Fertilization Methods for Organic and Conventional Potted Blueberry Plants
Bibliographic record
Abstract
This study determined optimal fertilization for each of three production methods (i.e., two organic and one conventional) of potted Vaccinium corymbosum ‘Duke’ northern highbush blueberry plants. The three production methods were as follows: 1) organic granular [(OG) organic coir substrate fertilized with Bio-Fert General Purpose + bloodmeal applied at 4.4, 7.3, 10.2, 13.1, and 16.0 g/pot nitrogen (N)], 2) organic liquid [(OL) organic coir substrate fertilized with Bio-Fert General-Purpose Liquid + calcium oxide (CaO) applied at 12.2, 14.7, 18.6, 25.3, and 39.5 mmol·L –1 N), and 3) conventional (C; pine bark, coir, and peat substrate fertilized with Osmocote Plus 15N–3.9P–9.9K, 5- to 6-month-duration controlled-release fertilizer applied at 4.4, 7.3, 10.2, 13.1, and 16.0 g/pot N). Blueberry plants were grown in #5 black, squat nursery containers outdoors in the Niagara peninsula, ON, Canada for two (2015–16) growing seasons. Both of the organic and the conventional production systems produced healthy blueberry plants when fertilizer was applied appropriately. With fertilizer application at 4.4 and 7.3 g/pot N for C, 12.2 and 14.7 mmol·L –1 N for the OL, and 8.50 to 13.95 g/pot N for the OG treatments, healthy plant growth was observed in combination with low nutrient leaching. High fertilizer rates resulted in excessive root zone electrical conductivity (EC), poor plant growth, and interveinal chlorosis, which affected fruit production negatively. For C and OL treatments, fertilization at rates of 4.4, 7.3 and 10.2 g/pot N, and 12.2, 14.7, and 18.6 mmol·L –1 N, respectively, produced the greatest total fresh weight of fruit. For OG, a large total fruit fresh weight was produced by all plants with no difference among fertilizer rates. This study suggests optimal fertilizer rates from 4.4 to 7.3 g/pot N for C, 12.2 to 14.7 mmol·L –1 N for the OL treatment, and from 8.50 to 13.95 g/pot N for the OG treatment can be applied based on the methods described in this study during potted blueberry production in nurseries and home gardens.
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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".