Development of a preliminary nitrogen index for different soil types in Quebec
Bibliographic record
Abstract
Corn is a major crop in North America, with over 360,000 ha intensively cultivated in Quebec.Much of this Quebec cropland is also subsurface tile drained.Corn requires 120 to 180 kg/ha of nitrogen (N) to be applied to optimize yield, resulting in 43 to 65 thousand tonnes of N being applied to corn lands in Quebec.This addition of N has major environmental impacts, including the contribution to global warming via the emission of nitrous oxide and nitrate (NO3-N) pollution of water bodies and groundwater, caused by fertilizer runoff and leaching.To explore more sustainable methods of corn production that reduce its contribution to global warming, this research aids in the development of a soil-type-dependent N index that include losses from nitrous oxide emissions, N uptake by the plant, N transformations in the soil, and NO3 fluxes at tile drainage outlets.The developed N index is a ratio of N lost to the total available N.Field work was conducted on four agricultural fields near St Hyacinthe, Quebec, to determine soil characteristics.An experimental field in St Emmanuel, Quebec was also considered using previously published data.DRAINMOD was used to simulate the hydrology of the sites in order to accurately simulate the NO3 fluxes.DRAINMOD performed satisfactorily with indices of agreement (IOA) of 0.58 to 0.95 and Kling-Gupta Efficiencies (KGE) of 0.31 to 0.72.NO3 fluxes were then generated using DRAINMOD-N II for the five sites and a total of three different soil textures (silty loam, sandy loam, and clay loam).Due to lack of data, it was only possible to calibrate DRAINMOD-N II at two of the sites.For these two sites, DRAINMOD-N II performed satisfactorily with IOA of 0.89 to 0.97 and KGE of 0.45 to 0.8.The soil N was calculated based on field work, and the remaining parameters were obtained from literature and agronomists.Five fertilizer management practices were considered: 120, 122, 127, 180 and 222 kg N/ha.Sandy loams were found to leach the most NO3 with simulated values of 52.39 to 82.12 kg N/ha.Clay loams leached more than the silty loams with simulated values of 11.6 to 33.77 kg N/ha and 32.6 to 55.13 kg N/ha, respectively.The N index showed that sandy loams were the most at risk for N losses with low index values of 0.2 to 0.36, followed by clay loams (0.32 to 0.59) and then silty loams (0.84 to 1.43).The N-index results indicate that N management is sableux avec des valeurs simulées de 11,6 à 33,77 kg N/ha et 32,6 à 55,13 kg N/ha, respectivement.L'indice N'a montré que les limons sableux étaient les plus à risque de pertes d'azote avec des valeurs d'indice faibles de 0,2 à 0,36, suivis des franco-argileux (0,32 à 0,59) puis des limons sableux (0,84 à 1,43).Les résultats de l'indice N indiquent que la gestion de l'azote est la plus importante sur les champs agricoles avec un sol franco-sableux puisque les résultats de l'indice N étaient les plus élevées pour les sites de limon sableux, quelle que soit la pratique de gestion des engrais.Les valeurs anormalement élevées de l'indice N pour les sites de limon sableux ont été causées par une surestimation de l'accumulation d'azote dans le sol en raison du moment des mesures de terrain.L'exactitude de l'indice N est discutable en raison de la disponibilité limitée des données.Sur la base des résultats de cette recherche, il est recommandé aux agriculteurs et aux spécialistes des éléments nutritifs de se concentrer principalement sur les indices N de niveau un, car un indice N de niveau trois nécessite beaucoup de données.Si l'indice N de niveau un signale que le site est à haut risque, il faut alors passer à un indice de niveau trois.Si l'on ne dispose pas de données précises pour réaliser un indice N de niveau trois, les résultats seraient moins fiables.v
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".