Morphological Characteristics, Nutritional Quality, and Bioactive Constituents in Fruits of Two Avocado (Persea americana) Varieties from Hainan Province, China
Bibliographic record
Abstract
We studied the morphological characteristics, nutritional quality, and the bioactive compounds in fruits of two avocado accessions, RN-7 and RN-8, produced in Hainan province, China. Edible and non-edible parts of the fruit (pulp and seed) were compared to evaluate their possible contribution to improve the sustainability of the food and pharmaceutical industries. The basic characteristics evaluated were moisture, ash, total lipid, fatty acid composition, soluble sugars, titratable acid, soluble protein, and minerals. We also measured the concentrations of six types of bioactive compounds; total phenolics, flavonoids, tannin, ascorbic acid, tocopheryl acetate, and carotenoids. Our analyses of the nutritional compositions demonstrated that the pulp of the RN-7 and RN-8 proved to be rich in moisture, total lipid, and soluble protein. The seed, in turn, had higher soluble sugar, titratable acidity, sodium, potassium, calcium, iron, copper, and zinc contents. Other nutritional compositions (ash, magnesium, and manganese) had little differences between the pulp and seed of avocado fruit. With regard to the contents of bioactive compounds, the seed was superior to the pulp in the contents of total phenolics, flavonoids, and tannin. Regarding the concentrations of ascorbic acid, tocopheryl acetate, and total carotenoids, the highest values were found in the pulp. The results of fatty acid compositions displayed that the palmitic, palmitoleic, stearic, oleic, and linoleic acid contents of the pulp were higher than those of the seed, while myristic and arachic acid had higher contents in the seed.
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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) | 0.000 | 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 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".