SEVERITY OF ASCOCHYTA BLIGHT IN RELATION TO LEAF TYPE IN CHICKPEA
Bibliographic record
Abstract
Severity of Ascochyta blight (Ab) [caused by Ascochyta rabiei (Pass.) Labrousse] in chickpea ( Cicer arietinum L.) can be reduced by use of cultivars with a desirable plant architecture. Field experiments were conducted in semiarid southwestern Saskatchewan in 2001 and 2002 to determine the relationship between Ab severity and leaf shape in chickpea. Seed was treated with thiabendazole [2‐(thiazol‐4‐yl)benzimidazole], and metalaxyl [ N ‐(2,6‐dimethylphenyl)‐ N ‐(methoxyacetyl)‐DL‐alanine methyl ester] to reduce seed‐borne diseases, and plots were sprayed with chlorothalonil (tetrachloroisophthalonitrile) and azoxystrobin [methyl (E)‐2‐{2‐[6‐(2‐cyanophenoxy) pyrimidin‐4‐yloxy]phenyl}‐3‐methoxyacrylate] to minimize leaf diseases. Chickpea with fern leaves were compared with those with unifoliate leaves for their susceptibility to Ab. No diseases were observed during the seedling stage. As the crop approached preflowering, Ab symptoms became evident and the differences in Ab severity became great between fern‐ and unifoliate‐leafed chickpea. Measured at the bloom stage in 2001, Ab severity was 36% for unifoliate‐leafed chickpea and 12% for fern‐leafed chickpea. In the cool, moist year of 2002, the disease was severe with the unifoliate‐leafed chickpea having an Ab severity of 95%, compared with 35% for the fern‐leafed chickpea. The relative rankings of Ab severity between the two leaf types remained the same even when plant population was increased from 21 to 76 plants m −2 Chickpea producers in the semiarid northern Great Plains should select cultivars with a fern leaf shape to reduce the Ascochyta disease pressure and minimize disease damage to the crop.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".