Field Trials of Genetically Modified Potatoes Resistant to Late Blight
Bibliographic record
Abstract
Late blight of potato is caused by pathogenic oocytes Phytophthora infestans. Long-term reliance on fungicides for control not only incurs high costs but also brings environmental and health risks. To achieve long-lasting and stable resistance, this study analyzed the disease resistance performance of transgenic potatoes introduced with wild Solanaceous plant resistance genes (Rpi genes) under field conditions in different regions and over multiple years. Although materials carrying a single Rpi gene can delay the onset of the disease to a certain extent, their resistance is easily broken through by pathogenic bacteria. By achieving the superposition of multiple Rpi genes with different sources and complementary recognition effectors through genetic engineering, stable, broad-spectrum, and even complete resistance to late blight can be demonstrated under natural infection conditions, and no significant resistance attenuation has been observed in multi-season trials. The study also combined the molecular detection and field resistance performance of the Rpi gene in Chinese potato germplasm resources to conduct a risk assessment of transgenic disease-resistant potatoes from aspects such as pathogen evolution, ecological security and gene flow. The transgenic and cis-gene breeding strategies with multi-gene superposition provide an important technical path for the sustainable prevention and control of late blight in potatoes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".