Lipidomic profiling of guava cultivars by UPLC/MS Q-TOF analysis
Bibliographic record
Abstract
• The 1371 lipids were found in guava, distributed in 6 classes and 50 subclasses. • The content of total lipids was the highest in GY, followed by GH, GZ and GJ. • NLs and SLs are the dominant lipids of the four varieties. • Hex1Cer, TG and PC are the most important lipid subclasses. This study aimed to perform a comprehensive lipidomic analysis of four representative guava cultivars using ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry. The analytical results revealed a wide range of lipids in four representative guava cultivars. A total of 1371 lipids were annotated, distributed in 6 categories and 50 subcategories. The total lipid content in GY was the highest among the four cultivars, followed by GH, GZ, and GJ. Neutral lipids and sphingolipids were the predominant lipid types in four cultivars, accounting for >50 %. Moreover, hexosylceramides, triglycerides, and phosphatidylcholines were the most predominant subcategories of lipids. Meanwhile, bioactive lipids, including sphingolipids and phytosterols, were also detected. The chain length and unsaturation were further determined to explore the digestive characteristics of guava fruit. The results showed ultralong-chain fatty acids (>26 carbon atoms) and polyunsaturated fatty acids (>2 double bonds) in the 4 cultivars, implying that guava fruit is not only a source of essential fatty acids but also a good energy provider for human beings. The rich diversity and notable abundance of bioactive lipids identified in this study highlight the exceptional potential of guava fruit as a prolific source of functional ingredients, which is highly promising for the development of nutraceuticals and functional foods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".