect pests and diseases are not due to climate changes only but are also a result of globalisation and poor biosecurity measures at country borders. There is limited information on the distribution of pests and diseases due to globalisation in African countries. New exotic pests will continue to be introduced to countries if biosecurity measures are not improved. Future research must focus on how to manage emerging pests and diseases influenced by high temperatures and carbon dioxide and other climatic conditions which influence pest severity under smallholder farmers in the southern African 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".