Non-Targeted Metabolomics Analysis of Differences in Fruit Metabolites of Different Plum Varieties
Bibliographic record
Abstract
A total of 951 metabolites including 489 primary ones and 315 secondary ones were detected in plum fruit from 5 different varieties/lines in Guangdong by non-targeted metabolomics. For all plum varieties/lines, lipids were the most abundant primary metabolites, followed by sugars, alcohols, amino acids and organic acids, while the contents of nucleotides and vitamins were relatively low. Polyphenols were the most abundant secondary metabolites, followed by plant hormones, alkaloids and terpenoids, while the contents of phenylpropanoids and lignan were very low. The most abundant lipid component in Dami plum was undecanoic acid, accounting for 92.9% of the total lipids. The content of sugar in the fruit of plum is second only to lipid. The most abundant sugar in Dami plum was turanose, 9.5, 8 and 14.6 times as abundant as sucrose, glucose and fructose, respectively, which might be the major contributor to the honey flavor in Dami plum. A total of 170 amino acids and their derivatives were identified, greater than that of any other primary metabolites. L-malic acid was the major organic acid, accounting for 57.1% of the total organic acids and their derivatives. VB6 was the most abundant vitamin, accounting for 51.5% of the total vitamins. Flavonoids were the most abundant polyphenols, accounting for 77.7% of the total polyphenols. Altogether, 84, 73, 113 and 34 differential metabolites were identified between Dami plum and Qingpi, Xiaomi, Hongxian and Daguochishu Sanhua plum, respectively. Metabolic pathway enrichment analysis of differential metabolites showed that the differential metabolites of the 4 groups were mainly enriched in amino acids, flavonoids, anthocyanins, alkaloids and synthetic and metabolic pathways. The major differential metabolites between Daguochishu Sanhua and Dami plum were flavonoids and phenols such as C-pentosyl-luteolin-C-hexoside, dopamine and trilobatin, and nucleotides such as nicotinamide adenine dinucleotide and β-nicotinamide mononucleotide. These substances may be the key differential metabolites between the 2 varieties at the mature stage.
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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 | 0.001 | 0.001 |
| 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".