The influence of microbial-based inoculants on N<sub>2</sub>O emissions from soil planted with corn (<i>Zea mays</i> L.) under greenhouse conditions with different nitrogen fertilizer regimens
Bibliographic record
Abstract
Nitrous oxide (N2O) emissions are increasing at an unprecedented rate owing to the increased use of nitrogen (N) fertilizers. Thus, new innovative management tools are needed to reduce emissions. One potential approach is the use of microbial inoculants in agricultural production. In a previous incubation study, we observed reductions in N2O emissions when microbial-based inoculants were added to soil (no plants present) with N fertilizers under laboratory incubations. This present study evaluated the effects of microbial-based inoculants on N2O and carbon dioxide (CO2) emissions when applied to soil planted with corn (Zea mays L.) under controlled greenhouse conditions. Inoculant treatments consisted of (i) SoilBuilder (SB), (ii) a metabolite extract of SoilBuilder (SBF), and (iii) a mixture of 4 strains of plant-growth-promoting Bacillus spp. (BM). Experiments included an unfertilized control and 3 N fertilizers: urea, urea – ammonium nitrate with 32% N (UAN-32), and calcium – ammonium nitrate with 17% N (CAN-17). Cumulative N2O fluxes from pots 41 days after planting showed significant reductions in N2O of 15% (SB), 41% (BM), and 28% (SBF) with CAN-17 fertilizer. When UAN-32 was used, reductions of 34% (SB), 35% (SBF), and 49% (BM) were obtained. However, no reductions in N2O emissions occurred with urea. Microbial-based inoculants did not affect total CO2 emissions from any of the fertilized treatments or the unfertilized control. N uptake was increased by an average of 56% with microbial inoculants compared with the control (nonmicrobial-based treatments). Significant increases in plant height, SPAD chlorophyll readings, and fresh and dry shoot mass were also observed when the microbial-based treatments were applied (with and without N). Overall, results demonstrate that microbial inoculants can reduce N2O emissions following fertilizer application depending on the N fertilizer type used and can enhance N uptake and plant growth. Future studies are planned to evaluate the effectiveness of these microbial inoculants in field-based trials and determine the mechanisms involved in N2O reduction.
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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) | 0.001 | 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".