Developing Rainfall- and Temperature-Based Models to Describe Infection of Canola Under Field Conditions Caused by Pycnidiospores of <i>Leptosphaeria maculans</i>
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».