Effects of phosphorus and potassium application on yield,quality,and storability of citurs fruits
Bibliographic record
Abstract
Phosphorus(P) and Potassium(K) are major important factors affecting citrus growth,yield and quality.Although the effects of P and K nutrition have well been documented for citrus trees in terms of fruit growth and yield,the influence of these two macronutrients on quality and storability of citrus fruits has not been fully elucidated.In the present study,a long-term field experiment was carried out for four years on Ponkan(Citrus reticulata Blanco var.Ponkan) in order to determine the effects of P and K application on fruit yield,quality and storability of citrus grown in a red-soil(orchard) with low P and K concentrations.The experiment was set up in a incomplete factorial design with 7 treatments,with three yearly rates of P(P 0,125 and 250 kg/ha) and K(K 0,250 and 500 kg/ha).The results showed that P or K,especially combined application of P and K greatly increased single fruit weight(62.93 to 114.11 g/fruit),fruit yield(19923 to 48234 kg/ha),content of soluble solids(12.2% to 13.3%) and soluble sugars(2.58% to 3.72%),(reducing) sugar content(4.51% to 6.16%),brixacid ratio(2.84 to 5.15)and vitamin C content(37.52 to 44.91(mg/100g FW)) of citrus fruits,and decreased titratable acidity(1.59% to 1.19%) of citrus fruits.Furthermore,P and K supply(effectively) reduced weight loss of fruit,rate of fruit decay,and modified the decrease of sugar content,acidity and Vc of fruit during storage of citrus fruits.It suggests that applying P and K could increase yield and quality of citrus fruit and improve sensory and nutritive quality and storability of fruit during storage.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".