Fluctuation in the soil nitrogen supply resulting from green manure plow-down are detected by ion exchange membranes and the nitrogen uptake of arugula (Eruca sativa L.)
Bibliographic record
Abstract
Green manure crop mixtures contain legumes that capture N2 from the atmosphere. When green manure is plowed down in agricultural soil, the decomposing green manure residues are a source of N fertilizer for the following crop. The challenge is to determine how quickly the green manure releases plant-available N and what proportion of the N requirements of the next crop can be met by green manure. Ion exchange membranes (IEMs) hold promise in evaluating the N supplied by green manure because these in situ measurement tools are placed in the same environment where roots grow, and they act as a sink for plant-available N. The objectives of my thesis were to 1) determine the pattern of plant-available N release from field pea-oat green manure under field conditions with IEMs, and relate this to the N demands of arugula (Eruca sativa L.); 2) to determine if IEMs could detect small changes in plant-available N dynamics in different soil types that were amended with green manure residues having a low C/N ratio; and 3) to determine how tillage practices that reduce the physical size of green manure residues may accelerate plant-available N release from green manure, as determined by IEMs, and meet crop N requirements; 4) to assess the potential contribution of root exudates from arugula on N mineralization after the incorporation of green manure mixture (peas-oats). In a field experiment, in two soil types in Quebec, Canada, a green manure mixture (field pea and oat) contributed to the plant-available N concentration and arugula N uptake. The IEM-NO3-N supply was greater than arugula N demand, suggesting that second crop or a winter cover crop could use the residual soil N released by the green manure. In an incubation experiment, I validated the use of IEMs by incorporating green manure residues with variable C/N ratios. The green manure residues with low C/N ratio (C/N = 8) showed immediate release of plant-available N, whereas residues with C/N = 12 ratio had a delay in releasing plant-available N. The delay suggested that the C/N ratio of green manure residue plus analysis with IEMs was a good indicator of plant-available N dynamics. In addition, the different soil texture (clay loam and sandy loam) modulated the decomposition process and plant-available N concentrations. Greater tillage intensity reduced the percentage of residues with larger particle size. While the higher concentration of plant-available N was released with 4 passes of the cultivator, the maximum N uptake by arugula was reached with 2 passes of the cultivator. Residues remaining after the experiment continued to release plant-available N, suggesting that residual soil N would be left after arugula harvest. The cash crop root exudate demonstrated to play a role in N mineralization through the exudate and showed greater impact on microbial biomass when green manure residues were 0.5 – 1 mm, followed by residues size 2 – 4 mm, and bare soil. In conclusion, the use of IEMs in situ and in incubation experiments could accurately assess the pattern of N release from green manure. This provides insight about the plant-available N dynamics and root input in soils receiving green manure and when N is available for subsequent crops. Farmers can use this information to select crops that will fully use the plant-available N, thus optimizing the N recovery from green manure crops.
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 | 0.000 | 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".