Nutritional implications of biosolids and paper mulch applications in high density apple orchards
Bibliographic record
Abstract
A field experiment was designed to assess the effects on tree nutrition of surface application of municipal biosolids and shredded paper mulch, which have previously been reported to improve the performance of high-density apples despite wide differences in nutrient content. The experiment involved four treatments which included two levels (with or without) of two organic amendments, shredded paper mulch and Greater Vancouver Regional District (GVRD) municipal biosolids. Treatments were established over a 2 m wide strip centred on the tree row in a high-density (3700 trees ha -1 ) Golden Delicious (Malus × domestica Borkh.) orchard in the year of planting (1997) and maintained until 2004. GVRD-biosolids was applied at 40 t ha -1 (DW) in 1997 and 20.3 t ha -1 (DW) in 2001 potentially supplying larger amounts of all plant nutrients (N, P, K, Mg, Zn, Cu and Mn) except Ca than the paper mulch. All trees received standard commercial treatments of drip fertigation of 30 g N tree -1 yr -1 and 20 g P tree -1 in the establishment year. Leaf N concentration was unaffected by biosolids application and decreased, but not to inadequate concentrations, in 3 of 6 yr for trees grown in the high C:N ratio shredded paper mulch. This response indicates the effectiveness of drip fertigated N. Leaf K declined to inadequate concentrations by the end of the experiment, regardless of treatment, but trees in the paper mulch treatment were able to sustain higher leaf K, were more vigourous, had higher yield the first three fruiting seasons and cumulatively after 8 yr despite the low N and K content of the paper. Improved K uptake was attributed to better distribution of soil moisture beneath the mulch but for long-term sustainable production, K fertigation would have been desirable. Biosolids application often raised leaf Zn, Cu and Mn concentration but increases were modest, with concentrations of Zn insufficient to change standard commercial recommendations for annual dormant Zn applications. Key words: Leaf N, K, Zn, Cu and Mn, nutrient additions, organic amendments, vigour, yield
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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".