Adaptation of alternative pulse and oilseed crops to the semiarid Canadian Prairie: Seed yield and water use efficiency
Bibliographic record
Abstract
Diversification and intensification of the cropping systems in the traditional wheat-fallow area of the semiarid Canadian prairie is necessary to improve sustainability. Selection of alternate crops to include in cropping systems requires information on production risks with different climate regimes. To understand water use/yield relationships of alternate crops, three pulse crops (leguminous grain crops) [chickpea (Cicer arietinum L.), pea (Pisum sativum L.) and lentil (Lens culinaris Medik.)], three oilseed crops [canola (Brassica napus L. and B. rapa L.) and mustard (B. juncea L.)], and one cereal crop [wheat (Triticum aestivum L.)] were studied under varying water regimes: during 1996–1998 under well-watered, rainfed, imposed drought conditions, and in 2001 under rainfed conditions. Generally, the relative ranking between crops for water use was maintained across water regimes, such that the crops separated into three general groups of water users (high: wheat, B. napus, mustard; medium: chickpea, B. rapa, lentil; low: pea) with pea using an average of 34 mm and 13 mm less water than high- and medium-water-using crop groups, respectively. The exceptions included desi chickpea, which tended to use less water and B. rapa, which tended to use more water relative to the other crops as water use decreased. Generally, pea and wheat produced the most grain and biomass, had the highest water use efficiency, and had moderately high to high harvest indices. Wheat and pea are well adapted to variable rainfall amounts inherent in semiarid climates. Desi chickpea and lentil produce good grain yields under dry conditions, and grain yields relative to those of other crops can be increased by some drought stress, especially mid- to late-season stress. Therefore, because of their relatively good performance under water-stressed conditions, they are also well adapted to semiarid climates. Conversely, the Brassica oilseeds yielded relatively poorly compared with wheat and pulse crops under severe water-stressed conditions, so they are not as well adapted to the semiarid climate. In 2001, grain yield of wheat and pulses seeded on stubble was ≥30% of the yield on fallow, whereas stubble-seeded Brassica oilseeds yielded only about 10% of that on fallow. Compared with stubble seeding, production of Brassica oilseeds on fallow will decrease the risk of very low yields under drought. We found little indication that mustard was more drought tolerant than B. napus. Key words: Yield, water use efficiency, oilseeds, pulse, semiarid prairie
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".