Stability of Carotenoid Composition in Orange Sweet Potato (Ipomoea batatas) Tuber Flesh Over Three Growing Seasons and Months Storage Time
Bibliographic record
Abstract
Considerable research interest has recently focused on the development of both transgenic and traditional breeding methods to increase total and individual carotenoid composition in sweet potatoes. Unfortunately little information is available on the influence of the environment on carotenoid profile stability in sweet potatoes especially growing seasons and storage. Therefore the aim of this study is to explore the composition and concentration of carotenoids in orange sweet potato tubers to enable their future enhancement through genetic manipulation over different growing seasons and storage time. Our findings revealed that orange sweet potato tubers contained α-carotene and β-carotene in the first and second season, whereas in the third season only lutein and zeaxanthin were detected. Analysis of carotenoid profiles of the orange sweet potato tubers grown in three different seasons showed that the growing season had a major effect on the carotenoid compounds stability. Besides growing seasons, the level of total and individual carotenoids in orange sweet potato tuber flesh are strongly influenced and affected by storage conditions. The storage of tubers over 6 months period of time appears to have distinct effects on carotenoid content and composition. Results showed that storage from 1 to 6 months resulted in the accumulation of zeaxanthin and β-carotene with a concomitant decreased of lutein, α-carotene and total carotenoid content.
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 | 0.000 |
| 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 | 0.000 |
| 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".