Developing Rainfall- and Temperature-Based Models to Describe Infection of Canola Under Field Conditions Caused by Pycnidiospores of <i>Leptosphaeria maculans</i>
Bibliographic record
Abstract
Blackleg, also known as Phoma stem canker, caused by Leptosphaeria maculans (Phoma lingam), is one of the most serious diseases of canola worldwide. In this study, the mean disease severity (Ds) and incidence (Di) of canola cv. Westar plants infected at the cotyledon, three-leaf, and six-leaf stages by pycnidiospores of L. maculans were monitored in the greenhouse after infection of the plants under field conditions in two successive years and associated with meteorological data during infection time. Pearson's correlation coefficient showed that total rainfall per week (R) was significantly correlated to Ds on plants infected at the cotyledon, three-leaf, and six-leaf stages, and average maximum temperature per week (Tmax) only showed significant correlation with plants infected at the cotyledon and six-leaf stages. These results also indicated that there is correlation between Di and R for plants infected at all three growth stages. A nonlinear model was developed to evaluate the combined effects of R and Tmax on Ds. The best model comprised monomolecular function and beta probability density function for plants infected at the above three growth stages. Parameters, including maximum potential for Ds at a given rainfall (d(max)), rate of changes with respect to rainfall (k), constant of integration (B), maximum potential for Ds with respect to Tmax (e), rate of increase with increasing Tmax to optimum (n), and rate of decrease as Tmax increased and passed the optimum Tmax (p), were estimated for plants infected at the above three growth stages. The effect of plant growth stage was characterized by differences in the upper limit parameter a. This parameter was greater for the plants infected at the cotyledon stage than for plants infected at the other two stages. The estimate of parameter k was the same for the plants infected at the cotyledon and three-leaf stages. This parameter was much lower for the plants infected at the six-leaf stage compared with two other stages. The logistic model could describe the disease incidence with respect to R slightly better than the other two models in the plants infected at all three growth stages. Based on the model, upper-limit estimate (d(max)) was approximately 100, 94.4, and 88.8% in the plants infected at cotyledon, three-leaf, and six-leaf stages, respectively. Di increased until rainfall reached approximately 18, 10, and 13 mm/week and became constant in the plants at cotyledon, three-leaf, and six-leaf stages, respectively. Effects of plant growth stage on the rate of change with respect to R (parameter k) were lower in the plants infected at cotyledon than at the other two stages. The accuracy of the nonlinear models suggests that they could be used to develop a comprehensive model to evaluate epidemics of blackleg based on pycnidiospores as sources of inoculum. However, additional years of data collection should improve model fit and evaluation of introduced models and contribute to the development of a more robust predictive model.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".