Starch as a source, starch as a sink: the bifunctional role of starch in carbon allocation
Bibliographic record
Abstract
Starch commands a central role in the carbon budget of the majority of plants on earth, and its biological role changes during development and in response to the environment. Throughout the life of a plant, starch plays a dual role in carbon allocation, acting as both a source, releasing carbon reserves in leaves for growth and development, and as a sink, either as a dedicated starch store in its own right (in seeds and tubers), or as a temporary reserve of carbon contributing to sink strength, in organs such as flowers, fruits, and developing non-starchy seeds. The presence of starch in tissues and organs thus has a profound impact on the physiology of the growing plant as its synthesis and degradation governs the availability of free sugars, which in turn control various growth and developmental processes. This review attempts to summarize the large body of information currently available on starch metabolism and its relationship to wider aspects of carbon metabolism and plant nutrition. It highlights gaps in our knowledge and points to research areas that show promise for bioengineering and manipulation of starch metabolism in order to achieve more desirable phenotypes such as increased yield or plant biomass.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".