Changes in Organic Acid Contents and Related Metabolic Enzyme Activities at Different Stages of Growth of Two Tangerine Cultivars
Bibliographic record
Abstract
Citric acid accumulation and decline and its related enzymes were studied at different stages of growth of two tangerine cultivars, ‘Sai Num Phueng’ and ‘See Thong’. Citric acidcontent increased to the peak at early growth stage (16-24 weeks after full bloom, WAF), then decreased rapidly for 28-34 WAFand slightly decreased during maturation (35-37 WAF). ‘Sai Num Phueng’ had higher citric acid content than ‘See Thong’. The activities of enzymes citrate synthase in mitochondrial fraction, aconitase in both mitochondrial and cytosolic fractions and NADP-isocitrate dehydrogenase (IDH) in cytosolic fraction were determined. The changes in these three enzyme activities followed similar patterns in both cultivars. For 16-24 WAF, citrate synthase activity increased and aconitase activity decreased in mitochondrial fraction, which accelerated the increasingin citric acid content of both cultivars. Therefore, citrate synthase and aconitase enzymes in mitochondria were essential forcitric acid accumulation at early growth stage. During 28-34 WAF, aconitase and NADP-IDH activities in cytosolic fraction were induced with the concomitant decrease of citric acid content. Thus, aconitase in cytosol played a key role in the reduction of citric acid. NADP-IDH could be consisted with aconitase for enhancement the reduction of citric acid in cytosol. Aconitase activity could account for the difference in citric acid contentbetween ‘Sai Num Phueng’ and ‘See Thong’. It was also found that the level of citrate synthase activity was quite similar between the two cultivars but aconitase activity was lower in ‘Sai Num Phueng’ than in ‘See Thong’.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".