Untargeted Metabolomics Profiling of High Beta Carotene Cassava with respect to Postharvest Physiological Deterioration
Bibliographic record
Abstract
Cassava roots undergo postharvest physiological deterioration (PPD), and for most varieties it sets in within 72 hours of harvest. An untargeted metabolomics approach combined with a data-driven approach for statistical analysis was used to characterize and profile high beta-carotene cassava varieties with the aim of identifying any relevant metabolite changes that occur during PPD. Sixteen cassava root samples from four cassava lines were planted in a greenhouse and harvested after four months. The samples included four of 2 conventionally bred beta carotene cassava varieties – UMUCASS 38, UMUCASS 45 and four of 2 transgenic high beta carotene cultivars - EC20-7 and EC20-8 cassava lines. Extracts of fresh cassava roots from 20-100 mg tissues were used for the analyses and data were processed using Elements for Metabolomics software. Starch and lipid metabolites were the major constituents which may help explain the observed differences in starch and dry matter content among the varieties. The results provide further insight in the understanding of PPD and suggestions on controlling this deterioration in cassava are made.
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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 | 0.000 |
| 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".