Solute transport in sub-irrigated peat-based growing media
Bibliographic record
Abstract
New legislation to reduce the amount of fertilizer leached into the environment by horticultural growers and the need to implement water-saving irrigation systems require an understanding of salt build-up and of nutrient cycles in order to develop efficient water-use strategies for growers. Solute transport in growing media is central to this process, but has received little attention thus far. The objectives of this study were to determine how solutes behave in sub-irrigated growing media and to assess a solute transport model for these media. A steady state evaporation (upward water flow) experiment was carried out with three different growing media in packed columns in the laboratory. Bromide, potassium and copper concentrations were determined using in-column pore water solution samplers and by sectioning the columns at the end of the experiment to obtain concentration profiles. The Hydrus-1D model was fitted to the solution sampler data assuming non-linear Freundlich adsorption, and then used to obtain favorable predictions of the measured concentration profiles. Independent adsorption isotherm results from batch experiments were found to be inadequate when used to predict solute movement and the results indicate that the preferred approach is an in-column evaluation of the transport parameters.Key words: Solute transport, sub-irrigation, peat, growing media
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 | 0.000 |
| 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 | 0.001 | 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".