Accumulation and distribution of micronutrients in Willamette red raspberry plants
Bibliographic record
Abstract
Willamette red raspberry (Rubus idaeus L.) plants were sampled monthly to determine the accumulation and distribution of copper (Cu), boron (B), zinc (Zn), manganese (Mn) and iron (Fe) over the growing seasons of four different years. The soil (Marble Hill series) was typical of that commonly used for commercial raspberry production in the area. No micronutrients were applied. The micronutrients generally accumulated as the season progressed in a manner similar to the accumulation of dry matter. Maximum accumulation of micronutrients in the aboveground portion of the plants did not necessarily occur at the end of the growing season because of different growth patterns of the floricanes and primocanes. The ripe berries, which would be removed by harvesting, contained a significant proportion of the total accumulation of micronutrients: Cu (18–26%), Zn (15–25%), B (3–16%), Fe (5–8%) and Mn (4–7%). However, concentrations of the micronutrients in the various parts of the plant varied considerably from month to month and year to year. There was no obvious relationship between weather conditions and the variations in micronutrient concentrations. Extreme variations within and between growing seasons suggest concentrations of micronutrients in leaves cannot readily be used to develop tissue-analysis-based fertility recommendations. Floricane stem micronutrient concentrations were more stable but the relationship between these concentrations and the overall nutrient status of the plants needs to be determined before they can be used for diagnostic purposes. Before accumulation and distribution patterns of micronutrients in raspberry can be used as a basis for development of fertilizer management strategies, additional measurements from other locations are needed. The results from this study should serve as guidelines for developing sampling procedures and their practical applications. Key words: Copper, boron, zinc, manganese, iron, Rubus idaeus L.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".