VARIATION OF ELECTROLYTES, AMINO ACIDS AND REDUCING SUGARS IN COCONUT WATER OF DIFFERENT AGES FROM AN INLAND REGION OF BANGLADESH
Bibliographic record
Abstract
Coconut water, extracted from the fruit of Cocos nucifera L., is a popular drinks throughout the tropics.The variable nature of the composition of the drinks had been established multiple times before, with regards to age, location and genetic variation.However, in Bangladesh, such studies were not carried out before.Thus, this study aims to compare electrolytes, amino acids and carbohydrates concentration in coconut water of different age collected from an inland region of the country.To determine electrolyte concentration atomic absorption spectrophotometry and Mohr titrimetric method were applied.Determination of carbohydrate and amino acid concentration required two separate high performance liquid chromatography (HPLC) methods.Regarding electrolytes concentration, rise of potassium, calcium and chloride ion concentration and fall of sodium and magnesium ion concentration were apparent.Potassium ion was the most abundant cation (50.88-67.56mEq/L) while steep rise of magnesium ion concentration from 4 month to 6 months (4.14±0.17 to 12.72±2.52mEq/L) was observed.Fructose and dextrose concentrations also escalated with coconut age.Amino acid concentrations varied as well.Histidine (0.43 g/100ml), arginine (0.053 g/100ml) and arginine (0.142 g/100ml) were the most abundant amino acids found in water 4, 6 and 8 months old coconuts.Overall, the trends of variation of components show intake of coconut water can bring different physical outcomes to different consumers and therefore, must be chosen carefully for patients with electrolytic imbalance and other medical complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".