Response of chickpea varieties to drought stress and Ascochyta blight, caused by <i>Ascochyta rabiei</i>
Bibliographic record
Abstract
Ascochyta blight, caused by Ascochyta rabiei, is an important constraint to chickpea production globally. Chickpea is often grown in drier areas, prone to drought, especially terminal drought. Drought is a problem for crop cultivation worldwide and as the climate changes, drought risk increases. The extent to which commercial chickpea varieties will respond to drought and how this will impact their susceptibility or resistance to Ascochyta blight under temperate conditions of Saskatchewan is not known. We evaluated the response of chickpea varieties CDC Leader, CDC Orion, CDC Orkney, and CDC Pearl to drought during vegetative growth, followed by ample watering and inoculation with A. rabiei at flowering in some experiments. Greenhouse and growth chambers experiments had randomized complete block designs with five replicates per experiment. Both moderate and severe drought reduced plant height, numbers of nodes, and often biomass. In an initial experiment, drought-exposed CDC Leader developed more severe Ascochyta blight (3.6 versus 2.2 on a 0–9 scale). However, in subsequent experiments, drought did not influence the disease. CDC Orion was more drought-tolerant than CDC Leader. CDC Orkney was less drought-resilient than CDC Leader or CDC Pearl. CDC Pearl exhibited lower disease than CDC Leader, regardless of drought. The scouting for Ascochyta blight in seasons with early-season drought would be beneficial when rain is forecast; however, drought during vegetative growth does not always lead to more severe disease under conducive conditions. Field trials are merited to enhance the utilization of commercial chickpea cultivars.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".