Rapid analysis of fructans and comparison of fructan profiles in several different types of asparagus storage roots using MALDI-TOF MS
Bibliographic record
Abstract
SummaryAppropriate conditions for analysing fructans in the storage roots of field-grown asparagus using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) were investigated. High resolution and ionisation were achieved when lyophilised and ground storage root powders were extracted twice with 1.0 ml distilled and deionised hot water (90°C), supplemented with 1.0 ml of 100% (v/v) ethanol, concentrated to approx. 1.0 ml, and mixed with 10 g l–1 2,5-dihydroxybenzoic acid (DHB) at 1:1 (v/v) before loading on a sample slide for MALDI-TOF MS, which was performed in the linear positive ion mode at a laser intensity of 15 kV. The mass spectral profiles showed that the degree of polymerisation (DP) of fructans ranged from three-to-21 in storage roots collected in the Winter.When different amounts of -cyclodextrin were added to each sample, a linear positive relationship was observed between the amount of -cyclodextrin and the relative positive ion intensity. With -cyclodextrin as an internal standard, fructan profiles were compared between Summer- and Winter-collected asparagus storage root samples. Furthermore, the fructan profiles of three different types of storage root of different colours (i.e., milky-white, yellow, or dark-brown) were also examined. Fructan contents were always higher in the Winter-collected samples than in those collected in the Summer, regardless of the DP. However, samples from the different coloured roots showed variable fructan profiles, depending on the DP. These results indicate that fructan analysis using MALDI-TOF MS would be useful for examining the dynamics of carbohydrate metabolism in asparagus storage roots because of its high degree of accuracy and its simplicity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".