Research Insight into the Genetic Regulation of Photosynthesis in Sweet Potato
Bibliographic record
Abstract
In sweet potato ( Ipomoea batatas ), improvements in photosynthetic capacity have significant implications for increasing yield, starch production, and resilience under environmental stress. This study explores the genetic regulation of photosynthesis in sweet potato, focusing on key genes, transcription factors, and pathways that enhance photosynthetic efficiency and carbohydrate metabolism. Genes such as IbVP1 and IbMIPS1 play pivotal roles in optimizing photosynthesis, while transcription factors like IbBBX29 and IbC3H18 are critical for stress tolerance and efficient light utilization. Recent advancements in genetic engineering, including CRISPR/Cas9 applications, provide new avenues for precisely modifying photosynthetic traits to boost productivity. Additionally, insights from high-photosynthetic sweet potato varieties and their genetic profiles offer valuable guidance for future breeding programs aimed at achieving higher yield and better adaptability. Understanding the molecular mechanisms behind these genetic factors can facilitate the development of resilient, high-yield sweet potato cultivars, contributing to food security and sustainable agriculture.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".