GROWTH AND FLOWERING OF ‘PUYAT’ DURIAN (Durio zibethinus Murr.) AS INFLUENCED BY DIFFERENT TYPES OF FERTILIZER APPLICATION
Bibliographic record
Abstract
This study was conducted to evaluate the effect of different types of fertilizer application on the growth and flowering of ‘Puyat Durian’ (Durio Zibethenus Murr.); and determine the best fertilizer application for the optimum production of Durian. Ten (10) year old trees at Canoy Durian Farm, Pindasan, Mabini, Compostela Valley Province were tested from November 2015 to March 2016. The experiment was laid out in Randomized Completely Block Design (RCBD) with six treatments, replicated three times. The treatments were: T1- Untreated; T2-Recommended Rate- RR (based on soil analysis); T3- Optimum Rate- OR + (3kg NPK+1kg MOP); T4- OR+ GOFF; T5- RR+ GOFF; T6- GOFF (Green-shield Organic-based Fortified Foliar Fertilizer).Statistical analysis showed that there were significant differences among treatments in terms of trees with flushes and number of flowers per cluster but no significant effects were observed in canopy diameter and number of flower cluster per tree. Result of the study showed that fertilizer application increased the number of flower per cluster of 'Puyat' Durian and enhanced flushing of durian trees. The study further revealed that organic based foliar fertilizer alone enhanced flowering up to five times higher than without application (control). While numerically, GOFF (Green-shield Organic-based Fortified Foliar Fertilizer) alone had the highest number of flower cluster per tree
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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 | 0.000 | 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 | 0.000 |
| 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 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".