Comparison of consecutive and alternate fertilizer applications in wild blueberry production
Bibliographic record
Abstract
Research has shown that improved nutrient uptake and yield of wild blueberries (Vaccinium angustifolium Ait) are very sporadic when fertilizers are applied. Growers are concerned with environment impacts and keeping fertilizer costs to a minimum. Two experiments were conducted to evaluate the response of wild blueberries to soil-applied fertilization over four cropping cycles in Prince Edward Island and Nova Scotia from 1997 to 2004. Commercial fertilizers (17-17-17, 1-46-0 and 13-26-5) were soil-applied in the sprout year either as a consecutive fertilizer application (every cropping cycle) or an alternate fertilizer application (every second cropping cycle). All fertilizers were applied at a rate of 200 kg ha-1. Fertilizer applications increased soil levels of P and K, leaf tissue concentrations of N and P and stem lengths of plants. Higher levels of soil P and leaf tissue concentrations of N, P and K were observed with consecutive than with alternate fertilizer applications. Average stem lengths, buds and blossoms per stem were higher over the length of the study when fertilizers were applied consecutively compared with alternately. Fruit yields were increased compared with the unfertilized control. Within applied fertilizers treatments, fruit yield was not affected when fertilizer was applied in either consecutive or alternate cropping cycles. Alternate fertilizer applications may reduce soil accumulation of P and production costs without comprising yields. Key words: Cropping cycles, fertilization, soil and tissue nutrients, yield
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".