Molybdenum Uptake by Forage Crops Grown on Sewage Sludge‐Amended Soils in the Field and Greenhouse
Bibliographic record
Abstract
Abstract Molybdenum (Mo) is a plant‐available element in soils that can adversely affect the health of farm animals. There is a need for more information on its uptake into forage crops from waste materials, such as sewage sludge, applied to agricultural land. Field and greenhouse experiments with several crops grown on long‐term sewage sludge‐amended soils as well as soils recently amended with dewatered (DW) and alkaline‐stabilized (ALK) sludges indicated that Mo supplied from sludge is readily taken up by legumes in particular. Excessive uptake into red clover ( Trifolium pratense L.) (>30 mg/kg) was seen in a soil that had been heavily amended with sewage sludge 20 yr earlier, where the soil contained about 3 mg Mo/kg soil, three times the background soil concentration. The greenhouse and field studies indicated that Mo can have a long residual availability in sludge‐amended soils. The effect of sludge application was to decrease Cu to Mo ratios in legume forages, canola ( Brassica napus var. napus ) and soybeans [ Glycine max (L.) Merr.] below the recommended limit of 2:1 for ruminant diets, a consequence of high bioavailability of Mo and low uptake of Cu added in sludge. Molybdenum uptake coefficients (UCs) for ALK sludge were higher than for DW sludge, presumably due to the greater solubility of Mo measured in the more alkaline sludges and soils. Based on these UCs, it is tentatively recommended that cumulative Mo loadings on forages grown on nonacid soils should not exceed 1.0 kg/ha from ALK sludge or 4.0 kg/ha from DW sludge.
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 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 | 0.001 | 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) | 0.001 | 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 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".