Quantification of the yield and protein response to N and water availability by two wheat classes in the semiarid prairies
Bibliographic record
Abstract
Genetic improvements have increased grain yield of newer wheat (Triticum spp.) cultivars relative to older benchmark cultivars. However, the improvements have been larger in the Canada Western Amber Durum wheat class (CWAD) [Triticum turgidum L. var. durum (T. durum)] than the Canada Western Red Spring class (CWRS) (Triticum aestivum L.). Thus, it is necessary to determine if N fertilizer recommendations for these two wheat classes need to be segregated. We conducted fertility trials for four CWAD and seven CWRS cultivars during 4 yr, in two soils in southwestern Saskatchewan, under fallow- and stubble-cropping to determine if there were differences in the N response of the two wheat classes under various water availability conditions. Grain yields of CWAD were consistently higher than those of CWRS, while protein concentrations were higher for CWRS than for CWAD. A regression model consisting of available water (W) plus the interactions of W with fertilizer N (NF), NF2, soil NO3-N in the 0- to 60-cm depth (NS), NS2, and with the NF × NS interaction explained 76% of the yield variability of all cultivars and site years. Inclusion of wheat class as an indicator variable increased the proportion of the explained variability to 80%, and determined that both classes of wheat had similar response to N availability, and that CWAD had a larger response to available water than CWRS. A regression model consisting of a quadratic function of N and a linear term for W with wheat class as an indicator variable explained 58% of the variability in grain protein of all varieties, and indicated that both classes had the same protein response to N availability, but that the protein of CWAD decreased faster than that of CWRS as water availability increased. Inclusion of wheat cultivars as indicator variable, instead of wheat class, did not increase the resolution of the regression model for either yield or protein responses. Results of these analyses indicate that the amount of N required for maximum yield is the same for both wheat classes. Key words: Durum wheat, hard red spring wheat, grain yield, grain protein, fertilizer N, soil N, available water
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".