Expression of N‐cycling genes of root microbiomes provides insights for sustaining oilseed crop production
Bibliographic record
Abstract
Summary Agricultural production is dependent on inputs of nitrogen (N) whose cycle relies on soil and crop microbiomes. Crop diversification has increased productivity; however, its impact on the expression of microbial genes involved in N‐cycling pathways remains unknown. Here, we assessed N‐cycling gene expression patterns in the root and rhizosphere microbiomes of five oilseed crops as influenced by three 2‐year crop rotations. The first phase consisted of fallow, lentil or wheat, and the second phase consisted of one of five oilseed crops. Expression of bacterial amoA , nirK and nirS genes showed that the microbiome of Ethiopian mustard had the lowest and that of camelina the highest potential for N loss. A preceding rotation phase of lentil significantly increased the expression of nifH gene by 23% compared with wheat and improved nxrA gene expression by 51% with chemical fallow in the following oilseed crops respectively. Lentil substantially increased biological N 2 fixation and reduced denitrification in the following oilseed crops. Our results also revealed that most N‐cycling gene transcripts are more abundant in the microbiomes associated with roots than with the rhizosphere. The outcome of our investigation brings a new level of understanding on how crop diversification and rotation sequences are related to N‐cycling in annual cropping systems.
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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".