Effects of Potassium, Calcium, and Magnesium Ratios in Soil on Their Uptake and Fruit Quality of Pummelo
Bibliographic record
Abstract
Potassium (K), Calcium (Ca), and Magnesium (Mg) are essential nutrients for pummelo. These nutrients are strongly antagonistic to each other. In case of excess concentration of one element, the uptake of the other elements is inhibited. This study was conducted on 17-year-old pummelo (Citrus maxima Merr.) during production year 2013 to 2015 to examine the effects of K, Ca, and Mg in soil on their uptake and fruit quality. The experiment was performed using six treatments with five replications. (NH4)2SO4, KCl, CaSO4·2H2O, and ZnSO4·7H2O were applied on top of farmer practice for the T1. (NH4)2SO4 was omitted for the T2, KCl was omitted for the T3, CaSO4·2H2O was omitted for the T4, no additional fertilizers were applied for the T5 (farmer practice), (NH4)2SO4 and CaSO4·2H2O were omitted for the T6, but 5Ca(NO3)2·NH4NO3·10H2O were applied instead. The soil pH was neutral and salinity was slight. Exchangeable K, Ca and Mg were higher than their optimum ranges. The extractable Zn in the soil and Zn in the leaves were lower than their optimum ranges. However, the problem can be solved by a single application 250 g tree-1 of ZnSO4·7H2O. Pummelo cannot uptake K to a sufficient level, even though it is abundant in the soil. High exchangeable Na and low K/Mg mole ratio in soil inhibited K uptake. Concentration of Ca in leaves corresponded to Ca and Ca/Mg mole ratio in the soil. Concentrations of Mg and K in leaves negatively correlated with each other. High Mg and Na in the soil inhibited the uptake of K and Ca, thereby causing extravagant consumptions of Mg. The fruit qualities were better in the treatment which mole ratios of K/Ca, K/Mg and Ca/Mg were 0.24 to 0.44, 0.31 to 0.44 and 0.89 to 1.29, respectively. Juice ratio of the pummelo positively correlated with the edible portion and negatively correlated with peel thickness.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".