Efficiency of fall-banded urea fertilizer in Manitoba : effect of application date, landscape position and fertilizer additives
Bibliographic record
Abstract
A two-year field study was initiated in the fall of 2000 to investigate the effects of application date, landscape position and a urease and nitrification inhibited formulation of urea on the transformation and efficiency of fall-banded nitrogen (N) fertilizer for Canadian Western Red Spring wheat (Triticum aestivum L. cv. AC Barrie) production under Manitoba conditions. Granular urea fertilizer at a rate of 80 kg N ha-1 was banded at three application dates in the fall, between mid-September and mid-October, and once in the spring at planting. In addition, there was a treatment where urea formulated with a urease and nitrification inhibitor (NBPT and DCD respectively) was banded in the early fall. During the fall, landscape position did not significantly influence the conversion of banded-urea to nitrate under the moisture conditions present at the intensive sites. However, delaying the date of application of fall-banded urea fertilizer N into the late fall and the presence of NBPT and DCD slowed nitrification and increased the percent recovery of fertilizer N as NH4+-N in the soil prior to freeze-up. Date of application, soil temperature on the date of application, the accumulation of soil heat units (SHU) and nitrification heat units [NHU) were all linearly related to the percent of recovered fertilizer N as NH4+-N. Accumulated SHU and NHU best described the relationship with the proportion of fertilizer N recovered as NH4+-N at the end of the fall, with and without inhibitors... In the spring, large over-winter losses of fall-banded N were observed in the first year of the study, with greater losses of apparent fertilizer N in the low landscape positions than in the high landscape positions... At harvest, the effects of landscape position were apparent at three of the four sites, with significantly greater grain yields, straw yields and total recovery of N in the high landscape positions than in the low landscape positions... In general, the efficiency of fall-banded urea was not affected by application date, soil temperature on date of application, cumulative soil heat units or cumulative nitrification heat units in the high landscape positions. In the low landscape positions, delaying application until late in the fall, when soil temperatures had cooled to 5 or 6oC, increased grain yelds and total N uptake by the crop relative to early fall-banded N. Soil temperature at application gave the best correlation with crop responses to N (relative grain yields, total N uptake, grain yield increases and N use efficiency) in the low landscape positions (r=-0.79**,-0.75**,-0.78** and -0.72** respectively); date of application gave slightly lower correlations (r=0.66*, 0.66*,0.64* and 0.62* respectively). Soil heat units and nitrification heat units accumulated from date of application until freeze-up gave inferior correlations (r=-0.56ns, -0.62*, -0.56ns and -0.58*, and r=-0.49ns, -0.59ns, -0,49ns and -0.51ns respectively). These results suggest that date of application and soil temperature at application are simple, robust approaches for estimating the effect of weather conditions on the efficiency of fall-banded N in southern Manitoba. The results also suggest that selection of suitable timing for application of fertilizer N to optimize crop yields is much more critical in wet years, for poorly drained fields, and for poorly drained areas within a field, than for better drained land.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".